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Papalamprakopoulou Z, Stavropoulos D, Moustakidis S, Avgerinos D, Efremidis M, Kampaktsis PN. Artificial intelligence-enabled atrial fibrillation detection using smartwatches: current status and future perspectives. Front Cardiovasc Med 2024; 11:1432876. [PMID: 39077110 PMCID: PMC11284169 DOI: 10.3389/fcvm.2024.1432876] [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: 05/14/2024] [Accepted: 07/02/2024] [Indexed: 07/31/2024] Open
Abstract
Atrial fibrillation (AF) significantly increases the risk of stroke and heart failure, but is frequently asymptomatic and intermittent; therefore, its timely diagnosis poses challenges. Early detection in selected patients may aid in stroke prevention and mitigate structural heart complications through prompt intervention. Smartwatches, coupled with powerful artificial intelligence (AI)-enabled algorithms, offer a promising tool for early detection due to their widespread use, easiness of use, and potential cost-effectiveness. Commercially available smartwatches have gained clearance from the FDA to detect AF and are becoming increasingly popular. Despite their promise, the evolving landscape of AI-enabled smartwatch-based AF detection raises questions about the clinical value of this technology. Following the ongoing digital transformation of healthcare, clinicians should familiarize themselves with how AI-enabled smartwatches function in AF detection and navigate their role in clinical settings to deliver optimal patient care. In this review, we provide a concise overview of the characteristics of AI-enabled smartwatch algorithms, their diagnostic performance, clinical value, limitations, and discuss future perspectives in AF diagnosis.
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Affiliation(s)
- Zoi Papalamprakopoulou
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY, United States
| | - Dimitrios Stavropoulos
- Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | | | | | | | - Polydoros N. Kampaktsis
- Department of Medicine, Aristotle University of Thessaloniki Medical School, Thessaloniki, Greece
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2
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Yang G, Kang Y, Charlton PH, Kyriacou PA, Kim KK, Li L, Park C. Energy-Efficient PPG-Based Respiratory Rate Estimation Using Spiking Neural Networks. SENSORS (BASEL, SWITZERLAND) 2024; 24:3980. [PMID: 38931763 PMCID: PMC11207339 DOI: 10.3390/s24123980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 06/12/2024] [Accepted: 06/18/2024] [Indexed: 06/28/2024]
Abstract
Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical signal processing and is strongly associated with other vital signs such as blood pressure, heart rate, and heart rate variability. Various physiological signals, such as photoplethysmogram (PPG) signals, are used to extract respiratory information. RR is also estimated by detecting peak patterns and cycles in the signals through signal processing and deep-learning approaches. In this study, we propose an end-to-end RR estimation approach based on a third-generation artificial neural network model-spiking neural network. The proposed model employs PPG segments as inputs, and directly converts them into sequential spike events. This design aims to reduce information loss during the conversion of the input data into spike events. In addition, we use feedback-based integrate-and-fire neurons as the activation functions, which effectively transmit temporal information. The network is evaluated using the BIDMC respiratory dataset with three different window sizes (16, 32, and 64 s). The proposed model achieves mean absolute errors of 1.37 ± 0.04, 1.23 ± 0.03, and 1.15 ± 0.07 for the 16, 32, and 64 s window sizes, respectively. Furthermore, it demonstrates superior energy efficiency compared with other deep learning models. This study demonstrates the potential of the spiking neural networks for RR monitoring, offering a novel approach for RR estimation from the PPG signal.
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Affiliation(s)
- Geunbo Yang
- Department of Computer Engineering, Kwangwoon University, Seoul 01897, Republic of Korea; (G.Y.); (Y.K.)
| | - Youngshin Kang
- Department of Computer Engineering, Kwangwoon University, Seoul 01897, Republic of Korea; (G.Y.); (Y.K.)
| | - Peter H. Charlton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK;
| | - Panayiotis A. Kyriacou
- Department of Engineering, School of Science and Technology (SST), City University of London, London EC1V 0HB, UK;
| | - Ko Keun Kim
- AI Lab, LG Electronics, Seoul 06763, Republic of Korea;
| | - Ling Li
- Department of Engineering, School of Science and Technology (SST), City University of London, London EC1V 0HB, UK;
| | - Cheolsoo Park
- Department of Computer Engineering, Kwangwoon University, Seoul 01897, Republic of Korea; (G.Y.); (Y.K.)
