RESEARCH CENTRE

Inria Branch at the University of
Montpellier

2023
ACTIVITY REPORT

Project-Team

CAMIN

Control of Artificial Movement & Intuitive
Neuroprosthesis

DOMAIN

Digital Health, Biology and Earth

THEME

Computational Neuroscience and
Medicine

Contents

Project-Team CAMIN

1 Team members, visitors, external collaborators

2 Overall objectives

3 Research program

3.1 Exploration and understanding of the origins and control of movement . . . . . . . . . . . .
3.2 Movement assistance and/or restoration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 Application domains

4.1 Movement Assistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Movement Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3 Evoked electrophysiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5 Social and environmental responsibility

5.1 Impact of research results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2 HLI: Humanlab INRIA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6 Highlights of the year

7 New software, platforms, open data

7.1 New software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.1.1 i-GRIP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.1.2 RAT_GAIT_GUI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2 New platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.1 RESCUEGRAPH: Gait analysis platform for rodents . . . . . . . . . . . . . . . . . . . .
7.2.2 ORTHYB experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8 New results

8.1 Brain Potentials Evoked by Direct Electrical Stimulation for on-line guidance of Neurosur-
gery: a combined experimental and simulation approach . . . . . . . . . . . . . . . . . . . .
8.1.1 Understanding the Effects of Direct Electrical Stimulation applied to the Brain: Elec-

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trogenesis of Direct Cortical Responses and Axono-Cortical Evoked Potentials . . . . 10

8.1.2 Pseudo-cortical model for better understanding of the effects of direct electrical

stimulation applied to the cortex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.2 Movement analysis, detection and modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.2.1 SOFTMOCAP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.2.2 i-GRIP: Towards intuitive upper-limb assistive devices, a vision-based interface for

grasping intention detection and grip selection . . . . . . . . . . . . . . . . . . . . . . 11
8.2.3 Trajectory optimization for biomechanics . . . . . . . . . . . . . . . . . . . . . . . . . 12
8.3 Motor functions assistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
8.3.1 Implanted multi-contact epineural stimulation to restore hand function in complete

upper-limb paralysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
8.3.2 Post Stroke upper limb neuroprosthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
8.3.3 GRASP-IT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
8.3.4 ORTHYB: an assistive hybrid orthosis for upper limb function . . . . . . . . . . . . . 14
8.3.5 FES-Induced pedaling optimization through real-time fatigue compensation for

individuals with Spinal Cord Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
8.3.6 RESCUEGRAPH: controlling electrical stimulation to elicit gait patterns in rat model 16
8.3.7 Novel design for a prono-supination orthosis . . . . . . . . . . . . . . . . . . . . . . . 16
8.3.8 Active knee orthosis for rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
8.3.9 Opticycle: Optimally designed tricycle for FES-Induced pedaling in patients with

Spinal Cord Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

9 Bilateral contracts and grants with industry

18
9.1 Neurinnov . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
9.2 REEV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

10 Partnerships and cooperations

10.2 International research visitors

18
10.1 International initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
10.1.1 Inria associate team not involved in an IIL or an international program . . . . . . . . 18
10.1.2 Other international collaborations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
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10.3.1 Horizon Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
10.3.2 H2020 projects
10.4 National initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
10.5 Regional initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

10.2.1 Visits to international teams

10.3 European initiatives

11 Dissemination

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11.1 Promoting scientific activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
11.1.1 Scientific events: organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
11.1.2 Scientific events: selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
11.1.3 Journal
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
11.1.4 Invited talks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
11.1.5 Research administration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
11.2 Teaching - Supervision - Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
11.2.1 Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
11.2.2 Supervision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
11.2.3 Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.3 Popularization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.3.1 Internal or external Inria responsibilities . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.3.2 Articles and contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.3.3 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.3.4 Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

12 Scientific production

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12.1 Major publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
12.2 Publications of the year
12.3 Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
12.4 Cited publications

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Project-Team CAMIN

Creation of the Project-Team: 2019 March 01

Keywords

Computer sciences and digital sciences

A1.2.6. – Sensor networks

A1.3. – Distributed Systems

A2.3. – Embedded and cyber-physical systems

A2.5.2. – Component-based Design

A4.4. – Security of equipment and software

A4.5. – Formal methods for security

A5.1.4. – Brain-computer interfaces, physiological computing

A5.9.2. – Estimation, modeling

A5.10.5. – Robot interaction (with the environment, humans, other robots)

A6.1.1. – Continuous Modeling (PDE, ODE)

A6.3.2. – Data assimilation

A6.4.1. – Deterministic control

A6.4.6. – Optimal control

Other research topics and application domains

B1.1.9. – Biomechanics and anatomy

B1.2.1. – Understanding and simulation of the brain and the nervous system

B2.2.1. – Cardiovascular and respiratory diseases

B2.2.2. – Nervous system and endocrinology

B2.2.6. – Neurodegenerative diseases

B2.5.1. – Sensorimotor disabilities

B2.5.3. – Assistance for elderly

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Inria Annual Report 2023

1 Team members, visitors, external collaborators

Research Scientists

• Christine Azevedo Coste [Team leader, INRIA, Senior Researcher, HDR]

• François Bailly [INRIA, Researcher]

• François Bonnetblanc [INRIA, Researcher, from Oct 2023, HDR]

• François Bonnetblanc [INRIA, Associate Professor Detachement, until Sep 2023, HDR]

• Thomas Guiho [INRIA, ISFP]

Post-Doctoral Fellows

• Tiago Coelho Magalhaes [INRIA, Post-Doctoral Fellow]

• Etienne Moullet [INRIA, Post-Doctoral Fellow]

• Sabrina Otmani [INRIA, Post-Doctoral Fellow, from Jun 2023]

• Fernanda Rodrigues Ferreira Lopes [UNIV MONTPELLIER, Post-Doctoral Fellow, until Mar 2023]

PhD Students

• Jonathan Baum [INRIA, from Dec 2023]

• Laurence Colas [REEV SAS, CIFRE]

• Gabriel Graffagnino [INRIA, from Nov 2023]

• Ronan Le Guillou [CHU TOULOUSE, until Nov 2023]

• Valentin Maggioni [INRIA, from Nov 2023]

• Felix Schlosser-Perrin [UNIV MONTPELLIER]

• Clément Trotobas [INRIA, until Aug 2023]

• Clotilde Turpin [INRIA, from Aug 2023]

• Clotilde Turpin [INNOPSYS, CIFRE, until Jul 2023]

• Lucie William [INRIA, until Jun 2023]

Technical Staff

• Sam Durand [INRIA, Engineer, until Jul 2023]

• Lucas Oliveira Da Fonseca [INRIA, Engineer, until Aug 2023]

• Olivier Rossel [INRIA, Engineer]

Interns and Apprentices

• Fanny Gerbet [INRIA, Intern, from Mar 2023 until Aug 2023]

• Alice Hernot [INRIA, Intern, from Feb 2023 until Aug 2023]

• Houssam Salama Alhandi [UNIV MONTPELLIER, Intern, from Jul 2023 until Aug 2023]

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Administrative Assistant

• Claire-Marine Parodi [INRIA, from Sep 2023]

External Collaborators

• Charles Fattal [Centre Bouffard Vercelli USSAP, HDR]

• David Guiraud [NEURINNOV, from Feb 2023, HDR]

• Benoît Sijobert [INSTITUT ST-PIERRE, from Oct 2023]

2 Overall objectives

CAMIN research team is dedicated to the design and development of realistic neuroprosthetic solu-
tions for sensorimotor deficiencies in collaboration with clinical partners. Our efforts are focused on
clinical impact: improving the functional evaluation and/or patients quality of life. Movement is at the
center of our investigative activity, and the exploration and understanding of the origins and control of
movement are one of our two main research priorities. Indeed, optimizing the neuroprosthetic solutions
depends on a deeper understanding of the roles of the central and peripheral nervous systems in motion
control. The second research priority is movement assistance and/or restoration. Based on the results
from our first research focus, neuroprosthetic approaches are deployed (Figure 1).

Electrical stimulation (ES) is used to activate muscle contractions by recruiting muscle fibers, just
as the action potentials initiated in motoneurons would normally do. When a nerve is stimulated, both
afferent (sensitive) and efferent (motor) pathways are excited. ES can be applied externally using surface
electrodes positioned on the skin over the nerves/muscles intended to be activated or by implantation
with electrodes positioned at the contact with the nerves/muscles or neural structures (brain and spinal
cord). ES is the only way to restore movement in many situations.

Although this technique has been known for decades, substantial challenges remain, including: (i)
detecting and reducing the increased early fatigue induced by artificial recruitment, (ii) finding solutions
to nonselective stimulation, which may elicit undesired effects, and (iii) allowing for complex amplitude
and time modulations of ES in order to produce complex system responses (synergies, coordinated
movements, meaningful sensory feedback, high-level autonomic function control).

We investigate functional restoration, as either a neurological rehabilitation solution (incomplete
spinal cord injury (SCI), hemiplegia) or for permanent assistance (complete SCI). Each of these contexts
imposes its own set of constraints on the development of solutions.
Functional ES (FES) rehabilitation mainly involves external FES, with the objective to increase neurolo-
gical recuperation by activating muscle contractions and stimulating both efferent and afferent pathways.
Our work in this area naturally led us to take an increasing interest in brain organization and plasticity,
as well as central nervous system (brain, spinal cord) responses to ES. When the objective of FES is a
permanent assistive aid, invasive solutions can be deployed. We pilot several animal studies to investig-
ate neurophysiological responses to ES and validate models. We also apply some of our technological
developments in the context of human per-operative surgery, including motor and sensory ES.
CAMIN research is focused on exploring and understanding human movement in order to propose
neuroprosthetic solutions in sensorimotor deficiency situations to assist or restore movement. Explora-
tion and understanding of human movement will allow us to propose assessment approaches and tools
for diagnosis and evaluation purposes, as well as to improve FES-based solutions for functional assistance.

We have chosen not to restrict our investigation spectrum to specific applications but rather to de-
ploy our general approach to a variety of clinical applications in collaboration with our medical partners.
Our motivation and ambition is to have an effective clinical impact.

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Inria Annual Report 2023

Figure 1: Overview of CAMIN general scientific approach.

3 Research program

3.1 Exploration and understanding of the origins and control of movement

One of CAMIN’s areas of expertise is motion measurement, observation and modeling in the context of
sensorimotor deficiencies. The team has the capacity to design advanced protocols to explore motor
control mechanisms in more or less invasive conditions in both animal and human.
Human movement can be assessed by several noninvasive means, from motion observation (MOCAP,
IMU) to electrophysiological measurements (afferent ENG, EMG, see below). Our general approach is to
develop solutions that are realistic in terms of clinical or home use by clinical staff and/or patients for
diagnosis and assessment purposes. In doing so, we try to gain a better understanding of motor control
mechanisms, including deficient ones, which in turn will give us greater insight into the basics of human
motor control. Our ultimate goal is to optimally match a neuroprosthesis to the targeted sensorimotor
deficiency.
The team is involved in research projects including:

• Peripheral nervous system (PNS): modeling, exploration and electrophysiology

Electroneurography (ENG) and electromyography (EMG) signals inform about neural and muscular
activities. The team investigates both natural and evoked ENG/EMG through advanced and
dedicated signal processing methods. Evoked responses to ES are very precious information for
understanding neurophysiological mechanisms, as both the input (ES) and the output (evoked
EMG/ENG) are controlled. CAMIN has the expertise to perform animal experiments (rabbits, rats,
earthworms and big animals with partners), design hardware and software setups to stimulate and
record in harsh conditions, process signals, analyze results and develop models of the observed
mechanisms. Experimental surgery is mandatory in our research prior to invasive interventions in
humans. It allows us to validate our protocols from theoretical, practical and technical aspects.

