This project demonstrates a motion tracking pipeline that accurately predicts CAHAI scores in children, highlighting effective assessments for spastic hemiparesis.
Background/Purpose: The severity of motor deficits in children with spastic hemiparesis can greatly differ, which emphasizes the need for accurate motor assessments in order to refine patient-specific therapies. Several sensor technologies have been tested to assess such motor impairments, but most sensor methods use body-attached objects, which may alter natural motion. The aim of this project is to develop a contactless motion tracking (MT) pipeline that provides objective and continuous measurements of upper limb movements in children with a spastic hemiparesis, including an accurate prediction of Chedoke Arm and Hand Activity Inventory (CAHAI) item scores. This approach will allow us to investigate how accurately we can predict CAHAI item scores based on kinematic information of the corresponding movements.
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Möri et al. (2025) studied this question.
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