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3
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Norweg A, Hofferber B, Oh C, Spinner M, Stavrolakes K, Pavol M, DiMango A, Raveis VH, Murphy CG, Allegrante JP, Buchholz D, Zarate A, Simon N. Capnography-Assisted Learned, Monitored (CALM) breathing therapy for dysfunctional breathing in COPD: A bridge to pulmonary rehabilitation. Contemp Clin Trials 2023; 134:107340. [PMID: 37730198 DOI: 10.1016/j.cct.2023.107340] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/20/2023] [Accepted: 09/15/2023] [Indexed: 09/22/2023]
Abstract
BACKGROUND Although dyspnea is a primary symptom of chronic obstructive pulmonary disease (COPD), its treatment is suboptimal. In both COPD and acute anxiety, breathing patterns become dysregulated, contributing to abnormal CO2, dyspnea, and inefficient recovery from breathing challenges. While pulmonary rehabilitation (PR) improves dyspnea, only 1-2% of patients access it. Individuals with anxiety who use PR have worse outcomes. METHODS We present the protocol of a randomized controlled trial designed to determine the feasibility and acceptability of a new, four-week mind-body intervention that we developed, called "Capnography-Assisted Learned, Monitored (CALM) Breathing," as an adjunct to PR. Eligible participants are randomized in a 1:1 ratio to either CALM Breathing program or Usual Care. CALM Breathing consists of 10 core, slow breathing exercises combined with real time biofeedback (of end-tidal CO2, respiratory rate, and airflow) and motivational interviewing. CALM Breathing promotes self-regulated breathing, linking CO2 changes to dyspnea and anxiety symptoms and targeting breathing efficiency and self-efficacy in COPD. Participants are randomized to CALM Breathing or a Usual Care control group. RESULTS Primary outcomes include feasibility and acceptability metrics of recruitment efficiency, participant retention, intervention adherence and fidelity, PR facilitation, patient satisfaction, and favorable themes from interviews. Secondary outcomes include breathing biomarkers, symptoms, health-related quality of life, six-minute walk distance, lung function, mood, physical activity, and PR utilization and engagement. CONCLUSION By disrupting the cycle of dyspnea and anxiety, and providing a needed bridge to PR, CALM Breathing may address a substantive gap in healthcare and optimize treatment for patients with COPD.
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Affiliation(s)
- Anna Norweg
- Department of Rehabilitation and Regenerative Medicine, Columbia University Irving Medical Center, New York, NY, USA.
