Praveen Jesudhas1,*, T. Raghuveera2
Computer Systems Science and Engineering, Vol.46, No.3, pp. 2995-3015, 2023, DOI:10.32604/csse.2023.036778
Abstract Timely identification and treatment of medical conditions could facilitate faster recovery and better health. Existing systems address this issue using custom-built sensors, which are invasive and difficult to generalize. A low-complexity scalable process is proposed to detect and identify medical conditions from 2D skeletal movements on video feed data. Minimal set of features relevant to distinguish medical conditions: AMF, PVF and GDF are derived from skeletal data on sampled frames across the entire action. The AMF (angular motion features) are derived to capture the angular motion of limbs during a specific action. The relative position of joints is represented by… More >
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