Wavelet based method for detection: application in proprioceptive rehabilitation

After knee or ankle injury, Freeman has proposed a rehabilitation program consisting in a prolonged maintain of monopodal equilibrium on an unstable plateform. The efficacy of such programs, often debated, is evaluated in the present study by a quantification of equilibrium criteria and electromyographical activities along the rehabilitation program. Our aim is to detect all events in the four EMG signals of soleus, tibialis anterior, peroneus longus and vastus medialis muscles and then deduce the stability of the person. To achieve the detection in EMG, the signals are considered to be piecewise stationary, with no a priori knowledge of the parameters of the hypotheses on the process state to be detected. The detector is based on a combination of dynamic cumulative sum (DCS) and the detail coefficients obtained after the application of the Mallat´s fast decomposition algorithm without reconstruction of the detail signals. The DCS detection algorithm is based on the recursive calculation of the local generalized likelihood ratios associated with a multi-scale decomposition using wavelet transform. Results show that there is a correlation between stability and the energy of EMG signals.