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Alshanskaia EI, Zhozhikashvili NA, Polikanova IS, Martynova OV. Heart rate response to cognitive load as a marker of depression and increased anxiety. Front Psychiatry 2024; 15:1355846. [PMID: 39056018 PMCID: PMC11269089 DOI: 10.3389/fpsyt.2024.1355846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 06/26/2024] [Indexed: 07/28/2024] Open
Abstract
Introduction Understanding the interplay between cardiovascular parameters, cognitive stress induced by increasing load, and mental well-being is vital for the development of integrated health strategies today. By monitoring physiological signals like electrocardiogram (ECG) and photoplethysmogram (PPG) in real time, researchers can discover how cognitive tasks influence both cardiovascular and mental health. Cardiac biomarkers resulting from cognitive strain act as indicators of autonomic nervous system function, potentially reflecting conditions related to heart and mental health, including depression and anxiety. The purpose of this study is to investigate how cognitive load affects ECG and PPG measurements and whether these can signal early cardiovascular changes during depression and anxiety disorders. Methods Ninety participants aged 18 to 45 years, ranging from symptom-free individuals to those with diverse psychological conditions, were assessed using psychological questionnaires and anamnesis. ECG and PPG monitoring were conducted as volunteers engaged in a cognitive 1-back task consisting of two separate blocks, each with six progressively challenging levels. The participants' responses were analyzed to correlate physiological and psychological data with cognitive stressors and outcomes. Results The study confirmed a notable interdependence between anxiety and depression, and cardiovascular responses. Task accuracy decreased with increased task difficulty. A strong relationship between PPG-measured heart rate and markers of depression and trait anxiety was observed. Increasing task difficulty corresponded to an increase in heart rate, linked with elevated levels of depression and trait anxiety. A strong relationship between ECG-measured heart rate and anxiety attacks was observed. Increasing task difficulty corresponded to an increase in heart rate, linked with elevated levels of anxiety attacks, although this association decreased under more challenging conditions. Discussion The findings underscore the predictive importance of ECG and PPG heart rate parameters in mental health assessment, particularly depression and anxiety under cognitive stress induced by increasing load. We discuss mechanisms of sympathetic activation explaining these differences. Our research outcomes have implications for clinical assessments and wearable device algorithms for more precise, personalized mental health diagnostics.
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Affiliation(s)
| | | | | | - Olga V. Martynova
- Faculty of Biology and Biotechnology, HSE University, Moscow, Russia
- Institute for Cognitive Neuroscience, HSE University, Moscow, Russia
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia
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Quigley KS, Gianaros PJ, Norman GJ, Jennings JR, Berntson GG, de Geus EJC. Publication guidelines for human heart rate and heart rate variability studies in psychophysiology-Part 1: Physiological underpinnings and foundations of measurement. Psychophysiology 2024:e14604. [PMID: 38873876 DOI: 10.1111/psyp.14604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 12/22/2023] [Accepted: 04/04/2024] [Indexed: 06/15/2024]
Abstract
This Committee Report provides methodological, interpretive, and reporting guidance for researchers who use measures of heart rate (HR) and heart rate variability (HRV) in psychophysiological research. We provide brief summaries of best practices in measuring HR and HRV via electrocardiographic and photoplethysmographic signals in laboratory, field (ambulatory), and brain-imaging contexts to address research questions incorporating measures of HR and HRV. The Report emphasizes evidence for the strengths and weaknesses of different recording and derivation methods for measures of HR and HRV. Along with this guidance, the Report reviews what is known about the origin of the heartbeat and its neural control, including factors that produce and influence HRV metrics. The Report concludes with checklists to guide authors in study design and analysis considerations, as well as guidance on the reporting of key methodological details and characteristics of the samples under study. It is expected that rigorous and transparent recording and reporting of HR and HRV measures will strengthen inferences across the many applications of these metrics in psychophysiology. The prior Committee Reports on HR and HRV are several decades old. Since their appearance, technologies for human cardiac and vascular monitoring in laboratory and daily life (i.e., ambulatory) contexts have greatly expanded. This Committee Report was prepared for the Society for Psychophysiological Research to provide updated methodological and interpretive guidance, as well as to summarize best practices for reporting HR and HRV studies in humans.
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Affiliation(s)
- Karen S Quigley
- Department of Psychology, Northeastern University, Boston, Massachusetts, USA
| | - Peter J Gianaros
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Greg J Norman
- Department of Psychology, The University of Chicago, Chicago, Illinois, USA
| | - J Richard Jennings
- Department of Psychiatry & Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Gary G Berntson
- Department of Psychology & Psychiatry, The Ohio State University, Columbus, Ohio, USA
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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Ding Z, Li W, Wang W, Zhao Z, Zhu Y, Hou B, Zhu L, Chen M, Che L. Highly Sensitive Iontronic Pressure Sensor with Side-by-Side Package Based on Alveoli and Arch Structure. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2309407. [PMID: 38491739 PMCID: PMC11199976 DOI: 10.1002/advs.202309407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/27/2024] [Indexed: 03/18/2024]
Abstract
Flexible pressure sensors play a significant role in wearable devices and electronic skin. Iontronic pressure sensors with high sensitivity, wide measurement range, and high resolution can meet requirements. Based on the significant deformation characteristics of alveoli to improve compressibility, and the ability of the arch to disperse vertical pressure into horizontal thrust to increase contact area, a graded hollow ball arch (GHBA) microstructure is proposed, greatly improving sensitivity. The fabrication of GHBA ingeniously employs a double-sided structure. One side uses mold casting to create convex structures, while the other utilizes the evaporation of moisture during the curing process to form concave structures. At the same time, a novel side-by-side package structure is proposed, ensuring pressure on flexible substrate is maximally transferred to the GHBA microstructure. Within the range of 0.2 Pa-300 kPa, the iontronic pressure sensor achieves a maximum sensitivity of 10 420.8 kPa-1, pressure resolution of 0.1% under the pressure of 100 kPa, and rapid response/recovery time of 40/35 ms. In wearable devices, it is capable of monitoring dumbbell curl exercises and wirelessly correcting sitting positions. In electronic skin, it can non-contactly detect the location of the wind source and achieve object classification prediction when combined with the CNN model.
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Affiliation(s)
- Zhi Ding
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- Center for MicroelectronicsShaoxing InstituteZhejiang UniversityShaoxing312035China
| | - Weijian Li
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Weidong Wang
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Zhengqian Zhao
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Ye Zhu
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Baoyin Hou
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Lijie Zhu
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Ming Chen
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
| | - Lufeng Che
- College of Information Science and Electronic EngineeringZhejiang UniversityHangzhou310027China
- Center for MicroelectronicsShaoxing InstituteZhejiang UniversityShaoxing312035China
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Addleman JS, Lackey NS, DeBlauw JA, Hajduczok AG. Heart Rate Variability Applications in Strength and Conditioning: A Narrative Review. J Funct Morphol Kinesiol 2024; 9:93. [PMID: 38921629 PMCID: PMC11204851 DOI: 10.3390/jfmk9020093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 06/27/2024] Open
Abstract
Heart rate variability (HRV) is defined as the fluctuation of time intervals between adjacent heartbeats and is commonly used as a surrogate measure of autonomic function. HRV has become an increasingly measured variable by wearable technology for use in fitness and sport applications. However, with its increased use, a gap has arisen between the research and the application of this technology in strength and conditioning. The goal of this narrative literature review is to discuss current evidence and propose preliminary guidelines regarding the application of HRV in strength and conditioning. A literature review was conducted searching for HRV and strength and conditioning, aiming to focus on studies with time-domain measurements. Studies suggest that HRV is a helpful metric to assess training status, adaptability, and recovery after a training program. Although reduced HRV may be a sign of overreaching and/or overtraining syndrome, it may not be a sensitive marker in aerobic-trained athletes and therefore has different utilities for different athletic populations. There is likely utility to HRV-guided programming compared to predefined programming in several types of training. Evidence-based preliminary guidelines for the application of HRV in strength and conditioning are discussed. This is an evolving area of research, and more data are needed to evaluate the best practices for applying HRV in strength and conditioning.
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Affiliation(s)
- Jennifer S. Addleman
- College of Osteopathic Medicine, Touro University California, Vallejo, CA 94592, USA
| | - Nicholas S. Lackey
- Center for Applied Biobehavioral Sciences (CABS), Alliant International University, San Diego, CA 92131, USA;
| | - Justin A. DeBlauw
- Department of Health and Human Physiological Sciences, Skidmore College, Saratoga Springs, NY 12866, USA
| | - Alexander G. Hajduczok
- Department of Cardiology, Thomas Jefferson University Hospital, Philadelphia, PA 19107, USA;
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Eriksson A, Kimmel MC, Furmark T, Wikman A, Grueschow M, Skalkidou A, Frick A, Fransson E. Investigating heart rate variability measures during pregnancy as predictors of postpartum depression and anxiety: an exploratory study. Transl Psychiatry 2024; 14:203. [PMID: 38744808 PMCID: PMC11094065 DOI: 10.1038/s41398-024-02909-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 03/29/2024] [Accepted: 04/12/2024] [Indexed: 05/16/2024] Open
Abstract
Perinatal affective disorders are common, but standard screening measures reliant on subjective self-reports might not be sufficient to identify pregnant women at-risk for developing postpartum depression and anxiety. Lower heart rate variability (HRV) has been shown to be associated with affective disorders. The current exploratory study aimed to evaluate the predictive utility of late pregnancy HRV measurements of postpartum affective symptoms. A subset of participants from the BASIC study (Uppsala, Sweden) took part in a sub-study at pregnancy week 38 where HRV was measured before and after a mild stressor (n = 122). Outcome measures were 6-week postpartum depression and anxiety symptoms as quantified by the Edinburgh Postnatal Depression Scale (EPDS) and the Beck Anxiety Inventory (BAI). In total, 112 women were included in a depression outcome analysis and 106 women were included in an anxiety outcome analysis. Group comparisons indicated that lower pregnancy HRV was associated with depressive or anxious symptomatology at 6 weeks postpartum. Elastic net logistic regression analyses indicated that HRV indices alone were not predictive of postpartum depression or anxiety outcomes, but HRV indices were selected as predictors in a combined model with background and pregnancy variables. ROC curves for the combined models gave an area under the curve (AUC) of 0.93 for the depression outcome and an AUC of 0.83 for the anxiety outcome. HRV indices predictive of postpartum depression generally differed from those predictive of postpartum anxiety. HRV indices did not significantly improve prediction models comprised of psychological measures only in women with pregnancy depression or anxiety.
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Affiliation(s)
- Allison Eriksson
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
- Women's Mental Health during the Reproductive Lifespan - WOMHER, Uppsala University, Uppsala, Sweden.
| | - Mary Claire Kimmel
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Tomas Furmark
- Department of Psychology, Uppsala University, Uppsala, Sweden
| | - Anna Wikman
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Marcus Grueschow
- Zurich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, Zurich, Switzerland
| | - Alkistis Skalkidou
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Andreas Frick
- Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala, Sweden
| | - Emma Fransson
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden
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Sammito S, Thielmann B, Klussmann A, Deußen A, Braumann KM, Böckelmann I. Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science. J Occup Med Toxicol 2024; 19:15. [PMID: 38741189 DOI: 10.1186/s12995-024-00414-9] [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: 12/10/2023] [Accepted: 04/24/2024] [Indexed: 05/16/2024] Open
Abstract
This updated guideline replaces the "Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science" first published in 2014. Based on the older version of the guideline, the authors have reviewed and evaluated the findings on the use of heart rate (HR) and heart rate variability (HRV) that have been published in the meantime and incorporated them into a new version of this guideline.This guideline was developed for application in clinical practice and research purposes in the fields of occupational medicine and occupational science to complement evaluation procedures with respect to exposure and risk assessment at the workplace by the use of objective physiological workload indicators. In addition, HRV is also suitable for assessing the state of health and for monitoring the progress of illnesses and preventive medical measures. It gives an overview of factors influencing the regulation of the HR and HRV at rest and during work. It further illustrates methods for measuring and analyzing these parameters under standardized laboratory and real workload conditions, areas of application as well as the quality control procedures to be followed during the recording and evaluation of HR and HRV.
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Affiliation(s)
- Stefan Sammito
- Department of Occupational Medicine, Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
- German Air Force Centre of Aerospace Medicine, Experimental Aerospace Medicine Research, Flughafenstraße 1, Cologne, 51147, Germany.
| | - Beatrice Thielmann
- Department of Occupational Medicine, Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Andre Klussmann
- Competence Centre Health (CCG), Department Health Sciences, University of Applied Sciences (HAW) Hamburg, Hamburg, Germany
| | - Andreas Deußen
- Department of Physiology, Medical Faculty, TU Dresden, Dresden, Germany
| | | | - Irina Böckelmann
- Department of Occupational Medicine, Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
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7
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Zhu S, Liu S, Jing X, Li B, Liu H, Yang Y, She C. Evaluation of transformation invariant loss function with distance equilibrium in prediction of imaging photoplethysmography characteristics. Physiol Meas 2024; 45:055004. [PMID: 38604181 DOI: 10.1088/1361-6579/ad3dbf] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 04/11/2024] [Indexed: 04/13/2024]
Abstract
Objective. Monitoring changes in human heart rate variability (HRV) holds significant importance for protecting life and health. Studies have shown that Imaging Photoplethysmography (IPPG) based on ordinary color cameras can detect the color change of the skin pixel caused by cardiopulmonary system. Most researchers employed deep learning IPPG algorithms to extract the blood volume pulse (BVP) signal, analyzing it predominantly through the heart rate (HR). However, this approach often overlooks the inherent intricate time-frequency domain characteristics in the BVP signal, which cannot be comprehensively deduced solely from HR. The analysis of HRV metrics through the BVP signal is imperative. APPROACH In this paper, the transformation invariant loss function with distance equilibrium (TIDLE) loss function is applied to IPPG for the first time, and the details of BVP signal can be recovered better. In detail, TIDLE is tested in four commonly used IPPG deep learning models, which are DeepPhys, EfficientPhys, Physnet and TS_CAN, and compared with other three loss functions, which are mean absolute error (MAE), mean square error (MSE), Neg Pearson Coefficient correlation (NPCC). MAIN RESULTS The experiments demonstrate that MAE and MSE exhibit suboptimal performance in predicting LF/HF across the four models, achieving the Statistic of Mean Absolute Error (MAES) of 25.94% and 34.05%, respectively. In contrast, NPCC and TIDLE yielded more favorable results at 13.51% and 11.35%, respectively. Taking into consideration the morphological characteristics of the BVP signal, on the two optimal models for predicting HRV metrics, namely DeepPhys and TS_CAN, the Pearson coefficients for the BVP signals predicted by TIDLE in comparison to the gold-standard BVP signals achieved values of 0.627 and 0.605, respectively. In contrast, the results based on NPCC were notably lower, at only 0.545 and 0.533, respectively. SIGNIFICANCE This paper contributes significantly to the effective restoration of the morphology and frequency domain characteristics of the BVP signal.