| | - Brittany Hofferber
- Department of Rehabilitation and Regenerative Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Cheongeun Oh
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Michael Spinner
- Department of Rehabilitation and Regenerative Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Kimberly Stavrolakes
- Outpatient Pulmonary Rehabilitation Program, New York Presbyterian Hospital, New York, NY, USA
| | - Marykay Pavol
- Department of Rehabilitation and Regenerative Medicine, Columbia University Irving Medical Center, New York, NY, USA; Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Angela DiMango
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Victoria H Raveis
- Department of Cariology and Comprehensive Care, College of Dentistry, New York University, New York, NY, USA
| | - Charles G Murphy
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - John P Allegrante
- Department of Health and Behavior Studies, Teachers College, Columbia University, New York, NY, USA; Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - David Buchholz
- Department of Primary Care, Columbia University Irving Medical Center, New York, NY, USA
| | - Alejandro Zarate
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Naomi Simon
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
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Hwang CS, Kim YH, Hyun JK, Kim JH, Lee SR, Kim CM, Nam JW, Kim EY. Evaluation of the Photoplethysmogram-Based Deep Learning Model for Continuous Respiratory Rate Estimation in Surgical Intensive Care Unit. Bioengineering (Basel) 2023; 10:1222. [PMID: 37892952 PMCID: PMC10604201 DOI: 10.3390/bioengineering10101222] [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: 08/21/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 10/29/2023] Open
Abstract
The respiratory rate (RR) is a significant indicator to evaluate a patient's prognosis and status; however, it requires specific instrumentation or estimates from other monitored signals. A photoplethysmogram (PPG) is extensively used in clinical environments as well as in intensive care units (ICUs) to primarily monitor peripheral circulation while capturing indirect information about intrathoracic pressure changes. This study aims to apply and evaluate several deep learning models using a PPG for the continuous and accurate estimation of the RRs of patients. The dataset was collected twice for 2 min each in 100 patients aged 18 years and older from the surgical intensive care unit of a tertiary referral hospital. The BIDMC and CapnoBase public datasets were also analyzed. The collected dataset was preprocessed and split according to the 5-fold cross-validation. We used seven deep learning models, including our own Dilated Residual Neural Network, to check how accurately the RR estimates match the ground truth using the mean absolute error (MAE). As a result, when validated using the collected dataset, our model showed the best results with a 1.2628 ± 0.2697 MAE on BIDMC and RespNet and with a 3.1268 ± 0.6363 MAE on our dataset, respectively. In conclusion, RR estimation using PPG-derived models is still challenging and has many limitations. However, if there is an equal amount of data from various breathing groups to train, we expect that various models, including our Dilated ResNet model, which showed good results, can achieve better results than the current ones.
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Affiliation(s)
- Chi Shin Hwang
- Spass Inc., 905Ho, RnD Tower, 396, Worldcup Buk-ro, Mapo-gu, Seoul 03925, Republic of Korea; (C.S.H.); (J.W.N.)
| | - Yong Hwan Kim
- Spass Inc., 905Ho, RnD Tower, 396, Worldcup Buk-ro, Mapo-gu, Seoul 03925, Republic of Korea; (C.S.H.); (J.W.N.)
| | - Jung Kyun Hyun
- Spass Inc., 905Ho, RnD Tower, 396, Worldcup Buk-ro, Mapo-gu, Seoul 03925, Republic of Korea; (C.S.H.); (J.W.N.)
| | - Joon Hwang Kim
- Spass Inc., 905Ho, RnD Tower, 396, Worldcup Buk-ro, Mapo-gu, Seoul 03925, Republic of Korea; (C.S.H.); (J.W.N.)
| | - Seo Rak Lee
- Spass Inc., 905Ho, RnD Tower, 396, Worldcup Buk-ro, Mapo-gu, Seoul 03925, Republic of Korea; (C.S.H.); (J.W.N.)
| | - Choong Min Kim
- Spass Inc., 905Ho, RnD Tower, 396, Worldcup Buk-ro, Mapo-gu, Seoul 03925, Republic of Korea; (C.S.H.); (J.W.N.)
| | - Jung Woo Nam
- Spass Inc., 905Ho, RnD Tower, 396, Worldcup Buk-ro, Mapo-gu, Seoul 03925, Republic of Korea; (C.S.H.); (J.W.N.)
