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Automatic sensor-based detection and classification of climbing activities
June 23, 2015 Β· Declared Dead Β· π IEEE Sensors Journal
"No code URL or promise found in abstract"
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Authors
JΓ©rΓ©mie Boulanger, Ludovic Seifert, Romain HΓ©rault, Jean-Francois Coeurjolly
arXiv ID
1508.04153
Category
stat.AP
Cross-listed
cs.HC
Citations
34
Venue
IEEE Sensors Journal
Last Checked
6 months ago
Abstract
This article presents a method to automatically detect and classify climbing activities using inertial measurement units (IMUs) attached to the wrists, feet and pelvis of the climber. The IMUs record limb acceleration and angular velocity. Detection requires a learning phase with manual annotation to construct the statistical models used in the cusum algorithm. Full-body activity is then classified based on the detection of each IMU.
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