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Affiliation(s)
- Shangwei Zhu
- School of Electronic Engineering, Beijing University of Posts and Telecommunications,People's Republic of China
| | - Shaohua Liu
- School of Electronic Engineering, Beijing University of Posts and Telecommunications,People's Republic of China
| | - Xingjian Jing
- Department of Mechanical Engineering, Hong Kong City University, Hong Kong, People's Republic of China
| | - Bing Li
- The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, People's Republic of China
| | - Hao Liu
- Peking University Shougang Hospital, People's Republic of China
| | - Yuchong Yang
- School of Electronic Engineering, Beijing University of Posts and Telecommunications,People's Republic of China
| | - Chundong She
- School of Electronic Engineering, Beijing University of Posts and Telecommunications,People's Republic of China
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Liu L, Yu D, Lu H, Shan C, Wang W. Camera-Based Seismocardiogram for Heart Rate Variability Monitoring. IEEE J Biomed Health Inform 2024; 28:2794-2805. [PMID: 38412075 DOI: 10.1109/jbhi.2024.3370394] [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: 02/29/2024]
Abstract
Heart rate variability (HRV) is a crucial metric that quantifies the variation between consecutive heartbeats, serving as a significant indicator of autonomic nervous system (ANS) activity. It has found widespread applications in clinical diagnosis, treatment, and prevention of cardiovascular diseases. In this study, we proposed an optical model for defocused speckle imaging, to simultaneously incorporate out-of-plane translation and rotation-induced motion for highly-sensitive non-contact seismocardiogram (SCG) measurement. Using electrocardiogram (ECG) signals as the gold standard, we evaluated the performance of photoplethysmogram (PPG) signals and speckle-based SCG signals in assessing HRV. The results indicated that the HRV parameters measured from SCG signals extracted from laser speckle videos showed higher consistency with the results obtained from the ECG signals compared to PPG signals. Additionally, we confirmed that even when clothing obstructed the measurement site, the efficacy of SCG signals extracted from the motion of laser speckle patterns persisted in assessing the HRV levels. This demonstrates the robustness of camera-based non-contact SCG in monitoring HRV, highlighting its potential as a reliable, non-contact alternative to traditional contact-PPG sensors.
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Hirten RP, Danieletto M, Landell K, Zweig M, Golden E, Pyzik R, Kaur S, Chang H, Helmus D, Sands BE, Charney D, Nadkarni G, Bagiella E, Keefer L, Fayad ZA. Remote Short Sessions of Heart Rate Variability Biofeedback Monitored With Wearable Technology: Open-Label Prospective Feasibility Study. JMIR Ment Health 2024; 11:e55552. [PMID: 38663011 PMCID: PMC11082734 DOI: 10.2196/55552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/06/2024] [Accepted: 02/20/2024] [Indexed: 05/01/2024] Open
Abstract
BACKGROUND Heart rate variability (HRV) biofeedback is often performed with structured education, laboratory-based assessments, and practice sessions. It has been shown to improve psychological and physiological function across populations. However, a means to remotely use and monitor this approach would allow for wider use of this technique. Advancements in wearable and digital technology present an opportunity for the widespread application of this approach. OBJECTIVE The primary aim of the study was to determine the feasibility of fully remote, self-administered short sessions of HRV-directed biofeedback in a diverse population of health care workers (HCWs). The secondary aim was to determine whether a fully remote, HRV-directed biofeedback intervention significantly alters longitudinal HRV over the intervention period, as monitored by wearable devices. The tertiary aim was to estimate the impact of this intervention on metrics of psychological well-being. METHODS To determine whether remotely implemented short sessions of HRV biofeedback can improve autonomic metrics and psychological well-being, we enrolled HCWs across 7 hospitals in New York City in the United States. They downloaded our study app, watched brief educational videos about HRV biofeedback, and used a well-studied HRV biofeedback program remotely through their smartphone. HRV biofeedback sessions were used for 5 minutes per day for 5 weeks. HCWs were then followed for 12 weeks after the intervention period. Psychological measures were obtained over the study period, and they wore an Apple Watch for at least 7 weeks to monitor the circadian features of HRV. RESULTS In total, 127 HCWs were enrolled in the study. Overall, only 21 (16.5%) were at least 50% compliant with the HRV biofeedback intervention, representing a small portion of the total sample. This demonstrates that this study design does not feasibly result in adequate rates of compliance with the intervention. Numerical improvement in psychological metrics was observed over the 17-week study period, although it did not reach statistical significance (all P>.05). Using a mixed effect cosinor model, the mean midline-estimating statistic of rhythm (MESOR) of the circadian pattern of the SD of the interbeat interval of normal sinus beats (SDNN), an HRV metric, was observed to increase over the first 4 weeks of the biofeedback intervention in HCWs who were at least 50% compliant. CONCLUSIONS In conclusion, we found that using brief remote HRV biofeedback sessions and monitoring its physiological effect using wearable devices, in the manner that the study was conducted, was not feasible. This is considering the low compliance rates with the study intervention. We found that remote short sessions of HRV biofeedback demonstrate potential promise in improving autonomic nervous function and warrant further study. Wearable devices can monitor the physiological effects of psychological interventions.
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Affiliation(s)
- Robert P Hirten
- The Dr Henry D Janowitz Division of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Matteo Danieletto
- Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Hasso Plattner Institute for Digital Health at the Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Kyle Landell
- Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Hasso Plattner Institute for Digital Health at the Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Micol Zweig
- Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Hasso Plattner Institute for Digital Health at the Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Eddye Golden
- The Hasso Plattner Institute for Digital Health at the Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Renata Pyzik
- The BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Sparshdeep Kaur
- Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Hasso Plattner Institute for Digital Health at the Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Helena Chang
- Center for Biostatistics, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Drew Helmus
- The Dr Henry D Janowitz Division of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Bruce E Sands
- The Dr Henry D Janowitz Division of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Dennis Charney
- Office of the Dean, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Girish Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Emilia Bagiella
- Center for Biostatistics, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Laurie Keefer
- The Dr Henry D Janowitz Division of Gastroenterology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Zahi A Fayad
- The BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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de Zambotti M, Goldstein C, Cook J, Menghini L, Altini M, Cheng P, Robillard R. State of the science and recommendations for using wearable technology in sleep and circadian research. Sleep 2024; 47:zsad325. [PMID: 38149978 DOI: 10.1093/sleep/zsad325] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 12/21/2023] [Indexed: 12/28/2023] Open
Abstract
Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research.
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Affiliation(s)
- Massimiliano de Zambotti
- Center for Health Sciences, SRI International, Menlo Park, CA, USA
- Lisa Health Inc., Oakland, CA, USA
| | - Cathy Goldstein
- Sleep Disorders Center, Department of Neurology, University of Michigan-Ann Arbor, Ann Arbor, MI, USA
| | - Jesse Cook
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Luca Menghini
- Department of Psychology and Cognitive Science, University of Trento, Trento, Italy
| | - Marco Altini
- Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip Cheng
- Sleep Disorders and Research Center, Henry Ford Health, Detroit, MI, USA
| | - Rebecca Robillard
- School of Psychology, University of Ottawa, Ottawa, ON, Canada
- Canadian Sleep Research Consortium, Canada
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Philippi CL, Weible E, Ehlers A, Walsh EC, Hoks RM, Birn RM, Abercrombie HC. Effects of cortisol administration on heart rate variability and functional connectivity across women with different depression histories. Behav Brain Res 2024; 463:114923. [PMID: 38408523 PMCID: PMC10942667 DOI: 10.1016/j.bbr.2024.114923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/15/2024] [Accepted: 02/23/2024] [Indexed: 02/28/2024]
Abstract
Abnormalities within the hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system have been implicated in depression. Studies have reported glucocorticoid insensitivity and reduced heart rate variability (HRV) in depressive disorders. However, little is known about the effects of cortisol on HRV and resting-state functional connectivity (rsFC) of the central autonomic network (CAN) in depression. We collected resting-state fMRI and cardiac data for women with different depression histories (n = 61) after administration of cortisol and placebo using a double-blind crossover design. We computed rsFC for R-amygdala and L-amygdala seeds and assessed the change in HRV after cortisol (cortisol-placebo). Analyses examined the effects of acute cortisol administration on HRV and rsFC of the R-amygdala and L-amygdala. There was a significant interaction between HRV and treatment for rsFC between the amygdala and CAN regions. We found lower rsFC between the L-amygdala and putamen for those with a greater decrease in HRV after cortisol. There was also reduced rsFC between the R-amygdala and dorsomedial prefrontal cortex, putamen, middle cingulate cortex, insula, and cerebellum in those with lower HRV after cortisol. These results remained significant after adjusting for depression symptoms, age, and race. Our findings suggest that the effect of cortisol on CAN connectivity is related to its effects on HRV. Overall, these results could inform transdiagnostic interventions targeting HRV and the stress response systems across clinical and non-clinical populations.
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Affiliation(s)
- Carissa L Philippi
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd, St. Louis, MO 63121, USA.
| | - Emily Weible
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd, St. Louis, MO 63121, USA
| | - Alissa Ehlers
- Department of Psychiatry, University of Wisconsin-Madison, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719, USA
| | - Erin C Walsh
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, CB# 7167, Chapel Hill, NC 27599, USA
| | - Roxanne M Hoks
- Department of Psychiatry, University of Wisconsin-Madison, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719, USA; Center for Healthy Minds, University of Wisconsin-Madison., 625 W. Washington Ave, Madison, WI 53703, USA
| | - Rasmus M Birn
- Department of Psychiatry, University of Wisconsin-Madison, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719, USA
| | - Heather C Abercrombie
- Department of Psychiatry, University of Wisconsin-Madison, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719, USA; Center for Healthy Minds, University of Wisconsin-Madison., 625 W. Washington Ave, Madison, WI 53703, USA
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12
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Wang J, Wang Z, Zhang Z, Li P, Pan H, Ren Y, Hou T, Wang C, Kwong CF, Zhang B, Yang S, Bie J. Simultaneous Measurement of Local Pulse Wave Velocities in Radial Arteries Using a Soft Sensor Based on the Fiber Bragg Grating Technique. MICROMACHINES 2024; 15:507. [PMID: 38675318 PMCID: PMC11052460 DOI: 10.3390/mi15040507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 03/29/2024] [Accepted: 04/02/2024] [Indexed: 04/28/2024]
Abstract
Arterial stiffness has been proved to be an important parameter in the evaluation of cardiovascular diseases, and Pulse Wave Velocity (PWV) is a strong indicator of arterial stiffness. Compared to regional PWV (PWV among different arteries), local PWV (PWV within a single artery) outstands in providing higher precision in indicating arterial properties, as regional PWVs are highly affected by multiple parameters, e.g., variations in blood vessel lengths due to individual differences, and multiple reflection effects on the pulse waveform. However, local PWV is less-developed due to its high dependency on the temporal resolution in synchronized signals with usually low signal-to-noise ratios. This paper presents a method for the noninvasive simultaneous measurement of two local PWVs in both left and right radial arteries based on the Fiber Bragg Grating (FBG) technique via correlation analysis of the pulse pairs at the fossa cubitalis and at the wrist. Based on the measurements of five male volunteers at the ages of 19 to 21 years old, the average left radial PWV ranged from 9.44 m/s to 12.35 m/s and the average right radial PWV ranged from 11.50 m/s to 14.83 m/s. What is worth mentioning is that a stable difference between the left and right radial PWVs was observed for each volunteer, ranging from 2.27 m/s to 3.04 m/s. This method enables the dynamic analysis of local PWVs and analysis of their features among different arteries, which will benefit the diagnosis of early-stage arterial stiffening and may bring more insights into the diagnosis of cardiovascular diseases.
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Affiliation(s)
- Jing Wang
- Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (Z.W.); (Z.Z.); (P.L.); (H.P.); (C.W.); (C.-F.K.); (S.Y.)
