
Review on hypertension diagnosis using expert system and wearable devices
Author(s) -
Muhammad Izzuddin Mohd Sani,
Nur Atiqah Sia Abdullah,
Marshima Mohd Rosli
Publication year - 2022
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v12i3.pp3166-3175
Subject(s) - wearable computer , computer science , wearable technology , smartwatch , artificial intelligence , medicine , embedded system
The popularity of smartphones and wearable devices is increasing in the global market. These devices track physical exercise records, heartbeat, medicines, and self-health diagnosis. The wearable devices can also collect personal health parameters include hypertension diagnosis. Hypertension is one of the risk factors for cardiovascular-related diseases among the Malaysian population. Many mobile applications are paired with wearable devices to monitor health conditions, but none of them able to diagnose hypertension. In this study, we reviewed research papers that focused on hypertension using expert systems and wearable devices. We performed a systematic literature review based on hypertension factors, expert systems, and wearable devices. We found 15 specific research papers after the filtering process. The key findings highlighted three main focuses, which are the factors of hypertension, the expert system techniques, and the types of sensors in wearable devices. Blood pressure is the most common factor of hypertension that can be collected by wearable devices. As for the expert system techniques, we determined the three most common techniques are machine learning, neural network, and fuzzy logic. Lastly, the wrist band is the most common sensor for wearable devices in hypertension-related research.