PhD Position F/M Improving post-stroke motor rehabilitation through EMG and gamification (F/M)

Inria, the French national research institute for the digital sciences; France; Sur place; EUR 30 000 - 40 000; Plein temps

Résumé du poste

A leading research institution in France is looking for a Researcher in telerehabilitation to enhance post-stroke care through innovative EMG signal processing and gamification techniques. The role involves developing algorithms and applications to support patient rehabilitation while ensuring rigorous experimental validation of methods. The successful candidate will work collaboratively with both academic and industrial partners, with opportunities for flexible working arrangements and comprehensive benefits.

Prestations

7 weeks of annual leave

Flexible working hours

Professional equipment provided

Qualifications

• Experience in EMG processing and muscle activity detection.
• Familiarity with gamification elements and user engagement strategies.
• Background in human-machine interaction preferred.

Responsabilités

• Develop algorithms for detecting muscle contractions.
• Create a telerehabilitation application with gamification elements.
• Conduct experimental validation of the designed methods.

Connaissances

EMG signal processing

Gamification design

Human-Machine Interaction (HMI)

Formation

Master's degree in relevant field

Description du poste

Inria, the French national research institute for the digital sciences

Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1) Country France Application Deadline 14 Jan 2026 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 38.5 Offer Starting Date 1 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 2025-09666 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Strokes are the leading cause of disability in France. Motor rehabilitation is crucial to reducing the effects of strokes. Although rehabilitation with a physiotherapist is essential, their availability is limited. This is why telerehabilitation is an important complement to post-stroke care. The challenges of telerehabilitation include the difficulty for patients to verify that exercises are being performed correctly and to maintain the motivation to follow their rehabilitation programme regularly.

This thesis is a collaboration between the Loki research team, specialising in Human-Machine Interaction (HMI), and Myodev, a company developing a rehabilitation solution based on EMG sensors. Our goal is to improve EMG telerehabilitation by accurately measuring muscle activity to ensure that exercises are performed correctly. In addition, we want to integrate gamification elements to encourage patients to follow their rehabilitation programme regularly.

The first phase aims to improve EMG signal processing, building on the candidate's master's degree internship. Initially, we will automatically and accurately detect the characteristics of a muscle contraction, such as its start, end and intensity. Next, we will optimise the algorithm developed during the internship to ensure effective real-time detection of muscle contractions. To do this, we will collect a set of data to obtain a reference, adjust the algorithm parameters and validate the automatic detections.

In the second phase, we will develop a telerehabilitation application incorporating gamification elements. We will base this on exercises validated by physiotherapists that patients can perform independently, with automatic validation of progress thanks to our muscle contraction detection and characterisation system. We will design gamification elements to encourage patients to follow their rehabilitation programme. One initial idea is to create forms of real-time biofeedback. Another idea would be to use the characteristics of contractions as input events for video games. The effectiveness of the new methods will be validated by comparative studies with users.

A third phase will focus on integrating additional sensors (IMU or other) to better track patient movements. This will involve combining information from the various sensors to estimate patient movements and adapt feedback and gamification.

All this work will be validated with therapists and patients through laboratory and field experiments, which will be subject to validation by an ethics committee.

• State of the art in telerehabilitation, particularly through gamification
• Improvement of the algorithm for detecting muscle contractions on an EMG signal
• Experimental validation of the detection algorithm and its parameters
• Design of video games controlled by muscle contractions
• Comparative study of gamification methods
• 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 and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities