Abstract
Electromyography (EMG) signal plays a crucial role in rehabilitation training of the lower limb. An-IoT-enabled stoke rehabilitation system was implemented in this study what was based on microprocessor, sensor, cloud and mobile application. Some of the main concerns that we can fix for stroke rehabilitation real time monitoring for long-term. Currently, there are a lot of focus on rehabilitation for upper limb muscle as this is more important as part of the stroke patient’s survival skills to use their hand for eating, drinking etc. However, the lower limb is also important skill for stroke patient to improve their mobility. Thus, this research is to help explore lower limb stroke rehabilitation. The prototype was designed by combining muscle sensor and accelerometer for real time monitoring through mobile application and server. This prototype suitable apply and use in the house for home therapy. With this prototype, doctor can monitor their patient health status in real time monitoring. Besides, can connect patient health status for the right information.
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Acknowledgements
I would like to thank the personnel and elderly from the Rumah Seri Kenangan, Seri Iskandar Perak who despite of being busy with their schedule, managed to take time out to provide support on the testing.
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Hawari, H.F.B., Abu, S.B. (2022). Development of an IoT-Enabled Stroke Rehabilitation System. In: Ibrahim, R., K. Porkumaran, Kannan, R., Mohd Nor, N., S. Prabakar (eds) International Conference on Artificial Intelligence for Smart Community. Lecture Notes in Electrical Engineering, vol 758. Springer, Singapore. https://doi.org/10.1007/978-981-16-2183-3_94
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DOI: https://doi.org/10.1007/978-981-16-2183-3_94
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