Myoelectric Pattern Recognition for Use in the Volitional Control of Above-Knee Prostheses

An algorithm through which above-knee (AK) amputees may exercise voluntary and subconscious control of knee flexion and extension with their prosthetic device is presented in this paper. It is hypothesized that spatial patterns of electromyograms (EMG) from muscles above the site of amputation can be separated into groups representing 1) knee flexion, 2) knee extension, and 3) hip action involving no knee activity. An experiment was designed and an apparatus constructed to apply known torques in various configurations to the right leg of normal subjects while sampling EMG from selected muscle groups. Various pattern classification techniques were then applied to judge the degree of separability among each of the three classes of patterns. It was found that the classification can be performed virtually without error depending upon the complexity of the training procedures used to develop the classifier parameters. In addition the magnitude of the classifier response (in the positive sense only) is correlated with the applied knee torque in the direction for which the classifier is designed. Similar results have been found with an above-knee amputee as a subject.