Analysis of the Severity of Dyskinesia in Patients with Parkinson's Disease via Wearable Sensors
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
The classification of human tremor signals using artificial neural network
Expert Systems with Applications: An International Journal
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An accelerometer-based motion sensing framework is developed for analyzing human motion (gait). In comparison to vision based motion sensing systems, this framework is extremely low in cost and weight, and is also portable to wide variety of places; even to the patient's personal room. On the other hand the device has minimum affect on the patient's normal motion. In this paper we will present the working principals and total configuration of the recommended framework which consists of ADXL accelerometer. In order to optimize system performance, the output signals are processed by means of signal processing tools. After generating appropriate output signals, the analysis of human motion are conducted using this framework. A group of 14 subjects has participated in our experiment and the error rate of detecting gait cycles is less than 0.05. In future it would be possible to convert this work to the wireless one; in this case the neurologist can monitor the patient while he is at home.