Machine Learning-based movement analysis for intention recognition and activity prediction - applications on restoring functions in persons with motor disabilities

Séminaire
Date de début
Date de fin
Lieu
IRISA Vannes
Salle
Aurigy - D165
Orateur
Lucas Fonseca

Abstract: Damage to the human nervous system can lead to loss of motor function. This can be a result of conditions such as spinal cord injuries or stroke. Nevertheless, patients usually retain some residual movement capabilities, or even full function in parts of the body. In this talk I present a few works in which I explored these residual movements with inertial sensors to decode user intent, and use it as commands to restore function with assistive devices.

Keywords: movement analysis, signal processing, machine learning, feature extraction, dimensionality reduction, PCA, LDA, SMV, real time systems., functional electrical stimulation.

Short Bio: Lucas Fonseca is a Marie Skłodowska-Curie Actions Fellow in the CAMIN team (Inria Antenne Montpellier, France).