Open Access

ARTICLE

IoMT-Based Smart Healthcare of Elderly People Using Deep Extreme Learning Machine

Muath Jarrah¹, Hussam Al Hamadi^4,*, Ahmed Abu-Khadrah², Taher M. Ghazal^1,3

1 School of Information Technology, Skyline University College, University City Sharjah, 1797, Sharjah, UAE
2 College of Computing and Informatics, Saudi Electronic University, Riyadh, 11673, Saudi Arabia
3 Center for Cyber Security, Faculty of Information Science and Technology, University Kebangsaan Malaysia (UKM), 43600, Bangi, Selangor, Malaysia
4 Center for Cyber-Physical Systems, Khalifa University, 127788, Abu Dhabi, UAE

* Corresponding Author: Hussam Al Hamadi. Email:

Computers, Materials & Continua 2023, 76(1), 19-33. https://doi.org/10.32604/cmc.2023.032775

Received 29 May 2022; Accepted 12 July 2022; Issue published 08 June 2023

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.

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Keywords

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