PhD scholarship in Machine Learning and Accessible Music Interfaces for Neurorehabilitation

Stroke patients who suffer from hemiparesis often reduce the use of the affected extremity, consequently leading to the further deterioration of the related motor function. Although traditional physiotherapy techniques have been shown to be effective in treating hemiparesis, such techniques present several limitations. In this PhD project, we propose to investigate novel music-based rehabilitation approaches in which patients control digital music instruments using motion capture sensors (e.g. webcam, mobile devices gyroscopes and accelerometers) and electromyogram sensors (e.g. Myo). This approach to stroke rehabilitation can be significantly more efficient than traditional physiotherapy as has been shown in a (randomized, double-blind, controlled) pilot study we conducted in the hospital Forum Consorci MAR. In the proposed project, we will investigate the benefits of different interventions for recovery in chronic stroke patients, explore interventions for motor function recovery of different parts of the body, target other conditions in addition to stroke, and potentiate the use of mobile devices’ sensors to enable at-home rehabilitation.

This position includes a teaching commitment load of 45 hours per academic year.

Requirements:

Master degree in computer science, sound music computing or related area, excellent programming skills, music knowledge

Admission to the PhD program of the Department of Information and Communication Technologies at UPF is a prerequisite to enjoy the contract.

Starting date (planned): October 2023

Application deadline: June 10th, /2023

Gross monthly salary: 1680€. (To increase to 2020€ during the fourth year of the PhD).

This position is co-funded by the PhD fellowship program of the Department of Information and Communication Technologies at Universitat Pompeu Fabra (DTIC-UPF), and the María de Maeztu Strategic Research Programme at DTIC-UPF on Artificial and Natural Intelligence for ICT and Beyond. Its benefits and conditions are available at: https://www.upf.edu/web/etic/predoctoral-research-contracts.

For application or further information, contact Dr Rafael Ramirez, Music and Machine Learning Lab, rafael.ramirez@upf.edu

More information about the María de Maeztu Strategic Research Programme at DTIC-UPF on Artificial and Natural Intelligence for ICT and beyond:https://www.upf.edu/web/mdm-dtic .