  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.