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo 315048, China
- Key Laboratory of More Electric Aircraft Technology of Zhejiang Province, University of Nottingham Ningbo China, Ningbo 315100, China
| | - Zhukun Wang
- Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (Z.W.); (Z.Z.); (P.L.); (H.P.); (C.W.); (C.-F.K.); (S.Y.)
| | - Zijun Zhang
- Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (Z.W.); (Z.Z.); (P.L.); (H.P.); (C.W.); (C.-F.K.); (S.Y.)
| | - Peiyun Li
- Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (Z.W.); (Z.Z.); (P.L.); (H.P.); (C.W.); (C.-F.K.); (S.Y.)
| | - Han Pan
- Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (Z.W.); (Z.Z.); (P.L.); (H.P.); (C.W.); (C.-F.K.); (S.Y.)
| | - Yong Ren
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo 315048, China
- Department of Mechanics, Materials and Manufacturing Engineering, University of Nottingham Ningbo China, Ningbo 315100, China;
- Key Laboratory of Carbonaceous Wastes Processing and Process Intensification Research of Zhejiang Province, University of Nottingham Ningbo China, Ningbo 315100, China
| | - Tuo Hou
- Department of Mechanics, Materials and Manufacturing Engineering, University of Nottingham Ningbo China, Ningbo 315100, China;
| | - Chengbo Wang
- Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (Z.W.); (Z.Z.); (P.L.); (H.P.); (C.W.); (C.-F.K.); (S.Y.)
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo 315048, China
| | - Chiew-Foong Kwong
- Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (Z.W.); (Z.Z.); (P.L.); (H.P.); (C.W.); (C.-F.K.); (S.Y.)
- Key Laboratory of More Electric Aircraft Technology of Zhejiang Province, University of Nottingham Ningbo China, Ningbo 315100, China
| | - Bei Zhang
- Department of Automation Science and Electrical Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China;
| | - Sen Yang
- Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (Z.W.); (Z.Z.); (P.L.); (H.P.); (C.W.); (C.-F.K.); (S.Y.)
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo 315048, China
| | - Jing Bie
- Department of Civil Engineering, University of Nottingham Ningbo China, Ningbo 315100, China;
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13
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Farmer G, Lloyd J. Two Sides of the Same Virtual Coin: Investigating Psychosocial Effects of Video Game Play, including Stress Relief Motivations as a Gateway to Problematic Video Game Usage. Healthcare (Basel) 2024; 12:772. [PMID: 38610194 PMCID: PMC11011277 DOI: 10.3390/healthcare12070772] [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: 01/23/2024] [Revised: 03/26/2024] [Accepted: 03/27/2024] [Indexed: 04/14/2024] Open
Abstract
Video gamers can play to negate the psychological impact of stress, which may become problematic when users over-rely on the stress relief potential of gaming. This study used a repeated measures experimental design to investigate the relationships between stress, video gaming, and problematic video gaming behaviours in a convenience sample of 40 students at a UK university. The results indicated that positive affect increased and negative affect decreased, whilst a biological stress measure (instantaneous pulse rate) also decreased after a short video gaming session (t(36) = 4.82, p < 0.001, d = 0.79). The results also suggested that video gaming can act as a short-term buffer against the physiological impact of stress. Further research should focus on testing individuals who have been tested for gaming disorder, as opposed to the general population. Research could also utilise variations of the methodological framework used in this study to examine the intensity of a stress relief effect under different social situations. The study's findings in relation to published works are also discussed.
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Affiliation(s)
- George Farmer
- Westminster Centre for Psychological Sciences, University of Westminster, London W1W 6UW, UK
| | - Joanne Lloyd
- Cyberpsychology Research—University of Wolverhampton, School of Psychology, Faculty of Education, Health and Wellbeing, University of Wolverhampton, Wolverhampton WV1 1LY, UK;
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14
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Dervishi A. A multimodal stacked ensemble model for cardiac output prediction utilizing cardiorespiratory interactions during general anesthesia. Sci Rep 2024; 14:7478. [PMID: 38553509 PMCID: PMC10980739 DOI: 10.1038/s41598-024-57971-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Accepted: 03/23/2024] [Indexed: 04/02/2024] Open
Abstract
This study examined the possibility of estimating cardiac output (CO) using a multimodal stacking model that utilizes cardiopulmonary interactions during general anesthesia and outlined a retrospective application of machine learning regression model to a pre-collected dataset. The data of 469 adult patients (obtained from VitalDB) with normal pulmonary function tests who underwent general anesthesia were analyzed. The hemodynamic data in this study included non-invasive blood pressure, plethysmographic heart rate, and SpO2. CO was recorded using Vigileo and EV1000 (pulse contour technique devices). Respiratory data included mechanical ventilation parameters and end-tidal CO2 levels. A generalized linear regression model was used as the metalearner for the multimodal stacking ensemble method. Random forest, generalized linear regression, gradient boosting machine, and XGBoost were used as base learners. A Bland-Altman plot revealed that the multimodal stacked ensemble model for CO prediction from 327 patients had a bias of - 0.001 L/min and - 0.271% when calculating the percentage of difference using the EV1000 device. Agreement of model CO prediction and measured Vigileo CO in 142 patients reported a bias of - 0.01 and - 0.333%. Overall, this model predicts CO compared to data obtained by the pulse contour technique CO monitors with good agreement.
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Affiliation(s)
- Albion Dervishi
- Anaesthesiology and Intensive Care Medicine, Medius CLINIC NÜRTINGEN-Academic Teaching Hospital of the University of Tübingen, Auf dem Säer 1, 72622, Nürtingen, Germany.
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15
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Martinez P, Grinand M, Cheggour S, Taieb J, Gourjon G. How to properly evaluate cardiac vagal tone in oncology studies: a state-of-the-art review. JOURNAL OF THE NATIONAL CANCER CENTER 2024; 4:36-46. [PMID: 39036385 PMCID: PMC11256691 DOI: 10.1016/j.jncc.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 07/23/2024] Open
Abstract
Heart rate variability (HRV) analysis provides an assessment of cardiac vagal tone and consequently global cardiac health as well as systemic condition. In systemic diseases such as cancer and during treatments that affect the whole body, like chemotherapy, the vagus nerve activity is low and deregulated. Some studies focus on using HRV to predict mortality in oncology. However, in cancer patients, systemic alterations substantially increase artifacts during HRV measurement, especially atrial ectopic beats. Moreover, HRV may be altered by various factors (duration and time of measurement, breathing, drugs, and other confounding factors) that alter each metric in different ways. The Standard Deviation of all Normal to Normal intervals (SDNN) is the most commonly used metric to evaluate HRV in oncology, but it does not appear to be specific to the cardiac vagal tone. Thus, cardiac vagal activity diagnosis and vital prognosis of cancer patients can be biased. Our review presents the main HRV metrics that can be currently used in oncology studies and their links with vagus nerve and cancer. We present the influence of external factors and the required duration and time of measurement. Considering all these parameters, this review proposes seven key points for an assessment of HRV and cardiac vagal tone in patients with cancer.
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Affiliation(s)
- Pierrick Martinez
- Scientific and Osteopathic Research Department, Institut de Formation en Ostéopathie du Grand Avignon, 403 Rue Marcel Demonque, Avignon, France
| | - Marilyne Grinand
- Département de recherche clinique, Centre hospitalier d'Avignon, 305A Rue Raoul Follereau, Avignon, France
| | - Saïda Cheggour
- Service de cardiologie, Centre hospitalier d'Avignon, 305A Rue Raoul Follereau, Avignon, France
| | - Jérôme Taieb
- Service de cardiologie, Centre Hospitalier du pays d'Aix-Pertuis, Avenue des Tamaris Aix-en-Provence, France
| | - Géraud Gourjon
- Scientific and Osteopathic Research Department, Institut de Formation en Ostéopathie du Grand Avignon, 403 Rue Marcel Demonque, Avignon, France
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16
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Saito I, Maruyama K, Yamauchi K, Funakoshi Y, Kato T, Kawamura R, Takata Y, Osawa H. Pulse rate variability and health-related quality of life assessment with the Short Form-8 Japanese version in the general Japanese population. Sci Rep 2024; 14:4157. [PMID: 38378714 PMCID: PMC10879517 DOI: 10.1038/s41598-024-54748-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 02/15/2024] [Indexed: 02/22/2024] Open
Abstract
We aimed to investigate the association between pulse rate variability (PRV) and health-related quality of life (HRQOL) in the general population. A cross-sectional study was conducted with 5908 Japanese men and women aged 30-79 years. PRV was assessed at rest using 5-min recordings of pulse waves with a photoplethysmographic signal from a fingertip sensor, and the time and frequency domains of PRV were determined. HRQOL was assessed with the Short Form-8 (SF-8) Japanese version, and poor HRQOL was defined as an SF-8 sub-scale score < 50. A test for nonlinear trends was performed with the generalized additive model with a smoothing spline adjusted for confounders. The lowest multivariable-adjusted odds ratios for poor physical component score were found in those who had second or third quartile levels of standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive difference (RMSSD), and high-frequency (HF) power and trended slightly upward in the higher levels. PRV-derived parameters were nonlinearly associated with poor physical component scores. In conclusion, reduced PRV-derived SDNN, RMSSD and HF power were associated with poor HRQOL in the domain of physical function. Higher levels of these parameters did not necessarily translate into better HRQOL.
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Affiliation(s)
- Isao Saito
- Department of Public Health and Epidemiology, Faculty of Medicine, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu, Oita, 879-5593, Japan.
| | - Koutatsu Maruyama
- Department of Bioscience, Graduate School of Agriculture, Ehime University, Matsuyama, Ehime, Japan
| | - Kanako Yamauchi
- Faculty of Education, Fukuyama City University, Fukuyama, Hiroshima, Japan
| | - Yayoi Funakoshi
- Department of Public Health and Epidemiology, Faculty of Medicine, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu, Oita, 879-5593, Japan
| | - Tadahiro Kato
- Division of Life Span Development and Clinical Psychology, Graduate School of Education, Ehime University, Matsuyama, Ehime, Japan
| | - Ryoichi Kawamura
- Department of Diabetes and Molecular Genetics, Ehime University Graduate School of Medicine, Toon, Ehime, Japan
| | - Yasunori Takata
- Department of Diabetes and Molecular Genetics, Ehime University Graduate School of Medicine, Toon, Ehime, Japan
| | - Haruhiko Osawa
- Department of Diabetes and Molecular Genetics, Ehime University Graduate School of Medicine, Toon, Ehime, Japan
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17
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Lu L, Zhu T, Morelli D, Creagh A, Liu Z, Yang J, Liu F, Zhang YT, Clifton DA. Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review. IEEE Rev Biomed Eng 2024; 17:180-196. [PMID: 37186539 DOI: 10.1109/rbme.2023.3271595] [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: 05/17/2023]
Abstract
Heart rate variability (HRV) is an important metric with a variety of applications in clinical situations such as cardiovascular diseases, diabetes mellitus, and mental health. HRV data can be potentially obtained from electrocardiography and photoplethysmography signals, then computational techniques such as signal filtering and data segmentation are used to process the sampled data for calculating HRV measures. However, uncertainties arising from data acquisition, computational models, and physiological factors can lead to degraded signal quality and affect HRV analysis. Therefore, it is crucial to address these uncertainties and develop advanced models for HRV analysis. Although several reviews of HRV analysis exist, they primarily focus on clinical applications, trends in HRV methods, or specific aspects of uncertainties such as measurement noise. This paper provides a comprehensive review of uncertainties in HRV analysis, quantifies their impacts, and outlines potential solutions. To the best of our knowledge, this is the first study that presents a holistic review of uncertainties in HRV methods and quantifies their impacts on HRV measures from an engineer's perspective. This review is essential for developing robust and reliable models, and could serve as a valuable future reference in the field, particularly for dealing with uncertainties in HRV analysis.
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18
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Zhang J, Li WC, Braithwaite G, Blundell J. Practice effects of a breathing technique on pilots' cognitive and stress associated heart rate variability during flight operations. Stress 2024; 27:2361253. [PMID: 38859613 DOI: 10.1080/10253890.2024.2361253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 05/22/2024] [Indexed: 06/12/2024] Open
Abstract
Commercial pilots endure multiple stressors in their daily and occupational lives which are detrimental to psychological well-being and cognitive functioning. The Quick coherence technique (QCT) is an effective intervention tool to improve stress resilience and psychophysiological balance based on a five-minute paced breathing exercise with heart rate variability (HRV) biofeedback. The current research reports on the application of QCT training within an international airline to improve commercial pilots' psychological health and support cognitive functions. Forty-four commercial pilots volunteered in a one-month training programme to practise self-regulated QCT in day-to-day life and flight operations. Pilots' stress index, HRV time-domain and frequency-domain parameters were collected to examine the influence of QCT practice on the stress resilience process. The results demonstrated that the QCT improved psychophysiological indicators associated with stress resilience and cognitive functions, in both day-to-day life and flight operation settings. HRV fluctuations, as measured through changes in RMSSD and LF/HF, revealed that the resilience processes were primarily controlled by the sympathetic nervous system activities that are important in promoting pilots' energy mobilization and cognitive functions, thus QCT has huge potential in facilitating flight performance and aviation safety. These findings provide scientific evidence for implementing QCT as an effective mental support programme and controlled rest strategy to improve pilots' psychological health, stress management, and operational performance.
