Article
Chemistry, Analytical
Felipe Pineda-Alpizar, Sergio Arriola-Valverde, Mitzy Vado-Chacon, Diego Sossa-Rojas, Haipeng Liu, Dingchang Zheng
Summary: This study evaluates the performance of a low-cost wireless PPG device in detecting ultra-short-term PRV parameters in different postures and breathing patterns. The results show that the sitting position has the lowest data loss and allows for reliable extraction of PPG signal and PRV indicators in real time using commercial PPG and BLE devices.
Article
Chemistry, Analytical
Su-Gyeong Yu, So-Eui Kim, Na Hye Kim, Kun Ha Suh, Eui Chul Lee
Summary: Pulse rate variability (PRV) is an indicator of an individual's autonomic nervous system health status, measured using photoplethysmography (PPG) signals. The study showed that PRV analysis performed with lab-based RPPG technology yielded results comparable in quality to analysis via CPPG, with similar temporal and frequency parameters extracted.
Article
Chemistry, Analytical
Valerie A. A. van Es, Richard G. P. Lopata, Enzo Pasquale Scilingo, Mimma Nardelli
Summary: Despite advancements in remote photoplethysmography (rPPG), extracting a reliable pulse rate variability (PRV) signal remains challenging. This study compared eight image-based photoplethysmography (iPPG) methods for pulse rate (PR) and PRV feature extraction. The algorithms were tested on a public dataset, and their performances were evaluated using statistical analysis. The study found that the POS and CHROM techniques were the most robust for PR estimation and assessing autonomic nervous system (ANS) dynamics. It also demonstrated that the Poincare map of PRV series derived from the POS and CHROM methods can reliably characterize vagal tone. This study supports the use of iPPG systems for obtaining clinically useful information about ANS dynamics.
Article
Multidisciplinary Sciences
Fatemeh Sarhaddi, Kianoosh Kazemi, Iman Azimi, Rui Cao, Hannakaisa Niela-Vilen, Anna Axelin, Pasi Liljeberg, Amir M. Rahmani
Summary: This study evaluated the accuracy of PPG signals collected by the Samsung Gear Sport smartwatch in free-living conditions. The results showed that the smartwatch provided acceptable parameters during sleep time, but had high errors for some parameters during awake time.
Article
Chemistry, Analytical
Gerardo H. Martinez-Delgado, Alfredo J. Correa-Balan, Jose A. May-Chan, Carlos E. Parra-Elizondo, Luis A. Guzman-Rangel, Antonio Martinez-Torteya
Summary: HRV has become a crucial risk assessment tool for diagnosing heart-related illnesses, with video-based methodologies offering high accuracy and accessibility in capturing various HRV-related variables. The study successfully extracted HRV from video using face detection algorithms and color augmentation, showing significant correlations with 38 variables related to HRV through different analytical methods.
Article
Computer Science, Information Systems
Vega Pradana Rachim, Jin-Hyeok Baek, Youngsoo Kim, Younho Kim, Sung-Min Park
Summary: Recent advancement of CMOS camera image sensor (CIS) on smartphone improves IoT-based mobile healthcare technology through CIS-photoplethysmography (CPPG). However, limited sampling rate on smartphones results in distorted CPPG signal and limits its use in advanced PPG-derived physiological analysis, making it only suitable for simple pulse rate monitoring.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Multidisciplinary Sciences
Mohammad Muntasir Rahman, Jadyn Cook, Amirtaha Taebi
Summary: This study proposes a novel contactless method for measuring SCG signals using chest videos recorded by a smartphone. The results show good similarity between the vision-based SCG estimations and the gold-standard measurements, and a good agreement between the estimated heart rate values and the gold-standard measurements. This method shows promise in developing a low-cost and widely available method for remote monitoring of cardiovascular activity using smartphone videos.
SCIENTIFIC REPORTS
(2023)
Article
Multidisciplinary Sciences
Weibo Wang, Zongkai Wei, Jin Yuan, Yu Fang, Yongkang Zheng
Summary: This paper proposes a new method named LA-SSA for extracting heart rate signals using remote photoplethysmography (rPPG) based on cameras. The method combines low-rank sparse matrix decomposition and autocorrelation function with singular spectrum analysis to remove irregular noise in the rPPG signals and obtain denoised heart rate signals through weighted reconstruction.
