The Internet of Medical Things (IoMT) is an emerging technology that enables physicians to remotely access elderly healthcare data via the cloud in real time to monitor and deliver intelligent health care services. In this paper, a novel architecture by integrating IoMT with cloud storage and optimized Deep Neural Network (DNN) to detect elderly health condition is built. The designed system gathers the elderly vital signs like heart rate, respiration rate, blood oxygen saturation, temperature, and blood pressureusing wearable sensors attached to the elderly people which will be transmitted to smart phone via Bluetooth and then to cloud storage. The collected data are preprocessed to make them suitable for the network. Finally, DNN is employed to detect elderly health condition. The DNNs parameters are tuned by using Particle Swarm Optimization Algorithm (PSOA). If abnormal condition is detected, the developed system sends an emergency alert message to both caretaker and family physician. Performance analysis is carried to validate the efficacy of developed system. The proposed method predicts elderly health condition with an accuracy of 99.5%.
Volume 12 | Issue 1
Pages: 499-505