JOURNAL ARTICLE

Design and Realization of an Early Pre-Impact Fall Alarm System Based on MEMS Inertial Sensing Units

Hui Qi LiDing LiangYun Kun NingQi ZhangGuo Ru Zhao

Year: 2013 Journal:   Applied Mechanics and Materials Vol: 461 Pages: 659-666   Publisher: Trans Tech Publications

Abstract

Falls are the second leading cause of unintentional injury deaths worldwide, so how to prevent falls has become a safety and security problem for elderly people. At present, because the sensing modules of most fall alarm devices generally only integrate the single 3-axis accelerometer, so the measured accuracy of sensing signals is limited. It results in that these devices can only achieve the alarm of post-fall detection but not the early pre-impact fall recognition in real fall applications. Therefore, this paper aimed to develop an early pre-impact fall alarm system based on high-precision inertial sensing units. A multi-modality sensing module embedded fall detection algorithm was developed for early pre-impact fall detection. The module included a 3-axis accelerometer, a 3-axis gyroscope and a 3-axis magnetometer, which could arouse the information of early pre-impact fall warning by a buzzer and a vibrator. Total 81 times fall experiments from 9 healthy subjects were conducted in simulated fall conditions. By combination of the early warning threshold algorithm, the result shows that the detection sensitivity can achieve 98.61% with a specificity of 98.61%, and the average pre-impact lead time is 300ms. In the future, GPS, GSM electronic modules and wearable protected airbag will be embedded in the system, which will enhance the real-time fall protection and timely immediate aid immensely for the elderly people.

Keywords:
Accelerometer ALARM Buzzer Gyroscope Warning system Inertial measurement unit Accidental fall Real-time computing Wearable computer Engineering GSM Simulation Computer science Embedded system Computer security Artificial intelligence Telecommunications Electrical engineering Medicine

Metrics

1
Cited By
0.00
FWCI (Field Weighted Citation Impact)
10
Refs
0.13
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Context-Aware Activity Recognition Systems
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Balance, Gait, and Falls Prevention
Health Sciences →  Health Professions →  Physical Therapy, Sports Therapy and Rehabilitation
Non-Invasive Vital Sign Monitoring
Physical Sciences →  Engineering →  Biomedical Engineering
© 2026 ScienceGate Book Chapters — All rights reserved.