Assessment of an automatic prosthetic elbow control strategy using residual limb motion for transhumeral amputated individuals with socket or osseointegrated prostheses
Journal article, 2020

Most transhumeral amputated individuals deplore the lack of functionality of their prosthesis due to control-related limitations. Commercialized prosthetic elbows are controlled via myoelectric signals, yielding complex control schemes when users have to control an entire prosthetic limb. Limited control causes the development of compensatory strategies. An alternative control strategy associates residual limb motions to automatize the prosthetic elbow motion using a model of physiological shoulder/elbow synergies. Preliminary studies have shown that elbow motion could be predicted from residual limb kinematic measurements, but results with transhumeral amputated individuals were lacking. This study focuses on the experimental assessment of automatic prosthetic elbow control during a reaching task, compared to conventional myoelectric control, with six transhumeral amputated individuals, among whom, three had an osseointegrated device. Part of the recruited participants had an osseointegrated prosthetic device. The task was achieved within physiological precision errors with both control modes. Automatic elbow control reduced trunk compensations, and restored a physiologically-like shoulder/elbow movement synchronization. However, the kinematic assessment showed that amputation and prosthesis wear modifies the shoulder movements in comparison with physiological shoulder kinematics. Overall, participants described the automatic elbow control strategy as intuitive, and this work highlights the interest of automatized prosthetic elbow motion.

Author

M. Merad

Sorbonne University

Etienne de Montalivet

Sorbonne University

Mathilde Legrand

Sorbonne University

Enzo Mastinu

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Max Jair Ortiz Catalan

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Amélie Touillet

Centre Louis Pierquin Institut Régional de Médecine Physique et de Réadaptation UGECAM Nord-Est

Noël Martinet

Centre Louis Pierquin Institut Régional de Médecine Physique et de Réadaptation UGECAM Nord-Est

Jean Paysant

Centre Louis Pierquin Institut Régional de Médecine Physique et de Réadaptation UGECAM Nord-Est

Agnès Roby-Brami

Sorbonne University

Nathanaël Jarrassé

Sorbonne University

IEEE Transactions on Medical Robotics and Bionics

25763202 (eISSN)

Vol. 2 1 38-49

Subject Categories

Physiotherapy

Robotics

Control Engineering

DOI

10.1109/TMRB.2020.2970065

More information

Latest update

1/3/2024 9