IoMT-Based Smart Healthcare of Elderly People Using Deep Extreme Learning Machine
Abstract
The Internet of Medical Things (IoMT) enables digital devices to gather, infer, and broadcast health data via the cloud platform. The phenomenal growth of the IoMT is fueled by many factors, including the widespread and growing availability of wearables and the ever-decreasing cost of sensor-based technology. There is a growing interest in providing solutions for elderly people living assistance in a world where the population is rising rapidly. The IoMT is a novel reality transforming our daily lives. It can renovate modern healthcare by delivering a more personalized, protective, and collaborative approach to care. However, the current healthcare system for outdoor senior citizens faces new challenges. Traditional healthcare systems are inefficient and lack user-friendly technologies and interfaces appropriate for elderly people in an outdoor environment. Hence, in this research work, a IoMT based Smart Healthcare of Elderly people using Deep Extreme Learning Machine (SH-EDELM) is proposed to monitor the senior citizens’ healthcare. The performance of the proposed SH-EDELM technique gives better results in terms of 0.9301 accuracy and 0.0699 miss rate, respectively.