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Human activity recognition and clinical biomechanics are challenging problemsin physical telerehabilitation medicine. However, most publicly availabledatasets on human body movements cannot be used to study both problems in anout-of-the-lab movement acquisition setting. The objective of the VIDIMUdataset is to pave the way towards affordable patient tracking solutions forremote daily life activities recognition and kinematic analysis. The datasetincludes 13 activities registered using a commodity camera and five inertialsensors. The video recordings were acquired in 54 subjects, of which 16 alsohad simultaneous recordings of inertial sensors. The novelty of VIDIMU lies in:i) the clinical relevance of the chosen movements, ii) the combined utilizationof affordable video and custom sensors, and iii) the implementation ofstate-of-the-art tools for multimodal data processing of 3D body pose trackingand motion reconstruction in a musculoskeletal model from inertial data. Thevalidation confirms that a minimally disturbing acquisition protocol, performedaccording to real-life conditions can provide a comprehensive picture of humanjoint angles during daily life activities.

VIDIMU. Multimodal video and IMU kinematic dataset on daily life activities using affordable devices