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Affiliation(s)
- Jingyi Zhang
- Safety and Accident Investigation Centre, Cranfield University, Bedfordshire, UK
| | - Wen-Chin Li
- Safety and Accident Investigation Centre, Cranfield University, Bedfordshire, UK
| | - Graham Braithwaite
- Safety and Accident Investigation Centre, Cranfield University, Bedfordshire, UK
| | - James Blundell
- Safety and Accident Investigation Centre, Cranfield University, Bedfordshire, UK
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19
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Chen H, Tse MMY, Chung JWY, Yau SY, Wong TKS. Effects of posture on heart rate variability in non-frail and prefrail individuals: a cross-sectional study. BMC Geriatr 2023; 23:870. [PMID: 38114894 PMCID: PMC10729458 DOI: 10.1186/s12877-023-04585-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 12/11/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Frailty is an aging-related syndrome leading to high mortality in older adults. Without effective assessment and prevention of frailty, the incidence of frailty and relevant adverse outcomes will increase by 2050 as worldwide populations age. Although evidence suggested heart rate variability (HRV) is a potential measure of frailty, the role of HRV in frailty assessment remains unclear because of controversial findings. This study examined the effects of posture on HRV parameters in non-frail and prefrail individuals to understand the role of HRV in assessing frailty. METHODS Forty-six participants aged ≥ 50 years were recruited between April and August 2022. Frailty was defined using Fried's criteria. HRV was measured in standing, sitting, and lying postures, respectively, using a Polar Watch, and analyzed using Kubios HRV Standard 3.5.0 (Kubios). The five most commonly used parameters were examined, including standard deviations of all normal-to-normal intervals (SDNN), root mean square of the successive differences (RMSSD), low frequency (LF), high frequency (HF), and LF/HF. Independent t-tests and Mann-Whitney tests were used for inter-group comparisons. Friedman tests were used for intra-group comparisons across postures. RESULTS The non-frail group showed significant differences in HRV parameters across postures (all p < 0.05), whereas the prefrail group did not demonstrate any difference (all p > 0.05). The differences in the non-frail group included higher RMSSD and HF in the lying posture compared to those in the standing posture (29.54 vs 21.99 p = 0.003, 210.34 vs 96.34 p = 0.001, respectively), and higher LF and LF/HF in the sitting posture compared to those in the lying posture (248.40 vs 136.29 P = 0.024, 1.26 vs 0.77 p = 0.011, respectively). CONCLUSIONS The effects of posture on HRV were blunted in the prefrail group, which suggests an impaired cardiac autonomic functioning. Measuring the effects of posture on HRV parameters may contribute to frailty assessment. However, further evidence from larger cohorts and including additional HRV parameters is needed.
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Affiliation(s)
- Huiling Chen
- School of Nursing and Health Studies, Hong Kong Metropolitan University, Sheung Shing Street, Ho Man Tin, Hong Kong, China.
| | - Mimi Mun Yee Tse
- School of Nursing and Health Studies, Hong Kong Metropolitan University, Sheung Shing Street, Ho Man Tin, Hong Kong, China
| | | | - Sui Yu Yau
- School of Nursing and Health Studies, Hong Kong Metropolitan University, Sheung Shing Street, Ho Man Tin, Hong Kong, China
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20
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Li K, Cardoso C, Moctezuma-Ramirez A, Elgalad A, Perin E. Heart Rate Variability Measurement through a Smart Wearable Device: Another Breakthrough for Personal Health Monitoring? INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:7146. [PMID: 38131698 PMCID: PMC10742885 DOI: 10.3390/ijerph20247146] [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: 08/03/2023] [Revised: 11/06/2023] [Accepted: 11/27/2023] [Indexed: 12/23/2023]
Abstract
Heart rate variability (HRV) is a measurement of the fluctuation of time between each heartbeat and reflects the function of the autonomic nervous system. HRV is an important indicator for both physical and mental status and for broad-scope diseases. In this review, we discuss how wearable devices can be used to monitor HRV, and we compare the HRV monitoring function among different devices. In addition, we have reviewed the recent progress in HRV tracking with wearable devices and its value in health monitoring and disease diagnosis. Although many challenges remain, we believe HRV tracking with wearable devices is a promising tool that can be used to improve personal health.
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Affiliation(s)
- Ke Li
- Center for Preclinical Cardiovascular Research, The Texas Heart Institute, Houston, TX 77030, USA
| | - Cristiano Cardoso
- Center for Preclinical Cardiovascular Research, The Texas Heart Institute, Houston, TX 77030, USA
| | - Angel Moctezuma-Ramirez
- Center for Preclinical Cardiovascular Research, The Texas Heart Institute, Houston, TX 77030, USA
| | - Abdelmotagaly Elgalad
- Center for Preclinical Cardiovascular Research, The Texas Heart Institute, Houston, TX 77030, USA
| | - Emerson Perin
- Center for Clinical Research, The Texas Heart Institute, Houston, TX 77030, USA
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21
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López-Belmonte Ó, Febles-Castro A, Gay A, Cuenca-Fernández F, Arellano R, Ruiz-Navarro JJ. Validity of the polar verity sense during swimming at different locations and intensities. Scand J Med Sci Sports 2023; 33:2623-2625. [PMID: 37727999 DOI: 10.1111/sms.14494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/01/2023] [Accepted: 09/05/2023] [Indexed: 09/21/2023]
Affiliation(s)
- Óscar López-Belmonte
- Aquatics Lab, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain
| | - Adrián Febles-Castro
- Aquatics Lab, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain
| | - Ana Gay
- Aquatics Lab, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain
| | - Francisco Cuenca-Fernández
- Aquatics Lab, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain
- Department of Sports and Computer Sciences, Universidad Pablo de Olavide, Seville, Spain
| | - Raúl Arellano
- Aquatics Lab, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain
| | - Jesús J Ruiz-Navarro
- Aquatics Lab, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain
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22
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Charlton PH, Allen J, Bailón R, Baker S, Behar JA, Chen F, Clifford GD, Clifton DA, Davies HJ, Ding C, Ding X, Dunn J, Elgendi M, Ferdoushi M, Franklin D, Gil E, Hassan MF, Hernesniemi J, Hu X, Ji N, Khan Y, Kontaxis S, Korhonen I, Kyriacou PA, Laguna P, Lázaro J, Lee C, Levy J, Li Y, Liu C, Liu J, Lu L, Mandic DP, Marozas V, Mejía-Mejía E, Mukkamala R, Nitzan M, Pereira T, Poon CCY, Ramella-Roman JC, Saarinen H, Shandhi MMH, Shin H, Stansby G, Tamura T, Vehkaoja A, Wang WK, Zhang YT, Zhao N, Zheng D, Zhu T. The 2023 wearable photoplethysmography roadmap. Physiol Meas 2023; 44:111001. [PMID: 37494945 PMCID: PMC10686289 DOI: 10.1088/1361-6579/acead2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 04/04/2023] [Accepted: 07/26/2023] [Indexed: 07/28/2023]
Abstract
Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.
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Affiliation(s)
- Peter H Charlton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, United Kingdom
- Research Centre for Biomedical Engineering, City, University of London, London, EC1V 0HB, United Kingdom
| | - John Allen
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, CV1 5RW, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Raquel Bailón
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Stephanie Baker
- College of Science and Engineering, James Cook University, Cairns, 4878 Queensland, Australia
| | - Joachim A Behar
- Faculty of Biomedical Engineering, Technion Israel Institute of Technology, Haifa, 3200003, Israel
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, 518055 Guandong, People’s Republic of China
| | - Gari D Clifford
- Department of Biomedical Informatics, Emory University, Atlanta, GA 30322, United States of America
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States of America
| | - David A Clifton
- Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, United Kingdom
| | - Harry J Davies
- Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, United Kingdom
| | - Cheng Ding
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States of America
- Department of Biomedical Engineering, Emory University, Atlanta, GA 30322, United States of America
| | - Xiaorong Ding
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China
| | - Jessilyn Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC 27708-0187, United States of America
- Department of Biostatistics & Bioinformatics, Duke University, Durham, NC 27708-0187, United States of America
- Duke Clinical Research Institute, Durham, NC 27705-3976, United States of America
| | - Mohamed Elgendi
- Biomedical and Mobile Health Technology Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, 8008, Switzerland
| | - Munia Ferdoushi
- Department of Electrical and Computer Engineering, University of Southern California, 90089, Los Angeles, California, United States of America
- The Institute for Technology and Medical Systems (ITEMS), Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America
| | - Daniel Franklin
- Institute of Biomedical Engineering, Translational Biology & Engineering Program, Ted Rogers Centre for Heart Research, University of Toronto, Toronto, M5G 1M1, Canada
| | - Eduardo Gil
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Md Farhad Hassan
- Department of Electrical and Computer Engineering, University of Southern California, 90089, Los Angeles, California, United States of America
- The Institute for Technology and Medical Systems (ITEMS), Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America
| | - Jussi Hernesniemi
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33720, Finland
- Tampere Heart Hospital, Wellbeing Services County of Pirkanmaa, Tampere, 33520, Finland
| | - Xiao Hu
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, 30322, Georgia, United States of America
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, 30322, Georgia, United States of America
- Department of Computer Sciences, College of Arts and Sciences, Emory University, Atlanta, GA 30322, United States of America
| | - Nan Ji
- Hong Kong Center for Cerebrocardiovascular Health Engineering (COCHE), Hong Kong Science and Technology Park, Hong Kong, 999077, People’s Republic of China
| | - Yasser Khan
- Department of Electrical and Computer Engineering, University of Southern California, 90089, Los Angeles, California, United States of America
- The Institute for Technology and Medical Systems (ITEMS), Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America
| | - Spyridon Kontaxis
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Ilkka Korhonen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33720, Finland
| | - Panicos A Kyriacou
- Research Centre for Biomedical Engineering, City, University of London, London, EC1V 0HB, United Kingdom
| | - Pablo Laguna
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Jesús Lázaro
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Chungkeun Lee
- Digital Health Devices Division, Medical Device Evaluation Department, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju, 28159, Republic of Korea
| | - Jeremy Levy
- Faculty of Biomedical Engineering, Technion Israel Institute of Technology, Haifa, 3200003, Israel
- Faculty of Electrical and Computer Engineering, Technion Institute of Technology, Haifa, 3200003, Israel
| | - Yumin Li
- State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, People’s Republic of China
| | - Chengyu Liu
- State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, People’s Republic of China
| | - Jing Liu
- Analog Devices Inc, San Jose, CA 95124, United States of America
| | - Lei Lu
- Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, United Kingdom
| | - Danilo P Mandic
- Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, United Kingdom
| | - Vaidotas Marozas
- Department of Electronics Engineering, Kaunas University of Technology, 44249 Kaunas, Lithuania
- Biomedical Engineering Institute, Kaunas University of Technology, 44249 Kaunas, Lithuania
| | - Elisa Mejía-Mejía
- Research Centre for Biomedical Engineering, City, University of London, London, EC1V 0HB, United Kingdom
| | - Ramakrishna Mukkamala
- Department of Bioengineering and Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Meir Nitzan
- Department of Physics/Electro-Optic Engineering, Lev Academic Center, 91160 Jerusalem, Israel
| | - Tania Pereira
- INESC TEC—Institute for Systems and Computer Engineering, Technology and Science, Porto, 4200-465, Portugal
- Faculty of Engineering, University of Porto, Porto, 4200-465, Portugal
| | | | - Jessica C Ramella-Roman
- Department of Biomedical Engineering and Herbert Wertheim College of Medicine, Florida International University, Miami, FL 33174, United States of America
| | - Harri Saarinen
- Tampere Heart Hospital, Wellbeing Services County of Pirkanmaa, Tampere, 33520, Finland
| | - Md Mobashir Hasan Shandhi
- Department of Biomedical Engineering, Duke University, Durham, NC 27708-0187, United States of America
| | - Hangsik Shin
- Department of Digital Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, Republic of Korea
| | - Gerard Stansby
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
- Northern Vascular Centre, Freeman Hospital, Newcastle upon Tyne, NE7 7DN, United Kingdom
| | - Toshiyo Tamura
- Future Robotics Organization, Waseda University, Tokyo, 1698050, Japan
| | - Antti Vehkaoja
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33720, Finland
- PulseOn Ltd, Espoo, 02150, Finland
| | - Will Ke Wang
- Department of Biomedical Engineering, Duke University, Durham, NC 27708-0187, United States of America
| | - Yuan-Ting Zhang
- Hong Kong Center for Cerebrocardiovascular Health Engineering (COCHE), Hong Kong Science and Technology Park, Hong Kong, 999077, People’s Republic of China
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, 999077, People’s Republic of China
| | - Ni Zhao
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong
| | - Dingchang Zheng
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, CV1 5RW, United Kingdom
| | - Tingting Zhu
- Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, United Kingdom
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23
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Abiri A, Chou EF, Shen W, Fisher MJ, Khine M. Changes in beat-to-beat blood pressure and pulse rate variability following stroke. Sci Rep 2023; 13:19245. [PMID: 37935766 PMCID: PMC10630489 DOI: 10.1038/s41598-023-45479-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 10/19/2023] [Indexed: 11/09/2023] Open
Abstract
Associations between cerebrovascular disease and impaired autonomic function and cerebrovascular reactivity have led to increased interest in variability of heart rate (HRV) and blood pressure (BPV) following stroke. In this study, beat-to-beat pulse rate variability (PRV) and BPV were measured in clinically stable stroke patients (6 ischemic, 2 hemorrhagic) at least one year after their last cerebrovascular event. Beat-to-beat blood pressure (BP) measurements were collected from subjects while resting in the sitting position for one hour. Compared with healthy controls, stroke patients exhibited significantly greater time-domain (standard deviation, coefficient of variation, average real variability) and normalized high-frequency BPV (all p < 0.05). Stroke patients also exhibited lower LF:HF ratios than control subjects (p = 0.003). No significant differences were observed in PRV between the two groups, suggesting that BPV may be a more sensitive biomarker of cerebrovascular function in long-term post-stroke patients. Given a paucity of existing literature investigating beat-to-beat BPV in clinically stable post-stroke patients long (> 1 year) after their cerebrovascular events, this pilot study can help inform future studies investigating the mechanisms and effects of BPV in stroke. Elucidating this physiology may facilitate long-term patient monitoring and pharmacological management to mitigate the risk for recurrent stroke.
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Affiliation(s)
- Arash Abiri
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA
| | - En-Fan Chou
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA
| | - Weining Shen
- Department of Statistics, University of California Irvine, Irvine, CA, USA
| | - Mark J Fisher
- Department of Neurology, Irvine Medical Center, University of California, Orange, CA, USA
| | - Michelle Khine
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA.
