Citation

Nyan MN, Tay FE, Tan AW, Seah KH. Med. Eng. Phys. 2006; 28(8): 842-849.

Affiliation

Department of Mechanical Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore.

Copyright

(Copyright © 2006, Institute of Physics and Engineering in Medicine, Publisher Elsevier Publishing)

DOI

10.1016/j.medengphy.2005.11.008

PMID

16406739

Abstract

Distinguishing sideways and backward falls from normal activities of daily living using angular rate sensors (gyroscopes) was explored in this paper. Gyroscopes were secured on a shirt at the positions of sternum (S), front of the waist (FW) and right underarm (RU) to measure angular rate in lateral and sagittal planes of the body during falls and normal activities. Moreover, the motions of the fall incidents were captured by a high-speed camera at a frame rate of 250 frames per second (fps) to study the body configuration during fall. The high-speed camera and the sensor data capture system were activated simultaneously to synchronize the picture frame of high-speed camera and the sensor data. The threshold level for each sensor was set to distinguish fall activities from normal activities. Lead time of fall activities (time after threshold value is surpassed to the time when the hip hits the ground) and relative angle of body configuration (angle beta between the vertical line and the line from the center point of the foot or the center point between the two legs to that of the waist) at the threshold level were studied. For sideways falls, lead times of sensors at positions FW and S were about 200-220ms and 135-182ms, respectively. The lead time of the slippery backward fall (about 98ms) from the sensor at position RU was shorter than that of the sideways falls from the sensors at positions FW and S. The relative angle of body configuration at threshold level for sideways and backward falls were about 40-43 degrees for the sensor at position FW, about 43-52 degrees for the sensor at position S and about 54 degrees for the sensor at position RU, respectively. This is the first study that investigates fall dynamics in detection of fall before the person hits the ground using angular rate sensors (gyroscopes).