Abstract
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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Acknowledgment
The research work was supported by the National Natural Science Foundation of China under Grant Nos. 61300043, 61373156 and 91438121, and the Science & Technology Commission of Shanghai Municipality under grant no. 14DZ2260800.
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Yang, H., Yang, Y., Xu, W., Pang, Y. (2017). An Automatic Fall Detection System Based on Derivative Dynamic Time Warping. In: Chen, G., Shen, H., Chen, M. (eds) Parallel Architecture, Algorithm and Programming. PAAP 2017. Communications in Computer and Information Science, vol 729. Springer, Singapore. https://doi.org/10.1007/978-981-10-6442-5_40
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DOI: https://doi.org/10.1007/978-981-10-6442-5_40
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