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Qiu Y, Ma X, Li X, Fan S, Deng Z, Huang X. Non-Contact Blood Pressure Estimation From Radar Signals by a Stacked Deformable Convolution Network. IEEE J Biomed Health Inform 2024; 28:4553-4564. [PMID: 38743528 DOI: 10.1109/jbhi.2024.3400961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
This study introduces a contactless blood pressure monitoring approach that combines conventional radar signal processing with novel deep learning architectures. During the preprocessing phase, datasets suitable for synchronization are created by integrating Kalman filtering, multiscale bandpass filters, and a periodic extraction method in the time domain. These data comprise data on chest micro variations, encapsulating a complex array of physiological and biomedical information reflective of cardiac micromotions. The Radar-based Stacked Deformable convolution Network (RSD-Net) integrates channel and spatial self attention mechanisms within a deformable convolutional framework to enhance feature extraction from radar signals. The network architecture systematically employs deformable convolutions for initial deep feature extraction from individual signals. Subsequently, continuous blood pressure estimation is conducted using self attention mechanisms on feature map from single source coupled with multi-feature map channel attention. The performance of model is corroborated via the open-source dataset procured using a non-invasive 24 GHz six-port continuous wave radar system. The dataset, encompassing readings from 30 healthy individuals subjected to diverse conditions including rest, the Valsalva maneuver, apnea, and tilt-table examinations. It serves to substantiate the validity and resilience of the proposed method in the non-contact assessment of continuous blood pressure. Evaluation metrics reveal Pearson correlation coefficients of 0.838 for systolic and 0.797 for diastolic blood pressure predictions. The Mean Error (ME) and Standard Deviation (SD) for systolic and diastolic blood pressure measurements are -0.32 ±6.14 mmHg and -0.20 ±5.50 mmHg, respectively. The ablation study assesses the contribution of different structural components of the RSD-Net, validating their significance in the overall of model performance.
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Weng WH, Baur S, Daswani M, Chen C, Harrell L, Kakarmath S, Jabara M, Behsaz B, McLean CY, Matias Y, Corrado GS, Shetty S, Prabhakara S, Liu Y, Danaei G, Ardila D. Predicting cardiovascular disease risk using photoplethysmography and deep learning. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0003204. [PMID: 38833495 PMCID: PMC11149850 DOI: 10.1371/journal.pgph.0003204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 04/12/2024] [Indexed: 06/06/2024]
Abstract
Cardiovascular diseases (CVDs) are responsible for a large proportion of premature deaths in low- and middle-income countries. Early CVD detection and intervention is critical in these populations, yet many existing CVD risk scores require a physical examination or lab measurements, which can be challenging in such health systems due to limited accessibility. We investigated the potential to use photoplethysmography (PPG), a sensing technology available on most smartphones that can potentially enable large-scale screening at low cost, for CVD risk prediction. We developed a deep learning PPG-based CVD risk score (DLS) to predict the probability of having major adverse cardiovascular events (MACE: non-fatal myocardial infarction, stroke, and cardiovascular death) within ten years, given only age, sex, smoking status and PPG as predictors. We compare the DLS with the office-based refit-WHO score, which adopts the shared predictors from WHO and Globorisk scores (age, sex, smoking status, height, weight and systolic blood pressure) but refitted on the UK Biobank (UKB) cohort. All models were trained on a development dataset (141,509 participants) and evaluated on a geographically separate test (54,856 participants) dataset, both from UKB. DLS's C-statistic (71.1%, 95% CI 69.9-72.4) is non-inferior to office-based refit-WHO score (70.9%, 95% CI 69.7-72.2; non-inferiority margin of 2.5%, p<0.01) in the test dataset. The calibration of the DLS is satisfactory, with a 1.8% mean absolute calibration error. Adding DLS features to the office-based score increases the C-statistic by 1.0% (95% CI 0.6-1.4). DLS predicts ten-year MACE risk comparable with the office-based refit-WHO score. Interpretability analyses suggest that the DLS-extracted features are related to PPG waveform morphology and are independent of heart rate. Our study provides a proof-of-concept and suggests the potential of a PPG-based approach strategies for community-based primary prevention in resource-limited regions.
