Title :
Portable Preimpact Fall Detector With Inertial Sensors
Author :
Wu, Ge ; Xue, Shuwan
Author_Institution :
Univ. of Vermont, Burlington
fDate :
4/1/2008 12:00:00 AM
Abstract :
Falls and the resulting hip fractures in the elderly are a major health and economic problem. The goal of this study was to investigate the feasibility of a portable preimpact fall detector in detecting impending falls before the body impacts on the ground. It was hypothesized that a single sensor with the appropriate kinematics measurements and detection algorithms, located near the body center of gravity, would be able to distinguish an in-progress and unrecoverable fall from nonfalling activities. The apparatus was tested in an array of daily nonfall activities of young (n = 10) and elderly (n = 14) subjects, and simulated fall activities of young subjects. A threshold detection method was used with the magnitude of inertial frame vertical velocity as the main variable to separate the nonfall and fall activities. The algorithm was able to detect all fall events at least 70 ms before the impact. With the threshold adapted to each individual subject, all falls were detected successfully, and no false alarms occurred. This portable preimpact fall detection apparatus will lead to the development of a new generation inflatable hip pad for preventing fall-related hip fractures.
Keywords :
biomechanics; biomedical equipment; fracture; geriatrics; sensors; detection algorithm; elderly; hip fractures; inertial frame vertical velocity; inertial sensors; inflatable hip pad; portable preimpact fall detector; threshold detection method; Elderly; elderly; fall dedetection; fall detection; inertial sensor; pre-impact; preimpact; Acceleration; Accidental Falls; Adult; Aged; Aged, 80 and over; Algorithms; Equipment Design; Equipment Failure Analysis; Feasibility Studies; Female; Hip Fractures; Humans; Male; Monitoring, Ambulatory; Pattern Recognition, Automated; Protective Clothing; Reproducibility of Results; Sensitivity and Specificity; Transducers;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2007.916282