Title :
Sensor-fault tolerant control of a powered lower limb prosthesis by mixing mode-specific adaptive Kalman filters
Author :
Dutta, Anirban ; Koerding, Konrad ; Perreault, Eric ; Hargrove, Levi
Author_Institution :
Dept. of Clinical Neurophysiol., Georg-August-Univ., Goettingen, Germany
fDate :
Aug. 30 2011-Sept. 3 2011
Abstract :
Machine learning methods for interfacing humans with machines is an emerging area. Here we propose a novel algorithm for interfacing humans with powered lower limb prostheses for restoring control of naturalistic gait following amputation. Unlike most previous neural machine interfaces, our approach fuses control information from the user with sensor information from the prosthesis to approximate the closed loop behavior of the unimpaired sensorimotor system. We present a Bayesian framework to control an artificial knee by probabilistically mixing of process state estimates from different Kalman filters, each addressing separate regimes of locomotion such as level ground walking, walking up a ramp, and walking down a ramp. We show its utility as a mode classifier that is tolerant to temporary sensor faults which are frequently experienced in practical applications.
Keywords :
Bayes methods; artificial limbs; brain-computer interfaces; closed loop systems; electromyography; fault tolerance; man-machine systems; medical control systems; signal classification; Bayesian framework; amputation; artificial knee; closed loop behavior; down ramp walking; human-machine interface; level ground walking; machine learning methods; mode classifier; mode specific adaptive Kalman filter mixing; naturalistic gait control restoration; neural machine interfaces; powered lower limb prosthesis; process state estimate probabilistic mixing; prosthesis sensor information; sensor fault tolerant control; unimpaired sensorimotor system; up ramp walking; Electromyography; Kalman filters; Knee; Legged locomotion; Prosthetics; Vectors; Artificial Limbs; Bayes Theorem; Humans; Models, Theoretical; Probability;
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2011.6090626