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Affiliation(s)
- Wei-Hung Weng
- Google LLC, Mountain View, California, United States of America
| | - Sebastien Baur
- Google LLC, Mountain View, California, United States of America
| | - Mayank Daswani
- Google LLC, Mountain View, California, United States of America
| | - Christina Chen
- Google LLC, Mountain View, California, United States of America
| | - Lauren Harrell
- Google LLC, Mountain View, California, United States of America
| | - Sujay Kakarmath
- Google LLC, Mountain View, California, United States of America
| | - Mariam Jabara
- Google LLC, Mountain View, California, United States of America
| | - Babak Behsaz
- Google LLC, Mountain View, California, United States of America
| | - Cory Y. McLean
- Google LLC, Mountain View, California, United States of America
| | - Yossi Matias
- Google LLC, Mountain View, California, United States of America
| | - Greg S. Corrado
- Google LLC, Mountain View, California, United States of America
| | - Shravya Shetty
- Google LLC, Mountain View, California, United States of America
| | | | - Yun Liu
- Google LLC, Mountain View, California, United States of America
| | - Goodarz Danaei
- Department of Global Health and Population, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Diego Ardila
- Google LLC, Mountain View, California, United States of America
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Mathieu AJW, Pascual MS, Charlton PH, Volovaya M, Venton J, Aston PJ, Nandi M, Alastruey J. Advanced waveform analysis of the photoplethysmogram signal using complementary signal processing techniques for the extraction of biomarkers of cardiovascular function. JRSM Cardiovasc Dis 2024; 13:20480040231225384. [PMID: 38314325 PMCID: PMC10838030 DOI: 10.1177/20480040231225384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 12/08/2023] [Accepted: 12/09/2023] [Indexed: 02/06/2024] Open
Abstract
Introduction Photoplethysmogram signals from wearable devices typically measure heart rate and blood oxygen saturation, but contain a wealth of additional information about the cardiovascular system. In this study, we compared two signal-processing techniques: fiducial point analysis and Symmetric Projection Attractor Reconstruction, on their ability to extract new cardiovascular information from a photoplethysmogram signal. The aim was to identify fiducial point analysis and Symmetric Projection Attractor Reconstruction indices that could classify photoplethysmogram signals, according to age, sex and physical activity. Methods Three datasets were used: an in-silico dataset of simulated photoplethysmogram waves for healthy male participants (25-75 years old); an in-vivo dataset containing 10-min photoplethysmogram recordings from 57 healthy subjects at rest (18-39 or > 70 years old; 53% female); and an in-vivo dataset containing photoplethysmogram recordings collected for 4 weeks from a single subject, in daily life. The best-performing indices from the in-silico study (5/48 fiducial point analysis and 6/49 Symmetric Projection Attractor Reconstruction) were applied to the in-vivo datasets. Results Key fiducial point analysis and Symmetric Projection Attractor Reconstruction indices, which showed the greatest differences between groups, were found to be consistent across datasets. These indices were related to systolic augmentation, diastolic peak positioning and prominence, and waveform variability. Both fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques provided indices that supported the classification of age and physical activity, but not sex. Conclusions Both fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques demonstrated utility in identifying cardiovascular differences between individuals and within an individual over time. Future research should investigate the potential utility of these techniques for extracting information on fitness and disease, to support healthcare-decision making.