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24
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Schoffl J, Pozzato I, Rodrigues D, Arora M, Craig A. Pulse rate variability: An alternative to heart rate variability in adults with spinal cord injury. Psychophysiology 2023; 60:e14356. [PMID: 37287336 DOI: 10.1111/psyp.14356] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 03/16/2023] [Accepted: 05/15/2023] [Indexed: 06/09/2023]
Abstract
Pulse rate variability (PRV) is often used as an alternative to heart rate variability (HRV) to measure psychophysiological function. However, its validity to do so is unclear, especially in adults with spinal cord injury (SCI). This study compared PRV and HRV in adults with higher-level SCI (SCI-H, n = 23), lower-level SCI (SCI-L, n = 22), and able-bodied participants (AB n = 44), in a seated position as a function of performance in a reactivity task (Oxford Sleep Resistance Test: OSLER). PRV and HRV was measured using reflective finger-based photoplethysmography (PPG) and electrocardiography, respectively, at baseline, immediately post-OSLER, and after five-minute recovery. Agreement between PRV and HRV was determined by Bland-Altman analysis and differences between PRV and HRV over time by linear mixed effects model (LMM) analysis. Concurrent validity was assessed through correlation analyses between PRV and HRV. Additional correlation analyses were performed with psychosocial factors. Results indicated insufficient to moderate agreement between PRV and HRV. LMM analyses indicated no differences over time for standard deviation of normal-to-normal intervals and low-frequency power but significant differences for root mean square of successive differences and high frequency power. Nevertheless, PRV and HRV were highly correlated (Median r = .878 (.675-.990)) during all assessment periods suggesting sufficient concurrent validity. Similar correlation patterns were also found for PRV and HRV with psychosocial outcomes. While differences existed, results suggest PRV derived from reflective finger-based PPG is a valid proxy of HRV in tracking psychophysiological function in adults with SCI and could therefore be used as a more accessible monitoring tool.
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Affiliation(s)
- Jacob Schoffl
- John Walsh Centre for Rehabilitation Research, The Kolling Institute, St Leonards, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Ilaria Pozzato
- John Walsh Centre for Rehabilitation Research, The Kolling Institute, St Leonards, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Dianah Rodrigues
- John Walsh Centre for Rehabilitation Research, The Kolling Institute, St Leonards, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Mohit Arora
- John Walsh Centre for Rehabilitation Research, The Kolling Institute, St Leonards, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Ashley Craig
- John Walsh Centre for Rehabilitation Research, The Kolling Institute, St Leonards, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
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25
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Brun R, Girsberger J, Rothenbühler M, Argyle C, Hutmacher J, Haslinger C, Leeners B. Wearable sensors for prediction of intraamniotic infection in women with preterm premature rupture of membranes: a prospective proof of principle study. Arch Gynecol Obstet 2023; 308:1447-1456. [PMID: 36098832 PMCID: PMC9469066 DOI: 10.1007/s00404-022-06753-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 08/12/2022] [Indexed: 11/25/2022]
Abstract
PURPOSE To evaluate the use of wearable sensors for prediction of intraamniotic infection in pregnant women with PPROM. MATERIALS AND METHODS In a prospective proof of principle study, we included 50 patients diagnosed with PPROM at the University Hospital Zurich between November 2017 and May 2020. Patients were instructed to wear a bracelet during the night, which measures physiological parameters including wrist skin temperature, heart rate, heart rate variability, and breathing rate. A two-way repeated measures ANOVA was performed to evaluate the difference over time of both the wearable device measured parameters and standard clinical monitoring values, such as body temperature, pulse, leucocytes, and C-reactive protein, between women with and without intraamniotic infection. RESULTS Altogether, 23 patients (46%) were diagnosed with intraamniotic infection. Regarding the physiological parameters measured with the bracelet, we observed a significant difference in breathing rate (19 vs 16 per min, P < .01) and heart rate (72 vs 67 beats per min, P = .03) in women with intraamniotic infection compared to those without during the 3 days prior to birth. In parallel to these changes standard clinical monitoring values were significantly different in the intraamniotic infection group compared to women without infection in the 3 days preceding birth. CONCLUSION Our results suggest that wearable sensors are a promising, noninvasive, patient friendly approach to support the early detection of intraamniotic infection in women with PPROM. However, confirmation of our findings in larger studies is required before implementing this technique in standard clinical management.
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Affiliation(s)
- Romana Brun
- Department of Obstetrics, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.
| | - Julia Girsberger
- Department of Reproductive Endocrinology, University Hospital Zurich, Zurich, Switzerland
- University of Zurich, Zurich, Switzerland
| | | | | | - Juliane Hutmacher
- Department of Gynecology and Obstetrics, Cantonal Hospital Frauenfeld, Frauenfeld, Switzerland
| | - Christian Haslinger
- Department of Obstetrics, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Brigitte Leeners
- Department of Reproductive Endocrinology, University Hospital Zurich, Zurich, Switzerland
- University of Zurich, Zurich, Switzerland
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26
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Welsh MR, Mosley E, Laborde S, Day MC, Sharpe BT, Burkill RA, Birch PDJ. The use of heart rate variability in esports: A systematic review. PSYCHOLOGY OF SPORT AND EXERCISE 2023; 69:102495. [PMID: 37665930 DOI: 10.1016/j.psychsport.2023.102495] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/14/2023] [Accepted: 07/17/2023] [Indexed: 09/06/2023]
Abstract
Heart rate variability (HRV) is a psychophysiological measure of particular interest in esports due to its potential to monitor player self-regulation. This study aimed to systematically review the utilisation of HRV in esports. Consideration was given to the methodological and theoretical underpinnings of previous works to provide recommendations for future research. The protocol was made available on the Open Science Framework. Inclusion criteria were empirical studies, examining HRV in esports, using esports players, published in English. Exclusion criteria were non-peer-reviewed studies, populations with pre-existing clinical illness other than Internet Gaming Disorder (IGD), opinion pieces or review papers. In November 2022 a search of Web of Science, PubMed, and EBSCOHost identified seven studies using HRV in esports. Risk of bias was assessed using the Mixed Methods Appraisal Tool. Narrative review identified two primary uses of HRV in esports; stress response and IGD. A lack of theoretical and methodological underpinning was identified as a major limitation of current literature. Further investigation is necessary before making recommendations regarding the use of HRV in esports. Future research should employ sound theoretical underpinning such as the use of vagally mediated HRV and the robust application of supporting methodological guidelines when investigating HRV in esports.
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Affiliation(s)
- Matthew R Welsh
- Institute of Applied Sciences, University of Chichester, Chichester, UK.
| | - Emma Mosley
- Department of Rehabilitation and Sport Sciences, Bournemouth University, Bournemouth, UK
| | - Sylvain Laborde
- Department of Performance Psychology, Institute of Psychology, German Sport University Cologne, Koln, Germany; UFR STAPS, Normandie Université Caen, Caen, France
| | - Melissa C Day
- Institute of Applied Sciences, University of Chichester, Chichester, UK
| | - Benjamin T Sharpe
- Institute of Psychology, Business, and Human Sciences, University of Chichester, Chichester, UK
| | | | - Phil D J Birch
- Institute of Applied Sciences, University of Chichester, Chichester, UK
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27
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Joessel F, Pichon S, Bavelier D. A video-game-based method to induce states of high and low flow. Behav Res Methods 2023:10.3758/s13428-023-02251-w. [PMID: 37864115 DOI: 10.3758/s13428-023-02251-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/18/2023] [Indexed: 10/22/2023]
Abstract
Flow has been defined as a state of full immersion that may emerge when the skills of a person match the challenge of an activity. It is a special case of being on task, as during flow, keeping focused on the task feels effortless. Most experimental investigations of the neural or physiological correlates of flow contrast conditions with different levels of challenge. Yet comparing different levels of challenge that are too distant may trigger states where the participant is off task, such as boredom or frustration. Thus, it remains unclear whether previously observed differences ascribed to flow may rather reflect differences in how much participants were on task-trying their best-across the contrasted conditions. To remedy this, we introduce a method to manipulate flow by contrasting two video game play conditions at personalized levels of difficulty calibrated such that participants similarly tried their best in both conditions. Across three experiments (> 90 participants), higher flow was robustly reported in our high-flow than in our low-flow condition (mean effect size d = 1.31). Cardiac, respiratory, and skin conductance measures confirmed the known difference between a period of rest and the two on-task conditions of high and low flow, but failed to distinguish between these latter two. In light of the conflicting findings regarding the physiological correlates of flow, we discuss the importance of ensuring a low-flow baseline condition that maintains participants on task, and propose that the present method provides a methodological advance toward that goal.
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Affiliation(s)
- Freya Joessel
- Faculté de Psychologie et Sciences de L'Education, (FPSE), Université de Genève, Boulevard du Pont d'Arve, 40, 1205, Geneva, Switzerland
- Campus Biotech, Chemin des Mines, 9, 1202, Geneva, Switzerland
| | - Swann Pichon
- Faculté de Psychologie et Sciences de L'Education, (FPSE), Université de Genève, Boulevard du Pont d'Arve, 40, 1205, Geneva, Switzerland
- Campus Biotech, Chemin des Mines, 9, 1202, Geneva, Switzerland
- Geneva School of Health Sciences, HES-SO University of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland
| | - Daphne Bavelier
- Faculté de Psychologie et Sciences de L'Education, (FPSE), Université de Genève, Boulevard du Pont d'Arve, 40, 1205, Geneva, Switzerland.
- Campus Biotech, Chemin des Mines, 9, 1202, Geneva, Switzerland.
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28
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Kumar SM, Vaishali K, Maiya GA, Shivashankar K, Shashikiran U. Analysis of time-domain indices, frequency domain measures of heart rate variability derived from ECG waveform and pulse-wave-related HRV among overweight individuals: an observational study. F1000Res 2023; 12:1229. [PMID: 37799491 PMCID: PMC10548108 DOI: 10.12688/f1000research.139283.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/23/2023] [Indexed: 10/07/2023] Open
Abstract
Background: Research on the compatibility of time domain indices, frequency domain measurements of heart rate variability obtained from electrocardiogram (ECG) waveforms, and pulse wave signal (pulse rate variability; PRV) features is ongoing. The promising marker of cardiac autonomic function is heart rate variability. Recent research has looked at various other physiological markers, leading to the emergence of pulse rate variability. The pulse wave signal can be studied for variations to understand better changes in arterial stiffness and compliance, which are key indicators of cardiovascular health. Methods: 35 healthy overweight people were included. The Lead II electrocardiogram (ECG) signal was transmitted through an analog-to-digital converter (PowerLab 8/35 software, AD Instruments Pty. Ltd., New South Wales, Australia). This signal was utilized to compute Heart Rate Variability (HRV) and was sampled at a rate of 1024 Hz. The same AD equipment was also used to capture a pulse signal simultaneously. The right index finger was used as the recording site for the pulse signal using photoplethysmography (PPG) technology. Results: The participants' demographic data show that the mean age was 23.14 + 5.27 years, the mean weight was 73.68 + 7.40 kg, the mean body fat percentage was 32.23 + 5.30, and the mean visceral fat percentage was 4.60 + 2.0. The findings revealed no noticeable difference between the median values of heart rate variability (HRV) and PRV. Additionally, a strong correlation was observed between HRV and PRV. However, poor agreement was observed in the measurement of PRV and HRV. Conclusion: All indices of HRV showed a greater correlation with PRV. However, the level of agreement between HRV and PRV measurement was poor. Hence, HRV cannot be replaced with PRV and vice-versa.
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Affiliation(s)
- Sinha Mukesh Kumar
- Department of Physiotherapy, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
| | - K. Vaishali
- Department of Physiotherapy, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
| | - G. Arun Maiya
- Department of Physiotherapy, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
| | - K.N. Shivashankar
- Department of Medicine, Kasturba Medical college, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
| | - U. Shashikiran
- Department of Medicine, Dr. TMA Pai Hospital, Udupi, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
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29
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Serrano-Finetti E, Hornero G, Mainar S, López F, Crailsheim D, Feliu O, Casas O. A non-invasive, concealed electrocardiogram and bioimpedance measurement system for captive primates. J Exp Biol 2023; 226:jeb245783. [PMID: 37599599 DOI: 10.1242/jeb.245783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 08/14/2023] [Indexed: 08/22/2023]
Abstract
Captive housed non-human primates, specifically great apes such as chimpanzees (Pan troglodytes) are frequently reported to have died from or are diagnosed with potentially fatal heart conditions that require the monitoring of physiological signals such as electrocardiogram (ECG) or respiratory rate. ECG screening must be conducted after applying full anaesthesia, causing potential physical and emotional stress as well as risk for the animal. Here, we present an electronic system that simultaneously measures the ECG and the electrical bioimpedance for the early detection of abnormal cardiovascular activity. Modified gloves whose fingers are equipped with electrodes enable the caregiver to obtain three cardiovascular signals (ECG, pulse rate and respiratory rate) by placing the fingertips on specific parts of the non-human primate without needing any prior physical preparations. Validation (ECG and bioimpedance) was performed both on humans and on captive housed chimpanzees, where all the signals of interest were correctly acquired.
