A mining technique using n-grams and motion transcripts for body sensor network data repository
WH '10 Wireless Health 2010
A method to evaluate metal filing skill level with wearable hybrid sensor
AH '12 Proceedings of the 3rd Augmented Human International Conference
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This paper introduces a compact, wireless, wearable system that measures signals indicative of forces, torques and other descriptive and evaluative features that the human body undergoes during bursts of extreme physical activity (such as during athletic performance). Standard approaches leverage high-speed camera systems, which need significant infrastructure and provide limited update rates and dynamic accuracy. This project uses 6 degree-of freedom inertial measurement units worn on various segments of an athlete’s body to directly make these dynamic measurements. A combination of low and high range sensors enables sensitivity for both slow and fast motion, and the addition of a compass helps in tracking joint angles. Data from the battery-powered nodes is acquired using a custom wireless protocol over an RF link and analyzed offline. Several professional pitchers and batters were instrumented with the system and data was gathered over many pitches and swings. We show some biomechanically descriptive parameters extracted from this data, and highlight ongoing work and system improvements