https://www.sciencedirect.com/science/article/pii/S0736585316307067
Highlights
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- Cloud-based rehabilitation services for post-stroke hand disability.
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- Tensor-based pattern recognition technique to detect the real-time condition of patient.
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- The integration of cloud computing with AR-based rehabilitation system.
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- Multi-sensory big data oriented tensor approach to handle patient’s collected data.
Abstract
Given
the flexibility and potential of cloud technologies, cloud-based
rehabilitation frameworks have shown encouraging results as assistive
tools for post-stroke disability rehabilitation exercises and treatment.
To treat post-stroke disability, cloud-based rehabilitation offers
great advantages over conventional, clinic-based rehabilitation,
providing ubiquitous flexible rehabilitation services and storage while
offering therapeutic feedback from a therapist in real-time during
patients' rehabilitative movements. With the development of sensory
technologies, cloud computing technology integrated with Augmented
Reality (AR) may make therapeutic exercises more enjoyable. To achieve
these objectives, this paper proposes a framework for cloud-based
rehabilitation services, which uses AR technology along with other
sensory technologies. We have designed a prototype of the framework that
uses the mechanism of sensor gloves to recognize gestures, detecting
the real-time condition of a patient doing rehabilitative exercises.
This prototype framework is tested on twelve patients not using sensor
gloves and on four patients wearing sensor gloves over six weeks. We
found statistically significant differences between the forces exerted
by patients’ fingers at week one compared to week six. Significant
improvements in finger strength were found after six weeks of
therapeutic rehabilitative exercises.
Keywords
- Post-stroke disability;
- Cloud-based serious games;
- Patient rehabilitation
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