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Optimization of a Pre-impact Fall Detection Algorithm and Development of a Hip Protection Airbag System
Soonjae Ahn, Dagyeong Choi, Jongman Kim, Seongjung Kim, Youngjae Jeong, Min Jo, and Youngho Kim
(Received March 31, 2017; Accepted February 16, 2018)
Keywords: pre-impact fall detection, airbag, inertial sensor unit, optimization
In this study, a pre-impact fall detection algorithm using a custom-made inertial sensor was optimized, and a spring-trigger airbag system was developed for preventing injuries from falls. Four different types of simulated falls were performed by 20 healthy volunteers (age 23.4 ± 4.4 years), and six different daily activities were tested in 14 elderly subjects (age 71.8 ± 4.0 years). An inertial sensor unit was used to measure acceleration, angular velocity, and vertical angle during all activities. Thresholds of 0.9 g acceleration, 47.3º/s angular velocity, and 24.7º vertical angle were determined based on optimizing lead time and accuracy in pre-impact fall detection. A belt-type airbag system consisted of a polyurethane inner skin, an artificial leather outer shell, and a spring-trigger inflator. To evaluate the accuracy of the airbag system, 10 healthy adult males (age 28.5 ± 2.7 years) wore the system and performed three sets of simulated falls. Fall detection was achieved 401.9 ± 46.9 ms before impact on average, and the airbag inflated without fail during the falls (100% sensitivity). In all daily activities, no airbag inflation occurred (100% specificity).
Corresponding author: Youngho Kim
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