PhD in Pattern recognition of bionic upper-limb devices/prosthetics

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PhD in Pattern recognition of bionic upper-limb devices/prosthetics

« on: December 17, 2022, 20:16:37 pm »

PhD Position: Machine Learning/ pattern recognition of bionic upper-limb devices in activities of daily living

The goal of upper-limb prostheses is to restore lost functionalities and autonomy in daily living tasks, work and social activities. The commercial solutions range from anything between simplistic body-powered hooks to advanced multiarticulated myoelectrically controlled hands. Most of the latter are designed to match the appearance and functionalities of the human hand. Such hands enables one to perform several hand motions through coordinated activation of independently motorized fingers.

These dexterous bionic devices usually use a pair of surface electromyography (sEMG) sensors to control one degree of freedom (DOF) at a time and adopt switching techniques via muscle co-activation, a mobile application and short-range proximity sensors to select the required grasp sequence. However, many consider such sophisticated myoelectric devices unreliable and difficult to use bringing out large variablity between the solutions available and users’ day-to-day needs. Applications are invited for a PhD student to work on the development and application of machine learning/ pattern recognition methods for better control and use of upper-limb prosthetic device in activities of daily living.

The candidate will closely work with Dr. Amartya Ganguly under the supervision of Prof. Alois Christian Knoll (The chair of Robotics, Artificial Intelligence and Real-Time systems) and Prof. Sami Haddadin (The Munich Institute of Robotics and Machine Intelligence (MIRMI) as one of TUM’s Integrative Research Institutes (IRI).

The candidate will be expected to:

Design, develop and modify ANN frameworks
Plan and conduct experiments, both individually and in collaboration with clinical experts
Acquire sEMG, motion capture and other related data.
Process and analyse signals in realtime
Generate computational models for simulation in loop evaluation and validation processes.

This work will contribute to a better use of myoelectric prosthesis among people with limb difference, development of new prosthetic devices driven by AI and regulatory procedures for such devices.

Interested applicants should send the necessary documents via email to applications@mirmi.tum.de quoting “PhD in AI driven upper limb prosthesis” in the e-mail subject line. Only shortlisted candidates will be notified. Preference will be given to applications received before January 10th, 2023 as a strict deadline.

More: https://portal.mytum.de/jobs/wissenschaftler/NewsArticle_20221205_152920


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