A gray prediction GM(1,1) fall detection signal analysis and implement in wearable device

摘要

This paper presented a gray prediction GM(1,1) implement 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 prediction GM(1,1) algorithms reinforced person fall signal which detected fall state more quickly. In the experimental results, we used wearable device with BLE (Bluetooth low energy) feedback person signal, in which Gray prediction GM(1,1) algorithms real time detected person fall state and satisfactory output response in wearable device.