DEVELOPMENT OF A LOW FALSE-ALARM-RATE FALL-DOWN DETECTION SYSTEM BASED ON MACHINE LEARNING FOR SENIOR HEALTH CARE
Yongkun Sui · OhioLink ETD Center (Ohio Library and Information Network) · 2015
The objective of this thesis is to develop a low false-alarm-rate fall-down detection system for senior health care with an inertial measurement unit (IMU) and a microcontroller embedded with machine learning algorithm.Fatal delay in medical treatment caused by unconsciousness after seniors' fall-down results in thousands of In conclusion, the low false-alarm-rate fall-down detection system with an inertial measurement unit (IMU) and a microcontroller embedded with machine learning algorithm has been successfully developed and characterized in this work, and the developed system can be greatly helpful for the health care of senior fall-down.iii