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Affiliation(s)
- Aristide Jun Wen Mathieu
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital, London, UK
| | - Miquel Serna Pascual
- School of Cancer and Pharmaceutical Science, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Peter H Charlton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, Cambridgeshire, UK
| | - Maria Volovaya
- School of Cancer and Pharmaceutical Science, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Jenny Venton
- School of Cancer and Pharmaceutical Science, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Philip J Aston
- Department of Mathematics, University of Surrey, Guildford, UK
| | - Manasi Nandi
- School of Cancer and Pharmaceutical Science, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Jordi Alastruey
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital, London, UK
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Hong J, Nandi M, Charlton PH, Alastruey J. Noninvasive hemodynamic indices of vascular aging: an in silico assessment. Am J Physiol Heart Circ Physiol 2023; 325:H1290-H1303. [PMID: 37737734 PMCID: PMC10908403 DOI: 10.1152/ajpheart.00454.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/12/2023] [Accepted: 09/12/2023] [Indexed: 09/23/2023]
Abstract
Vascular aging (VA) involves structural and functional changes in blood vessels that contribute to cardiovascular disease. Several noninvasive pulse wave (PW) indices have been proposed to assess the arterial stiffness component of VA in the clinic and daily life. This study investigated 19 of these indices, identified in recent review articles on VA, by using a database comprising 3,837 virtual healthy subjects aged 25-75 yr, each with unique PW signals simulated under various levels of artificial noise to mimic real measurement errors. For each subject, VA indices were calculated from filtered PW signals and compared with the precise theoretical value of aortic Young's modulus (EAo). In silico PW indices showed age-related changes that align with in vivo population studies. The cardio-ankle vascular index (CAVI) and all pulse wave velocity (PWV) indices showed strong linear correlations with EAo (Pearson's rp > 0.95). Carotid distensibility showed a strong negative nonlinear correlation (Spearman's rs < -0.99). CAVI and distensibility exhibited greater resilience to noise compared with PWV indices. Blood pressure-related indices and photoplethysmography (PPG)-based indices showed weaker correlations with EAo (rp and rs < 0.89, |rp| and |rs| < 0.84, respectively). Overall, blood pressure-related indices were confounded by more cardiovascular properties (heart rate, stroke volume, duration of systole, large artery diameter, and/or peripheral vascular resistance) compared with other studied indices, and PPG-based indices were most affected by noise. In conclusion, carotid-femoral PWV, CAVI and carotid distensibility emerged as the superior clinical VA indicators, with a strong EAo correlation and noise resilience. PPG-based indices showed potential for daily VA monitoring under minimized noise disturbances.NEW & NOTEWORTHY For the first time, 19 noninvasive pulse wave indices for assessing vascular aging were examined together in a single database of nearly 4,000 subjects aged 25-75 yr. The dataset contained precise values of the aortic Young's modulus and other hemodynamic measures for each subject, which enabled us to test each index's ability to measure changes in aortic stiffness while accounting for confounding factors and measurement errors. The study provides freely available tools for analyzing these and additional indices.
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Affiliation(s)
- Jingyuan Hong
- Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, United Kingdom
| | - Manasi Nandi
- School of Cancer and Pharmaceutical Science, King's College London, London, United Kingdom
| | - Peter H Charlton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jordi Alastruey
- Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, United Kingdom
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Choi SO, Choi JG, Yun JY. A Study of Brain Function Characteristics of Service Members at High Risk for Accidents in the Military. Brain Sci 2023; 13:1157. [PMID: 37626513 PMCID: PMC10452066 DOI: 10.3390/brainsci13081157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 07/23/2023] [Accepted: 07/29/2023] [Indexed: 08/27/2023] Open
Abstract
Military accidents are often associated with stress and depressive psychological conditions among soldiers, and they often fail to adapt to military life. Therefore, this study analyzes whether there are differences in EEG and pulse wave indices between general soldiers and three groups of soldiers who have not adapted to military life and are at risk of accidents. Data collection was carried out using a questionnaire and a device that can measure EEG and pulse waves, and data analysis was performed using SPSS. The results showed that the concentration level and brain activity indices were higher in the general soldiers and the soldiers in the first stage of accident risk. The body stress index was higher for each stage of accident risk, and the physical vitality index was higher for general soldiers. Therefore, it can be seen that soldiers who have not adapted to military life and are at risk of accidents have somewhat lower concentration and brain activity than general soldiers, and have symptoms of stress and lethargy. The results of this study will contribute to reducing human accidents through EEG and pulse wave measurements not only in the military but also in occupations with a high risk of accidents such as construction.
