Muscle synergy analysis method, muscle synergy analyzer, and muscle synergy interface

摘要

Disclosed is a muscle synergy analysis which comprises detecting a myoelectric signal generated at each muscle of an antagonistic muscle pair group of a subject; calculating, as time-series data, an antagonistic muscle ratio of an antagonistic muscle pair at a myoelectric signal level from a myoelectric signal detected during a predetermined motion by the subject; and conducting multi variate analysis using the antagonistic muscle ratio at each time of the time-series data as a variable to calculate a principal component including at least a first principal component having high contribution to correlation.

主权项

1. A muscle synergy analysis method, comprising:
detecting in a time-divisional manner, at each one muscle of an antagonistic muscle pair group of a first human using a first electrode attached to a skin surface overlying said one muscle, a first myoelectric signal generated at said one muscle during a predetermined motion; storing said myolelectric signal into a RAM as reference data; detecting in said time-divisional manner, at each one muscle of an antagonistic muscle pair group of a compared human using a second electrode attached to a skin surface overlying said one muscle of said compared human, a second myoelectric signal generated at said one muscle of said compared human during a comparison predetermined motion, wherein the compared human is one of either a same person or a different person than the first human; storing said second myolelectric signal into said RAM as comparison data; evaluating by a microcomputer a difference in an antagonistic muscle ratio between a principal component of a first antagonistic muscle ratio calculated from said reference data and a principal component of a second antagonistic muscle ratio calculated from said comparison data; and displaying said evaluated, antagonistic muscle ratio difference at a display monitor; and wherein said evaluating comprises:
reading the reference data from said RAM,calculating said first antagonistic muscle ratio as a time series of first antagonistic muscle ratio values from a time series of said reference data corresponding to said first myolectric signal of said each one muscle of said antagonistic muscle pair of said first human,conducting multivariate analysis on said time series of reference data in which a corresponding first antagonistic muscle ratio value from said times series of said first antagonistic muscle ratio values is a variable at a corresponding time of the time-series of said reference data, and calculating the principal component of said first antagonistic muscle ratio to include at least a first principal component having high contribution to a first correlation;reading the comparison data from said RAM,calculating said second antagonistic muscle ratio as a time series of second antagonistic ratio values from a time series of said comparison data corresponding to said second myolectric signal of said each one muscle of said antagonistic muscle pair of said compared human, andconducting multivariate analysis on said time series of comparison data in which a corresponding second antagonistic muscle ratio value from said times series of said second antagonistic muscle ratio values is a variable at a corresponding time of the time-series of said comparison data, and calculating the principal component of said second antagonistic muscle ratio to include at least a second principal component having high contribution to a second correlation.