The electromyogram (EMG) as a control signal for functional neuromuscular stimulation. I. Autoregressive modeling as a means of EMG signature discrimination

The successful application of functional neuromuscular stimulation to the muscles of paraplegics depends to a large extent on the adequate provision of a means by which the subject can exercise control over the resulting movement. The use of above-lesion electromyographic signals as a solution to the control problem is considered. A number of criteria for such a control system are defined. The general concepts underlying time-series analysis are described and the suitability of this method as a means of processing electromyographic signals is investigated. The electromyogram, which exhibits weak stationarity over short time intervals, is represented by a fourth-order autoregressive model. A sequential least-squares algorithm is used to determine the model parameters, which are then used to achieve signature discrimination.