| | - Eun Young Kim
- Division of Trauma and Surgical Critical Care, Department of Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea
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Jung H, Kim D, Choi J, Joo EY. Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring. SENSORS (BASEL, SWITZERLAND) 2023; 23:7976. [PMID: 37766031 PMCID: PMC10536355 DOI: 10.3390/s23187976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/10/2023] [Accepted: 09/16/2023] [Indexed: 09/29/2023]
Abstract
Wrist-based respiratory rate (RR) measurement during sleep faces accuracy limitations. This study aimed to assess the accuracy of the RR estimation function during sleep based on the severity of obstructive sleep apnea (OSA) using the Samsung Galaxy Watch (GW) series. These watches are equipped with accelerometers and photoplethysmography sensors for RR estimation. A total of 195 participants visiting our sleep clinic underwent overnight polysomnography while wearing the GW, and the RR estimated by the GW was compared with the reference RR obtained from the nasal thermocouple. For all participants, the root mean squared error (RMSE) of the average overnight RR and continuous RR measurements were 1.13 bpm and 1.62 bpm, respectively, showing a small bias of 0.39 bpm and 0.37 bpm, respectively. The Bland-Altman plots indicated good agreement in the RR measurements for the normal, mild, and moderate OSA groups. In participants with normal-to-moderate OSA, both average overnight RR and continuous RR measurements achieved accuracy rates exceeding 90%. However, for patients with severe OSA, these accuracy rates decreased to 79.45% and 75.8%, respectively. The study demonstrates the GW's ability to accurately estimate RR during sleep, even though accuracy may be compromised in patients with severe OSA.
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Affiliation(s)
- Hyunjun Jung
- Samsung Electronics, Suwon 16677, Republic of Korea
| | - Dongyeop Kim
- Department of Neurology, Ewha Womans University Seoul Hospital, Ewha Womans University College of Medicine, Seoul 07804, Republic of Korea
| | - Jongmin Choi
- Samsung Electronics, Suwon 16677, Republic of Korea
| | - Eun Yeon Joo
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
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Coutu FA, Iorio OC, Ross BA. Remote patient monitoring strategies and wearable technology in chronic obstructive pulmonary disease. Front Med (Lausanne) 2023; 10:1236598. [PMID: 37663662 PMCID: PMC10470466 DOI: 10.3389/fmed.2023.1236598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/03/2023] [Indexed: 09/05/2023] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is highly prevalent and is associated with a heavy burden on patients and health systems alike. Exacerbations of COPD (ECOPDs) are a leading cause of acute hospitalization among all adult chronic diseases. There is currently a paradigm shift in the way that ECOPDs are conceptualized. For the first time, objective physiological parameters are being used to define/classify what an ECOPD is (including heart rate, respiratory rate, and oxygen saturation criteria) and therefore a mechanism to monitor and measure their changes, particularly in an outpatient ambulatory setting, are now of great value. In addition to pre-existing challenges on traditional 'in-person' health models such as geography and seasonal (ex. winter) impacts on the ability to deliver in-person visit-based care, the COVID-19 pandemic imposed additional stressors including lockdowns, social distancing, and the closure of pulmonary function labs. These health system stressors, combined with the new conceptualization of ECOPDs, rapid advances in sophistication of hardware and software, and a general openness by stakeholders to embrace this technology, have all influenced the propulsion of remote patient monitoring (RPM) and wearable technology in the modern care of COPD. The present article reviews the use of RPM and wearable technology in COPD. Context on the influences, factors and forces which have helped shape this health system innovation is provided. A focused summary of the literature of RPM in COPD is presented. Finally, the practical and ethical principles which must guide the transition of RPM in COPD into real-world clinical use are reviewed.
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Affiliation(s)
- Felix-Antoine Coutu
- Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Department of Medicine, McGill University, Montreal, QC, Canada
| | - Olivia C. Iorio
- Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Bryan A. Ross
- Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Department of Medicine, McGill University, Montreal, QC, Canada
- Division of Respiratory Medicine, Department of Medicine, McGill University Health Centre, Montreal, QC, Canada
- Montreal Chest Institute, McGill University Health Centre, Montreal, QC, Canada
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Zavanelli N, Lee SH, Guess M, Yeo WH. Soft wireless sternal patch to detect systemic vasoconstriction using photoplethysmography. iScience 2023; 26:106184. [PMID: 36879814 PMCID: PMC9985026 DOI: 10.1016/j.isci.2023.106184] [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: 11/17/2022] [Revised: 01/16/2023] [Accepted: 02/07/2023] [Indexed: 02/16/2023] Open
Abstract
Vasoconstriction is a crucial physiological process that serves as the body's primary blood pressure regulation mechanism and a key marker of numerous harmful health conditions. The ability to detect vasoconstriction in real time would be crucial for detecting blood pressure, identifying sympathetic arousals, characterizing patient wellbeing, detecting sickle cell anemia attacks early, and identifying complications caused by hypertension medications. However, vasoconstriction manifests weakly in traditional photoplethysmogram (PPG) measurement locations, like the finger, toe, and ear. Here, we report a wireless, fully integrated, soft sternal patch to capture PPG signals from the sternum, an anatomical region that exhibits a robust vasoconstrictive response. With healthy controls, the device is highly capable of detecting vasoconstriction induced endogenously and exogenously. Furthermore, in overnight trials with patients with sleep apnea, the device shows a high agreement (r2 = 0.74) in vasoconstriction detection with a commercial system, demonstrating its potential use in portable, continuous, long-term vasoconstriction monitoring.