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Affiliation(s)
| | | | - Jong-Yong Yun
- Department of Protection and Safety Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea
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Jin J, Zhang H, Geng X, Zhang Y, Ye T. The pulse waveform quantification method basing on contour and derivative. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 220:106784. [PMID: 35405435 DOI: 10.1016/j.cmpb.2022.106784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/15/2022] [Accepted: 03/29/2022] [Indexed: 06/14/2023]
Abstract
OBJECTIVE Pulse waveform contains abundant physiological and pathological information. The condition of surrounding arteries can be reflected sensitively by the contour and derivative changes of pulse waves. In order to express these changes objectively, the pulse wave needs to be quantified. METHODS This study provides a novel quantification method for pulse waveform in the entire cardiac cycle. It involves two new quantification parameters k1 and k2 to display the waveform change caused by the superimposition of wave reflection in the systolic reflex period, which is the most significant changes period. In this method, multi parameters were fused by Kalman filter to obtain an optimal estimation, involving the new parameters and other parameters: k0 for the early systolic period, C1 and C2 for diastole period, and K for pulse pressure. RESULTS Use correlation analysis to verify the effectiveness of new parameters that the coefficient is 0.7 between them and the typical augmentation index (AIx). The quantification results of 462 single-cycle pulse waves have consistent change trends with aging in 25-75 different age groups. For respiration analysis, the correlation coefficients are all greater than 0.6, even achieved 0.8 in six multi-cycle data between Kalman optimal estimation and breath wave. CONCLUSION This method has quantified the waveform change with physiological status, and these quantification parameters can display the detail of each period. SIGNIFICANCE It will be used to verify waveform recognition accuracy and has a vast potential to detect diseases.
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Affiliation(s)
- Ji Jin
- Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, P.R. China; School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, P.R. China
| | - Haiying Zhang
- Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, P.R. China; School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, P.R. China.
| | - Xingguang Geng
- Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, P.R. China; School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, P.R. China
| | - Yitao Zhang
- Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, P.R. China; School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, P.R. China
| | - Tianchun Ye
- Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, P.R. China; School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, P.R. China
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Almarshad MA, Islam MS, Al-Ahmadi S, BaHammam AS. Diagnostic Features and Potential Applications of PPG Signal in Healthcare: A Systematic Review. Healthcare (Basel) 2022; 10:healthcare10030547. [PMID: 35327025 PMCID: PMC8950880 DOI: 10.3390/healthcare10030547] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/03/2022] [Accepted: 03/11/2022] [Indexed: 02/04/2023] Open
Abstract
Recent research indicates that Photoplethysmography (PPG) signals carry more information than oxygen saturation level (SpO2) and can be utilized for affordable, fast, and noninvasive healthcare applications. All these encourage the researchers to estimate its feasibility as an alternative to many expansive, time-wasting, and invasive methods. This systematic review discusses the current literature on diagnostic features of PPG signal and their applications that might present a potential venue to be adapted into many health and fitness aspects of human life. The research methodology is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines 2020. To this aim, papers from 1981 to date are reviewed and categorized in terms of the healthcare application domain. Along with consolidated research areas, recent topics that are growing in popularity are also discovered. We also highlight the potential impact of using PPG signals on an individual’s quality of life and public health. The state-of-the-art studies suggest that in the years to come PPG wearables will become pervasive in many fields of medical practices, and the main domains include cardiology, respiratory, neurology, and fitness. Main operation challenges, including performance and robustness obstacles, are identified.
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Affiliation(s)
- Malak Abdullah Almarshad
- Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia; (M.S.I.); (S.A.-A.)
- Computer Science Department, College of Computer and Information Sciences, Al-Imam Mohammad Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia
- Correspondence:
| | - Md Saiful Islam
- Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia; (M.S.I.); (S.A.-A.)
| | - Saad Al-Ahmadi
- Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia; (M.S.I.); (S.A.-A.)
| | - Ahmed S. BaHammam
- The University Sleep Disorders Center, Department of Medicine, College of Medicine, King Saud University, Riyadh 11324, Saudi Arabia;
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Charlton PH, Kyriacou PA, Mant J, Marozas V, Chowienczyk P, Alastruey J. Wearable Photoplethysmography for Cardiovascular Monitoring. PROCEEDINGS OF THE IEEE. INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS 2022; 110:355-381. [PMID: 35356509 PMCID: PMC7612541 DOI: 10.1109/jproc.2022.3149785] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 01/06/2022] [Accepted: 01/27/2022] [Indexed: 05/29/2023]
Abstract
Smart wearables provide an opportunity to monitor health in daily life and are emerging as potential tools for detecting cardiovascular disease (CVD). Wearables such as fitness bands and smartwatches routinely monitor the photoplethysmogram signal, an optical measure of the arterial pulse wave that is strongly influenced by the heart and blood vessels. In this survey, we summarize the fundamentals of wearable photoplethysmography and its analysis, identify its potential clinical applications, and outline pressing directions for future research in order to realize its full potential for tackling CVD.
