Body tracking method of symptoms of Parkinson’s disease using projection of patterns with kinect technology

Abstract

The analysis of the body movement is relevant in different areas, such as therapy, rehabilitation, bioinformatics and medicine. The Parkinson’s disease (PD) is a progressive degenerative process of the central nervous system that primarily affects the movement. To measure motor disorders, body sensor networks and portable technologies are the trend for tracking and monitoring symptoms in PD. Through the use of technological tools, such as sensors, whether sensors for movement acquisition (accelerometers, gyroscopes, inclinometers) or environment sensors (sensors that record physiological properties), it is possible to track the symptoms of Parkinsonism in a person. A system has been designed using a Kinect sensor, that uses the projection of patterns technology for monitoring change in body posture, obtaining information for a set of points or joints, and variation that could have during the observed period. The designed Kinect sensor system consists of four modules: the first acquisition of the body movement of the patient with the Kinect sensor V1.0, the second feature extraction module to process captured scene by Kinect V1.0, the third recognition of the skeleton module and finally the acquired data processing module, developed with MatLab. The acquisition of the center of mass with the presented methodology, through projection of patterns used by the Kinect sensor technology, is non-invasive a method and convenient to use in people.