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Affiliation(s)
- Ernesto Serrano-Finetti
- Instrumentation, Sensor and Interfaces Group, Electronic Engineering Department, Castelldefels School of Telecommunications and Aerospace Engineering, Universitat Politècnica de Catalunya, 08860 Barcelona, Spain
| | - Gemma Hornero
- Instrumentation, Sensor and Interfaces Group, Electronic Engineering Department, Castelldefels School of Telecommunications and Aerospace Engineering, Universitat Politècnica de Catalunya, 08860 Barcelona, Spain
| | - Sergio Mainar
- Instrumentation, Sensor and Interfaces Group, Electronic Engineering Department, Castelldefels School of Telecommunications and Aerospace Engineering, Universitat Politècnica de Catalunya, 08860 Barcelona, Spain
| | - Francisco López
- Instrumentation, Sensor and Interfaces Group, Electronic Engineering Department, Castelldefels School of Telecommunications and Aerospace Engineering, Universitat Politècnica de Catalunya, 08860 Barcelona, Spain
| | | | - Olga Feliu
- Research Department, Fundació Mona, 17457 Girona, Spain
| | - Oscar Casas
- Instrumentation, Sensor and Interfaces Group, Electronic Engineering Department, Castelldefels School of Telecommunications and Aerospace Engineering, Universitat Politècnica de Catalunya, 08860 Barcelona, Spain
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Tan C, Xiao C, Wang W. Camera-based Cardiovascular Screening based on Heart Rate and Its Variability In Pre- and Post-Exercise Conditions. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-5. [PMID: 38083672 DOI: 10.1109/embc40787.2023.10340871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Analysis of heart rate (HR) and heart rate variability (HRV) in pre- and post-exercise conditions can provide useful information about the health condition of cardiovascular system. Remote photoplethysmography (rPPG) that uses a contactless camera to measure vital signs from the human face might allow for ubiquitous applications in the fitness scenario. This paper benchmarks the accuracy of HR and HRV measured by ECG, PPG and rPPG, and investigates the difference of HR and HRV parameters between individuals with/without the exercise habit in pre- and post-exercise phases. We built a fitness benchmark consisting of 14 healthy subjects to perform running exercise on a treadmill, with video and reference data recorded simultaneously. The results show that rPPG has a similar performance as PPG in both the estimation of HR and HRV. The HRV parameters (Mean IBI, SDNN, LF, VLF, and SD2) of rPPG/PPG show good agreements with the ECG reference. Subjects with a regular exercise habit show lower resting HR and smaller values of HRV parameters in pre-exercise phase, fewer changes in HR and HRV at the same exercise intensity, and faster HR recovery after exercising, as compared with those without an exercise habit. The preliminary results suggest that rPPG is a promising surrogate of PPG for screening HR and HRV before and after exercise, to indicate the performance of cardiac training.
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Wang JJ, Liu SH, Tsai CH, Manousakas I, Zhu X, Lee TL. Signal Quality Analysis of Single-Arm Electrocardiography. SENSORS (BASEL, SWITZERLAND) 2023; 23:5818. [PMID: 37447668 DOI: 10.3390/s23135818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 06/15/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023]
Abstract
The number of people experiencing mental stress or emotional dysfunction has increased since the onset of the COVID-19 pandemic, as many individuals have had to adapt their daily lives. Numerous studies have demonstrated that mental health disorders can pose a risk for certain diseases, and they are also closely associated with the problem of mental workload. Now, wearable devices and mobile health applications are being utilized to monitor and assess individuals' mental health conditions on a daily basis using heart rate variability (HRV), typically measured by the R-to-R wave interval (RRI) of an electrocardiogram (ECG). However, portable or wearable ECG devices generally require two electrodes to perform bipolar limb leads, such as the Einthoven triangle. This study aims to develop a single-arm ECG measurement method, with lead I ECG serving as the gold standard. We conducted static and dynamic experiments to analyze the morphological performance and signal-to-noise ratio (SNR) of the single-arm ECG. Three morphological features were defined, RRI, the duration of the QRS complex wave, and the amplitude of the R wave. Thirty subjects participated in this study. The results indicated that RRI exhibited the highest cross-correlation (R = 0.9942) between the single-arm ECG and lead I ECG, while the duration of the QRS complex wave showed the weakest cross-correlation (R = 0.2201). The best SNR obtained was 26.1 ± 5.9 dB during the resting experiment, whereas the worst SNR was 12.5 ± 5.1 dB during the raising and lowering of the arm along the z-axis. This single-arm ECG measurement method offers easier operation compared to traditional ECG measurement techniques, making it applicable for HRV measurement and the detection of an irregular RRI.
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Affiliation(s)
- Jia-Jung Wang
- Department of Biomedical Engineering, I-Shou University, Kaohsiung 84001, Taiwan
| | - Shing-Hong Liu
- Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan
| | - Cheng-Hsien Tsai
- Department of Biomedical Engineering, I-Shou University, Kaohsiung 84001, Taiwan
| | - Ioannis Manousakas
- Department of Biomedical Engineering, I-Shou University, Kaohsiung 84001, Taiwan
| | - Xin Zhu
- Division of Information Systems, School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City 965-8580, Japan
| | - Thung-Lip Lee
- Department of Cardiology, E-Da Hospital, Kaohsiung 84001, Taiwan
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López-Galán E, Vitón-Castillo AA, Carrazana-Escalona R, Planas-Rodriguez M, Fernández-García AA, Cutiño-Clavel I, Pascau-Simon A, Connes P, Sánchez-Hechavarría ME, Muñoz-Bustos GA. Autonomic and Vascular Responses during Reactive Hyperemia in Healthy Individuals and Patients with Sickle Cell Anemia. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1141. [PMID: 37374344 DOI: 10.3390/medicina59061141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 04/07/2023] [Accepted: 05/10/2023] [Indexed: 06/29/2023]
Abstract
Background and Objectives: To compare autonomic and vascular responses during reactive hyperemia (RH) between healthy individuals and patients with sickle cell anemia (SCA). Materials and Methods: Eighteen healthy subjects and 24 SCA patients were subjected to arterial occlusion for 3 min at the lower right limb level. The pulse rate variability (PRV) and pulse wave amplitude were measured through photoplethysmography using the Angiodin® PD 3000 device, which was placed on the first finger of the lower right limb 2 min before (Basal) and 2 min after the occlusion. Pulse peak intervals were analyzed using time-frequency (wavelet transform) methods for high-frequency (HF: 0.15-0.4) and low-frequency (LF: 0.04-0.15) bands, and the LF/HF ratio was calculated. Results: The pulse wave amplitude was higher in healthy subjects compared to SCA patients, at both baseline and post-occlusion (p < 0.05). Time-frequency analysis showed that the LF/HF peak in response to the post-occlusion RH test was reached earlier in healthy subjects compared to SCA patients. Conclusions: Vasodilatory function, as measured by PPG, was lower in SCA patients compared to healthy subjects. Moreover, a cardiovascular autonomic imbalance was present in SCA patients with high sympathetic and low parasympathetic activity in the basal state and a poor response of the sympathetic nervous system to RH. Early cardiovascular sympathetic activation (10 s) and vasodilatory function in response to RH were impaired in SCA patients.
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Affiliation(s)
- Erislandis López-Galán
- Departamento de Ciencias Básicas Biomédicas, Facultad de Medicina, Universidad de Ciencias Médicas de Santiago de Cuba, Santiago de Cuba 90100, Cuba
| | - Adrián Alejandro Vitón-Castillo
- Facultad de Ciencias Médicas "Dr. Ernesto Che Guevara de la Serna", Universidad de Ciencias Médicas de Pinar del Rio, Pinar del Rio 20100, Cuba
| | - Ramón Carrazana-Escalona
- Departamento de Ciencias Clínicas Básicas, Facultad de Medicina, Universidad Católica de la Santísima Concepción, Concepción 4090541, Chile
| | - Maylet Planas-Rodriguez
- Departamento de Ciencias Básicas Biomédicas, Facultad de Medicina, Universidad de Ciencias Médicas de Santiago de Cuba, Santiago de Cuba 90100, Cuba
| | | | - Ileana Cutiño-Clavel
- Departamento de Ciencias Básicas Biomédicas, Facultad de Medicina, Universidad de Ciencias Médicas de Santiago de Cuba, Santiago de Cuba 90100, Cuba
| | - Alexander Pascau-Simon
- Hospital General "Dr. Juan Bruno Zayas Alfonso", Laboratorio Vascular no Invasivo, Santiago de Cuba 90400, Cuba
| | - Philippe Connes
- LIBM Laboratory, Team "Vascular Biology and Red Blood Cell", Claude Bernard University Lyon 1, 69622 Lyon, France
| | - Miguel Enrique Sánchez-Hechavarría
- Grupo Bio-Bio Complejidad, Departamento de Ciencias Clínicas y Preclínicas, Facultad de Medicina, Universidad Católica de la Santísima Concepción, Concepción 4090541, Chile
- Núcleo Científico de Ciencias de la Salud, Facultad de Ciencias de la Salud, Universidad Adventista de Chile, Chillán 3780000, Chile
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Fiani D, Campbell H, Solmi M, Fiedorowicz JG, Calarge CA. Impact of antidepressant use on the autonomic nervous system: A meta-analysis and systematic review. Eur Neuropsychopharmacol 2023; 71:75-95. [PMID: 37075594 DOI: 10.1016/j.euroneuro.2023.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 03/20/2023] [Accepted: 03/29/2023] [Indexed: 04/21/2023]
Abstract
Changes in cardiac autonomic nervous system (ANS) regulation observed in psychiatric disorders may be mitigated by antidepressants. We meta-analyzed and systematically reviewed studies examining antidepressants' effects on ANS outcomes, including heart rate variability (HRV). We conducted a PRISMA/MOOSE-compliant search of PubMed and Scopus until March 28th, 2022. We included randomized placebo-controlled trials (RCTs) and pre-post studies, regardless of diagnosis. We pooled results in random-effects meta-analyses, pooling homogeneous study designs and outcomes. We conducted sensitivity analyses and assessed quality of included studies. Thirty studies could be meta-analyzed. Selective serotonin reuptake inhibitors (SSRIs) were significantly associated with a reduction in the square root of the mean-squared difference between successive R-R intervals (RMSSD) (SMD= -0.48) and skin conductance response (SMD= -0.55) in RCTs and with a significant increase in RMSSD in pre-post studies (SMD=0.27). In pre-post studies, tricyclic antidepressants (TCAs) were associated with a significant decrease in several HRV outcomes while agomelatine was associated with a significant increase in high frequency power (SMD= 0.14). In conclusion, SSRIs reduce skin conductance response but have no or inconclusive effects on other ANS outcomes, depending on study design. TCAs reduce markers of parasympathetic function while agomelatine might have the opposite effect. Studies are needed to investigate the impact of SSRIs on the recovery of cardiac ANS regulation after acute myocardial infarction, and the effects of newer antidepressants.
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Affiliation(s)
- Dimitri Fiani
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Hannah Campbell
- Duke Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, United States
| | - Marco Solmi
- Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada; Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Jess G Fiedorowicz
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Chadi A Calarge
- Menninger Department of Psychiatry and Behavioral Sciences, Department of Pediatrics, Baylor College of Medicine, Houston, TX, United States.
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Sato S, Hiratsuka T, Hasegawa K, Watanabe K, Obara Y, Kariya N, Shinba T, Matsui T. Screening for Major Depressive Disorder Using a Wearable Ultra-Short-Term HRV Monitor and Signal Quality Indices. SENSORS (BASEL, SWITZERLAND) 2023; 23:3867. [PMID: 37112208 PMCID: PMC10143236 DOI: 10.3390/s23083867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/06/2023] [Accepted: 04/07/2023] [Indexed: 06/19/2023]
Abstract
To encourage potential major depressive disorder (MDD) patients to attend diagnostic sessions, we developed a novel MDD screening system based on sleep-induced autonomic nervous responses. The proposed method only requires a wristwatch device to be worn for 24 h. We evaluated heart rate variability (HRV) via wrist photoplethysmography (PPG). However, previous studies have indicated that HRV measurements obtained using wearable devices are susceptible to motion artifacts. We propose a novel method to improve screening accuracy by removing unreliable HRV data (identified on the basis of signal quality indices (SQIs) obtained by PPG sensors). The proposed algorithm enables real-time calculation of signal quality indices in the frequency domain (SQI-FD). A clinical study conducted at Maynds Tower Mental Clinic enrolled 40 MDD patients (mean age, 37.5 ± 8.8 years) diagnosed on the basis of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and 29 healthy volunteers (mean age, 31.9 ± 13.0 years). Acceleration data were used to identify sleep states, and a linear classification model was trained and tested using HRV and pulse rate data. Ten-fold cross-validation showed a sensitivity of 87.3% (80.3% without SQI-FD data) and specificity of 84.0% (73.3% without SQI-FD data). Thus, SQI-FD drastically improved sensitivity and specificity.