Article
Engineering, Biomedical
Bella Eszter Ajtay, Szabolcs Beres, Laszlo Hejjel
Summary: The present study examined the beat-to-beat pulse arrival time (PAT) and analyzed the relationship between pulse rate variability (PRV) and heart rate variability (HRV). The results showed that PAT had the minimum relative precision (RP%) at the 1/2 amplitude point and the maximum RP% at the base point. The observed fine oscillation of PAT was associated with breathing. The instantaneous slope of photoplethysmogram (PPG) rise was inversely proportional to the corresponding PAT. Comparisons of PRV and HRV parameters showed excellent agreement in most of the analysis. The difference between HRV and PRV is caused by the difference between two consecutive PATs.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Chemistry, Analytical
Meiyun Cao, Timothy Burton, Gennadi Saiko, Alexandre Douplik
Summary: This study aimed to demonstrate the utility of photoplethysmography (PPG) for physiological investigations, specifically using remote/contactless PPG (rPPG) imaging. Data collected from 22 healthy volunteers were analyzed, showing significant differences in the amplitude and lead time of the PPG signals. These results highlight the potential of rPPG imaging as a tool for fundamental physiological studies and device development.
Article
Chemistry, Analytical
Flora Antali, Daniel Kulin, Konrad Istvan Lucz, Balazs Szabo, Laszlo Szucs, Sandor Kulin, Zsuzsanna Miklos
Summary: The study evaluated the PRV analysis module of a digital arterial PPG-based telemedical system and found good agreement between PRV and HRV parameters in healthy individuals and diabetic patients.
Article
Chemistry, Multidisciplinary
Shuqiang Yang, Deqiang Cheng, Jun Wang, Huafeng Qin, Yike Liu
Summary: Introducing heart rate information into vein authentication technology can enhance the security of identity verification systems. The hand vein transillumination imaging experiment validates the accuracy and stability of this method, showing great potential for application in security systems.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Biomedical
Elisa Mejia-Mejia, Panicos A. Kyriacou
Summary: Pulse rate variability (PRV) is a method to assess the changes in pulse rate using pulsatile signals such as the photoplethysmogram (PPG). There are differences between PRV and heart rate variability (HRV), and it is hypothesized that these differences may be due to physiological processes or technical aspects. This study investigated the effects of using PPG signals with different duration for the extraction of PRV indices. The results suggest that PRV indices can be reliably estimated from ultra-short PPG signals, allowing for more efficient acquisition and processing of this variable.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Interdisciplinary Applications
Elisa Mejia-Mejia, James M. May, Mohamed Elgendi, Panayiotis A. Kyriacou
Summary: Features extracted from photoplethysmography (PPG) based Pulse Rate Variability (PRV) can effectively classify hypertensive, hypotensive, and normotensive events, as well as estimate blood pressure values in critically ill patients. 5-minute segments show improved performance compared to 1-minute segments in classification and estimation tasks.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Review
Computer Science, Artificial Intelligence
Sumbal Maqsood, Shuxiang Xu, Son Tran, Saurabh Garg, Matthew Springer, Mohan Karunanithi, Rami Mohawesh
Summary: Machine learning systems have been widely used in the healthcare industry over the past two decades. Photoplethysmography (PPG) and Electrocardiography (ECG) are promising techniques for tracking cardiovascular health. This paper analyzes and summarizes the state-of-the-art machine learning-based blood pressure estimation methods using continuous, cuffless, and non-invasive PPG signals, and provides a comparison between PPG and ECG.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Behavioral Sciences
James C. Christensen, Justin R. Estepp
Article
Neurosciences
James C. Christensen, Justin R. Estepp, Glenn F. Wilson, Christopher A. Russell
Article
Neurosciences
Ping He, Justin R. Estepp
NEUROSCIENCE LETTERS
(2013)
Article
Neurosciences
Kevin E. Alexander, Justin R. Estepp, Sherif M. Elbasiouny
Proceedings Paper
Engineering, Biomedical
Justin R. Estepp, James C. Christensen
2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
(2011)
Proceedings Paper
Engineering, Biomedical
Justin R. Estepp, Samantha L. Klosterman, James C. Christensen
2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
(2011)