Development of a microcontrolled bioinstrumentation system for active control of leg prostheses.
This article describes the design of a microcontrolled bioinstrumentation system for active control of leg prostheses, using 4-channel electromyographic signal (EMG) detection and a single-channel electrogoniometer. The system is part of a control and instrumentation architecture in which a master processor controls the tasks of slave microcontrollers, through a RS-485 interface. Several signal processing methods are integrated in the system, for feature extraction (Recursive Least Squares), feature projection (Self Organizing Maps), and pattern classification (Levenberg-Marquardt Neural Network). The acquisition of EMG signals and additional mechanical information could help improving the precision in the control of leg prostheses.
Delis
Alberto Lopez
AL
Department of Electric Engineering - Universidade de Brasilia, DF, Brazil. lopez_delis@yahoo.com
da Rocha
Adson Ferreira
AF
Dos Santos
Icaro
I
Sene
Iwens Gervasio
IG
Salomoni
Sauro
S
Borges
Geovany Araujo
GA
D000465:Algorithms; D001186:Artificial Limbs; D004576:Electromyography / Q000295:instrumentation*; D006801:Humans; D007719:Knee Joint / Q000502:physiology; D007866:Leg; D016571:Neural Networks, Computer; D011474:Prosthesis Design / Q000295:instrumentation*; D012815:Signal Processing, Computer-Assisted