Review on hypertension diagnosis using expert system and wearable devices

Sani, Muhammad Izzuddin Mohd; Abdullah, Nur Atiqah Sia; Rosli, Marshima Mohd

doi:10.11591/ijece.v12i3.pp3166-3175

Cited by 4 publications

(4 citation statements)

References 28 publications

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“…Hypertension is a type of cardiovascular disease that occurs when the systolic blood pressure is over 130 mmHg or the diastolic blood pressure is over 80 mmHg [6]. Higher blood increases the risk of health which leads to other heart diseases including heart failure [7]- [9]. It is the leading cause of other CVDs and myocardial infarction [10], [11].…”

Section: Introductionmentioning

confidence: 99%

Hardware and software co-design for detecting hypertension from photoplethysmogram

Chowdhury,

Das

et al. 2024

IJECE

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Hypertension is one of the leading causes of cardiovascular disease morbidity in the world. If remains untreated, it may cause severe damage like heart attack or even death. Early detection is required to prevent the development of other cardiac abnormalities. Photoplethysmogram (PPG) is a bio signal that can be obtained optically by a sensor. It is studied to monitor the change of volume of blood and detect heart conditions. Previous studies have already applied PPG to detect hypertension at the software level. In this article, along with software-based detection, we have implemented a digital hardware-based system for detecting hypertension from signals recorded using PPG sensor. Xilinx ZedBoard Zynq-7000 field programmable gate array (FPGA) board is utilized for designing the embedded system. The hypertension detection accuracy is 98.02% at the software level while for the digital system, it is 96.05% consuming 0.374 W power. The study can be analyzed for other cardiac disease detection and medical equipment development.

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Section: Introductionmentioning

confidence: 99%

Hardware and software co-design for detecting hypertension from photoplethysmogram

Chowdhury,

Das

et al. 2024

IJECE

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“…Common risk factors include blood pressure, body mass index (BMI), heart rate, physical activity, age, diabetes, genetics/family history. In addition, other studies have included additional factors such as cholesterol levels, smoking, unhealthy diet, obesity, and gender in determining hypertension [5] .…”

Section: Introductionmentioning

confidence: 99%

“…Other research by Izzuddin, et al [5] provided a review of hypertension diagnosis using expert systems and wearable devices. They focused on hypertension factors, expert system techniques, and the types of sensors in such devices.…”

Section: Introductionmentioning

confidence: 99%

Classification of Hypertension Using Naïve Bayes Method with Data Discretization Approach Risk Factors

Munali,

Armansyah

2024

JSC

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Generally, patients are unaware of their hypertension condition before having their blood pressure checked. One out of three Indonesians suffers from hypertension, and this figure continues to rise annually. Hypertension is often referred to as the silent killer because individuals with high blood pressure do not exhibit symptoms. This study aims to classify hypertensive patients in an effort to reduce the prevalence of hypertension in Indonesia by aiding in early detection of the disease and increasing awareness of hypertension among the Indonesian population. By using the Naïve Bayes method and implementing data discretization of risk factors, the dataset used comprises 11,627 health examination records of 4,434 participants from the Framingham Heart Study (FHS) organized by the National Institutes of Health. The classification method utilizes the Naïve Bayes Algorithm, and data discretization is performed using the CART (Classification and Regression Trees) method. The system provides an estimation of the probability of hypertension occurrence based on input factors/symptoms, where Naive Bayes achieves an accuracy rate 84.28%.

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“…Given this problematic reality, it was considered extremely important to investigate an expert system based on mobile technology for the diagnosis of diseases transmitted by the Aedes mosquito. Since smartphones are becoming more common and used in many aspects of our daily lives, including in the health sector [9], these devices are especially useful in the self-diagnosis of health [10]. Furthermore, the use of software technologies in fields such as healthcare is growing daily, and the invention of new technologies, including smartphones, has made it possible for people to take care of their own health [11].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Prototype Mobile Application Based on an Expert System for the Diagnosis of Diseases Transmitted by the Aedes Aegypti Mosquito

Jaúregui-Velarde,

Molina-Velarde,

Yactayo-Arias

et al. 2023

Int. J. Onl. Eng.

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The Aedes aegypti mosquito transmits the dengue, zika, and chikungunya viruses, endangering the health and lives of people in affected countries due to a lack of timely diagnosis. The objective of this study is to design and evaluate the feasibility of a mobile application based on an expert system for early diagnosis of diseases transmitted by the Aedes aegypti mosquito. The Buchanan methodology was used to develop the application. The results obtained show that the proposed mobile application has a diagnostic accuracy of 83%, a sensitivity of 91%, a specificity of 63%, and an error rate of 17%. The technical aspects of the application were also evaluated through a questionnaire administered to five computer experts. The results showed that the technical aspects of the application received an average rating of 3.91 out of a maximum of 5, with a standard deviation of 0.482. In addition, the usability of the application was evaluated using the standardized System Usability Scale (SUS), which was administered to a total of 15 users. The results of this evaluation showed that the application received an average score of 83 on the SUS scale, indicating a positive level of usability. In conclusion, the results support the effectiveness and potential of the application for the early diagnosis of diseases transmitted by the Aedes aegypti mosquito, providing a useful tool for the rapid detection of these diseases. Although it requires more attention to specificity and error rate to improve the accuracy of the diagnosis.

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Review on hypertension diagnosis using expert system and wearable devices

Cited by 4 publications

References 28 publications

Hardware and software co-design for detecting hypertension from photoplethysmogram

Hardware and software co-design for detecting hypertension from photoplethysmogram

Classification of Hypertension Using Naïve Bayes Method with Data Discretization Approach Risk Factors

Evaluation of a Prototype Mobile Application Based on an Expert System for the Diagnosis of Diseases Transmitted by the Aedes Aegypti Mosquito

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