• Central nervous system (CNS) exploration

Stimulating the CNS directly instead of nerves enables direct activation of the neural networks
responsible for generating functions. Once again, if selectivity is achieved the number of implanted
electrodes and cables would be reduced, as would the energy demand. We have investigated spinal
electrical stimulation in animals (pigs) for urinary track and lower limb function management.
This work is very important in terms of both future applications and the increase in knowledge
about spinal circuitry. The challenges are technical, experimental and theoretical, and the prelimin-
ary results have enabled us to test some selectivity modalities through matrix electrode stimulation.
This research area will be further intensified in the future as one of the ways to improve neuropros-
thetic solutions.
We intend to gain a better understanding of the electrophysiological effects of Direct Electrical Stim-

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ulation (DES) through electroencephalographic (EEG) and electrocorticographic (ECoG) recordings
in order to optimize anatomo-functional brain mapping, to better understand brain dynamics and
plasticity, and to improve surgical planning, rehabilitation, and the quality of life of patients.

• Muscle models and fatigue exploration

Muscle fatigue is one of the major limitations in all FES studies. Simply, the muscle torque varies
over time even when the same stimulation pattern is applied. As there is also muscle recovery when
there is a rest between stimulations, modeling the fatigue is almost an impossible task. Therefore, it
is essential to monitor the muscle state and assess the expected muscle response by FES to improve
the current FES system in the direction of greater adaptive force/torque control in the presence of
muscle fatigue.

• Movement interpretation

We intend to develop ambulatory solutions to allow ecological observation. We have extensively
investigated the possibility of using inertial measurement units (IMUs) within body area networks
to observe movement and assess posture and gait variables. We have also proposed extracting gait
parameters like stride length and foot-ground clearance for evaluation and diagnosis purposes.

3.2 Movement assistance and/or restoration

The challenges in movement restoration are: (i) improving nerve/muscle stimulation modalities and
efficiency and (ii) global management of the function that is being restored in interaction with the rest of
the body under voluntary control. For this, both local (muscle) and global (function) controls have to be
considered.
Online modulation of ES parameters in the context of lower limb functional assistance requires the
availability of information about the ongoing movement. Different levels of complexity can be considered,
going from simple open-loop to complex control laws (Figure 2). Real-time adaptation of the stimulation

Figure 2: FES assistance should take into account the coexistence of artificial and natural controllers.
Artificial controllers should integrate both global (posture/gait) and local (limb/joint) observations.

patterns is an important challenge in most of the clinical applications we consider.The modulation of
ES parameters requires more advanced adaptative controllers based on sensory information in order to
adapt to muscle fatigue or environmental changes. A special care in minimizing the number of sensors
and their impact on patient motion should be taken.

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Inria Annual Report 2023

4 Application domains

4.1 Movement Assistance

CAMIN develops neuroprosthetic solutions dedicated to restore or assist movements of paralyzed limbs.
Among the considered functions we can cite: pedalling, grasping or walking. Different users are con-
sidered: individuals with post-stroke hemiplegia, people with spinal cord lesions and persons with
Parkinson disease.

We have also started to develop skills in orthosis design.

4.2 Movement Analysis

For the purpose of assisting movement, CAMIN has developped an important expertise in movement
interpretation using a large range of sensors: inertial measurement units, MOCAP systems, encoders,
goniometers... Various Classification methods are used depending on the objective.

This knowledge is applied in other applications than movement assistance, like in MEDITAPARK
project where we developped an application (PARAKEET) embedded in a smartwatch to monitor hand
tremor in persons with parkinson disease.

4.3 Evoked electrophysiology

CAMIN develops solutions to trigger, record and process electrophysiological signals evoked by electrical
stimulation applied to various neural tissues. These evoked responses are used to control the activity of
the excitable tissue, to probe its electrophysiological status for diagnostic purposes and to investigate
the conductivity/connectivity between the stimulation and the recording sites (electrophysiological
mapping).

These neural engineering procedures can be applied to muscle, nerve, spinal cord and brain, in

animals and humans.

For instance, electrical stimulations can be applied externally and non-invasively on muscles to

induce muscle contractions as well as invasively on the human brain in order to guide neurosurgeries.

5 Social and environmental responsibility

5.1 Impact of research results

CAMIN research is clearly dedicated to applications which intend to improve quality of life and/or self
esteem of individuals with sensori-motor deficiencies.
We give a very important place to ethics in our work. Christine Azevedo is a member of INRIA ethical
committee COERLE.

Our activities are associated to an important working load on designing protocols and obtaining
authorizations from ethical committees and/or health agencies. We list in the following the protocols
that have obtained authorizations and were valid in 2023.

1. Measure of the Potential Evoked by Electric Stimulation (PE & CE). CHU Montpellier. Autorisation

CPP RCB 2014-A00056-43. ClinicalTrials.gov Identifier: NCT02509442

2. Exofinger: a tool for entering objects. COERLE (autorisation nº 2021-47 Exofinger)

3. SOFTMOCAP : Comparaison de trois méthodes d’analyse des mouvements de la main chez des

sujets valides. COERLE (autorisation nº 2022-57 SOFTMOCAP)

4. AGILISTIM: Functional Evaluation of Grip Restoration in tetraplegic patients by implanted neural

stimulation. Autorisation CPP/ANSM ID-RCB: 2022-A00205-3815.

5. Ethics approval for an experiment on hybrid orthosis from Institutional Ethics Committee of the

Federal University of Minas Gerais (CAAE Registration: 53757521.3.0000.5149)

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6. “EEG-FES stroke rehabilitation evaluation based on runtime data” (GRASP-IT project) COERLE

(autorisation nº 2023-12 EEG-FES).

7. GRASPHYB. COERLE (autorisation nº 2023-14 GRASPHYB).

8. Prehens-Stroke 2: Prospective multicenter study on the evaluation in clinical setting of a Grasp
NeuroProsthesis and self-triggering control modalities for the restauration of paretic side prehen-
sion capabilities in post-stroke subjects. Study carried by the University Hospital (CHU) of Toulouse
in collaboration with the Le Grau du Roi rehabilitation center from the University Hospital (CHU)
of Nîmes (ClinicalTrial.gov ID: NCT04804384; Autorisation CPP ID-RCB: 2020-A01660-39).

9. Grasp-Again: Prospective monocentric, real-life, feasibility case series study on 2 months long
usage of a wearable grasp neuroprosthesis, at home in autonomy by post-stroke participants.
Study carried by the University Hospital (CHU) of Toulouse (ClinicalTrial.gov ID: NCT05625113;
Autorisation CPP ID-RCB: 2022-A01202-41).

5.2 HLI: Humanlab INRIA

Humanlabs are collaborative spaces for digital fabrication or repair of objects, open to people with
disabilities to enable them to appropriate technology for their own use. In 2021, Christine Azevedo and
Roger Pissard-Gibollet (SED INRIA Montbonnot) have launched the Inria’s HumanLab intiative. HLI
contributes to meeting the needs expressed by individuals with disabilities within the framework of the
Humanlabs network or via clinical partners. Our action is part of a frugal and opensource innovation
approach and aims to implement the scientific and technological know-how of Inria’s staff to meet
specific needs. www.inria.fr/en/hli

6 Highlights of the year

Ai-Hand EU project was launched in August 2023. This project is the last stage of a 10-year effort in the
team to propose a solution to patients with complete tetraplegia.

7 New software, platforms, open data

7.1 New software

7.1.1 i-GRIP

Keywords: Handicap, Computer vision, Persons attendant, Exoskeleton, Detection

Scientific Description: Detection of object grasping intention and automatic selection of grasp type for

shared control of (neuro)prostheses.

Functional Description: From a video stream of hands and objects, i-GRIP detects the intention to
grasp one of them and identifies the grip the hand should adopt to appropriately seize it based on
the approaching movement. i-GRIP will enable intuitive and low cognitive load control of hand
movement assistive devices (exoskeletons, functional electrical stimulation, prosthetics).

Authors: Etienne Moullet, Christine Azevedo Coste, Francois Bailly

Contact: Etienne Moullet

7.1.2 RAT_GAIT_GUI

Keyword: GUI (Graphical User Interface)

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Inria Annual Report 2023

Functional Description: This Python program provides a graphical user interface (GUI) to control a
Neurinnov Stim RG stimulator and perform functional electrical stimulation (FES) artificial gait
cycles on rats. The GUI is built using the Tkinter library and allows users to interact with the StimRG
stimulator in an intuitive and user-friendly manner.

Authors: Sam Durand, Christine Azevedo Coste

Contact: Christine Azevedo Coste

7.2 New platforms

7.2.1 RESCUEGRAPH: Gait analysis platform for rodents

Participants:

Sam Durand, François Bailly, Christine Azevedo.

Within RESCUEGRAPH project (FLAGERA), the objective is to set up a gait platform to analyze rat gait
and assess electrical stimulation effects. We have set up a platform for the analysis of 2D kinematics of
the 2 hindlimbs of the rat during gait. During visits to the UAB lab, cameras and devices available were
tested, and the requirements for the in vivo studies were set. Infrared cameras available at UAB and INRIA
have been used to record movements of reflexive markers placed on key points of the hindlimbs of the
animal. The idea is to have a sagittal analysis of kinematics of the two hindlimbs over consecutive steps.
New colour skin markers are also implemented to improve the detection. Preliminary tests have been
done with a setup to detect in real time the stepping of the rat with a conductive fabric adapted on the
treadmill and conductive paint in the animal paw (fig.3).

Figure 3: RESCUEGRAPH gait analysis platform.

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9

7.2.2 ORTHYB experimental setup

A motorized mechanical cable-driven orthosis for the wrist and fingers was designed and developed
(Exo Hand, Aufratech, France). A prototype was manufactured for the right arm. Two drive units are
integrated, comprising a 3W DC motor, a reduction stage, and an encoder. Each motor unit pulls cables,
one motor actuating flexion-extension of the wrist joint, and one motor actuating flexion of all 5 fingers
simultaneously. The orthosis is powered from the main supply (14V - 700mA). The mechanical orthosis is
controlled by an Adafruit Feather nrf52840 control board, which is coupled with a DC double-channel
driver (L298N). The two encoders of the mechanical orthosis are connected to input pins on the control
board to receive signals and are powered by the board itself. To facilitate control and communication,
the microcontroller is connected to a computer via a serial communication protocol (serial COM). An
electrical stimulator (Phenix Neo©, Montpellier, France) composed of a base controller connected to a
computer and two wireless stimulation units (PODs) featuring 2 stimulation channels each. 3 pairs of
surface electrodes were used, for activating (1) extension of the wrist and fingers (2) finger flexion, and (3)
thumb flexion. The controller base is connected to the computer with a serial COM.