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Affiliation(s)
- Shohei Sato
- Department of Electrical Engineering and Computer Science, Faculty of Systems Design, Tokyo Metropolitan University, Tokyo 191-0065, Japan
| | - Takuma Hiratsuka
- Department of Electrical Engineering and Computer Science, Faculty of Systems Design, Tokyo Metropolitan University, Tokyo 191-0065, Japan
| | - Kenya Hasegawa
- Department of Electrical Engineering and Computer Science, Faculty of Systems Design, Tokyo Metropolitan University, Tokyo 191-0065, Japan
| | - Keisuke Watanabe
- Department of Electrical Engineering and Computer Science, Faculty of Systems Design, Tokyo Metropolitan University, Tokyo 191-0065, Japan
| | - Yusuke Obara
- Maynds Tower Mental Clinic, Tokyo 151-0053, Japan
| | | | - Toshikazu Shinba
- Department of Psychiatry, Shizuoka Saiseikai General Hospital, Shizuoka 422-8527, Japan
- Research Division, Saiseikai Research Institute of Health Care and Welfare, Tokyo 108-0073, Japan
| | - Takemi Matsui
- Department of Electrical Engineering and Computer Science, Graduate School of System Design, Tokyo Metropolitan University, Tokyo 191-0065, Japan
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Cao YT, Zhao XX, Yang YT, Zhu SJ, Zheng LD, Ying T, Sha Z, Zhu R, Wu T. Potential of electronic devices for detection of health problems in older adults at home: A systematic review and meta-analysis. Geriatr Nurs 2023; 51:54-64. [PMID: 36893611 DOI: 10.1016/j.gerinurse.2023.02.007] [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: 12/11/2022] [Revised: 02/11/2023] [Accepted: 02/13/2023] [Indexed: 03/09/2023]
Abstract
OBJECTIVE The aim of this review was to evaluate the overall diagnostic performance of e-devices for detection of health problems in older adults at home. METHODS A systematic review was conducted following the PRISMA-DTA guidelines. RESULTS 31 studies were included with 24 studies included in meta-analysis. The included studies were divided into four categories according to the signals detected: physical activity (PA), vital signs (VS), electrocardiography (ECG) and other. The meta-analysis showed the pooled estimates of sensitivity and specificity were 0.94 and 0.98 respectively in the 'VS' group. The pooled sensitivity and specificity were 0.97 and 0.98 respectively in the 'ECG' group. CONCLUSIONS All kinds of e-devices perform well in diagnosing the common health problems. While ECG-based health problems detection system is more reliable than VS-based ones. For sole signal detection system has limitation in diagnosing specific health problems, more researches should focus on developing new systems combined of multiple signals.
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Affiliation(s)
- Yu-Ting Cao
- Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200092, China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of the Ministry of Education, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, 200065 Shanghai, China
| | - Xin-Xin Zhao
- Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200092, China
| | - Yi-Ting Yang
- Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200092, China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of the Ministry of Education, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, 200065 Shanghai, China
| | - Shi-Jie Zhu
- Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200092, China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of the Ministry of Education, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, 200065 Shanghai, China
| | - Liang-Dong Zheng
- Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200092, China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of the Ministry of Education, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, 200065 Shanghai, China
| | - Ting Ying
- Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200092, China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of the Ministry of Education, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, 200065 Shanghai, China
| | - Zhou Sha
- Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200092, China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of the Ministry of Education, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, 200065 Shanghai, China
| | - Rui Zhu
- Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200092, China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of the Ministry of Education, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, 200065 Shanghai, China.
| | - Tao Wu
- Shanghai University of Medicine & Health Sciences, 201318 Shanghai, China
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36
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Wei K, Zou L, Liu G, Wang C. MS-Net: Sleep apnea detection in PPG using multi-scale block and shadow module one-dimensional convolutional neural network. Comput Biol Med 2023; 155:106469. [PMID: 36842220 DOI: 10.1016/j.compbiomed.2022.106469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 11/11/2022] [Accepted: 12/19/2022] [Indexed: 01/11/2023]
Abstract
Sleep Apnea (SA) is a respiratory disorder that affects sleep. However, the SA detection method based on polysomnography is complex and not suitable for home use. The detection approach using Photoplethysmography is low cost and convenient, which can be used to widely detect SA. This study proposed a method combining a multi-scale one-dimensional convolutional neural network and a shadow one-dimensional convolutional neural network based on dual-channel input. The time-series feature information of different segments were extracted from multi-scale temporal structure. Moreover, shadow module was adopted to make full use of the redundant information generated after multi-scale convolution operation, which improved the accuracy and ensured the portability of the model. At the same time, we introduced balanced bootstrapping and class weight, which effectively alleviated the problem of unbalanced classes. Our method achieved the result of 82.0% average accuracy, 74.4% average sensitivity and 85.1% average specificity for per-segment SA detection, and reached 93.6% average accuracy for per-recording SA detection after 5-fold cross validation. Experimental results show that this method has good robustness. It can be regarded as an effective aid in SA detection in household use.
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Affiliation(s)
- Keming Wei
- School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China; Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangzhou, Guangdong, China.
| | - Lang Zou
- School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China; Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangzhou, Guangdong, China.
| | - Guanzheng Liu
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China; Laboratory of Wearable Technology and Artificial Intelligence for Healthcare of Guangdong Province, Shenzhen, Guangdong, China.
| | - Changhong Wang
- School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China; Laboratory of Wearable Technology and Artificial Intelligence for Healthcare of Guangdong Province, Shenzhen, Guangdong, China.
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37
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Channel Intensity and Edge-Based Estimation of Heart Rate via Smartphone Recordings. COMPUTERS 2023. [DOI: 10.3390/computers12020043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
Smartphones, today, come equipped with a wide variety of sensors and high-speed processors that can capture, process, store, and communicate different types of data. Coupled with their ubiquity in recent years, these devices show potential as practical and portable healthcare monitors that are both cost-effective and accessible. To this end, this study focuses on examining the feasibility of smartphones in estimating the heart rate (HR), using video recordings of the users’ fingerprints. The proposed methodology involves two-stage processing that combines channel-intensity-based approaches (Channel-Intensity mode/Counter method) and a novel technique that relies on the spatial and temporal position of the recorded fingerprint edges (Edge-Detection mode). The dataset used here included 32 fingerprint video recordings taken from 6 subjects, using the rear camera of 2 smartphone models. Each video clip was first validated to determine whether it was suitable for Channel-Intensity mode or Edge-Detection mode, followed by further processing and heart rate estimation in the selected mode. The relative accuracy for recordings via the Edge-Detection mode was 93.04%, with a standard error of estimates (SEE) of 6.55 and Pearson’s correlation r > 0.91, while the Channel-Intensity mode showed a relative accuracy of 92.75%, with an SEE of 5.95 and a Pearson’s correlation r > 0.95. Further statistical analysis was also carried out using Pearson’s correlation test and the Bland–Altman method to verify the statistical significance of the results. The results thus show that the proposed methodology, through smartphones, is a potential alternative to existing technologies for monitoring a person’s heart rate.
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Qi Y, Zhang A, Ma Y, Chang T, Xu J. Comparison of pulse rate variability from post-auricula and heart rate variability during different body states for healthy subjects. J Med Eng Technol 2023; 47:179-188. [PMID: 36794319 DOI: 10.1080/03091902.2023.2175061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Heart rate variability (HRV) extracted from the electrocardiogram (ECG) is an essential indicator for assessing the autonomic nervous system in clinical. Some scholars have studied the feasibility of pulse rate variability (PRV) instead of HRV. However, there is little qualitative research in different body states. In this paper, the photoplethysmography (PPG) of postauricular and finger and the ECG of fifteen subjects were synchronously collected for comparative analysis. The eleven experiments were designed according to the daily living state, including the stationary state, limb movement state, and facial movement state. The substitutability of nine variables was investigated in the time, frequency, and nonlinearity domain by Passing Bablok regression and Bland Altman analysis. The results showed that the PPG of the finger was destroyed in the limb movement state. There were six variables of postauricular PRV, which showed a positive linear relationship and good agreement (p > 0.05, ratio ≤0.2) with HRV in all experiments. Our study suggests that the postauricular PPG could retain the necessary information of the pulse signal under the limb movement state and facial movement state. Therefore, postauricular PPG could be a better substitute for HRV, daily PPG detection, and mobile health than finger PPG.
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Affiliation(s)
- Yusheng Qi
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China.,Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou, China.,National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou, China
| | - Aihua Zhang
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China.,Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou, China.,National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou, China.,College of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Yurun Ma
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China.,Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou, China.,National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou, China
| | - Tingting Chang
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China.,Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou, China.,College of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Jianwen Xu
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China.,Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou, China.,National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou, China
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Martín-Escudero P, Cabanas AM, Dotor-Castilla ML, Galindo-Canales M, Miguel-Tobal F, Fernández-Pérez C, Fuentes-Ferrer M, Giannetti R. Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise? Bioengineering (Basel) 2023; 10:bioengineering10020254. [PMID: 36829748 PMCID: PMC9952291 DOI: 10.3390/bioengineering10020254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/28/2023] [Accepted: 01/30/2023] [Indexed: 02/17/2023] Open
Abstract
The market for wrist-worn devices is growing at previously unheard-of speeds. A consequence of their fast commercialization is a lack of adequate studies testing their accuracy on varied populations and pursuits. To provide an understanding of wearable sensors for sports medicine, the present study examined heart rate (HR) measurements of four popular wrist-worn devices, the (Fitbit Charge (FB), Apple Watch (AW), Tomtom runner Cardio (TT), and Samsung G2 (G2)), and compared them with gold standard measurements derived by continuous electrocardiogram examination (ECG). Eight athletes participated in a comparative study undergoing maximal stress testing on a cycle ergometer or a treadmill. We analyzed 1,286 simultaneous HR data pairs between the tested devices and the ECG. The four devices were reasonably accurate at the lowest activity level. However, at higher levels of exercise intensity the FB and G2 tended to underestimate HR values during intense physical effort, while the TT and AW devices were fairly reliable. Our results suggest that HR estimations should be considered cautiously at specific intensities. Indeed, an effective intervention is required to register accurate HR readings at high-intensity levels (above 150 bpm). It is important to consider that even though none of these devices are certified or sold as medical or safety devices, researchers must nonetheless evaluate wrist-worn wearable technology in order to fully understand how HR affects psychological and physical health, especially under conditions of more intense exercise.
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Affiliation(s)
- Pilar Martín-Escudero
- Professional Medical School of Physical Education and Sport, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Ana María Cabanas
- Departamento de Física, FACI, Universidad de Tarapacá, Arica 1010069, Chile
- Correspondence:
| | | | - Mercedes Galindo-Canales
- Professional Medical School of Physical Education and Sport, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Francisco Miguel-Tobal
- Professional Medical School of Physical Education and Sport, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Cristina Fernández-Pérez
- Servicio de Medicina Preventiva Complejo Hospitalario de Santiago de Compostela, Instituto de Investigación Sanitaria de Santiago, 15706 Santiago de Compostela, Spain
| | - Manuel Fuentes-Ferrer
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, 38010 Santa Cruz de Tenerife, Spain
| | - Romano Giannetti
- IIT, Institute of Technology Research, Universidad Pontificia Comillas, 28015 Madrid, Spain
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40
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Mejía-Mejía E, Kyriacou PA. Duration of photoplethysmographic signals for the extraction of Pulse Rate Variability Indices. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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41
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Mejía-Mejía E, Kyriacou PA. Effects of noise and filtering strategies on the extraction of pulse rate variability from photoplethysmograms. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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42
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van Es VAA, Lopata RGP, Scilingo EP, Nardelli M. Contactless Cardiovascular Assessment by Imaging Photoplethysmography: A Comparison with Wearable Monitoring. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23031505. [PMID: 36772543 PMCID: PMC9919512 DOI: 10.3390/s23031505] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 01/16/2023] [Accepted: 01/20/2023] [Indexed: 05/27/2023]
Abstract
Despite the notable recent developments in the field of remote photoplethysmography (rPPG), extracting a reliable pulse rate variability (PRV) signal still remains a challenge. In this study, eight image-based photoplethysmography (iPPG) extraction methods (GRD, AGRD, PCA, ICA, LE, SPE, CHROM, and POS) were compared in terms of pulse rate (PR) and PRV features. The algorithms were made robust for motion and illumination artifacts by using ad hoc pre- and postprocessing steps. Then, they were systematically tested on the public dataset UBFC-RPPG, containing data from 42 subjects sitting in front of a webcam (30 fps) while playing a time-sensitive mathematical game. The performances of the algorithms were evaluated by statistically comparing iPPG-based and finger-PPG-based PR and PRV features in terms of Spearman's correlation coefficient, normalized root mean square error (NRMSE), and Bland-Altman analysis. The study revealed POS and CHROM techniques to be the most robust for PR estimation and the assessment of overall autonomic nervous system (ANS) dynamics by using PRV features in time and frequency domains. Furthermore, we demonstrated that a reliable characterization of the vagal tone is made possible by computing the Poincaré map of PRV series derived from the POS and CHROM methods. This study supports the use of iPPG systems as promising tools to obtain clinically useful and specific information about ANS dynamics.
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Affiliation(s)
- Valerie A. A. van Es
- Department of Biomedical Engineering, University of Technology, P.O. Box 513, 5600 Eindhoven, The Netherlands
| | - Richard G. P. Lopata
- Department of Biomedical Engineering, University of Technology, P.O. Box 513, 5600 Eindhoven, The Netherlands
| | - Enzo Pasquale Scilingo
- Bioengineering and Robotics Research Centre E. Piaggio, Dipartimento di Ingegneria dell’Informazione, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, Italy
| | - Mimma Nardelli
- Bioengineering and Robotics Research Centre E. Piaggio, Dipartimento di Ingegneria dell’Informazione, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, Italy
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43
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Nakagawa N, Sato N. Potential impact of non-dipping pulse rate pattern and nocturnal high pulse rate variability on target organ damage in patients with cardiovascular risk. Hypertens Res 2023; 46:1054-1055. [PMID: 36697875 DOI: 10.1038/s41440-023-01186-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 12/29/2022] [Indexed: 01/26/2023]
Affiliation(s)
- Naoki Nakagawa
- Division of Cardiology, Nephrology, Pulmonology, and Neurology, Department of Internal Medicine, Asahikawa, Japan.
| | - Nobuyuki Sato
- Division of Cardiology, Nephrology, Pulmonology, and Neurology, Department of Internal Medicine, Asahikawa, Japan.,Educational center, Asahikawa Medical University, Asahikawa, Japan
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44
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Gomes N, Pato M, Lourenço AR, Datia N. A Survey on Wearable Sensors for Mental Health Monitoring. SENSORS (BASEL, SWITZERLAND) 2023; 23:1330. [PMID: 36772370 PMCID: PMC9919280 DOI: 10.3390/s23031330] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 01/20/2023] [Accepted: 01/21/2023] [Indexed: 06/18/2023]
Abstract
Mental illness, whether it is medically diagnosed or undiagnosed, affects a large proportion of the population. It is one of the causes of extensive disability, and f not properly treated, it can lead to severe emotional, behavioral, and physical health problems. In most mental health research studies, the focus is on treatment, but fewer resources are focused on technical solutions to mental health issues. The present paper carried out a systematic review of available literature using PRISMA guidelines to address various monitoring solutions in mental health through the use of wearable sensors. Wearable sensors can offer several advantages over traditional methods of mental health assessment, including convenience, cost-effectiveness, and the ability to capture data in real-world settings. Their ability to collect data related to anxiety and stress levels, as well as panic attacks, is discussed. The available sensors on the market are described, as well as their success in providing data that can be correlated with the aforementioned health issues. The current wearable landscape is quite dynamic, and the current offerings have enough quality to deliver meaningful data targeted for machine learning algorithms. The results indicate that mental health monitoring is feasible.
