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A Motion Recognition Technique Based on Linear Matrix Representation to Improve Parkinson's Disease Treatments

Abstract : The analysis of certain pathological movements of Parkinson's disease often allows the neurologist to establish a precise diagnosis and to propose an adapted treatment for the patient. This work considers a motion capture device with embedded sensors such as inertial measurement unit without using camera. This paper presents a movement modeling method in a matrix representation by exploiting the Ordinary Least Squares approach. The quality and simplicity of the model allow movement recognition in real time. This method was tested as part of an experiment including 5 movements, each performed by 14 people wearing the motion capture device (Perception Neuron Pro suit). The global accuracy involved by this method is about 92.85%. \textcopyright 2021 IEEE.
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Communication dans un congrès
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https://hal-u-picardie.archives-ouvertes.fr/hal-03681741
Contributeur : Louise DESSAIVRE Connectez-vous pour contacter le contributeur
Soumis le : lundi 30 mai 2022 - 15:06:58
Dernière modification le : vendredi 5 août 2022 - 11:25:56

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P. Moreau, D. Durand, Jérôme Bosche, Michel Lefranc. A Motion Recognition Technique Based on Linear Matrix Representation to Improve Parkinson's Disease Treatments. 9th International Conference on Systems and Control, ICSC 2021, Nov 2021, Caen, France. pp.237--242, ⟨10.1109/ICSC50472.2021.9666608⟩. ⟨hal-03681741⟩

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