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Affiliation(s)
- Nathan Zavanelli
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30024, USA.,IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Sung Hoon Lee
- IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA.,School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Matthew Guess
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30024, USA.,IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30024, USA.,IEN Center for Human-Centric Interfaces and Engineering at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA.,Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University School of Medicine, Atlanta, GA 30332, USA.,Parker H. Petit Institute for Bioengineering and Biosciences, Neural Engineering Center, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
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8
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Argüello-Prada EJ, Cantín MAD, Victoria JC. A photoplethysmography-based system for talking detection in bedridden patients. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Seo S, Jo H, Kim J, Lee B, Bien F. An ultralow power wearable vital sign sensor using an electromagnetically reactive near field. Bioeng Transl Med 2023; 8:e10502. [DOI: 10.1002/btm2.10502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 12/31/2022] [Accepted: 02/12/2023] [Indexed: 03/01/2023] Open
Affiliation(s)
- Seoktae Seo
- Department of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea
| | - Hyunkyeong Jo
- Department of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea
| | - Jungho Kim
- Department of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea
| | - Bonyoung Lee
- Department of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea
| | - Franklin Bien
- Department of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea
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Cao M, Burton T, Saiko G, Douplik A. Remote Photoplethysmography with a High-Speed Camera Reveals Temporal and Amplitude Differences between Glabrous and Non-Glabrous Skin. SENSORS (BASEL, SWITZERLAND) 2023; 23:615. [PMID: 36679411 PMCID: PMC9866593 DOI: 10.3390/s23020615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/30/2022] [Accepted: 01/02/2023] [Indexed: 06/17/2023]
Abstract
Photoplethysmography (PPG) is a noninvasive optical technology with applications including vital sign extraction and patient monitoring. However, its current use is primarily limited to heart rate and oxygenation monitoring. This study aims to demonstrate the utility of PPG for physiological investigations. In particular, we sought to demonstrate the utility of simultaneous data acquisition from several regions of tissue using remote/contactless PPG (rPPG). Specifically, using a high-speed scientific-grade camera, we collected rPPG from the hands (palmar/dorsal) of 22 healthy volunteers. Data collected through the red and green channels of the RGB CMOS sensor were analyzed. We found a statistically significant difference in the amplitude of the glabrous skin signal over the non-glabrous skin signal (1.41 ± 0.85 in the red channel and 2.27 ± 0.88 in the green channel). In addition, we found a statistically significant lead of the red channel over the green channel, which is consistent between glabrous (17.13 ± 10.69 ms) and non-glabrous (19.31 ± 12.66 ms) skin. We also found a statistically significant lead time (32.69 ± 55.26 ms in the red channel and 40.56 ± 26.97 ms in the green channel) of the glabrous PPG signal over the non-glabrous, which cannot be explained by bilateral variability. These results demonstrate the utility of rPPG imaging as a tool for fundamental physiological studies and can be used to inform the development of PPG-based devices.