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Affiliation(s)
- Peter H. Charlton
- Department of Biomedical EngineeringSchool of Biomedical Engineering and Imaging SciencesKing’s College London, King’s Health PartnersLondonSE1 7EUU.K.
- Research Centre for Biomedical Engineering, CityUniversity of LondonLondonEC1V 0HBU.K.
- Department of Public Health and Primary CareUniversity of CambridgeCambridgeCB1 8RNU.K.
| | - Panicos A. Kyriacou
- Research Centre for Biomedical Engineering, CityUniversity of LondonLondonEC1V 0HBU.K.
| | - Jonathan Mant
- Department of Public Health and Primary CareUniversity of CambridgeCambridgeCB1 8RNU.K.
| | - Vaidotas Marozas
- Department of Electronics Engineering and the Biomedical Engineering Institute, Kaunas University of Technology44249KaunasLithuania
| | - Phil Chowienczyk
- Department of Clinical PharmacologyKing’s College LondonLondonSE1 7EHU.K.
| | - Jordi Alastruey
- Department of Biomedical EngineeringSchool of Biomedical Engineering and Imaging SciencesKing’s College London, King’s Health PartnersLondonSE1 7EUU.K.
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Charlton PH, Paliakaitė B, Pilt K, Bachler M, Zanelli S, Kulin D, Allen J, Hallab M, Bianchini E, Mayer CC, Terentes-Printzios D, Dittrich V, Hametner B, Veerasingam D, Žikić D, Marozas V. Assessing hemodynamics from the photoplethysmogram to gain insights into vascular age: A review from VascAgeNet. Am J Physiol Heart Circ Physiol 2021; 322:H493-H522. [PMID: 34951543 PMCID: PMC8917928 DOI: 10.1152/ajpheart.00392.2021] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/07/2022]
Abstract
The photoplethysmogram (PPG) signal is widely measured by clinical and consumer devices, and it is emerging as a potential tool for assessing vascular age. The shape and timing of the PPG pulse wave are both influenced by normal vascular aging, changes in arterial stiffness and blood pressure, and atherosclerosis. This review summarizes research into assessing vascular age from the PPG. Three categories of approaches are described: 1) those which use a single PPG signal (based on pulse wave analysis), 2) those which use multiple PPG signals (such as pulse transit time measurement), and 3) those which use PPG and other signals (such as pulse arrival time measurement). Evidence is then presented on the performance, repeatability and reproducibility, and clinical utility of PPG-derived parameters of vascular age. Finally, the review outlines key directions for future research to realize the full potential of photoplethysmography for assessing vascular age.
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Affiliation(s)
- Peter H Charlton
- Department of Public Health and Primary Care, University of Cambridge, United Kingdom.,Research Centre for Biomedical Engineering, City, University of London, London, United Kingdom
| | - Birutė Paliakaitė
- Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania
| | - Kristjan Pilt
- Department of Health Technologies, Tallinn University of Technology, Tallinn, Estonia
| | - Martin Bachler
- Biomedical Systems, Center for Health and Bioresources, AIT Austrian Institute of Technology, Vienna, Austria
| | - Serena Zanelli
- Laboratoire Analyse, Géométrie et Applications (LAGA), University Sorbonne Paris Nord, Paris, France.,Axelife, 44460 Saint Nicolas de Redon, France
| | - Daniel Kulin
- Institute of Translational Medicine, Semmelweis University, Budapest, Hungary.,E-Med4All Europe Ltd., Budapest, Hungary
| | - John Allen
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom.,Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Magid Hallab
- Axelife, 44460 Saint Nicolas de Redon, France.,Centre de recherche et d'Innovation, Clinique Bizet, Paris, France
| | | | - Christopher C Mayer
- Biomedical Systems, Center for Health and Bioresources, AIT Austrian Institute of Technology, Vienna, Austria
| | - Dimitrios Terentes-Printzios
- Hypertension and Cardiometabolic Unit, First Department of Cardiology, Hippokration Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | | | - Bernhard Hametner
- Biomedical Systems, Center for Health and Bioresources, AIT Austrian Institute of Technology, Vienna, Austria
| | - Dave Veerasingam
- Department of Cardiothoracic Surgery, Galway University Hospitals, Ireland
| | - Dejan Žikić
