A exponential smoothing gray prediction fall detection signal analysis in wearable device

This paper presented an exponential smoothing gray model ESGM(1,1) analysis in fall detection signal analysis. The fall detection is a popular research topic in health care fields that combined wearable device real time detection older person situation. Gray model GM(1,1) prediction algorithms reinforced person fall signal which detected fall situation more quickly. In the experimental results, we used exponential smoothing modify gray prediction model to analysis person fall signal. Moreover, the proposed ESGM(1,1) implemented in wearable device that combined BLE (Bluetooth low energy) feedback output response real time.

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