A framework for early event detection for wearable systems

Dorschky E, Schuldhaus D, Koerger H, Eskofier B (2015)


Publication Type: Conference contribution, Conference Contribution

Publication year: 2015

Edited Volumes: Proceedings of the 2015 ACM International Symposium on Wearable Computers

Pages Range: 109-112

Conference Proceedings Title: Proceedings of the 2015 ACM International Symposium on Wearable Computers

Event location: Osaka

Abstract

A considerable number of wearable system applications necessitate early event detection (EED). EED is defined as the detection of an event with as much lead time as possible. Applications include physiological (e.g., epileptic seizure or heart stroke) or biomechanical (e.g., fall movement or sports event) monitoring systems. EED for wearable systems is under-investigated in literature. Therefore, we introduce a novel EED framework for wearable systems based on hybrid Hidden Markov Models. Our study specifically targets EED based on inertial measurement unit (IMU) signals in sports. We investigate the early detection of high intensive soccer kicks, with the possible pre-kick adaptation of a soccer shoe before the shoe-ball impact in mind. We conducted a study with ten subjects and recorded 226 kicks using a custom IMU placed in a soccer shoe cavity. We evaluated our framework in terms of EED accuracy and EED latency. In conclusion, our framework delivers the required accuracy and lead times for EED of soccer kicks and can be straightforwardly adapted to other wearable system applications that necessitate EED.

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APA:

Dorschky, E., Schuldhaus, D., Koerger, H., & Eskofier, B. (2015). A framework for early event detection for wearable systems. In Proceedings of the 2015 ACM International Symposium on Wearable Computers (pp. 109-112). Osaka.

MLA:

Dorschky, Eva, et al. "A framework for early event detection for wearable systems." Proceedings of the International Symposium on Wearable Computers, Osaka 2015. 109-112.

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