- Institute of Biophysics, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vaidotas Marozas
- Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania
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Seo JW, Choi J, Lee K, Kim JU. Age-Related Changes in the Characteristics of the Elderly Females Using the Signal Features of an Earlobe Photoplethysmogram. SENSORS 2021; 21:s21237782. [PMID: 34883786 PMCID: PMC8659530 DOI: 10.3390/s21237782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/31/2021] [Accepted: 11/18/2021] [Indexed: 12/02/2022]
Abstract
Non-invasive measurement of physiological parameters and indicators, specifically among the elderly, is of utmost importance for personal health monitoring. In this study, we focused on photoplethysmography (PPG), and developed a regression model that calculates variables from the second (SDPPG) and third (TDPPG) derivatives of the PPG pulse that can observe the inflection point of the pulse wave measured by a wearable PPG device. The PPG pulse at the earlobe was measured for 3 min in 84 elderly Korean women (age: 71.19 ± 6.97 years old). Based on the PPG-based cardiovascular function, we derived additional variables from TDPPG, in addition to the aging variable to predict the age. The Aging Index (AI) from SDPPG and Sum of TDPPG variables were calculated in the second and third differential forms of PPG. The variables that significantly correlated with age were c/a, Tac, AI of SDPPG, sum of TDPPG, and correlation coefficient ‘r’ of the model. In multiple linear regression analysis, the r value of the model was 0.308, and that using deep learning on the model was 0.839. Moreover, the possibility of improving the accuracy of the model using supervised deep learning techniques, rather than the addition of datasets, was confirmed.
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Affiliation(s)
- Jeong-Woo Seo
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34504, Korea;
| | - Jungmi Choi
- Human Anti-Aging Standards Research Institute, Uiryeong, Gyungnam 52151, Korea;
| | - Kunho Lee
- Gwangju Alzheimer’s Disease and Related Dementias (GARD) Cohort Research Center, Chosun University, Gwangju 61452, Korea;
- Department of Biomedical Science, Chosun University, Gwangju 61452, Korea
- Dementia Research Group, Korea Brain Research Institute, Daegu 41602, Korea
| | - Jaeuk U. Kim
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34504, Korea;
- Korean Convergence Medicine, University of Science and Technology, Daejeon 34054, Korea
- Correspondence: ; Tel.: +82-42-868-9558
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11
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Luo J, Yan Z, Guo S, Chen W. Recent Advances in Atherosclerotic Disease Screening Using Pervasive Healthcare. IEEE Rev Biomed Eng 2021; 15:293-308. [PMID: 34003754 DOI: 10.1109/rbme.2021.3081180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Atherosclerosis screening helps the medical model transform from therapeutic medicine to preventive medicine by assessing degree of atherosclerosis prior to the occurrence of fatal vascular events. Pervasive screening emphasizes atherosclerotic monitoring with easy access, quick process, and advanced computing. In this work, we introduced five cutting-edge pervasive technologies including imaging photoplethysmography (iPPG), laser Doppler, radio frequency (RF), thermal imaging (TI), optical fiber sensing and piezoelectric sensor. IPPG measures physiological parameters by using video images that record the subtle skin color changes consistent with cardiac-synchronous blood volume changes in subcutaneous arteries and capillaries. Laser Doppler obtained the information on blood flow by analyzing the spectral components of backscattered light from the illuminated tissues surface. RF is based on Doppler shift caused by the periodic movement of the chest wall induced by respiration and heartbeat. TI measures vital signs by detecting electromagnetic radiation emitted by blood flow. The working principle of optical fiber sensor is to detect the change of light properties caused by the interaction between the measured physiological parameter and the entering light. Piezoelectric sensors are based on the piezoelectric effect of dielectrics. All these pervasive technologies are noninvasive, mobile, and can detect physiological parameters related to atherosclerosis screening.