ORTHYB controller pilots the 3 electrical stimulation channels and the 2 DC motors. A multi-threaded
Graphical User Interface (GUI) has been developed in Python (fig.4). It manages the communication with
the motor control board and the stimulator controller through Serial COM. The controller operates as a
state machine, allowing independent control of the orthosis or stimulator, as well as the simultaneous
control of both devices based on the selected settings. A push button controlled with the contralateral
fist has been developed for the participant to trigger the change of state. The orthosis incorporates two
sensors which are rotary encoders, one per actuator. ORTHYB controller continuously estimates the
relative position from the input signals.

Figure 4: ORTHYB platform.

8 New results

We have organized this section around 3 main subsections: 8.1) Brain Potentials Evoked by Direct
Electrical Stimulation for on-line guidance of Neurosurgery, 8.2) Movement analysis, detection and
modelling and 8.3) Motor functions assistance

8.1 Brain Potentials Evoked by Direct Electrical Stimulation for on-line guidance of

Neurosurgery: a combined experimental and simulation approach

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Inria Annual Report 2023

Participants: Clotilde Turpin, Felix Schlosser-Perrin, Olivier Rossel, Emmanuel Man-
donnet [AP-HP, France], Hugues Duffau [CHU-Montpellier, France],
Sam Ng [CHU-Montpellier, France], Riki Matsumoto, François Bon-
netblanc.

8.1.1 Understanding the Effects of Direct Electrical Stimulation applied to the Brain: Electrogenesis

of Direct Cortical Responses and Axono-Cortical Evoked Potentials

Measuring potentials evoked (EP) by direct electrical stimulation (DES) during brain surgery is emerging
as a real-time method for identifying structural or anatomical connectivity while preserving it. This
novel approach enables recording and observation of various responses in the operating room, including
(i) direct cortical response (DCR: DES and recording at the same cortical site, on the same gyrus), (ii)
cortico-cortical evoked potentials (CCEP: DES and recording on distant cortical sites), and (iii) axono-
cortical (ACEP: DES on white matter tracts with corresponding cortical recording). Whether applied in
the cavity on white matter pathways or on the cortical surface on grey matter, these two response types
share common features, strongly suggesting the involvement of identical electrophysiological activities
by DES. However, DES applied directly to the cortex could also generate activities in intra-cortical axons
and dendrites in contrast to “more natural” activations through the white matter pathways as is the case
for ACEP. Specifically, the application of DES to the cortical surface for DCR appears to induce additional
activation of smaller and slower intra-cortical non-myelinated axons within the cortical layer surrounding
pyramidal neurons. This tangential intra-cortical activation induces changes in the later componenets of
the N1 for DCR (Fig. 5). An average frequency spectrum of DCR and ACEP was conducted to identifiy
more significant and continuous Gamma activity during the relaxation phase of DCR. However, punctual
activity in the 50Hz band was only significantly more pronounced for DCRs in two time windows centered
around 20 and 25 ms (with a step of 5ms), particulalry in the vicinity of the maximum amplitude of the
response. Another important difference between DCR and ACEP is associated with the delay between
axon stimulation in the case of ACEP and its propagation to the cortical layer. The zero crossing of the
signals illustrates this delay of a few milliseconds induced by DES applied to subcortical white matter
pathways in the case of ACEP.

8.1.2 Pseudo-cortical model for better understanding of the effects of direct electrical stimulation

applied to the cortex

Participants:

Felix Schlosser-Perrin, Olivier Rossel, Emmanuel Mandonnet [AP-HP,
France], Riki Matsumoto, François Bonnetblanc.

To better understand the effects of direct electrical stimulation applied to the cortex and to know how
it induces evoked potentials at a distance from the stimulation site (cortico-cortical evoked potential:
CCEP), we used models of classical axons arranged radially and developped somatic and dendritic endings
(Fig. 6). We planned to compare the simulations produced by this model with the experimental data and
the potentials evoked by electrical stimulation to verify that the variation of the electrical stimulation
parameters (in particular the intensity) predicts the variation of the early components of the measured
CCEPs, this in connection with the variation of local responses (i.e. direct cortical response, DCR). This
approach should allow us to better understand evoked electrogenesis and optimize electrical stimulation
applied to the brain in the case of neurosurgery.

8.2 Movement analysis, detection and modelling

8.2.1 SOFTMOCAP

Participants: Christine Azevedo, François Bailly, Sam Durand, Valentin Maggioni.

Project CAMIN

11

In this work, we assess the accuracy of three motion capture systems for conducting biomechanical
analysis of the hand. The systems evaluated are a computer vision and CNN-based method [29], a
combination of three Leap Motion [27] controllers (a commercial infrared hand motion capture device),
and a traditional motion capture setup considered as the gold standard.

Our study aims to quantify the error of two markerless motion capture systems, specifically the
video-based method and Leap Motion, compared to traditional motion capture during ecological tasks
such as free-field movement and object grasping. We employed inverse kinematics to compare the joint
angles of a hand model superimposed to the point clouds obtained from each system. This evaluation
will enable us to ascertain if these markerless devices can be reasonably considered viable alternatives to
marker-based motion capture systems for such manual tasks.

Accurately tracking hand movements has a multitude of potential applications in different domains,
including biomedical research, sports (e.g., climbing, e-sports), leisure (e.g., music playing), or whenever
there is handling movement involved. In rehabilitation, accurate tracking of hand movements will be a
valuable tool for monitoring and improving patient progress in our current AI-HAND project, which aims
to restore hand function in tetraplegics through selective electrical neural stimulation [24].

8.2.2 i-GRIP: Towards intuitive upper-limb assistive devices, a vision-based interface for grasping

intention detection and grip selection

Participants:

Etienne Moullet, Christine Azevedo, François Bailly, Justin Carpentier
[INRIA WILLOW].

Grasping is crucial for many daily activities, and its impairment considerably impacts quality of life
and autonomy. Attempts to restore this function may rely on various approaches and devices (functional
electrical stimulation, exoskeletons, prosthesis. . . ) with command modalities often exert considerable
cognitive loads on users and lack controllability and intuitiveness in daily life [24, 25]. We propose a novel
user interface for grasping movement control in which the user delegates the grasping task decisions to
the device, only moving their (potentially prosthetic) hand toward the targeted object.

Apparatus and computer vision tools Required information for assisting an ongoing grasping task
is the following: 1) hand position and orientation; 2) object position and orientation; 3) object nature
(including shape and potentially weight and texture). We use an OAK-D S2 (Luxonis) stereoscopic RGB
camera as a data acquisition sensor, prioritizing cost, ease of use, installation and universality, as it may be
easily mounted on a wheelchair or a hat. Hand pose estimation was performed using Google’s MediaPipe
[29], leveraging stereoscopic vision for depth estimation. Object identification and pose estimation were
achieved using CosyPose [26], a multi-object 6D pose estimator trained on a set of objects with known 3D
models.

Grasping intention detection Hand and objects’ pose are estimated and represented in a 3D virtual
scene for grasping intention detection. The hand movement’s direction is predicted from the hand’s
past trajectory and instantaneous velocity. A virtual cone with a length and diameter embedding scalar
velocity is formed by multiple rays, whose intercepts with objects’ 3D mesh are used to determine what
(if any) object is targeted.

Time before impact estimation We defined the expected area of impact as the mesh triangle intercep-
ted by a ray defined as the barycenter of the intercepting rays. Time before impact was evaluated by
integrating the extrapolated velocity of the hand up to the area of impact.

Grip selection Once the target is identified, the foreseen vector of impact is used to select the appropriate
grip among a predefined set. A 4-dimensional table (illustrated in Fig. 7) was constituted for each object
of the used set in which a grip is attributed to every tuple formed by the mesh triangle representing the
expected area of impact ∆i mp and the hand’s normed velocity vhand .

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Inria Annual Report 2023

Result and experiment Figure 8 shows a snapshot of the video feed of a grasping task on the upper part
and the corresponding virtual scene on the lower part. Object 000028 was correctly detected as the target,
while object 000023 was ignored. Area of impact was estimated from the ray intercepts figured as red
dots, and a palmar grip was accordingly selected [19].

An experimental study has been initiated and is divided in three phases :

1. Participants are randomly instructed to grasp an object (among 4) with a given grip. Video re-
cordings of the task are analyzed offline to fine-tune the parameters of our algorithm and the grip
selection table.

2. During a similar task, real-time performances of the i-GRIP algorithm for static objects are assessed.

3. During a similar task, real-time performances of the i-GRIP algorithm for mobile objects.

8.2.3 Trajectory optimization for biomechanics

Participants:

François Bailly, Pierre Puchaud [Univ. Montréal], Amedeo Ceglia [Univ.
Montréal], Mickael Begon [Univ. Montréal], Benjamin Michaud [Univ.
Montréal].

In this collaboration with Université de Montréal, we develop software [12] and methods [13, 9] to
improve trajectory optimization applied to biomechanics. These tools are then aplied to multiple applied
research project inside the CAMIN team (see 8.3.B).

8.3 Motor functions assistance

We have organized this subsection around 3 main sub-parts: A) Upper-limb function restoration, B)
Lower-limb function restoration and C) Towards new designs for assistive devices.

A. Upper-limb function restoration

8.3.1 Implanted multi-contact epineural stimulation to restore hand function in complete upper-

limb paralysis

AGILISTIM

Participants:

Lucie William, François Bailly, Thomas Guiho, Christine Azevedo,
David Guiraud [Neurinnov, France], Charles Fattal [USSAP, France],
Jacques Teissier [Clinique St Jean Sud de France], Antoine Geffrier
[AP-HP Paris, France].

Following AGILIS project (EIT Health), AGILISTIM project (funded by ISITE-MUSE University of
Montpellier) consisted in implanting three multi-contact neural cuff electrodes around radial, ulnar
and median nerves of 2 new participants with high tetraplegia (NCT04306328). The electrodes were
maintained during 28 days. The purpose was to study the safety and capability of these electrodes to
generate synergistic motor activation and functional movements and to test control interfaces that allow
subjects to trigger pre-programmed stimulation sequences. The device consisted of a pair of epineural
electrodes and percutaneous cables with two extracorporeal connection cables inserted during a surgical
procedure and removed after 28 days (see Fig. 9).

Both participants were able to execute several grasping tasks using the approach. The new AI-HAND
project (EIC pathfinder) starting from August 2023 intends to test an implant developed by NEURINNOV
company in a first in man trial in 2025. project.inria.fr/aihand

Project CAMIN

AI-Hand

Participants:

Valentin Maggioni, Jonathan Baum, François Bailly, Thomas Guiho,
Christine Azevedo, David Guiraud [Neurinnov, France], Charles Fattal
[USSAP, France], Jacques Teissier [Clinique St Jean Sud de France],
Antoine Geffrier [AP-HP Paris, France].

13

The AI-Hand European project, which began in August 2023, focuses on the development of an im-
plant for neural stimulation - supported by Neurinnov - to restore wrist and hand function in individuals
with tetraplegia. In this framework, the project is divided into two successive phases, a phase dedicated
to the development/refinement of the approach that will immediately be followed by a clinical phase by
2026 (first implantation in people with tetraplegia). The CAMIN team, which is coordinating the project,
is currently focusing its efforts on two areas:

• Preparing experiments on large animals (pigs) to support the manufacture of the implant (involving

Jonathan Baum, Thomas Guiho, Christine Azevedo, David Guiraud).

