Nur Atiqah Sia Abdullah
Universiti Teknologi MARA

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

Review on hypertension diagnosis using expert system and wearable devices Muhammad Izzuddin Mohd Sani; Nur Atiqah Sia Abdullah; Marshima Mohd Rosli
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp3166-3175

Abstract

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.
Overlapping issues and solutions in data visualization techniques Nur Diana Izzati Husin; Nur Atiqah Sia Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1600-1608

Abstract

The tremendous growth of big data has caused the data visualization process becomes more complex and challenging, and yet, data is expected to be increased from time to time. With these massive and complex data, it is getting harder for the data analyst to interpret or read the data in order to gain new knowledge or information. Therefore, it is important to visualize these data using different techniques. However, there are many remaining issues in data visualization techniques. These issues make the data visualization a big challenge to the data analyst. The most common issue in data visualization techniques is the overlapping issue. This paper reviews the overlapping issues in multidimensional and network data visualization techniques. The existing solutions are also reviewed and discussed in term of advantages and disadvantages. This paper concludes the advantages of the overlapping issues and solutions, before discussing their drawbacks. This paper suggests the color-based approach, relocation, and reduction of data sets to solve the overlapping issues.