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Affiliation(s)
- Nuno Gomes
- ISEL, Lisbon School of Engineering, R. Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - Matilde Pato
- ISEL, Lisbon School of Engineering, R. Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
- LASIGE & IBEB, FCUL, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
- FIT-ISEL, R. Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - André Ribeiro Lourenço
- ISEL, Lisbon School of Engineering, R. Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
- CardioID Technologies Lda., Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - Nuno Datia
- ISEL, Lisbon School of Engineering, R. Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
- FIT-ISEL, R. Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
- NOVA LINCS, NOVA School of Science and Technology, 2829-516 Caparica, Portugal
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45
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Collard D, Westerhof BE, Karemaker JM, Stok WJ, Postema PG, Krediet CTP, Vogt L, van den Born BJH. Automated analysis of finger blood pressure recordings provides insight in determinants of baroreflex sensitivity and heart rate variability-the HELIUS study. Med Biol Eng Comput 2023; 61:1183-1191. [PMID: 36683125 PMCID: PMC10083154 DOI: 10.1007/s11517-023-02768-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 01/02/2023] [Indexed: 01/24/2023]
Abstract
Sympathovagal balance is important in the pathogenesis of hypertension and independently associated with mortality. We evaluated the value of automated analysis of cross-correlation baroreflex sensitivity (xBRS) and heart rate variability (HRV) and its relationship with clinical covariates in 13,326 participants from the multi-ethnic HELIUS study. Finger blood pressure (BP) was continuously recorded, from which xBRS, standard deviation of normal-to-normal intervals (SDNN), and squared root of mean squared successive difference between normal-to-normal intervals (RMSDD) were determined. A subset of 3356 recordings > 300 s was used to derive the minimally required duration by comparing shortened to complete recordings, defined as intraclass correlation (ICC) > 0.90. For xBRS and SDNN, 120 s and 180 s were required (ICC 0.93); for RMSDD, 60 s (ICC 0.94) was sufficient. We included 10,252 participants (median age 46 years, 54% women) with a recording > 180 s for the regression. xBRS, SDNN, and RMSDD decreased linearly up to 50 years of age. For xBRS, there was a signification interaction with sex, with for every 10 years a decrease of 4.3 ms/mmHg (95%CI 4.0-4.6) for men and 5.9 ms/mmHg (95%CI 5.6-6.1) for women. Using splines, we observed sex-dependent nonlinearities in the relation with BP, waist-to-hip-ratio, and body mass index. Future studies can help unravel the dynamics of these relations and assess their predictive value. Panel 1 depicts automatic analysis and filtering of finger BP recordings, panel 2 depicts computation of xBRS from interpolated beat to beat data of systolic BP and interbeat interval, and (IBI) SDNN and RMSDD are computed directly from the filtered IBI dataset. Panel 3 depicts the results of large-scale analysis and relation of xBRS with age, sex, blood pressure and body mass index.
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Affiliation(s)
- D Collard
- Department of Internal Medicine, Section Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, PO box 22660, 1100 DD, Amsterdam, The Netherlands.
| | - B E Westerhof
- Department of Pulmonary Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Medical Biology, Section Systems Physiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - J M Karemaker
- Department of Medical Biology, Section Systems Physiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - W J Stok
- Department of Medical Biology, Section Systems Physiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - P G Postema
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Heart Center, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - C T P Krediet
- Department of Internal Medicine, Section Nephrology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - L Vogt
- Department of Internal Medicine, Section Nephrology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - B J H van den Born
- Department of Internal Medicine, Section Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, PO box 22660, 1100 DD, Amsterdam, The Netherlands
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
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46
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Ajtay BE, Béres S, Hejjel L. The oscillating pulse arrival time as a physiological explanation regarding the difference between ECG- and Photoplethysmogram-derived heart rate variability parameters. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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47
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Li Y, Li J, Yan C, Dong K, Kang Z, Zhang H, Liu C. Sleep Quality Evaluation Based on Single-Lead Wearable Cardiac Cycle Acquisition Device. SENSORS (BASEL, SWITZERLAND) 2022; 23:328. [PMID: 36616927 PMCID: PMC9823989 DOI: 10.3390/s23010328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 11/24/2022] [Accepted: 12/22/2022] [Indexed: 06/17/2023]
Abstract
In clinical conditions, polysomnography (PSG) is regarded as the "golden standard" for detecting sleep disease and offering a reference of objective sleep quality. For healthy adults, scores from sleep questionnaires are more reliable than other methods in obtaining knowledge of subjective sleep quality. In practice, the need to simplify PSG to obtain subjective sleep quality by recording a few channels of physiological signals such as single-lead electrocardiogram (ECG) or photoplethysmography (PPG) signal is still very urgent. This study provided a two-step method to differentiate sleep quality into "good sleep" and "poor sleep" based on the single-lead wearable cardiac cycle data, with the comparison of the subjective sleep questionnaire score. First, heart rate variability (HRV) features and ECG-derived respiration features were extracted to construct a sleep staging model (wakefulness (W), rapid eye movement (REM), light sleep (N1&N2) and deep sleep (N3)) using the multi-classifier fusion method. Then, features extracted from the sleep staging results were used to construct a sleep quality evaluation model, i.e., classifying the sleep quality as good and poor. The accuracy of the sleep staging model, tested on the international public database, was 0.661 and 0.659 in Cardiology Challenge 2018 training database and Sleep Heart Health Study Visit 1 database, respectively. The accuracy of the sleep quality evaluation model was 0.786 for our recording subjects, with an average F1-score of 0.771. The proposed sleep staging model and sleep quality evaluation model only requires one channel of wearable cardiac cycle signal. It is very easy to transplant to portable devices, which facilitates daily sleep health monitoring.
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Affiliation(s)
- Yang Li
- School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
| | - Jianqing Li
- School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
| | - Chang Yan
- School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
| | - Kejun Dong
- School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
- School of Information Science and Engineering, Southeast University, Nanjing 210096, China
| | - Zhiyu Kang
- Aerospace System Engineering Shanghai, Shanghai 201109, China
| | - Hongxing Zhang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Chengyu Liu
- School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
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Mavragani A, Khau M, Lavoie-Hudon L, Vachon F, Drapeau V, Tremblay S. Comparing a Fitbit Wearable to an Electrocardiogram Gold Standard as a Measure of Heart Rate Under Psychological Stress: A Validation Study. JMIR Form Res 2022; 6:e37885. [PMID: 36542432 PMCID: PMC9813817 DOI: 10.2196/37885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 10/28/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Wearable devices collect physiological and behavioral data that have the potential to identify individuals at risk of declining mental health and well-being. Past research has mainly focused on assessing the accuracy and the agreement of heart rate (HR) measurement of wearables under different physical exercise conditions. However, the capacity of wearables to sense physiological changes, assessed by increasing HR, caused by a stressful event has not been thoroughly studied. OBJECTIVE This study followed 3 objectives: (1) to test the ability of a wearable device (Fitbit Versa 2) to sense an increase in HR upon induction of psychological stress in the laboratory; (2) to assess the accuracy of the wearable device to capture short-term HR variations caused by psychological stress compared to a gold-standard electrocardiogram (ECG) measure (Biopac); and (3) to quantify the degree of agreement between the wearable device and the gold-standard ECG measure across different experimental conditions. METHODS Participants underwent the Trier Social Stress Test protocol, which consists of an oral phase, an arithmetic stress phase, an anticipation phase, and 2 relaxation phases (at the beginning and the end). During the stress protocol, the participants wore a Fitbit Versa 2 and were also connected to a Biopac. A mixed-effect modeling approach was used (1) to assess the effect of experimental conditions on HR, (2) to estimate several metrics of accuracy, and (3) to assess the agreement: the Bland-Altman limits of agreement (LoA), the concordance correlation coefficient, the coverage probability, the total deviation index, and the coefficient of an individual agreement. Mean absolute error and mean absolute percent error were calculated as accuracy indices. RESULTS A total of 34 university students were recruited for this study (64% of participants were female with a mean age of 26.8 years, SD 8.3). Overall, the results showed significant HR variations across experimental phases. Post hoc tests revealed significant pairwise differences for all phases. Accuracy analyses revealed acceptable accuracy according to the analyzed metrics of accuracy for the Fitbit Versa 2 to capture the short-term variations in psychological stress levels. However, poor indices of agreement between the Fitbit Versa 2 and the Biopac were found. CONCLUSIONS Overall, the results support the use of the Fitbit Versa 2 to capture short-term stress variations. The Fitbit device showed acceptable levels of accuracy but poor agreement with an ECG gold standard. Greater inaccuracy and smaller agreement were found for stressful experimental conditions that induced a higher HR. Fitbit devices can be used in research to measure HR variations caused by stress, although they cannot replace an ECG instrument when precision is of utmost importance.
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Affiliation(s)
| | - Michelle Khau
- Faculty of Social Sciences, Laval University, Québec, QC, Canada
| | | | - François Vachon
- School of Psychology, Faculty of Social Sciences, Laval University, Québec, QC, Canada
| | - Vicky Drapeau
- Quebec Heart and Lung Institute Research Center, Department of Physical Education, Faculty of Educational Sciences, Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Laval University, Québec, QC, Canada
| | - Sébastien Tremblay
- School of Psychology, Faculty of Social Sciences, Laval University, Québec, QC, Canada
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Singh Solorzano C, Violani C, Grano C. Pre-partum HRV as a predictor of postpartum depression: The potential use of a smartphone application for physiological recordings. J Affect Disord 2022; 319:172-180. [PMID: 36162652 DOI: 10.1016/j.jad.2022.09.056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/05/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND This study aimed to investigate the role of a time-domain Heart Rate Variability index (the root mean square of successive difference between NN intervals, rMSSD) as a predictor of the onset of postpartum depression. HRV has been related to an increased risk of depression in the general population. However, its role in pregnant women is not clear, and the potential use of smartphone applications to evaluate HRV in this population has not been investigated. METHODS In study 1, simultaneous electrocardiogram and smartphone photoplethysmography were collected. The rMSSD was determined from each recording to evaluate the accuracy of a smartphone application in the measurement of HRV. In study 2, 135 pregnant women provided rMSSD values measured through a smartphone application in the prepartum (second or third trimester) and filled in the Edinburgh Postnatal Depression Scale in the postpartum (one month after the childbirth). RESULTS Study 1 showed the excellent accuracy of the smartphone application in the measurement of rMSSD. Study 2 indicated that lower prepartum rMSSD predicted higher depressive symptoms in the postpartum (β = -0.217, p = 0.010) after controlling for prepartum depressive symptoms and other potential covariates. LIMITATIONS Artefacts (e.g., hand movements) might have corrupted the physiological signal registered. CONCLUSION This study showed that a reduced vagal tone, indexed by lower rMSSD, during pregnancy was a predictor of depressive symptoms one month after childbirth. The prepartum period may offer an important timeframe to implement preventive intervention on vagal modulation in order to prevent depressive symptoms in the postpartum.
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Affiliation(s)
| | | | - Caterina Grano
- Department of Psychology, Sapienza University, Rome, Italy.
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50
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Mejía-Mejía E, Kyriacou PA. Spectral analysis for pulse rate variability assessment from simulated photoplethysmographic signals. Front Physiol 2022; 13:966130. [PMID: 36569750 PMCID: PMC9780434 DOI: 10.3389/fphys.2022.966130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 11/29/2022] [Indexed: 12/13/2022] Open
Abstract
Introduction: Pulse rate variability (PRV) refers to the changes in pulse rate through time and is extracted from pulsatile signals such as the photoplethysmogram (PPG). Although PRV has been used as a surrogate of heart rate variability (HRV), which is measured from the electrocardiogram (ECG), these variables have been shown to have differences, and it has been hypothesised that these differences may arise from technical aspects that may affect the reliable extraction of PRV from PPG signals. Moreover, there are no guidelines for the extraction of PRV information from pulsatile signals. Aim: In this study, the extraction of frequency-domain information from PRV was studied, in order to establish the best performing combination of parameters and algorithms to obtain the spectral representation of PRV. Methods: PPG signals with varying and known PRV content were simulated, and PRV information was extracted from these signals. Several spectral analysis techniques with different parameters were applied, and absolute, relative and centroid-related frequency-domain indices extracted from each combination. Indices from extracted and known PRV were compared using factorial analyses and Kruskal-Wallis tests to determine which spectral analysis technique gave the best performing results. Results: It was found that using fast Fourier transform and the multiple signal classification (PMUSIC) algorithms gave the best results, combined with cubic spline interpolation and a frequency resolution of 0.0078 Hz for the former; and a linear interpolation with a frequency resolution as low as 1.22 × 10-4, as well as applying a fifth order model, for the latter. Discussion: Considering the lower complexity of FFT over PMUSIC, FFT should be considered as the appropriate technique to extract frequency-domain information from PRV signals.
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