• The development of an upper limb neuromusculoskeletal simulator capable of supporting the
refinement of movements by optimizing stimulation parameters (thesis work by Valentin Maggioni
and involvement of François Bailly and Christine Azevedo).

PLASTICISTIM

Participants:

Jonathan Baum, Thomas Guiho, Christine Azevedo, David Guiraud
[Neurinnov, France].

The PLASTICISTIM project can be described as a complementary initiative to the AI-Hand project. Its
aim is to study the benefits of combining peripheral nerve stimulation (PNS) - as investigated in AI-Hand
- with spinal cord stimulation (SCS) for restoring motor function in spinal cord injured individuals. The
aim of this combination is to potentiate the direct restoration of motor function enabled by PNS with a
progressive refinement of movements due to SCS. Indeed, recent studies attest to the impact of SCS in
facilitating the passage of degraded voluntary commands and also in the progressive restoration of motor
functions (following long-term clinical trials combining SCS and physical rehabilitation exercise). The
literature does not reference any study exploring this combination and the aim of the PLASTICISTIM
project, which should be seen as a proof of concept, is to pave the way for a new therapeutic approach
enabling the restoration of numerous functions in people with spinal cord injuries. PLASTICISTIM is the
topic of Jonathan Baum’s PhD thesis - which started in December 2023 - and will be based on alternating
phases of in vivo exploration (on large animals - pigs) and biosignals processing. The project is currently
at the literature survey stage, but should be based on transcutaneous SCS in order to benefit from its ease
of access, low cost and non-invasive nature.

8.3.2 Post Stroke upper limb neuroprosthesis

Participants:

Ronan Le Guillou, Christine Azevedo, David Gasq [CHU Toulouse].

Post Stroke upper limb neuroprosthesis : Clinical evaluation (Project Prehens-Stroke 2) The improve-
ment of grasping abilities remains a challenge in 50% of post-stroke subjects who have not recovered
a functional grasp on their paretic side due to paralysis of the finger’s extensor muscles. Following the
Prehens-Stroke 1 (ePrehension-Stroke) study in 2019-2020 and its informative results, a new study was
started. The PHRCi Prehens-Stroke 2 project (ClinicalTrials.gov Identifier: NCT04804384) aims to evaluate

14

Inria Annual Report 2023

the piloting modalities and the functional impact of a grasping neuroprosthesis in the vascular hemi-
paretic patient (Fig. 10). Head lateral inclination, foot motion and voice control are being investigated
as self-triggering modalities for the user to perform FES induced paretic hand opening. As of the end of
2022, a total of 15 patients had been fully included in this protocol. Inclusions continued throughout
2023, with a total of 21 participants by the end of 2023. This was notably done through the opening of
a second inclusion center in the medical rehabilitation center of the University Hospital of Nîmes in
Le Grau-du-Roi, collaborating with the CHU of Toulouse on this study. We have evaluated the system’s
responsiveness, the control modalities proposed and the functional improvements provided by the GNP.

Post Stroke upper limb neuroprosthesis : Home-use investigation (Project Grasp-Again) An embed-
ded version of the Grasp Neuro-Prosthesis developed for the Prehens-Stroke studies, based on the CE
marked FESIA Grasp upper-limb rehabilitation stimulator (Fig. 11) was designed, developed and tested
throughout the year 2022. This embedded version was used in the Grasp-Again protocol (ClinicalTrial.gov
ID: NCT05625113; ID-RCB: 2022-A01202-41), carried out in 2023 from January to July, with 6 post stroke
participants, aiming to investigate the use of such a wearable grasp neuro-prosthesis in practical condi-
tions, at home, in autonomy. We evaluated various aspects such as its functional impact on activities of
daily living, its responsiveness to user commands and followed and described its use by the participants
throughout the 2 months of usage in the protocol.

The software APPs of this platform can be found at https://bil.inria.fr/fr/software/view/3520/tab and
https://bil.inria.fr/fr/software/view/3559/tab as the IMUSEF and NeuroPrehens projects respectively,
with the Bil Ids: Software_3520 and Software_3559. The IMUSEF software was made Open-source in
October 2023.

Before and after the two months of autonomous usage by the participants in this protocol, the brain
activity generated by using the device was recorded in EEG and fMRI sessions. These results are being
processed. An example of the pathological cortical activations related to voluntary attempts at paretic
hand opening by the post-stroke participants can be found in Fig. 12

8.3.3 GRASP-IT

Participants: Ronan Le Guillou [CHU Toulouse], Christine Azevedo, David Gasq

[CHU Toulouse, France], Lucas Fonseca.

The GRASP-IT project is dedicated to addressing the challenges faced by stroke survivors in gener-
ating pertinent kinesthetic motor imagery (KMI) for rehabilitation therapy. The project’s overarching
objectives encompass the comprehensive assessment of user requirements, as well as the usability and
acceptability of the innovative GRASP-IT device. This device incorporates diverse feedback modalities,
including sensory and motor functional electrical stimulation (FES), as well as tactile/kinesthetic and
tangible interfaces, within a gamified therapeutic framework. Users engage with physical devices, such
as wearable, 3D-printable orthoses, via a Brain-Computer Interface (BCI) (Fig. 13). Within the CAMIN
team, our primary focus is on investigating the impact of FES on BCI signals during KMI. To achieve
this, we conducted Electroencephalography (EEG) data collection sessions with 12 able-bodied subjects
performing a wrist extension task, accompanied by randomized FES applied to their wrist extensors. The
FES protocols encompassed various intensity levels, including the absence of stimulation, sensory, and
motor intensities. Each session recorded approximately 30 minutes of EEG activity across 32 channels.
Currently, the acquired data is undergoing thorough analysis (see Fig. 14).

8.3.4 ORTHYB: an assistive hybrid orthosis for upper limb function

Participants: Clément Trotobas, Christine Azevedo, Fernanda Rodrigues Fer-
reira Lopes, Henrique Resende Martins [UFMG, Belo Horinzonte,
Brazil/Associate team GOIABA].

Project CAMIN

15

We have developed a new approach to assisting prehension by combining functional electrical
stimulation (FES) and a motorized orthosis (Fig. 15). The aim was to induce movements of the fingers
and wrist joints by activating the muscles using FES and locking the joints in the desired positions using
electric motors, in order to reduce muscle fatigue and enable prolonged grasping of objects. Another
hypothesis was that the mechanical orthosis would improve grip quality by constraining joint positioning
and guiding hand movements. The hybrid orthosis combined electrical stimulation of the extensors
and flexors of the fingers, thumb and wrist muscles with a mechanical structure equipped with low-
power motors to accompany the movements induced by the stimulation and maintain the position thus
achieved by the passive properties of the motors [28].

The clinical protocol was approved by the Ethics Committee of the Federal University of Minas Gerais
(CAAE Registration: 53757521.3.0000.5149). Five participants with spinal cord injury were recruited from
rehabilitation centers and hospitals in Belo Horizonte, Minas Gerais, Brazil, and through dissemination
of the research on social media. The prototype was tested by the 5 participants, comparing the grasping
of 3 objects (ball, fork, bottle) with the ORTHYB solution with that achieved through functional electrical
stimulation alone. The evaluation was carried out by monitoring the quality of grip for 30 seconds on
3 different objects; perceived effort using the Borg RPE (Rating of Perceived Exertion) scale; the visual
analog scale (VAS); acceptability using the QUEST (Quebec User Evaluation of Satisfaction Technology
with Assistive Technology) scale and the SUS (System Usability Scale) were applied. Results indicate that
the orthosis provides added value compared to FES alone. Object grasping is possible for 30 seconds
without muscular fatigue affecting the grip. Yet, the prototype will have to be improved to reach an
acceptable level of usability.

B. Lower-limb function restoration

8.3.5 FES-Induced pedaling optimization through real-time fatigue compensation for individuals

with Spinal Cord Injury

Participants:

Tiago Coelho Magalhaes, François Bailly, Christine Azevedo.

In this project, we use trajectory optimization to simulate the application of Functional Electrical
Stimulation (FES) in assisting individuals with spinal cord injuries (SCIs) and other neurological impair-
ments to perform functional activities such as cycling. The framework is based on the biorbd rigid-body
dynamics library and benefits from the algorithmic differentiation provided by CasADi. It interfaces both
Ipopt and Acados solvers for solving optimal control problems (OCP) in biomechanics. Using trajectory
optimization (direct multiple shooting), we hypothesized that it was possible to achieve a more efficient
application of electrical stimulation, while evaluating biomechanical constraints and exploring stimula-
tion patterns aligned with individualized settings. Therefore, it will be possible to address problems such
as determining when each muscle should be activated in the pedaling cycle, achieving more efficient
electrical charge expenditure, etc.

In this sense, our approach involves integrating biomechanics and optimal control techniques to
optimize the stimulation patterns during the activity. The primary goal is to develop new control laws
that adapt electrical stimulation parameters based on the subject’s muscular state. We aim to address
challenges associated with the reversed order of muscle fiber recruitment caused by electrically evoked
contractions coupled to muscle atrophy and increased fatigue that hinders prolonged pedaling.

For synthesizing the optimal stimulation pattern, we chose to first optimize the pulse width while
minimizing the joint trajectory tracking errors and the activation of the two antagonistic muscles. The
goal was to find the control input that minimizes a cost function subject to dynamic and boundary
constraints. In Bioptim, the mathematical transcription of the OCP is as follows:

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Inria Annual Report 2023

min
x,u,p

s.t.

(cid:90) T

L(x, u, p) d t

0
˙x = f (x(t ), u(t ), p)
u ∈ U
x ∈ X
p ∈ P
x(0) = x0

Dynamics constraints

Control path constraints

State path constraints

time-independent variables

Initial state constraint

(1)

(2)

(3)

(4)

(5)

(6)

In a brief, the optimization variables are the states (x), controls (u) and parameters (p). They represent
the state of the system at each node subject to continuity constraints, the control variables at each node
that drive the system, and optimization variables, respectively. The cost function can include Lagrange
terms (functions are integrated over the duration of the phase) and Mayer terms (function are evaluated
at one node).

For demonstration (Fig. 16), we show the results of a basic example where the objective was to perform
an optimal reaching task with a one muscle (rectus femoris) and one degree of freedom (knee joint)
model. The shank was supposed to reach a marker placed upward in front while minimizing the muscles
activity and optimize the pulse width value.

Now, our actual objective is to evaluate the electrically evoked muscle activity and optimize the
stimulation pattern in more complexes scenarios, for instance, during the FES-cycling modality (Fig. 17).
We believe that this research will significantly contribute to the achievement of more efficient application
of electrical stimulation during FES-assisted cycling activities by synthesizing the optimal stimulation
patterns, therefore providing valuable insights into designing protocols tailored to the specific needs of
individuals with SCIs, ultimately enhancing their motor function and overall quality of life.

We believe that this research will significantly contribute to personalized rehabilitation approaches
and facilitate the achievement of more efficient use of FES, therefore providing valuable insights into
designing protocols tailored to the specific needs of individuals with SCIs, ultimately enhancing their
motor function and overall quality of life.

8.3.6 RESCUEGRAPH: controlling electrical stimulation to elicit gait patterns in rat model

Participants:

François Bailly, Christine Azevedo, Sam Durand.

