Logo image
The theoretical development of a multichannel time-series myoprocessor for simultaneous limb function detection and muscle force estimation
Journal article   Peer reviewed

The theoretical development of a multichannel time-series myoprocessor for simultaneous limb function detection and muscle force estimation

R.J Triolo and G.D Moskowitz
IEEE transactions on biomedical engineering, v 36(10), pp 1004-1017
Oct 1989
PMID: 2793194

Abstract

Autoregressive processes Economic forecasting Electromyography Information filtering Information filters Muscles Power generation economics Predictive models Reliability theory Surface treatment
The theoretical development and simulation of a complete time-series myoprocessor which provides reliable and economical predictions of both the magnitude and direction of limb motion from the spectral content of the surface EMG is discussed. Treating multiple channels of surface EMG as a vector-valued autoregressive process incorporates spatially distributed information which extends the operating range of parallel filtering limb function classifiers and reduces their sensitivity to modeling conditions. Active joint moment is estimated simultaneously from the pooled variance of the prewhitened EMG generated during the classification procedure. Estimation from the prewhitened sequence imposes no additional computational requirements and extends optimal myoprocessor to include multiple channels of serially dependent data. Such a system may be applied to the control of actively powered prostheses or orthoses.< >

Metrics

16 Record Views
21 citations in Scopus

Details

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Engineering, Biomedical
Logo image