KinesiOS: A Telerehabilitation and Functional Analysis System for Post-Stroke Physical Rehabilitation Therapies?

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Data

2021-01-01

Autores

Scudeletti, Luiz Rogério [UNESP]
Brandão, Alexandre Fonseca
Dias, Diego Roberto Colombo [UNESP]
Brega, José Remo Ferreira [UNESP]

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Resumo

The stroke (also known as a Cerebrovascular Accident) is one of the medical conditions that most kills and incapacitates people in the world, affecting men, women and children of many different age brackets. Studies have been presented in recent years addressing the use of systems for motion capture in post stroke rehabilitation, showing that these tools could be just as efficient as the more traditional methods. In this study, we shall present KinesiOS, a system for telerehabilitation and recognition of movements for the motor and neurofunctional assessment of patients who are undergoing rehabilitation. The system tracks the joints in the human body based on their respective spatial coordinates, and then using the obtained data to construct a guide to movements in the form of a virtual skeleton, while measuring the amplitude of the movements (also known as a Range of Motion) within a certain motor action and showing the results in real time. The tracking of the joints is carried out using a Microsoft Kinect® sensor v2, while data processing, we used the C# programming language. We created the visualizations using the Windows Presentation Foundation® technology, and the data was saved in a cloud structure using the MongoDB® database. Preliminary tests performed on six healthy volunteers showed the efficiency of the system for the calculation of amplitude of movements, enabling data analysis in real time and through telemonitoring. KinesiOS is an alternative tool, portable and low-cost, compared with the traditional systems based on tracking of joints.

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Kinect v2, Motion capture, Telerehabilitation

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 12950 LNCS, p. 174-185.