A concept of detecting patient hazards during exoskeleton-aided remote home motor rehabilitation

The paper presents a concept of detecting dangerous situations for the patient during exoskeleton-aided home remote rehabilitation. For this purpure, a literature review was conducted to define potential traumas with corresponding causes, measuring approaches and the method of modelling based on these two to assess the risk during treatment. The original concept is based on a numerically modelled digital twin of a patient and an exoskeleton. It consists of a multibody model of a skeletal system and the mechatronic device combined with the soft tissue advanced models. Moreover, the implementation of neural networks and biosignals tracking is suggested in order to predict hazards instead of just monitoring them in real-time. The presented solution can be created within the OpenSim environment. The advantages and challenges of this approach are also discussed.

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Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).