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Affiliation(s)
- Meiyun Cao
- Department of Physics, Toronto Metropolitan University, Toronto, ON M5B 1E9, Canada
| | - Timothy Burton
- Department of Biomedical Engineering, Toronto Metropolitan University, Toronto, ON M5B 1E9, Canada
| | - Gennadi Saiko
- Department of Physics, Toronto Metropolitan University, Toronto, ON M5B 1E9, Canada
| | - Alexandre Douplik
- Department of Physics, Toronto Metropolitan University, Toronto, ON M5B 1E9, Canada
- iBest, Keenan Research Centre of the LKS Knowledge Institute, St. Michael’s Hospital, Toronto Metropolitan University, Toronto, ON M5B 1E9, Canada
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Stockwell SJ, Kwok TC, Morgan SP, Sharkey D, Hayes-Gill BR. Forehead monitoring of heart rate in neonatal intensive care. Front Physiol 2023; 14:1127419. [PMID: 37082236 PMCID: PMC10110846 DOI: 10.3389/fphys.2023.1127419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/21/2023] [Indexed: 04/22/2023] Open
Abstract
Heart rate is an extremely important physiological parameter to measure in critically unwell infants, as it is the main physiological marker that changes in response to a change in infant condition. Heart rate is routinely measured peripherally on a limb with a pulse oximeter. However, when infants are critically unwell, the blood supply to these peripheries is reduced in preference for central perfusion of vital organs such as the brain and heart. Measurement of heart rate with a reflection mode photoplethysmogram (PPG) sensor on the forehead could help minimise this problem and make it easier for other important medical equipment, such as cannulas, to be placed on the limbs. This study compares heart rates measured with a forehead-based PPG sensor against a wrist-based PPG sensor in 19 critically unwell infants in neonatal intensive care collecting 198 h of data. The two heart rates were compared using positive percentage agreement, Spearman's correlation coefficient and Bland-Altman analysis. The forehead PPG sensor showed good agreement with the wrist-based PPG sensor with limits of agreement of 8.44 bpm, bias of -0.22 bpm; positive percentage agreement of 98.87%; and Spearman's correlation coefficient of 0.9816. The analysis demonstrates that the forehead is a reliable alternative location for measuring vital signs using the PPG.
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Affiliation(s)
- S. J. Stockwell
- Optics and Photonics Research Group, Faculty of Engineering, University of Nottingham, Nottingham, United Kingdom
| | - T. C. Kwok
- Centre for Perinatal Research, Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - S. P. Morgan
- Optics and Photonics Research Group, Faculty of Engineering, University of Nottingham, Nottingham, United Kingdom
| | - D. Sharkey
- Centre for Perinatal Research, Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - B. R. Hayes-Gill
- Optics and Photonics Research Group, Faculty of Engineering, University of Nottingham, Nottingham, United Kingdom
- *Correspondence: B. R. Hayes-Gill,
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Burton T, Saiko G, Cao M, Douplik A. Remote photoplethysmography with consumer smartphone reveals temporal differences between glabrous and nonglabrous skin: Pilot in vivo study. JOURNAL OF BIOPHOTONICS 2023; 16:e202200187. [PMID: 36054679 DOI: 10.1002/jbio.202200187] [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: 06/21/2022] [Revised: 08/05/2022] [Accepted: 08/17/2022] [Indexed: 06/15/2023]
Abstract
Photoplethysmography (PPG) is a noninvasive optical technology, with applications including vital sign extraction and patient monitoring. The PPG acquisition skin type may be of importance. Skin is either nonglabrous (~90%) or glabrous (~10%). Clinical PPG collection is typically from glabrous (fingerpad), while proliferating wearables collecting PPG, which may perform critical functions like arrythmia detection, often acquire from atypical sites. Glabrous skin has significant differences from nonglabrous, including microcirculation, yet comparisons between their PPG signals have not been well reported. Using a smartphone-based remote/contactless PPG, a pilot dataset was collected from the hands (palmar/dorsal) of five healthy volunteers. The data shows statistically significant lead time (52 ± 36 ms) of glabrous over nonglabrous. Further, a trend of glabrous amplitude increase over nonglabrous (31%) was found. Although our study has a small number of participants, these results further the characterization of PPG skin differences, and can be used to inform development of PPG-based devices.