Within RESCUEGRAPH project, the software StimRG Rat Gait was developed to define cyclic stimula-
tion patterns for controlling the rat gait pattern (Fig. 18). This graphical user interface (GUI) interacts
with the electrical stimulator developped by NEURINNOV company through its API. The software was
successfully tested during preliminary experiments at UAB (Barcelona, Spain) in June 2023.

C. Towards new designs for assistive devices

8.3.7 Novel design for a prono-supination orthosis

Participants: Clément Trotobas, Christine Azevedo, Andrew Murray[DimLab, Uni-

versity of Dayton (Ohio), USA] .

The goal of this project is to imagine a novel light and wearable orthotic solution for pronation and
supination movement assistance. The objective is to give functional mobility to paralyzed forearms. The
main complexity of this kind of device is to induce a rotational movement at the wrist according to the
elbow without being inside the body space and with minimized spatial encumbrance.

Initial work in the design of a mechanism for a portable assistive orthosis is expected to include
powered prono-supination. The component proposed in this work is based on a spherical mechanism

Project CAMIN

17

architecture. The capacity of these mechanisms to have a hollow center and to produce paths that follow
arcs on spheres make them worth consideration in this application. A MATLAB optimization was used
to perform path generation of a single spherical four-bar with the intent of replicating it three times to
create the device proposed in this work. The concept was modeled in SOLIDWORKS and printed to gauge
its potential (Fig. 19). Input parameters are the inner radius (space for the forearm) and the length. They
define the range of motion of the rotation. Activities of daily living require a range of motion of 103
for
the prono-supination movement. Reaching this criteria requires stacking two layers of three mechanisms
- the top ring of the first layer being the bottom ring of the second layer (Fig. 20)- enabling a 160
rotation.
This means a forearm orthosis would require 3 x 2 actuators which seems not compatible with a wearable
device. This work was initiated during the stay of Andrew Murray as invited researcher in the team (Labex
Numev support). The current work is to reduce the number of actuators required for such device by
slaving spherical mechanims among layers and potentially between layers.

◦

◦

8.3.8 Active knee orthosis for rehabilitation

Participants:

Laurence Colas [REEV], Christine Azevedo, François Bailly.

The project started in September 2022 in the form of a PhD thesis in collaboration with the REEV
company, on the design and control of a walking assistance exoskeleton at the knee (Fig. 21). The
particularity of REEV’s device comes from its ability to work in concentric and eccentric modes both
during flexion and extension. This is allowed thanks to its optimized hydraulic actuators.

This year, the work was mainly focused on finalizing the mechanical optimization of the orthosis
transmission prototype that will be used for the first trials on healthy users and on patients suffering from
light walking disabilities. That part was very challenging due to manufacturing issues but the prototype is
essential for experimental purposes.

The second part of the project is to develop the assistive sub controller of the high level control law.
This includes building a biomecanichal model of the patient (Fig. 22) and applying inverse dynamics to
this model in order to deduced the external forces acting on the model and the torques applied on each
joint depending on the position of the user.

8.3.9 Opticycle: Optimally designed tricycle for FES-Induced pedaling in patients with Spinal Cord

Injury

Participants:

Sabrina Otmani, François Bailly, Andrew Murray [Dimlab, Dayton
(Ohio), USA], Christine Azevedo.

The objective of the OPTICYCLE project is to improve the performance of FES assisted pedaling by
co-optimizing the design of the tricycle and the FES control law, in accordance with the biomechanical
capabilities of the patient. So far, we have conducted numerical optimization on the adjustable paramet-
ers of the tricycle using literature-derived surfaces of maximum joint torques varying with joint position
and velocity [23]. In simulation, this approach allows us to maximize the power recovered at the crank
by changing the geometry of the tricycle, for an able-bodied rider, at constant speed. In a second step,
we will generalize this approach to FES-stimulated patients (scaling of the torque surfaces) and we will
co-optimize the FES control law. We aim to achieve the most efficient possible combination of tricycle
and control law to delay the apparition of fatigue and let the patient ride the system for larger periods of
time (aiming to attend the 2024 Cybathlon).

Our research focuses on optimizing tricycle architecture by modeling three distinct design variations,
ranging from the simplest (TRT - Traditional Recumbent Tricycle) to the most intricate configurations
(CDT - Coupler Driven Tricycle). Our findings highlight the transformative potential of data-driven
optimization, particularly in leveraging real joint torque information and anthropometric data extracted
from studied subjects.

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Inria Annual Report 2023

The optimization is based on the maximization of power transmitted to the crank. Grashof constraints
are used to ensure the system’s kinematic feasability. The knee and hip angular positions are enforced in
the domain defined in the literature. Additional options can be chosen to specify some parameters of the
optimization (maximum iterations, tolerance, etc).

This approach enhances tricycle efficiency by personalizing the model based on the user’s anthro-
pometry (Fig. 23). This is especially beneficial for individuals with limited ankle joint mobility or motor
disorders. Through meticulous integration of this data into the design process, we iteratively refine key
parameters such as frame geometry, back inclination, and crank velocity.

The overarching goal of our research is to maximize the output of the crank while preserving the
ankle (which is considered without any mobility), ultimately enhancing tricycle performance and user
satisfaction. Our final objective is to integrate an optimized tricycle design with FES-Induced pedaling
optimization. This involves real-time fatigue compensation for individuals with Spinal Cord Injury,
providing a comprehensive solution for improved mobility and user experience.

9 Bilateral contracts and grants with industry

9.1 Neurinnov

Participants:

Jonathan Baum, Thomas Guiho, David Guiraud, Christine Azevedo.

NEURINNOV startup finances half of the PhD thesis salary of Jonathan Baum (from December 2023 -

PLASTICISTIM Project).
A convention was signed with Neurinnov for David Guiraud to join the team as a collaborator.

9.2 REEV

Participants:

Laurence Colas, François Bailly, Christine Azevedo.

REEV startup obtained a CIFRE grant to finance the PhD of Laurence Colas (started in October 1st

2022).

10 Partnerships and cooperations

Participants: Christine Azevedo-Coste,

François Bailly,

Jonathan Baum,
François Bonnetblanc,
Sam Durand, Charles Fattal, Gab-
riel Graffagnino, Thomas Guiho, David Guiraud, Ronan Le Guillou,
Tiago Coelho Magalhaes, Valentin Maggioni, Etienne Moullet,
Sabrina Otmani, Olivier Rossel, Felix Schlosser-Perrin, Clotilde Turpin.

10.1 International initiatives

10.1.1 Inria associate team not involved in an IIL or an international program

• BrEl-Mapping: France-Japan Inria associated team website. PI: François Bonnetblanc and Pr Riki
Matsumoto (Kobe University Graduate School of Medecine). This team focuses on the methodolo-
gical aspects of measuring brain potentials evoked by electrical stimulation with two complement-
ary approaches. Prof Matsumoto has gained a worldwide reputation for the study of distant CCEPs
in epileptic patients. We have developed more specific expertise in the collection and analysis of
ACEP during tumor surgery.

Project CAMIN

19

• GOIABA: Brazil-France associated team website. PI: Christine Azevedo and Henrique Resende
Martins. The team involves researchers from Federal University of Minas Gerais (UFMG) and
Universidade de Brasília (UnB) in Brazil as well as Centre Bouffard-Vercelli USSAP Perpignan in
France. The research carried in GOIABA considers approaches to motor assistance that combine
mechatronic systems and functional electrical stimulation (FES). The use of FES in interaction with
an instrumented tricycle for instance allows people with spinal cord injuries to pedal. FES can also
be combined with orthoses, in particular for the upper limb. Our aim is to develop a collaboration
to optimize the outcomes of hybrid mechatronic devices in the context of functional rehabilitation.

10.1.2 Other international collaborations

François Bailly has a strong partnership with Université de Montréal (S2M lab) around the development
of the Bioptim software and the work of several PhD students and postdoc researchers.

10.2 International research visitors

Other international visits to the team Prof. Henrique Resende Martins (Federal University of Minas
Gerais (UFMG), Brazil) visited CAMIN team during 1 week in December 2023 within GOIABA associate
team. He was accompanied by a Master student.

10.2.1 Visits to international teams

Research stays abroad Christine Azevedo spent 2 weeks in November 2023 in Federal University of
Minas Gerais (UFMG), Brazil within GOIABA associate team. 5 participants were included in ORTHYB
protocol and 3 experimental sessions with each of them realized.

10.3 European initiatives

10.3.1 Horizon Europe

AI-HAND AI-HAND project on cordis.europa.eu

Title: Advanced Intelligent stimulation device: HAND movement restoration

Duration: From August 1, 2023 to February 28, 2027

Partners:

• INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE (INRIA),

France

• CORTEC GMBH (CORTEC), Germany

• ALBERT-LUDWIGS-UNIVERSITAET FREIBURG (ALU-FR), Germany

• NEURINNOV, France

• UNION SANITAIRE ET SOCIALE POUR L’ACCOMPAGNEMENT ET LA PREVENTION (USSAP),

France

• CENTRE NATIONAL DE REEDUCATION FONCTIONNELLE ET DE READAPTATION, Luxem-

bourg

Inria contact: Christine Azevedo

Coordinator: Christine Azevedo, INRIA

Summary: Very advanced stimulation paradigms applied to peripheral nervous system (PNS) have been
studied for years even decades among which the 3D current distribution through multi-contact
epineural electrodes. Non rectangular stimulus waveforms are also of strong interest to provide
more efficient or fibre type selective stimulation. However none were implemented in an Active
Implanted Medical Device and thus almost none validated through clinical trials. One of the reasons

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Inria Annual Report 2023

is the high complexity of the needed analogue front end and its safe control by a microcontroller
or a digital system. AI-HAND project aims at developing a breakthrough, ASIC based technology,
together with a specific self adapting epineural multi contact electrode to provide such an AIMD.
The demonstration of the clinical relevance of such an approach will be achieved through a first-
in-man proof of concept aiming at the restoration of hand movements in persons with complete
quadriplegia. It means that a full innovative device should be developed and validated in animals,
but the real added value will be supported by the clinical trial; indeed, no animal model exists
while the clinical needs is clearly stated by clinicians and patients. Thus this project will innovate
concerning both the technology and the therapeutic approach with a minimally invasive concept.
Indeed, spatial selectivity allows to stimulate nerves selectively targeting muscles through 3D
currents shaping instead of implanting one electrode per muscle. The technology clearly addresses
generic issues so that the paradigms and the innovative technology can be further used to stimulate
the central nervous system (spinal cord and brain) and, on a long term basis, may drastically open
new therapeutics for medical needs that are still unmet.

10.3.2 H2020 projects

RESCUEGRAPH FLAG-ERA JTC(2021-24) The RESCUEGRAPH project aims at using graphene-based flex-
ible electrodes as the neural interface of a FES system to reproduce and allow rehabilitation of gait and, at
the sametime, to drive neuroplasticity at spinal and brain levels to enhance functional recovery of mo-tor
and somatosensory processing after SCI. Partners: Universitat Autonoma de Barcelona(Spain), Fundacio
Institut Catala de Nanociencia i Nanotecnologia (Spain), Bogazici University (Turkey), Neurinnov (France)

10.4 National initiatives

INRIA-INSERM Phd thesis grant (2023-26)

We obtained a grant to finance the PhD thesis of Gabriel Graffagnino between CAMIN and INSERM

Tonic team in collaboration with Institut Saint Pierre (Palavas)

ANR Grasp-It (2019-24)

Design and evaluation of a tangible and haptic BCI for upper limb rehabilitation after stroke. The
project aims to recover upper limb control improving the kinesthetic motor imagery (KMI) generation of
post-stroke patients using a tangible and haptic interface within a gamified Brain-Computer Interface
(BCI) training environment.

