Mubashir Ali^1,2, Jingzhen Li¹, Zedong Nie^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4153-4177, 2025, DOI:10.32604/cmes.2025.073048 - 23 December 2025

Abstract Diabetes imposes a substantial burden on global healthcare systems. Worldwide, nearly half of individuals with diabetes remain undiagnosed, while conventional diagnostic techniques are often invasive, painful, and expensive. In this study, we propose a noninvasive approach for diabetes detection using photoplethysmography (PPG), which is widely integrated into modern wearable devices. First, we derived velocity plethysmography (VPG) and acceleration plethysmography (APG) signals from PPG to construct multi-channel waveform representations. Second, we introduced a novel multiset spatiotemporal feature fusion framework that integrates hand-crafted temporal, statistical, and nonlinear features with recursive feature elimination and deep feature extraction using… More >

Florentin Smarandache¹, Saleh I. Alzahrani², Sulaiman Al Amro³, Ijaz Ahmad⁴, Mubashir Ali^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3715-3735, 2025, DOI:10.32604/cmes.2025.068736 - 30 September 2025

Abstract Hemoglobin is a vital protein in red blood cells responsible for transporting oxygen throughout the body. Its accurate measurement is crucial for diagnosing and managing conditions such as anemia and diabetes, where abnormal hemoglobin levels can indicate significant health issues. Traditional methods for hemoglobin measurement are invasive, causing pain, risk of infection, and are less convenient for frequent monitoring. PPG is a transformative technology in wearable healthcare for noninvasive monitoring and widely explored for blood pressure, sleep, blood glucose, and stress analysis. In this work, we propose a hemoglobin estimation method using an adaptive lightweight… More >

Shu-Yin Chiang^*, Dong-Ye Wu

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2509-2526, 2023, DOI:10.32604/cmc.2023.036466 - 31 March 2023

Abstract Physiological signals indicate a person’s physical and mental state at any given time. Accordingly, many studies extract physiological signals from the human body with non-contact methods, and most of them require facial feature points. However, under COVID-19, wearing a mask has become a must in many places, so how non-contact physiological information measurements can still be performed correctly even when a mask covers the facial information has become a focus of research. In this study, RGB and thermal infrared cameras were used to execute non-contact physiological information measurement systems for heart rate, blood pressure, respiratory… More >

Hoon Ko¹, Chul Park², Wu Seong Kang³, Yunyoung Nam⁴, Dukyong Yoon⁵, Jinseok Lee^1,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2369-2381, 2023, DOI:10.32604/csse.2023.035641 - 09 February 2023

Abstract Adequate oxygen in red blood cells carrying through the body to the heart and brain is important to maintain life. For those patients requiring blood, blood transfusion is a common procedure in which donated blood or blood components are given through an intravenous line. However, detecting the need for blood transfusion is time-consuming and sometimes not easily diagnosed, such as internal bleeding. This study considered physiological signals such as electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure, oxygen saturation (SpO2), and respiration, and proposed the machine learning model to detect the need for blood transfusion accurately. For More >

Qiuyu Hu¹, Wu Zeng^1,*, Yi Sheng¹, Jian Xu¹, Weihua Ou², Ruochen Tan³

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1397-1408, 2023, DOI:10.32604/csse.2023.027980 - 15 June 2022

Abstract Heart rate is an important vital characteristic which indicates physical and mental health status. Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly. Therefore, the study of non-contact heart rate measurement methods is of great importance. Based on the principles of photoelectric volumetric tracing, we use a computer device and camera to capture facial images, accurately detect face regions, and to detect multiple facial images using a multi-target tracking algorithm. Then after the regional segmentation of the facial image, the signal acquisition of the region of interest is More >

Chih-Ta Yen^1,*, Cheng-Hong Liao²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1973-1986, 2022, DOI:10.32604/cmc.2022.022679 - 03 November 2021

Abstract In this study, single-channel photoplethysmography (PPG) signals were used to estimate the heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A deep learning model was proposed using a long-term recurrent convolutional network (LRCN) modified from a deep learning algorithm, the convolutional neural network model of the modified inception deep learning module, and a long short-term memory network (LSTM) to improve the model's accuracy of BP and HR measurements. The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository. How to design a filter of More >

Hafifah Ab Hamid¹, Nazrul Anuar Nayan^1,*, Mohd Zubir Suboh¹, Nurin Izzati Mohamad Azizul¹, Mohamad Nazhan Mohd Nizar¹, Amilia Aminuddin², Mohd Shahrir Mohamed Said³, Saharuddin Ahmad⁴

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 287-304, 2022, DOI:10.32604/cmc.2022.021987 - 03 November 2021

Abstract Hyperuricemia is an alarming issue that contributes to cardiovascular disease. Uric acid (UA) level was proven to be related to pulse wave velocity, a marker of arterial stiffness. A hyperuricemia prediction method utilizing photoplethysmogram (PPG) and arteriograph by using machine learning (ML) is proposed. From the literature search, there is no available papers found that relates PPG with UA level even though PPG is highly associated with vessel condition. The five phases in this research are data collection, signal preprocessing including denoising and signal quality indexes, features extraction for PPG and SDPPG waveform, statistical analysis… More >

Wu Zeng¹, Yi Sheng^1,*, Qiuyu Hu¹, Zhanxiong Huo¹, Yingge Zhang¹, Yuxuan Xie²

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 377-387, 2022, DOI:10.32604/iasc.2022.017748 - 26 October 2021

Abstract According to the World Health Organization, the death rate of cardiovascular diseases ranks first in the composition of disease deaths. Research shows that the heart rate can be employed as an important physiological parameter to measure the health status of people’s cardiac health. A pressure pulse is formed by the periodic beating and contraction of the heart, so its rate and the pressure pulse signal have a distinct synchronous periodicity. Certain wavelengths of light are known to be absorbed by the capillaries in the human skin, where this absorption fluctuates in accordance with the heartbeat… More >

Yudan Zhao^*, Chaoyu Wang

Journal of Information Hiding and Privacy Protection, Vol.3, No.3, pp. 121-130, 2021, DOI:10.32604/jihpp.2021.026380 - 07 February 2022

Abstract Heart rate is an important data reflecting human vital characteristics and an important reference index to describe human physical and mental state. Currently, widely used heart rate measurement devices require direct contact with a person’s skin, which is not suitable for people with burns, delicate skin, newborns and the elderly. Therefore, the research of non-contact heart rate measurement method is of great significance. Based on the basic principle of Photoplethysmography, we use the camera of computer equipment to capture the face image, detect the face region accurately, and detect multiple faces in the image based More >

Jiancheng Zou¹, Shouyu Zhou^1,*, Bailin Ge¹, Xin Yang²

Journal of New Media, Vol.3, No.2, pp. 41-51, 2021, DOI:10.32604/jnm.2021.017764 - 23 April 2021

Abstract Blood pressure is an important physiological parameter to reflect human vital signs. In order to achieve the non-contact dynamic blood pressure acquisition based on ordinary optical camera, a theoretical understanding of the functional relationship between blood pressure and pulse wave signal conduction time. And through imaging photoelectric plethysmography (IPPG), pulse wave signal conduction time of forehead and hand was obtained with ordinary optical camera. First, the pulse wave conduction time was obtained by recording the video with an ordinary optical camera. Second, real-time blood pressure values were collected. Finally, based on the relationship between blood… More >