TY - JOUR
T1 - Mobile human airbag system for fall protection using mems sensors and embedded SVM classifier
AU - Shi, Guangyi
AU - Chan, Cheung Shing
AU - Li, Wen Jung
AU - Leung, Kwok-Sui
AU - Zou, Yuexian
AU - Jin, Yufeng
PY - 2009/5
Y1 - 2009/5
N2 - 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.
AB - 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.
KW - Digital signal processing (DSP)
KW - Human motion sensing
KW - Inertial measurement unit ( IMU)
KW - Microelectromechanical systems (MEMS)
KW - Mobile airbags
KW - Support vector machine (SVM)
UR - http://www.scopus.com/inward/record.url?scp=63849156752&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-63849156752&origin=recordpage
U2 - 10.1109/JSEN.2008.2012212
DO - 10.1109/JSEN.2008.2012212
M3 - RGC 21 - Publication in refereed journal
SN - 1530-437X
VL - 9
SP - 495
EP - 503
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 5
M1 - 4806274
ER -