Method, System and Apparatus for Real-Time Classification of Muscle Signals from Self-Selected Intentional Movements
Project Number
1455
Description
Background
Externally powered prosthetic hands are typically controlled using electromyographic (EMG) signals. These signals originate from the polarization and depolarization of the muscle membrane during voluntary contractions and can be measured at the skin surface using either dry or wet-type electrodes. The EMG control signal can be derived from a single site or from multiple sites. Past studies have employed two up to eight recording sites with varying levels of success. However, some studies have shown that there is both a practical and theoretical limit to increasing the number of channels.
Technology
The muscle signals are then processed to extract unique features from the signals, which can be accomplished using a suitable feature extractor means. In a preferred embodiment of the present invention, the features are extracted by calculating the natural logarithm of root-mean-square values. These features then define a feature space, which can be subsequently clustered using a suitable clustering algorithm.
