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Bird K, Chan G, Lu H, Greeff H, Allen J, Abbott D, Menon C, Lovell NH, Howard N, Chan WS, Fletcher RR, Alian A, Ward R, Elgendi M. Assessment of Hypertension Using Clinical Electrocardiogram Features: A First-Ever Review. Front Med (Lausanne) 2020; 7:583331. [PMID: 33344473 PMCID: PMC7746856 DOI: 10.3389/fmed.2020.583331] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/16/2020] [Indexed: 12/31/2022] Open
Abstract
Hypertension affects an estimated 1.4 billion people and is a major cause of morbidity and mortality worldwide. Early diagnosis and intervention can potentially decrease cardiovascular events later in life. However, blood pressure (BP) measurements take time and require training for health care professionals. The measurements are also inconvenient for patients to access, numerous daily variables affect BP values, and only a few BP readings can be collected per session. This leads to an unmet need for an accurate, 24-h continuous, and portable BP measurement system. Electrocardiograms (ECGs) have been considered as an alternative way to measure BP and may meet this need. This review summarizes the literature published from January 1, 2010, to January 1, 2020, on the use of only ECG wave morphology to monitor BP or identify hypertension. From 35 articles analyzed (9 of those with no listed comorbidities and confounders), the P wave, QTc intervals and TpTe intervals may be promising for this purpose. Unfortunately, with the limited number of articles and the variety of participant populations, we are unable to make conclusions about the effectiveness of ECG-only BP monitoring. We provide 13 recommendations for future ECG-only BP monitoring studies and highlight the limited findings in pregnant and pediatric populations. With the advent of convenient and portable ECG signal recording in smart devices and wearables such as watches, understanding how to apply ECG-only findings to identify hypertension early is crucial to improving health outcomes worldwide.
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Affiliation(s)
- Kathleen Bird
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Gabriel Chan
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Huiqi Lu
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Heloise Greeff
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - John Allen
- Research Center for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
| | - Derek Abbott
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia.,Center for Biomedical Engineering, The University of Adelaide, Adelaide, SA, Australia
| | - Carlo Menon
- School of Mechatronic Systems Engineering, Simon Fraser University, Burnaby, BC, Canada
| | - Nigel H Lovell
- Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, Australia
| | - Newton Howard
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Wee-Shian Chan
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Richard Ribon Fletcher
- D-Lab, Massachusetts Institute of Technology, Cambridge, MA, United States.,Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, United States
| | - Aymen Alian
- Yale School of Medicine, Yale University, New Haven, CT, United States
| | - Rabab Ward
- School of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Mohamed Elgendi
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,School of Mechatronic Systems Engineering, Simon Fraser University, Burnaby, BC, Canada.,Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.,School of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada.,BC Children's & Women's Hospital, Vancouver, BC, Canada
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Tang Q, Chen Z, Ward R, Elgendi M. Synthetic photoplethysmogram generation using two Gaussian functions. Sci Rep 2020; 10:13883. [PMID: 32807897 PMCID: PMC7431427 DOI: 10.1038/s41598-020-69076-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2020] [Accepted: 06/19/2020] [Indexed: 12/13/2022] Open
Abstract
Evaluating the performance of photoplethysmogram (PPG) event detection algorithms requires a large number of PPG signals with different noise levels and sampling frequencies. As publicly available PPG databases provide few options, artificially constructed PPG signals can also be used to facilitate this evaluation. Here, we propose a dynamic model to synthesize PPG over specified time durations and sampling frequencies. In this model, a single pulse was simulated by two Gaussian functions. Additionally, the beat-to-beat intervals were simulated using a normal distribution with a specific mean value and a specific standard deviation value. To add periodicity and to generate a complete signal, the circular motion principle was used. We synthesized three classes of pulses by emulating three different templates: excellent (systolic and diastolic waves are salient), acceptable (systolic and diastolic waves are not salient), and unfit (systolic and diastolic waves are noisy). The optimized model fitting of the Gaussian functions to the templates yielded 0.99, 0.98, and 0.85 correlations between the template and synthetic pulses for the excellent, acceptable, and unfit classes, respectively, with mean square errors of 0.001, 0.003, and 0.017, respectively. By comparing the heart rate variability of real PPG and randomly synthesized PPG for 5 min in 116 records from the MIMIC III database, strong correlations were found in SDNN, RMSSD, LF, HF, SD1, and SD2 (0.99, 0.89, 0.84, 0.89, 0.90 and 0.95, respectively).