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Affiliation(s)
- Timothy Burton
- Department of Biomedical Engineering, Toronto Metropolitan University, Toronto, Canada
| | - Gennadi Saiko
- Department of Physics, Toronto Metropolitan University, Toronto, Canada
| | - Meiyun Cao
- Department of Physics, Toronto Metropolitan University, Toronto, Canada
| | - Alexandre Douplik
- Department of Physics, Toronto Metropolitan University, Toronto, Canada
- iBest, Keenan Research Centre of the LKS Knowledge Institute, St. Michael's Hospital, Toronto, Canada
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Correlation Mapping of Perfusion Patterns in Cutaneous Tissue. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12157658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Perfusion patterns of cutaneous tissue represent a valuable source of information about the state of the patient’s cardiovascular system and autonomic nervous system (ANS). This concept aims to observe the perfusion changes in the foot sole in two healthy individuals and two subjects affected by diabetes mellitus (DM). We use photoplethysmography imaging (PPGI) to monitor cutaneous perfusion changes. This method, in contrast to conventional contact photoplethysmography (PPG), allows the monitoring of skin perfusion with spatial distribution. We use a machine vision camera and an illumination system using the green light. To induce the perfusion changes, we perform an experiment in the form of a deep breathing test (DBT). The experiment consists of three stages, with the middle stage being the DBT. To evaluate spatial perfusion changes, we use a normalized measure of the correlation of PPGI signals with a reference PPG signal obtained from the foot’s little toe. This method also increases the signal-to-noise ratio (SNR). Subjects with DM shows different patterns of tissue perfusion changes compared to healthy subjects. The DM subjects show increased perfusion after DBT compared to the pre-DBT state, whereas in healthy subjects, the tissue perfusion does not reach the level of the pre-DBT phase. This work can be considered as proof of concept in developing a non-contact and non-intrusive monitoring system that allows a different view of microcirculatory damage in patients with diabetes mellitus, focusing on its spatial distribution.
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Merschel S, Reinhardt L. Analyzability of Photoplethysmographic Smartwatch Data by the Preventicus Heartbeats Algorithm During Everyday Life: Feasibility Study. JMIR Form Res 2022; 6:e29479. [PMID: 35343902 PMCID: PMC9002588 DOI: 10.2196/29479] [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: 04/08/2021] [Revised: 12/14/2021] [Accepted: 12/30/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Continuous heart rate monitoring via mobile health technologies based on photoplethysmography (PPG) has great potential for the early detection of sustained cardiac arrhythmias such as atrial fibrillation. However, PPG measurements are impaired by motion artifacts. OBJECTIVE The aim of this investigation was to evaluate the analyzability of smartwatch-derived PPG data during everyday life and to determine the relationship between the analyzability of the data and the activity level of the participant. METHODS A total of 41 (19 female and 22 male) adults in good cardiovascular health (aged 19-79 years) continuously wore a smartwatch equipped with a PPG sensor and a 3D accelerometer (Cardio Watch 287, Corsano Health BV) for a period of 24 hours that represented their individual daily routine. For each participant, smartwatch data were analyzed on a 1-minute basis by an algorithm designed for heart rhythm analysis (Preventicus Heartbeats, Preventicus GmbH). As outcomes, the percentage of analyzable data (PAD) and the mean acceleration (ACC) were calculated. To map changes of the ACC and PAD over the course of one day, the 24-hour period was divided into 8 subintervals comprising 3 hours each. RESULTS Univariate analysis of variance showed a large effect (ηp2> 0.6; P<.001) of time interval (phase) on the ACC and PAD. The PAD ranged between 34% and 100%, with an average of 71.5% for the whole day, which is equivalent to a period of 17.2 hours. Between midnight and 6 AM, the mean values were the highest for the PAD (>94%) and the lowest for the ACC (<6×10-3 m/s2). Regardless of the time of the day, the correlation between the PAD and ACC was strong (r=-0.64). A linear regression analysis for the averaged data resulted in an almost perfect coefficient of determination (r2=0.99). CONCLUSIONS This study showed a large relationship between the activity level and the analyzability of smartwatch-derived PPG data. Given the high yield of analyzable data during the nighttime, continuous arrhythmia screening seems particularly effective during sleep phases.
