Research Intern In Processing Of Muscle Activities Evoked By Functional Neural Stimulation H/F - 34

A propos d'Inria

Inria est l'institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l'interface d'autres disciplines. L'institut fait appel à de nombreux talents dans plus d'une quarantaine de métiers différents. 900 personnels d'appui à la recherche et à l'innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'eorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.Research intern in processing of muscle activities evoked by functional neural stimulation
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : Convention de stage

Niveau de diplôme exigé : Bac +4 ou équivalent

Autre diplôme apprécié : equivalent to a four-year or five-year university degree

Fonction : Stagiaire de la recherche

A propos du centre ou de la direction fonctionnelle

Inria is the French National Institute for Research in Digital Science, of which the Inria Côte d'Azur University Center is a part. With strong expertise in computer science and applied mathematics, the research projects of the Inria Côte d'Azur University Center cover all aspects of digital science and technology and generate innovation. Based mainly in Sophia Antipolis, but also in Nice and Montpellier, it brings together 47 research teams and nine support services. It is active in the fields of artificial intelligence, data science, IT system security, robotics, network engineering, natural risk prevention, ecological transition, digital biology, computational neuroscience, health data, and more. The Inria Center at Université Côte d'Azur is a major player in terms of scientific excellence, thanks to the results it has achieved and its collaborations at both European and international level.

Contexte et atouts du poste

Functional Electrical Stimulation (FES) is a key technology for restoring lost motor functions, particularly in individuals with partial or complete paralysis. Since motor commands and muscle contractions are conveyed through electrical signals, electrical stimulation of nerves provides an effective means of eliciting muscle contractions. In this context, when rehabilitation and/or surgery fail to restore limb mobility, direct stimulation of the nerves in the arm can restore movement in the wrist and fingers. Given that nerves convey information from and to many muscles and have a variable architecture - which differs from one individual to another - one of the main scientific and clinical challenge is to deliver stimulation in a precise and selective manner, so that stimulation-evoked movements effectively support motor actions.

A critical issue in FES-based movement assistance is the selective recruitment of muscles, which directly impacts motor control quality, smoothness of movement, and functional outcomes. Achieving this level of control requires a detailed analysis of electrically evoked electromyographic (eEMG) signals. eEMG signals measured through surface electrodes (located on the skin above muscles) contain rich but complex information, as they often represent a mixture of activities from multiple muscles.

Decomposing these signals is therefore essential to:

- Identify the respective contributions of target and neighboring muscles,
- Quantify and improve the selectivity of electrical stimulation,
- Design optimized stimulation strategies for closed-loop motor assistive control,
- Enhance the reliability of FES systems for clinical movement assistance.

This project is part of a broader research effort aimed at developing advanced EMG signal processing tools to support neuroprosthetic control and motor assistance, combining both theoretical and experimental approaches. You will contribute to cutting-edge research within an internationally recognized team.

Internship Objectives

The main objective of this internship is to develop, compare, and evaluate three different approaches for decomposing EMG signals evoked by functional electrical stimulation. These methods will be applied to both experimental data and simulated signals generated using a forward model that explicitly controls signal components.

Preliminary work

In order to objectively assess the project's progress, existing MATLAB scripts for processing EMG signals will be made available to the student. Similarly, a set of eEMG data from a clinical trial investigating the impact of arm nerve stimulation on the restoration of wrist and hand function in four individuals with tetraplegia will be provided.

Mission confiée

The technical objective is to improve eEMG signal decomposition techniques, such as Semi Non-Negative Matrix Factorization (SNNMF), in order to separate and quantify the contributions of different muscular sources. This work will build on the team's previous work and will be evaluated/refined using a simulation-generated dataset.

In a second stage, these algorithms will be tested on real data from a clinical trial before comparison of the estimated muscle recruitment levels obtained with this approach with those derived from time-frequency decomposition methods and parametric fitting techniques - other methods also investigated within the team.

Principales activités

- Activity 1 : State-of-the-art review and system analysis
Review of EMG decomposition methods and muscle recruitment models for assisted movement control.
- Activity 2 : Algorithm development and implementation
Design, implementation, and optimization of EMG decomposition algorithms in MATLAB.
- Activity 3 : Simulation and experimental validation
Testing on controlled simulated data and recorded EMG signals.

Compétences

- Programming language: MATLAB or Python (knowledge of MATLAB would be a plus)
- Language: French or English. A good level of English would be an advantage for French-speaking students.

Avantages

- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage

Rémunération

Traineeship grant depending on attendance hours