ARC FOUNDATION for Research Against Cancer (2022-2025)

Guiding brain tumor surgery in real time using electrophysiology (collaboration with Pr Hugues Duffau
and Pr Emmanuel Mandonnet). During the resection of brain tumors, the neuro-surgeon has substantial
imaging data allowing him/her to plan his/her gesture upstream. However, during the actual surgical
gesture, in real time, this imaging becomes ineffective due to the deformation of the brain (so called brain
shift). It is then possible to use direct electrical stimulation of the brain in an awake patient who cooper-
ates with the neurosurgeon to determine the functional areas and those which are not. When patients are
under general anesthesia this possibility no longer exists. We have planned to use the electrophysiology
evoked by the DES of the brain during brain surgery to diagnose and determine the location the tumor
and the anatomical connectivity on-line in order to guide the surgery in awake patients or under general
anesthesia. This needs to go beyond the proof of concept, we have alrealdy performed, and necessitates
to address and solve some methodological challenges. At a fundamental level, this will also help to better
understand the electrophysiological effect of DES in order to optimize its use.

BAYFRANCE (France Bavaria) (2022-2023)

Collaboration and exchange with Pr Andréa Szélenyi, Munich Hospital on the theme of brain evoked

potentials and their use in Neurosurgery.

Project CAMIN

21

LABEX NUMEV thesis co-funding (2021-2024)

Additional funding through an agree-ment with the APHP (Paris) and Pr Emmanuel Mandonnet. Felix

Schlosser-Perrin thesis.

AGILISTIM-SITE MUSE grant - Soutien a la recherche (2021-23)

AGILISTIM proposes to implant 3 epineural electrodes around the median, radial and ulnar nerves, just
above the elbow of volunteer participants with complete tetraplegia for 30 days. The multi-contact neural
stimulation will synergistically activate the forearm muscles to trigger: hand opening, a digito-palmar
grip or a functional terminal grip. The project must consolidate and extend the scientific results of the
previous work and the innovative technologies which result from it. It should allow to reach a crucial
proof-of-concept stage before the development of a unique finalized product responding to an unsolved
need in order to improve the quality of life and the autonomy of the users.

Human Lab Inria (HLI) (2021-24)
Exploratory Research Action.

10.5 Regional initiatives

OPTICYCLE (2023-2024)

Occitanie region’s Défi Clef Robotique centrée sur l’humain finances the postdoc of Sabrina Otmani.

PLASTICISTIM (2023-2026)

Occitanie region’s EMERGENCE call for projects finances half of the PhD thesis salary of Jonathan

Baum (PLASTICISTIM Project).

The PLASTICISTIM project can be described as a complementary initiative to the AI-Hand project. Its
aim is to study the benefits of combining peripheral nerve stimulation (PNS) - as investigated in AI-Hand
- with spinal cord stimulation (SCS) for restoring motor function in spinal cord injured individuals. The
aim of this combination is to potentiate the direct restoration of motor function enabled by PNS with a
progressive refinement of movements due to SCS. Indeed, recent studies attest to the impact of SCS in
facilitating the passage of degraded voluntary commands and also in the progressive restoration of motor
functions (following long-term clinical trials combining SCS and physical rehabilitation exercise). Actually,
the literature does not reference any study exploring this combination and the aim of the PLASTICISTIM
project, which should be seen as a proof of concept, is to pave the way for a new therapeutic approach
enabling the restoration of numerous functions in people with spinal cord injuries. PLASTICISTIM is the
topic of Jonathan Baum’s PhD thesis - which started in December 2023 - and will be based on alternating
phases of in vivo exploration (on large animals - pigs) and biosignals processing. The project is currently
at the literature survey stage, but should be based on transcutaneous SCS in order to benefit from its ease
of access, low cost and non-invasive nature.

11 Dissemination

Participants: Christine Azevedo-Coste,

François Bailly,

Jonathan Baum,
François Bonnetblanc, Charles Fattal, Lucas Fonseca, Gab-
riel Graffagnino, Thomas Guiho, David Guiraud, Ronan Le Guillou,
Tiago Coelho Magalhaes, Valentin Maggioni, Etienne Moullet,
Sabrina Otmani, Olivier Rossel, Felix Schlosser-Perrin, Clotilde Turpin.

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Inria Annual Report 2023

11.1 Promoting scientific activities

11.1.1 Scientific events: organisation

Member of the organizing committees

• Christine Azevedo was member of the organizing committee of IFESS at RehabWeek 2023 (Singa-

pour).

• François Bailly was organizer of an invited workshop on trajectory optimization in biomechanics
at the 18th International Symposium on Computer Methods in Biomechanics and Biomedical
Engineering in Paris, 2023.

11.1.2 Scientific events: selection

Reviewer

• Christine Azevedo participated in the Researchers with disabilities 2023 campaign

11.1.3 Journal

Member of the editorial boards

• Christine Azevedo is member of the International Functional Electrical Stimulation Society (IFESS)

society board.

• Christine Azevedo is member of editorial boards of Frontiers in Neurology and Frontiers in Neur-
oscience and associate editor for Institute of Electrical and Electronics Engineers Robotics and
Automation Letters (IEEE RA-L) and IEEE EMBC (Engineering in Medicine and Biology Society)
(Theme 6).

• Christine Azevedo and Lucas Fonseca are Guest Editors in Sensors Special Issue "Sensors for

Artificial Movement Control".

Reviewer - reviewing activities

• Christine Azevedo was reviewer for IEEE TNSRE (Transactions on neural systems and rehabilitation
engineering), SENSORS MDPI, Frontiers in Neurorobotics Frontiers in Neuroscience, Journal of
NeuroEngineering and Rehabilitation...

• Thomas Guiho was reviewer for Journal of Neural Engineering, Neuromodulation: Technology at

Neural Interface, Neurophysiologie Clinique...

• François Bailly was reviewer for IEEE Robotics and Automation Letters (IEEE RA-L), IEEE Intelligent
Robots and Systems (IROS), IEEE International Conference on Robotics and Automation (ICRA),
Medical & Biological Engineering & Computing...

• Tiago Coelho Magalhaes was reviewer for Research on Biomedical Engineering.

• Olivier Rossel was reviewer for Journal of Neural Engineering, Medical & Biological Engineering &

Computing.

11.1.4 Invited talks

• Master class g.tec "BCI & NEUROTECH MASTERCLASS FRANCE" 19 septembre 2023 (link): François

Bonnetblanc, Olivier Rossel, Félix Schlosser-Perrin France

• Inomed user meeting 28 novembre 2023: François Bonnetblanc, Emmendingen, Germany

Project CAMIN

23

• Journées nationales de la robotique humanoïde, François Bailly, 5-7 juillet 2023 Bordeaux (France).

• Christine Azevedo presented AGILIS project during INRIA Sciendific Days JSI in August 2023 (Bor-

deaux).

• Christine Azevedo presented HumanLab HLI actions during a workshop about accessibilité at

INRIA Rennes in October 2023.

• Christine Azevedo presented FREEWHEELS project during the European Week for the Employment

of People with Disabilities (SEEPH) in November 2023 (INRIA Sophia Antipolis).

11.1.5 Research administration

• Thomas Guiho is responsible for the “Neuroprostheses” teaching unit. This unit is an option
common to all the masters of the Information and Communication Technologies (ICT) for health
training package.

• Thomas Guiho was part of the pool of session secretaries for the Sophia Antipolis project-team

committees until September 2023.

• François Bailly is part of the pool of session secretaries for the Sophia Antipolis project-team com-

mittees since October 2023.

• François Bailly is a member of the NICE committee (postdoc selection).

• Christine Azevedo is a member of COERLE (Inria Comité d’éthique)

• Christine Azevedo is a member of projects committee office (BCEP)

• Christine Azevedo and Roger Pissard-Gibollet (SED Grenoble) coordinate the HumanLab Inria

action project.inria.fr/humanlabinria

11.2 Teaching - Supervision - Juries

11.2.1 Teaching

• Master ICT for Health, Neuroprostheses option: Thomas Guiho, “Neuroanatomy and Motor Con-

trol”, 6h, M1, Montpellier University, France

• Master ICT for Health, Neuroprotheses option: Ronan Le Guillou, “Control basics and signal pro-

cessing”, 10.5h, M1, Montpellier University, France

• Master ICT for Health, Neuroprotheses option: Olivier Rossel, “Modeling of the peripheral nervous

system”, 6h, M1 and M2, Montpellier University, France

• Master ICT for Health, Neuroprotheses option: Felix Schlosser-Perrin, “Electrophysiological map-

ping during awake brain surgery”, 3h, M1, Montpellier University, France

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Inria Annual Report 2023

• Master ICT for Health, Neuroprotheses option: Charles Fattal, “Neuroprosthesis and motor support

strategies after spinal cord injuries”, 3h, M2, Montpellier University, France

• Master ICT for Health, Neuroprotheses option: Sabrina Otmani, “Strategies of control”, 3h, M2,

Montpellier University, France

• Master ICT for Health, Neuroprotheses option: Jonathan Baum, “Signal processing of neural sig-

nals”, 3h, M2, Montpellier University, France

• Master ICT for Health, Neuroprotheses option: Clotilde Turpin, “Activating Function”, 9h, M2,

Montpellier University, France

• Master ICT for Health, Neuroprotheses option: Gabriel Graffagnino, “Sensory supplementation:

overview and prospects”, 1.5h, M2, Montpellier University, France

• Master ICT for Health, Neuroprotheses option: Valentin Maggioni, “Biomaterials and biocompatib-

ility”, 1.5h, M2, Montpellier University, France

• Master Cognitive and integrated neuroscience, "Sensorimotor Deficiencies and palliative strategies
teaching unit": Thomas Guiho, “Implantable neuroprosthesis for motor rehabilitation”, 4.5h, M2,
Paul Sabatier University, Toulouse, France

• Master Health, "Integrated Pathophysiology": Thomas Guiho, “Neuroprosthesis and Robots for

motor replacement”, 4.5h, M2, Montpellier University, France

• Master clinical neuropsychology in adults, "Cognitive rehabilitation and contributions of new tech-
nologies": Ronan Le Guillou, “New technologies for rehabilitation after cognitive impairements”,
3h, M2, Jean Jaurès University, Toulouse, France

• Engineering degree, "Microelectronics and automation": Oliver Rossel, “Discrete event system”,

30h, 4th year, Polytech Engineering School, Montpellier, France

• Master ICT for Health, "Health device engineering": David Guiraud, “Regulatory pathway for Med-
ical Devices under the new regulation MDR 2017/745”, 12h, M1, Montpellier University, France

• Master in Sport, Education and Healthcare, "Science, Technology, Movement": David Guiraud,
“Electrophysiology of movement, Basics in Electrophysiology of movement”, 6h, M2, Montpellier
University, France

