An Automatic Fall Detection System Based on Derivative Dynamic Time Warping

Maturation of Internet and rapid development in mobile communication make smart device could bring enhanced services to person especially in health care center. Therefore, we focus on developing a fall detection application running on Android mobile phones. The detector is fit to indoor and outdoor, without confine of its surroundings. We propose a novel method which fuses Derivative Dynamic Time Warping (DDTW) to detect a fall event and algorithm sensitivity is 84.7%, as well as 94% of specificity. Our algorithm is considerable concise and efficient, what’s more, it do not intrude on privacy of its users or degrade the quality of life. And above all, the method not only overcomes the shortage of thresholding-based fall detection method, but also applicable to all kinds of people with different weight and height.

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