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In this paper, a novel technique for human daily motion analysis and recognition is proposed. The technique is based on the use of inertial sensors, and integrates a longest common subsequences (LCSS) algorithm as the kernel function for support vector machines (SVM), which measures the similarity of human daily motion time-series. In our system, we use the wearable motion capture system to obtain...
Sleep apnea contributes to a variety of health threatening problems. However, there is a extremely low public and medical awareness of this disease. In order to identify sleep apnea/hyopnea, some effective features have been extracted from ECG signal, PPG signal and EEG signal. In this work, a novel combined of features characterizing physiological signals for monitoring epochs of sleep apnea is presented...
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