• Master in Pharmaceutical Sciences, "Neuroprosthesis": Félix Schlosser-Perrin, “Signal processing

and basic electronics”, 64h, L1, Montpellier University, France

Project CAMIN

11.2.2 Supervision

25

• PhD defended on June 19th 2023: Lucie William, "Selective implanted neural stimulation to recover
the prehension for quadriplegic", University of Montpellier-Inria-NEURINNOV, october 2019-June
2023, supervised by David Guiraud and Christine Azevedo

• PhD defended on August 28th: Clément Trotobas, "Design of arm assistive technologies", University
of Montpellier-Inria-Dayton University, september 2020-september 2023, supervised by Christine
Azevedo and Andrew Murray (Dayton Univ)

• PhD defended on December 19th: Ronan Le Guillou, "Design of a wearable neuroprosthetic
solution for arm rehabilitation in post-stroke hemiplegia", University of Montpellier-Inria-CHU
Toulouse, December 2020-December 2023, supervised by Christine Azevedo and David Gasq (CHU
Toulouse)

• PhD in progress : Félix Schlosser-Perrin (2021-...), "Modélisation des effets électrophysiologiques
de la stimulation électrique sur le cerveau et preuves expérimentales en chirurgie des tumeurs
cérébrales : variation de l’intensité, de la distance inter-électrode et de la largeur du pulse de
stimulation", University of Montpellier, september 2021-september 2024, supervised by François
Bonnetblanc and Emmanuel Mandonnet (PU-PH in Neurosurgery at APHP)

• PhD in progress : Laurence Colas (2022-...) Développement, contrôle et validation d’un système
mécatronique pour orthèse d’assistance des membres inférieurs. Thèse CIFRE - société REEV.
Supervised by François Bailly and Christine Azevedo.

• PhD in progress : Clotilde Turpin (2022-...), "Variation des paramètres de la stimulation électrique
directe dans le cadre de la chirurgie des tumeurs cérébrales: Typologie des réponses ", Inria, super-
vised by François Bonnetblanc.

• PhD in progress : Gabriel Graffagnino (November 2023-...) , " Apport des nouvelles technologies
numériques dans la rééducation pédiatrique : stimulation électrique fonctionnelle, réalité virtuelle
et robotique d’assistance dans la rééducation de la marche chez l’enfant atteint de paralysie
cérébrale", Inria-INSERM-Institut St Pierre, supervised by Christine Azevedo, Benoît Sijobert,
Karinne Patte and David Gasq.

• PhD in progress : Valentin Maggioni (November 2023-...), "Développement d’un simulateur neur-
omusculosquelettique du membre supérieur sous stimulation électrique fonctionnelle", University
of Montpellier-Inria, supervised by François Bailly and Christine Azevedo.

• PhD in progress : Jonathan Baum (December 2023-...), "Precise neural stimulation and underlying
electrophysiological mechanisms", University of Montpellier-Inria-NEURINNOV, supervised by
Thomas Guiho, David Guiraud and Christine Azevedo.

• Internship : Alice Hernot, "Comparaison de systèmes de capture de mouvement : application à la

main", Inria, March 2023-August 2023, supervised by François Bailly.

• Internship : Fanny Gerbet, March 2023-August 2023, "Links between electromyographic signals
(EMGs) and evoked functional movements in the context of implanted peripheral nerve stimula-
tion.", University of Montpellier-Inria, supervised by Thomas Guiho.

• Internship : Houssam Salama Alhandi (June 2023-August 2023), "Conduction velocity in long-range

Axono-cortical evoked potentials (ACEP))", Inria, supervised by François Bonnetblanc.

26

11.2.3 Juries

Inria Annual Report 2023

Christine Azevedo was reviewer of the PhD thesis of KAJGANIC Petar ENS de Lyon in september 2023.

11.3 Popularization

11.3.1 Internal or external Inria responsibilities

• Thomas Guiho is the Montpellier referent for the "1 Chercheur, 1 Classe : Chiche!" programme.

• François Bailly is the Montpellier contact for the AGOS local management committee.

11.3.2 Articles and contents

AGILIS project was presented in several supports, here is a selection:

• MidiLibre Newspaper

• LUM university Montpellier Magazine

• Allo Docteurs website

• Mag Santé France 5 - Paralysie : Des électrodes pour retrouver de la mobilité

11.3.3 Education

Christine Azevedo gave an introduction to programming interventions using MICROBIT and MCQUEEN
Robot in Collège Léon Cordas (4 sessions of 3 hours).

Christine Azevedo teached how to use Thymio Robot with 6-10 years old children to introduce

programming to 6 teachers of Ecole Valfalis Montbazin (5 hours) .

11.3.4 Interventions

Christine Azevedo participated in Robotic Days organized by Agde High School in April 2023.

Christine Azevedo, Clotilde Turpin, Etienne Moullet, Tiago Coelho Magalhaes, Sabrina Otmani parti-

cipated in Fabrikarium hackaton in June 2023 for HumanLab INRIA, in Palavas.
CAMIN team welcomed 1 week internships of 2 schoolchildren this year.

12 Scientific production

12.1 Major publications

[1] C. Azevedo Coste, L. William, L. Fonseca, A. Hiairrassary, D. Andreu, A. Geffrier, J. Teissier, C. Fattal
and D. Guiraud. ‘Activating effective functional hand movements in individuals with complete
tetraplegia through neural stimulation’. In: Scientific Reports 12.1 (Dec. 2022), p. 16189. DOI: 10.10
38/s41598-022-19906-x. URL: https://hal.archives-ouvertes.fr/hal-03817189.

[2] A. Boyer, S. Ramdani, H. Duffau, M. Dali, M. Vincent, E. Mandonnet, D. Guiraud and F. Bonnetblanc.
‘Electrophysiological Mapping During Brain Tumor Surgery: Recording Cortical Potentials Evoked
Locally, Subcortically and Remotely by Electrical Stimulation to Assess the Brain Connectivity
On-line’. In: Brain Topography: a Journal of Cerebral Function and Dynamics (2020). DOI: 10.1007
/s10548-020-00814-0. URL: https://hal.inria.fr/hal-03106388.

[3] C. Fattal, B. Sijobert, A. Daubigney, E. Fachin-Martins, B. Lucas, J.-M. Casillas and C. Azevedo Coste.
‘Training with FES-assisted cycling in a subject with spinal cord injury: Psychological, physical and
physiological considerations’. In: Journal of Spinal Cord Medicine (July 2018), pp. 1–12. DOI: 10.10
80/10790268.2018.1490098. URL: https://hal.archives-ouvertes.fr/hal-01875806.

Project CAMIN

27

[4] T. Guiho, C. Delleci, C. Azevedo Coste, C. Fattal, D. Guiraud, J.-R. Vignes and L. Bauchet. ‘Impact
of direct epispinal stimulation on bladder and bowel functions in pigs: A feasibility study’. In:
Neurourology and Urodynamics 37.1 (Jan. 2018), pp. 138–147. DOI: 10.1002/nau.23325. URL:
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01539038.

[5] F. M. Petrini, M. Bumbasirevic, G. Valle, V. Ilic, P. Mijovi´c, P. ˙Cvan˙cara, F. Barberi, N. Katic, D. Borto-
lotti, D. Andreu, K. Lechler, A. Lesic, S. Mazic, B. Mijovi´c, D. Guiraud, T. Stieglitz, A. Alexandersson,
S. Micera and S. Raspopovic. ‘Sensory feedback restoration in leg amputees improves walking
speed, metabolic cost and phantom pain’. In: Nature Medicine 25.9 (Sept. 2019), pp. 1356–1363. DOI:
10.1038/s41591-019-0567-3. URL: https://hal-lirmm.ccsd.cnrs.fr/lirmm-02282558.

[6] F. M. Petrini, G. Valle, M. Bumbasirevic, F. Barberi, D. Bortolotti, P. Cvancara, A. Hiairrassary, P.
Mijovic, A. O. Sverrisson, A. Pedrocchi, J.-L. Divoux, I. Popovic, K. Lechler, B. Mijovic, D. Guiraud,
T. Stieglitz, A. Alexandersson, S. Micera, A. Lesic and S. Raspopovic. ‘Enhancing functional abilities
and cognitive integration of the lower limb prosthesis’. In: Science Translational Medicine 11.512
(Oct. 2019). DOI: 10.1126/scitranslmed.aav8939. URL: https://hal-lirmm.ccsd.cnrs.fr
/lirmm-02307824.

[7] W. Tigra, B. Navarro, A. Cherubini, X. Gorron, A. Gélis, C. Fattal, D. Guiraud and C. Azevedo Coste.
‘A novel EMG interface for individuals with tetraplegia to pilot robot hand grasping’. In: IEEE
Transactions on Neural Systems and Rehabilitation Engineering 26.2 (2018), pp. 291–298. DOI: 10.1
109/TNSRE.2016.2609478. URL: https://hal.archives-ouvertes.fr/lirmm-01373668.

[8] M. Vincent, O. Rossel, B. Poulin-Charronnat, G. Herbet, M. Hayashibe, H. Duffau, D. Guiraud and F.
Bonnetblanc. ‘Case report: remote neuromodulation with direct electrical stimulation of the brain,
as evidenced by intra-operative EEG recordings during wide-awake neurosurgery’. In: Clinical
Neurophysiology (Nov. 2015). Letter to the editor, pp. 1752–1754. DOI: 10.1016/j.clinph.2015
.11.005. URL: https://hal-lirmm.ccsd.cnrs.fr/lirmm-01237964.

12.2 Publications of the year

International journals

[9] A. Ceglia, F. Bailly and M. Begon. ‘Moving Horizon Estimation of Human Kinematics and Muscle
Forces’. In: IEEE Robotics and Automation Letters 8.8 (4th July 2023), pp. 5212–5219. DOI: 10.1109
/LRA.2023.3291921. URL: https://inria.hal.science/hal-04151820.

[10] P. ˇCvanˇcara, G. Valle, M. Müller, I. Bartels, T. Guiho, A. Hiairrassary, F. Petrini, S. Raspopovic, I.
Strauss, G. Granata, E. Fernandez, P. M. Rossini, M. Barbaro, K. Yoshida, W. Jensen, J.-L. Divoux,
D. Guiraud, S. Micera and T. Stieglitz. ‘Bringing sensation to prosthetic hands—chronic assessment
of implanted thin-film electrodes in humans’. In: npj Flexible eletronics 7.1 (19th Nov. 2023), p. 51.
DOI: 10.1038/s41528-023-00284-x. URL: https://inria.hal.science/hal-04296540.

[11] E. Goubault, F. Verdugo, F. Bailly, M. Begon and F. D. Maso. ‘Inertial Measurement Units and
Partial Least Square Regression to Predict Perceived Exertion During Repetitive Fatiguing Piano
Tasks’. In: IEEE Transactions on Human-Machine Systems 53.4 (19th June 2023), pp. 802–810. DOI:
10.1109/THMS.2023.3278874. URL: https://inria.hal.science/hal-04133070.

[12] B. Michaud, F. Bailly, E. Charbonneau, A. Ceglia, L. Sanchez and M. Begon. ‘Bioptim, a Python
Framework for Musculoskeletal Optimal Control in Biomechanics’. In: IEEE Transactions on Systems,
Man, and Cybernetics: Systems 53.1 (Jan. 2023), pp. 321–332. DOI: 10.1109/TSMC.2022.3183831.
URL: https://inria.hal.science/hal-03932361.