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Daniolou S, Rapp A, Haase C, Ruppert A, Wittwer M, Scoccia Pappagallo A, Pandis N, Kressig RW, Ienca M. Digital Predictors of Morbidity, Hospitalization, and Mortality Among Older Adults: A Systematic Review and Meta-Analysis. Front Digit Health 2021; 2:602093. [PMID: 34713066 PMCID: PMC8521803 DOI: 10.3389/fdgth.2020.602093] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 12/17/2020] [Indexed: 12/17/2022] Open
Abstract
The widespread adoption of digital health technologies such as smartphone-based mobile applications, wearable activity trackers and Internet of Things systems has rapidly enabled new opportunities for predictive health monitoring. Leveraging digital health tools to track parameters relevant to human health is particularly important for the older segments of the population as old age is associated with multimorbidity and higher care needs. In order to assess the potential of these digital health technologies to improve health outcomes, it is paramount to investigate which digitally measurable parameters can effectively improve health outcomes among the elderly population. Currently, there is a lack of systematic evidence on this topic due to the inherent heterogeneity of the digital health domain and the lack of clinical validation of both novel prototypes and marketed devices. For this reason, the aim of the current study is to synthesize and systematically analyse which digitally measurable data may be effectively collected through digital health devices to improve health outcomes for older people. Using a modified PICO process and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, we provide the results of a systematic review and subsequent meta-analysis of digitally measurable predictors of morbidity, hospitalization, and mortality among older adults aged 65 or older. These findings can inform both technology developers and clinicians involved in the design, development and clinical implementation of digital health technologies for elderly citizens.
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Affiliation(s)
- Sofia Daniolou
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | | | | | | | | | | | - Nikolaos Pandis
- Department of Orthodontics and Dentofacial Orthopedics, School of Dentistry, University of Bern, Bern, Switzerland
| | - Reto W. Kressig
- University Department of Geriatric Medicine FELIX PLATTER, Faculty of Medicine, University of Basel, Basel, Switzerland
| | - Marcello Ienca
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
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Associations between Job Strain and Arterial Stiffness: A Large Survey among Enterprise Employees from Thailand. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15040659. [PMID: 29614802 PMCID: PMC5923701 DOI: 10.3390/ijerph15040659] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 03/25/2018] [Accepted: 03/27/2018] [Indexed: 12/12/2022]
Abstract
As an intermediate endpoint to cardiovascular disease, arterial stiffness has received much attention recently. So far, the research on work stress and arterial stiffness is still sparse and inconsistent, and no investigations on work stress and cardiovascular health among the Thai working population have been reported. Therefore, we conducted an epidemiological study among 2141 Thai enterprise employees (858 men and 1283 women) who were free from any diagnosed cardiovascular disease. Work stress was measured using Karasek’s Job Demand–Control model for job strain (a combination of high demand and low control). Arterial stiffness was evaluated by a non-invasive approach using pulse-wave analysis based on a finger photoplethysmogram. Multivariable linear regression was applied to examine associations between job strain and arterial stiffness. In men, job strain was significantly associated with arterial stiffness (β = 0.078, 95% confidence interval = 0.026 to 0.130), after accounting for sociodemographic, behavioral, dietary and biomedical factors. However, the association in women was not significant. As the first study in Thailand on work stress and cardiovascular risk, we found that job strain might be an important risk factor for cardiovascular disease among Thai working men. Further studies with longitudinal design are warranted.
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Abstract
Photoplethysmogram (PPG) signals collected using a pulse oximeter are increasingly being used for screening and diagnosis purposes. Because of the non-invasive, cost-effective, and easy-to-use nature of the pulse oximeter, clinicians and biomedical engineers are investigating how PPG signals can help in the management of many medical conditions, especially for global health application. The study of PPG signal analysis is relatively new compared to research in electrocardiogram signals, for instance; however, we anticipate that in the near future blood pressure, cardiac output, and other clinical parameters will be measured from wearable devices that collect PPG signals, based on the signal’s vast potential. This article attempts to organize and standardize the names of PPG waveforms to ensure consistent terminologies, thereby helping the rapid developments in this research area, decreasing the disconnect within and among different disciplines, and increasing the number of features generated from PPG waveforms.
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Miyashita H. The time is ripe to reevaluate the second derivative of the digital photoplethysmogram (SDPTG), originating in Japan, as an important tool for cardiovascular risk and central hemodynamic assessment. Hypertens Res 2017; 40:429-431. [DOI: 10.1038/hr.2016.175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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