Mobile human airbag system for fall protection using mems sensors and embedded SVM classifier

Guangyi Shi, Cheung Shing Chan, Wen Jung Li, Kwok-Sui Leung, Yuexian Zou, Yufeng Jin

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

150 Citations (Scopus)

Abstract

This paper introduces a mobile human airbag system designed for fall protection for the elderly. A Micro Inertial Measurement Unit ( \muIMU) of 56 mm × 23 mm × 15 mm in size is built. This unit consists of three dimensional MEMS accelerometers, gyroscopes, a Bluetooth module and a Micro Controller Unit (MCU). It records human motion information, and, through the analysis of falls using a high-speed camera, a lateral fall can be determined by gyro threshold. A human motion database that includes falls and other normal motions (walking, running, etc.) is set up. Using a support vector machine (SVM) training process, we can classify falls and other normal motions successfully with a SVM filter. Based on the SVM filter, an embedded digital signal processing (DSP) system is developed for real-time fall detection. In addition, a smart mechanical airbag deployment system is finalized. The response time for the mechanical trigger is 0.133 s, which allows enough time for compressed air to be released before a person falls to the ground. The integrated system is tested and the feasibility of the airbag system for real-time fall protection is demonstrated. © 2006 IEEE.
Original languageEnglish
Article number4806274
Pages (from-to)495-503
JournalIEEE Sensors Journal
Volume9
Issue number5
DOIs
Publication statusPublished - May 2009
Externally publishedYes

Research Keywords

  • Digital signal processing (DSP)
  • Human motion sensing
  • Inertial measurement unit ( IMU)
  • Microelectromechanical systems (MEMS)
  • Mobile airbags
  • Support vector machine (SVM)

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