Optimization of a Pre-impact Fall Detection Algorithm and Development of Hip Protection Airbag System

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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Sensors and materials Ročník 30; číslo 8; s. 1743
Hlavní autoři: Ahn, Soonjae, Choi, Dagyeong, Kim, Jongman, Kim, Seongjung, Jeong, Youngjae, Jo, Min, Kim, Youngho
Médium: Journal Article
Jazyk:angličtina
Vydáno: Tokyo MYU Scientific Publishing Division 01.01.2018
Témata:
ISSN:0914-4935
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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, 47.3°/s angular velocity, and 24.7° vertical angle were determined on the basis of 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).
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0914-4935
DOI:10.18494/SAM.2018.1876