Abstract
Stroke is one of the most disabling diseases today, so investigating methods for rehabilitation of post-stroke patients is of utmost importance. Thus, significant benefits can be achieved by using body tracking systems and virtual environments. However, the development of such applications involves a large set of requirements, such as the construction of virtual environments, the interaction devices, and the storage and processing of data collected during rehabilitation sessions. This paper presents a multi-agent framework that abstracts the difficulties involved in developing applications using body tracking devices and virtual environments in neuromotor and neurofunctional rehabilitation.
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Valente, F.R., de Paiva Guimarães, M., Cirilo, E.J.R., Dias, D.R.C. (2022). A Multi-agent Body Tracking Application Framework Applied to Physical and Neurofunctional Rehabilitation. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13382. Springer, Cham. https://doi.org/10.1007/978-3-031-10592-0_33
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