DocumentCode
3685593
Title
A multi-channel biomimetic neuroprosthesis to support treadmill gait training in stroke patients
Author
Noelia Chia;Emilia Ambrosini;Walter Baccinelli;Antonio Nardone;Marco Monticone;Giancarlo Ferrigno;Alessandra Pedrocchi;Simona Ferrante
Author_Institution
Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo Da Vinci, 32, 20133, Italy
fYear
2015
Firstpage
7159
Lastpage
7162
Abstract
This study presents an innovative multi-channel neuroprosthesis that induces a biomimetic activation of the main lower-limb muscles during treadmill gait training to be used in the rehabilitation of stroke patients. The electrostimulation strategy replicates the physiological muscle synergies used by healthy subjects to walk on a treadmill at their self-selected speed. This strategy is mapped to the current gait sub-phases, which are identified in real time by a custom algorithm. This algorithm divides the gait cycle into six sub-phases, based on two inertial sensors placed laterally on the shanks. Therefore, the pre-defined stimulation profiles are expanded or stretched based on the actual gait pattern of each single subject. A preliminary experimental protocol, involving 10 healthy volunteers, was carried out to extract the muscle synergies and validate the gait-detection algorithm, which were afterwards used in the development of the neuroprosthesis. The feasibility of the neuroprosthesis was tested on one healthy subject who simulated different gait patterns, and a chronic stroke patient. The results showed the correct functioning of the system. A pilot study of the neurorehabilitation treatment for stroke patients is currently being carried out.
Keywords
"Muscles","Electromyography","Training","Physiology","Sensors","Biomechanics","Integrated circuits"
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
ISSN
1094-687X
Electronic_ISBN
1558-4615
Type
conf
DOI
10.1109/EMBC.2015.7320043
Filename
7320043
Link To Document