An IoMT-Based Healthcare Model to Monitor Elderly People Using Transfer Learning

The real-time need for a multiaccess healthcare monitoring system, health data acquisition, and effective disease detection of health conditions is a complex procedure at the moment. The Internet of medical things (IoMT) and improvements in information technology have facilitated widespread use of the smart system. In the healthcare industry, IoMT performs a vital role in improving the health of the elderly. This work describes an IoMT-based healthcare model that employs transfer learning to track the health of elderly individuals and offer them service-oriented emergency responses in the event of a medical emergency. The world’s population is aging rapidly, putting traditional healthcare approaches that rely on in-person health monitoring at risk. The proposed model shows better performance for monitoring elderly people’s health by employing TL techniques as compared to the Artificial Neural Network technique, which accomplishes an accuracy of 93.6%.