TY - GEN
T1 - Application of a multilayer perceptron neural network for classifying software platforms of a powered prosthesis through a force plate
AU - Lemoyne, Robert
AU - Mastroianni, Timothy
AU - Hessel, Anthony
AU - Nishikawa, Kiisa C
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/3/2
Y1 - 2016/3/2
N2 - The amalgamation of conventional gait analysis devices, such as a force plate, with a machine learning platform facilitates the capability to classify between two disparate software platforms for the same bionic powered prosthesis. The BiOM powered prosthesis is applied with its standard software platform that incorporates a finite state machine control architecture and a biomimetic software platform that uniquely accounts for the muscle modeling history dependence known as the winding filament hypothesis. The feature set is derived from a series of kinetic and temporal parameters derived from the force plate recordings. The multilayer perceptron neural network achieves 91% classification between the software platforms for the BiOM powered prosthesis conventional finite state machine control architecture and biomimetic software platform based on the force plate derived feature set.
AB - The amalgamation of conventional gait analysis devices, such as a force plate, with a machine learning platform facilitates the capability to classify between two disparate software platforms for the same bionic powered prosthesis. The BiOM powered prosthesis is applied with its standard software platform that incorporates a finite state machine control architecture and a biomimetic software platform that uniquely accounts for the muscle modeling history dependence known as the winding filament hypothesis. The feature set is derived from a series of kinetic and temporal parameters derived from the force plate recordings. The multilayer perceptron neural network achieves 91% classification between the software platforms for the BiOM powered prosthesis conventional finite state machine control architecture and biomimetic software platform based on the force plate derived feature set.
KW - BiOM powered prosthesis
KW - Gait analysis
KW - Machine learning
KW - Multilayer perceptron
KW - Neural network
KW - Powered prosthesis
UR - http://www.scopus.com/inward/record.url?scp=84969716655&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84969716655&partnerID=8YFLogxK
U2 - 10.1109/ICMLA.2015.211
DO - 10.1109/ICMLA.2015.211
M3 - Conference contribution
AN - SCOPUS:84969716655
T3 - Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015
SP - 402
EP - 405
BT - Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015
Y2 - 9 December 2015 through 11 December 2015
ER -