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Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of
Hyo-Jung Kim1, Seol-Young Jeong2, Soon-Ju Kang1
1School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea.
Sensors (Basel, Switzerland)
|October 27, 2022
Summary
This study introduces an IoT system and e-coaching framework to accurately assess elderly patients' activities of daily living (ADL) non-invasively. This technology enables real-time remote monitoring and rehabilitation, improving degenerative brain disease evaluation.
Area of Science:
- Gerontology
- Biomedical Engineering
- Rehabilitation Science
Background:
- Activities of daily living (ADL) assessment is crucial for evaluating degenerative brain diseases in the elderly.
- Current face-to-face interviews provide only a limited snapshot of a patient's ADL ability.
- Accurate, real-time ADL evaluation technology is a significant global research challenge.
Purpose of the Study:
- To develop an innovative IoT architecture for non-invasive, autonomous ADL ability measurement in patients' home environments.
- To introduce an "e-coaching framework" for remote rehabilitation, enabling real-time performance monitoring.
- To validate the proposed system's accuracy in remote ADL assessment and rehabilitation scenarios.
Main Methods:
- Designed and implemented a self-organized IoT architecture for autonomous, non-invasive ADL monitoring.
- Developed an "e-coaching framework" for remote instruction and real-time patient performance measurement.
- Conducted various remotely directed ADL scenarios to verify measurement accuracy.
Main Results:
- The self-organized IoT architecture successfully enabled autonomous and non-invasive ADL measurement.
- The "e-coaching framework" demonstrated the feasibility of real-time, remote performance assessment.
- Experimental verification confirmed the accuracy of the proposed system in diverse ADL scenarios.
Conclusions:
- The developed IoT architecture and e-coaching framework offer a novel solution for accurate ADL assessment in elderly patients.
- This system facilitates remote rehabilitation and improves the evaluation of degenerative brain diseases.
- The technology holds significant potential for enhancing elderly care and remote healthcare solutions.