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Affiliation(s)
- Qunfeng Tang
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada.,School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, China
| | - Zhencheng Chen
- School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, China.
| | - Rabab Ward
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Mohamed Elgendi
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada. .,Faculty of Medicine, University of British Columbia, Vancouver, Canada. .,BC Children's and Women's Hospital, Vancouver, Canada.
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Vavrinsky E, Subjak J, Donoval M, Wagner A, Zavodnik T, Svobodova H. Application of Modern Multi-Sensor Holter in Diagnosis and Treatment. SENSORS (BASEL, SWITZERLAND) 2020; 20:E2663. [PMID: 32392697 PMCID: PMC7273207 DOI: 10.3390/s20092663] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/04/2020] [Accepted: 05/04/2020] [Indexed: 12/11/2022]
Abstract
Modern Holter devices are very trendy tools used in medicine, research, or sport. They monitor a variety of human physiological or pathophysiological signals. Nowadays, Holter devices have been developing very fast. New innovative products come to the market every day. They have become smaller, smarter, cheaper, have ultra-low power consumption, do not limit everyday life, and allow comfortable measurements of humans to be accomplished in a familiar and natural environment, without extreme fear from doctors. People can be informed about their health and 24/7 monitoring can sometimes easily detect specific diseases, which are normally passed during routine ambulance operation. However, there is a problem with the reliability, quality, and quantity of the collected data. In normal life, there may be a loss of signal recording, abnormal growth of artifacts, etc. At this point, there is a need for multiple sensors capturing single variables in parallel by different sensing methods to complement these methods and diminish the level of artifacts. We can also sense multiple different signals that are complementary and give us a coherent picture. In this article, we describe actual interesting multi-sensor principles on the grounds of our own long-year experiences and many experiments.
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Affiliation(s)
- Erik Vavrinsky
- Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia; (J.S.); (M.D.); (T.Z.)
- Institute of Medical Physics, Biophysics, Informatics and Telemedicine, Faculty of Medicine, Comenius University, Sasinkova 2, 81272 Bratislava, Slovakia
| | - Jan Subjak
- Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia; (J.S.); (M.D.); (T.Z.)
| | - Martin Donoval
- Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia; (J.S.); (M.D.); (T.Z.)
| | - Alexandra Wagner
- Department of Simulation and Virtual Medical Education, Faculty of Medicine, Comenius University, Sasinkova 4, 81272 Bratislava, Slovakia; (A.W.); (H.S.)
| | - Tomas Zavodnik
- Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia; (J.S.); (M.D.); (T.Z.)
| | - Helena Svobodova
- Department of Simulation and Virtual Medical Education, Faculty of Medicine, Comenius University, Sasinkova 4, 81272 Bratislava, Slovakia; (A.W.); (H.S.)
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Multimodal Photoplethysmography-Based Approaches for Improved Detection of Hypertension. J Clin Med 2020; 9:jcm9041203. [PMID: 32331360 PMCID: PMC7230564 DOI: 10.3390/jcm9041203] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 04/07/2020] [Accepted: 04/13/2020] [Indexed: 12/14/2022] Open
Abstract
Elevated blood pressure (BP) is a major cause of death, yet hypertension commonly goes undetected. Owing to its nature, it is typically asymptomatic until later in its progression when the vessel or organ structure has already been compromised. Therefore, noninvasive and continuous BP measurement methods are needed to ensure appropriate diagnosis and early management before hypertension leads to irreversible complications. Photoplethysmography (PPG) is a noninvasive technology with waveform morphologies similar to that of arterial BP waveforms, therefore attracting interest regarding its usability in BP estimation. In recent years, wearable devices incorporating PPG sensors have been proposed to improve the early diagnosis and management of hypertension. Additionally, the need for improved accuracy and convenience has led to the development of devices that incorporate multiple different biosignals with PPG. Through the addition of modalities such as an electrocardiogram, a final measure of the pulse wave velocity is derived, which has been proved to be inversely correlated to BP and to yield accurate estimations. This paper reviews and summarizes recent studies within the period 2010–2019 that combined PPG with other biosignals and offers perspectives on the strengths and weaknesses of current developments to guide future advancements in BP measurement. Our literature review reveals promising measurement accuracies and we comment on the effective combinations of modalities and success of this technology.
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