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This article presents a method to automatically detect and classify climbingactivities using inertial measurement units (IMUs) attached to the wrists, feetand pelvis of the climber. The IMUs record limb acceleration and angularvelocity. Detection requires a learning phase with manual annotation toconstruct the statistical models used in the cusum algorithm. Full-bodyactivity is then classified based on the detection of each IMU.

Automatic sensor-based detection and classification of climbing activities