On-line estimation of myoelectric signal spectral parameters and nonstationarities detection

In this communication, we present a method for detecting nonstationarities of random time series with an approximately Gaussian distribution of amplitudes. This method is suitable for real time implementation. Here we report some results obtained by applying them to a time series of spectral parameters of surface myoelectric signals, collected during voluntary isometric contractions of human muscles. Moreover, we describe the computerized system that we used to implement our detector of nonstationarity. This system is based on the TMS 320C25 DSP chip and realizes on-line estimation and display of spectral parameters, as well as detection of their nonstationarities, featuring a sampling frequency up to 20 k samples/s. A friendly user interface, fully menu driven, allows the user to select different options during the system's operation by means of hot keys. The accuracy of the system was tested by comparing its estimates with those of an off-line system, previously characterized, which we took as a reference. The estimates of spectral parameters obtained by means of the two systems were always consistent. The on-line stationarity detector was able to recognize rates of variation of the spectral parameters as small as 1%/s during contractions lasting 10-15 s. This sensitivity makes it suitable for clinical application. The set of results herein presented has been selected to highlight the main characteristics of the system.