An IoT-based Multi-sensory Intelligent Device for Bedridden Elderly Monitoring
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Abstract
A significant responsibility of elderly caregivers is monitoring the health condition of the elderly. Health monitoring can become increasingly difficult for caregivers of bedridden older adults since they cannot lie in the same position for periods longer than two hours. Therefore, we used an artificial intelligence to alert caregivers and alleviating their workload. This work aims to develop a system to support the care of bedridden older adults using the SensorTag CC2650STK as a motion sensor. We used accelerometers and gyroscopes to generate the model for analyzing the lying position of older adults. The system can help caregivers by sending notifications when older adults have been lying in the same position for too long. We dened the lying position into four classes: sit, left, right, and back. Three machine learning models (K-NN, Decision Tree, and Naïve Bayes) were generated and evaluated in our work. We found that the decision tree could achieve the best classification results among these ML models, obtaining scores of 0.98, 0.97, and 0.97 for precision, recall, and F1 scores, respectively.
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