Abstract
Novel algorithm and real-time ambulatory monitoring system for fall detection in elderly people is described. Our system is comprised of accelerometer, tilt sensor and gyroscope. For real-time monitoring, we used Bluetooth™. Accelerometer measures kinetic force, tilt sensor and gyroscope estimates body posture. Also, We suggested algorithm using signals which obtained from the system attached to the chest for fall detection. To evaluate our system and algorithm, we experimented on three people aged over 26 years. The experiment of four cases such as forward fall, backward fall, side fall and sit-stand was repeated ten times and the experiment in daily life activity was performed one time to each subject. These experiments showed that our system and algorithm could distinguish beween falling and daily life activity. Moreover, the accuracy of fall detection is 96.7%. Our system is especially adapted for long-time and real-time ambulatory monitoring of elderly people in emergency situation.
| Original language | English |
|---|---|
| Pages (from-to) | 2204-2207 |
| Number of pages | 4 |
| Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
| Volume | 26 III |
| State | Published - 2004 |
| Event | Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States Duration: 1 Sep 2004 → 5 Sep 2004 |
Keywords
- Ambulatory system, fall detection, Bluetooth, accelerometer, tilt sensor, gyroscope, real-time monitoring, emergency situation