Abstract
We have developed a wearable airbag that incorporates a fall detection system that uses both acceleration and angular velocity signals to trigger inflation of the airbag. The fall detection algorithm was devised using a thresholding technique with the signals of an accelerometer and gyro sensor. The thresholds of acceleration less than ± 3 m/s2 and the integral of angular velocity exceed 0.52 rad/s were used. Five young healthy subjects mimicked falls, and their signals of acceleration and angular velocity were monitored. Then, we developed a fall detection algorithm that could detect signals 300 ms before the fall. This signal was used as a trigger to inflate the airbag to a capacity of 2.4 L. The system has been manufactured but the accuracy was not 100% of operation. In this study we have improved fall detection algorithm to operate correctly in daily life.
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Tamura, T., Yoshimura, T., Sekine, M., Uchida, M. (2011). Development of a Wearable Airbag for Preventing Fall Related Injuries. In: Kurosu, M. (eds) Human Centered Design. HCD 2011. Lecture Notes in Computer Science, vol 6776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21753-1_38
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DOI: https://doi.org/10.1007/978-3-642-21753-1_38
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