[13] P. Puchaud, F. Bailly and M. Begon. ‘Direct multiple shooting and direct collocation perform
similarly in biomechanical predictive simulations’. In: Computer Methods in Applied Mechanics
and Engineering 414 (Sept. 2023), p. 116162. DOI: 10.1016/j.cma.2023.116162. URL: https:
//inria.hal.science/hal-04151816.

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Inria Annual Report 2023

[14] O. Rossel, M. Chateaux, N. Jarrassé, F. Vérité, A. Touillet, C. Nicol, J. Paysant and J. B. De Graaf.
‘Phantom movement training without classifier performance feedback improves mobilization
ability while maintaining EMG pattern classification’. In: IEEE Transactions on Medical Robotics
and Bionics 5.1 (20th Jan. 2023), pp. 133–142. DOI: 10.1109/TMRB.2023.3237918. URL: https:
//inria.hal.science/hal-04137971.

[15] O. Rossel, F. Schlosser-Perrin, H. Duffau, R. Masumoto, E. Mandonnet and F. Bonnetblanc. ‘Short-
range axono-cortical evoked-potentials in brain tumor surgery: Waveform characteristics as mark-
ers of direct connectivity’. In: Clinical Neurophysiology 48.8 (Aug. 2023), pp. 550–554. DOI: 10.101
6/j.clinph.2023.05.011. URL: https://inria.hal.science/hal-04135237.

[16] F. Schlosser-Perrin, O. Rossel, H. Duffau, F. Bonnetblanc and E. Mandonnet. ‘How far does electrical
stimulation activate white matter tracts? A computational modeling study’. In: Clinical Neuro-
physiology 153 (July 2023), pp. 68–78. DOI: 10.1016/j.clinph.2023.06.017. URL: https://hal
.science/hal-04166602.

[17] F. Schlosser-Perrin, O. Rossel, H. Duffau, R. Matsumoto, E. Mandonnet and F. Bonnetblanc. ‘The
orientation of the stimulating bipolar probe modulates axono-cortical evoked potentials’. In:
Brain Stimulation 16.4 (June 2023), pp. 1009–1011. DOI: 10.1016/j.brs.2023.06.008. URL:
https://hal.science/hal-04137996.

International peer-reviewed conferences

[18] L. Colas, K. Giraud-Esclasse and R. Temporelli. ‘Mechanical performances of DREEVEN, a novel mo-
torization unit for custom knee orthosis’. In: 48eme Congrès annuel de la Société de Biomécanique.
Grenoble, France, 25th Oct. 2023. URL: https://hal.science/hal-04227858.

[19] E. Moullet, F. Bailly, J. Carpentier and C. Azevedo Coste. ‘Vision-based interface for grasping
intention detection and grip selection : towards intuitive upper-limb assistive devices’. In: Congrès
annuel de la Société de Biomécanique. Grenoble, France, 25th Oct. 2023. URL: https://hal.scie
nce/hal-04141469.

Doctoral dissertations and habilitation theses

[20] C. Trotobas. ‘Restoration of grasping functions through assistive orthoses for individuals with arm
paralysis’. Université de Montpellier, 28th Aug. 2023. URL: https://inria.hal.science/tel-0
4455138.

[21] L. William. ‘Selective Epidural Electrical Stimulation for the Restoration of Grasping in Individuals
with Complete Tetraplegia’. Université de Montpellier, 19th June 2023. URL: https://inria.hal
.science/tel-04455177.

12.3 Other

Patents

[22] D. Andreu, D. Guiraud, B. Sorli and A. Vena. ‘Active implantable medical device’. US20230364431A1

(United States). 16th Nov. 2023. URL: https://hal.science/hal-04461236.

12.4 Cited publications

[23] D. E. Anderson, M. L. Madigan and M. A. Nussbaum. ‘Maximum voluntary joint torque as a function
of joint angle and angular velocity: model development and application to the lower limb’. In:
Journal of Biomechanics 40.14 (2007), pp. 3105–3113.

[24] C. Azevedo Coste, L. William, L. Fonseca, A. Hiairrassary, D. Andreu, A. Geffrier, J. Teissier, C. Fattal
and D. Guiraud. ‘Activating effective functional hand movements in individuals with complete
tetraplegia through neural stimulation’. In: Scientific Reports 12.1 (Dec. 2022), p. 16189. DOI: 10.10
38/s41598-022-19906-x. URL: https://hal.science/hal-03817189.

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[25] N. Jiang and D. Farina. ‘Myoelectric control of upper limb prosthesis: current status, challenges

and recent advances’. In: Front Neuroeng 7.4 (2014), pp. 7–9.

[26] Y. Labbé, J. Carpentier, M. Aubry and J. Sivic. ‘Cosypose: Consistent multi-view multi-object 6d
pose estimation’. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August
23–28, 2020, Proceedings, Part XVII 16. Springer. 2020, pp. 574–591.

[27] T. Novacek, C. Marty and M. Jirina. ‘Project MultiLeap: Fusing Data from Multiple Leap Motion
Sensors’. In: 2021 IEEE 7th International Conference on Virtual Reality (ICVR). 2021, pp. 19–25. DOI:
10.1109/ICVR51878.2021.9483819.

[28] C. Trotobas, F. Marcia Rodrigues Martins Ferreira, H. Martins Resende, A. Murray and C. Azevedo
Coste. ‘Development of a hybrid orthosis solution to reduce fatigue during grasping’. In: RehabWeek.
Rotterdam (Netherlands), July 2022. URL: https://inria.hal.science/hal-03666816v1.

[29] F. Zhang, V. Bazarevsky, A. Vakunov, A. Tkachenka, G. Sung, C.-L. Chang and M. Grundmann.
‘Mediapipe hands: On-device real-time hand tracking’. In: arXiv preprint arXiv:2006.10214 (2020).

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Inria Annual Report 2023

Figure 5: (A) Schematic diagram of the electrophysiological events provoked by the application of
DES to different sites and generating the two evoked responses: 1) DES at the cortical surface and in
the same gyrus for DCR, 2) DES on white matter pathways in the case of ACEP; (B) DCR and ACEP
electrophysiological signals recorded from 8 patients; (C) Drawings showing the different metrics studied;
(D) Diagram of the zero crossing (tzc_1) of the different signals (student test, t-value =-3.12 , pvalue =
0.02); (E) Diagram showing negative vs. positive areas under the curves between 40 and 100 ms for DCR
and ACEP respectively (student test, t-value = -4.05, pvalue = 0.007). (F) Average frequency spectra of DCR
and ACEP respectively (student test, t-value = -4.05, pvalue = 0.007) (G) The power centered on the 50Hz
activity for the 20 and 25 ms windows.

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Figure 6: Segmented anatomy of the various components of the pyramidal neurons that will be activated
by the electrical stimulation and electrical equivalent of each compartment.

Figure 7: Illustration of the adaptive grip selection: different approach movements (represented as arrows
embedding ∆i mp and vhand ) yield either a palmar grip (green) or a pinch grip (purple)

Figure 8: Visualization of the adaptive grasping assistance algorithm

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Inria Annual Report 2023

Figure 9: AGILISTIM setup.

Figure 10: Experimental devices constituting the Prehens-Stroke self-triggered grasping neuroprosthesis.

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Figure 11: Wearable Grasp Neuro Prosthesis used by post-stroke participants at home in autonomy. (A.)
Onboard computer unit (Raspberry Pi 4B) in a wearable bag including a USB microphone. (B.) FES sleeve
garment (Fesia Grasp). (C.) User interface module (M5StickC Plus) with change control modality button
and change prehension type button.

Figure 12: fMRI activation contrast map of paretic hand voluntary opening attempt at the beginning of
study inclusion (Participant 2, brain lesion on the left hemisphere). P-value (FWE): 1e-11

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Inria Annual Report 2023

Figure 13: Grasp-it experimental setup

Figure 14: Sample overview of the brain activity (ERD/ERS) recorded on a participant during kinesthetic
motor imagery tasks of hand opening with FES induced hand opening using the 6 parameters configura-
tions

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Figure 15: ORTHYB setup.

Figure 16: Simulation results of the optimal reaching task.

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Inria Annual Report 2023

Figure 17: Musuculoskeletal model performing FES driven cycling using numerical optimization.

Figure 18: StimRG Gait pattern Control software interface.

Figure 19: Solidworks model of the designed spherical mechanism for a prono-supination orthosis.

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Figure 20: Model of the designed prono-supination orthosis with a forearm.

Figure 21: High-level control law of the active knee orthosis developped with REEV.

Figure 22: Personalized biomechanical model of the patient, used in the inverse dynamics-based control
law of the active knee orthesis.

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Inria Annual Report 2023

Figure 23: CDT optimized architecture using anthropometric data from the user.
<scratchpad>
- Main topic: Inria's CAMIN project for developing neuroprosthetic solutions for sensorimotor deficiencies
- Key points:
  - CAMIN research team focuses on clinical impact, improving functional evaluation and/or patient quality of life
  - Two main research priorities: exploration and understanding of the origins and control of movement, and movement assistance and/or restoration
  - Research program includes exploration of brain potentials evoked by direct electrical stimulation, muscle models and fatigue exploration, and movement interpretation
  - Application domains include movement assistance, movement analysis, and evoked electrophysiology
  - Social and environmental responsibility includes ethics, impact of research results, and collaborations with industry and international partners
- Structure: The document is organized into sections for project-team, activity report, research program, application domains, social and environmental responsibility, highlights of the year, new software, platforms, and open data, new results, and dissemination
- Potential artifacts to ignore: unnecessary web-related elements, such as links, HTML tags, and other web-related elements
</scratchpad>

<final_summary>
The CAMIN project, a research initiative within Inria, aims to develop neuroprosthetic solutions for sensorimotor deficiencies, focusing on clinical impact and improving functional evaluation and/or patient quality of life. The project's research program explores the origins and control of movement, movement assistance and/or restoration, and brain potentials evoked by direct electrical stimulation. CAMIN's application domains include movement assistance, movement analysis, and evoked electrophysiology, while social and environmental responsibility emphasizes ethics and collaborations with industry and international partners. The project has made significant progress in recent years, including the development of new software, platforms, and open data, as well as the publication of several research papers and the initiation of new projects, such as the AI-Hand and PLASTICISTIM projects. Overall, the CAMIN project is a comprehensive and innovative initiative that seeks to improve the lives of individuals with sensorimotor deficiencies.
The CAMIN project, a research initiative within Inria, aims to develop neuroprosthetic solutions for sensorimotor deficiencies, focusing on clinical impact and improving functional evaluation and/or patient quality of life. The project's research program explores the origins and control of movement, movement assistance and/or restoration, and brain potentials evoked by direct electrical stimulation. CAMIN's application domains include movement assistance, movement analysis, and evoked electrophysiology, while social and environmental responsibility emphasizes ethics and collaborations with industry and international partners. The project has made significant progress in recent years, including the development of new software, platforms, and open data, as well as the publication of several research papers and the initiation of new projects, such as the AI-Hand and PLASTICISTIM projects. Overall, the CAMIN project is a comprehensive and innovative initiative that seeks to improve the lives of individuals with sensorimotor deficiencies.