Time series analysis of arm and forearm measurement for functional electrical stimulation control

Identify the dynamics of the muscular group of arm and forearm related to accelerometric and surface electromyographic signals is not an easy task especially in persons affected by pathological tremor, in which irregular tremor is not voluntary. The vibrational phenomena studied in this work regards the arm and forearm vibration that are monitored by means of SEMG (surface electro-myographic) sensor and accelerometer sensor with the purpose to detect and recognize the dynamic properties and correlations of onset of pathological tremor in patients affected by Parkinson disease and essential tremor. These pathologies that affect skeletal muscles present a typical characteristic vibration frequency between 1Hz and 12Hz, this property is monitored in out-patient tests. A condition monitoring system has been developed to monitor the tremor and produce an electrical stimulation to reduce the tremor: the system allows data monitoring with a portable microcontroller board powered with low voltage batteries and is based on a cDAQ9191 data acquisition system with a chassis controller module designed for data input, controlling and output generation. The algorithm generates functional electrical stimulation signals for control purpose. Experimental measurement data on parkinsonian patient are presented. Data are analyzed, and the results are presented.