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The fall is a crucial problem in the elderly people's daily life, and the early detection of fall is very important to rescue the subjects and avoid the badly prognosis. In this paper, we use a wearable tri-axial accelerometer to capture the movement data of human body, and propose a novel fall detection method based on one-class support vector machine(More)
This paper describes an ongoing researched remote rehabilitation assessment system that has a 6-freedom double-eyes vision robot to catch vision information, and a group of wearable sensors to acquire biomechanical signals. A server computer is fixed on the robot, to provide services to the robot's controller and all the sensors. The robot is connected to(More)
The previous research reveals the presence of relatively strong spatial correlations from spontaneous activity over cortex in Electroencephalography (EEG) and Magnetoencephalography (MEG) measurement. A critical obstacle in MEG current source mapping is that strong background activity masks the relatively weak local information. In this paper, the(More)