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Affiliation(s)
| | - Lars Reinhardt
- Institute for Applied Training Science, Leipzig, Germany
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15
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Stankoski S, Kiprijanovska I, Mavridou I, Nduka C, Gjoreski H, Gjoreski M. Breathing Rate Estimation from Head-Worn Photoplethysmography Sensor Data Using Machine Learning. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22062079. [PMID: 35336250 PMCID: PMC8951087 DOI: 10.3390/s22062079] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/02/2022] [Accepted: 03/05/2022] [Indexed: 05/20/2023]
Abstract
Breathing rate is considered one of the fundamental vital signs and a highly informative indicator of physiological state. Given that the monitoring of heart activity is less complex than the monitoring of breathing, a variety of algorithms have been developed to estimate breathing activity from heart activity. However, estimating breathing rate from heart activity outside of laboratory conditions is still a challenge. The challenge is even greater when new wearable devices with novel sensor placements are being used. In this paper, we present a novel algorithm for breathing rate estimation from photoplethysmography (PPG) data acquired from a head-worn virtual reality mask equipped with a PPG sensor placed on the forehead of a subject. The algorithm is based on advanced signal processing and machine learning techniques and includes a novel quality assessment and motion artifacts removal procedure. The proposed algorithm is evaluated and compared to existing approaches from the related work using two separate datasets that contains data from a total of 37 subjects overall. Numerous experiments show that the proposed algorithm outperforms the compared algorithms, achieving a mean absolute error of 1.38 breaths per minute and a Pearson's correlation coefficient of 0.86. These results indicate that reliable estimation of breathing rate is possible based on PPG data acquired from a head-worn device.
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Affiliation(s)
- Simon Stankoski
- Emteq Ltd., Brighton BN1 9SB, UK; (I.K.); (I.M.); (C.N.); (H.G.)
- Correspondence:
| | | | | | - Charles Nduka
- Emteq Ltd., Brighton BN1 9SB, UK; (I.K.); (I.M.); (C.N.); (H.G.)
| | - Hristijan Gjoreski
- Emteq Ltd., Brighton BN1 9SB, UK; (I.K.); (I.M.); (C.N.); (H.G.)
- Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, 1000 Skopje, North Macedonia
| | - Martin Gjoreski
- Faculty of Informatics, Università della Svizzera Italiana, 6900 Lugano, Switzerland;
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Information Retrieval from Photoplethysmographic Sensors: A Comprehensive Comparison of Practical Interpolation and Breath-Extraction Techniques at Different Sampling Rates. SENSORS 2022; 22:s22041428. [PMID: 35214329 PMCID: PMC8877143 DOI: 10.3390/s22041428] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 02/07/2022] [Accepted: 02/08/2022] [Indexed: 11/17/2022]
Abstract
The increasingly widespread diffusion of wearable devices makes possible the continuous monitoring of vital signs, such as heart rate (HR), heart rate variability (HRV), and breath signal. However, these devices usually do not record the “gold-standard” signals, namely the electrocardiography (ECG) and respiratory activity, but a single photoplethysmographic (PPG) signal, which can be exploited to estimate HR and respiratory activity. In addition, these devices employ low sampling rates to limit power consumption. Hence, proper methods should be adopted to compensate for the resulting increased discretization error, while diverse breath-extraction algorithms may be differently sensitive to PPG sampling rate. Here, we assessed the efficacy of parabola interpolation, cubic-spline, and linear regression methods to improve the accuracy of the inter-beat intervals (IBIs) extracted from PPG sampled at decreasing rates from 64 to 8 Hz. PPG-derived IBIs and HRV indices were compared with those extracted from a standard ECG. In addition, breath signals extracted from PPG using three different techniques were compared with the gold-standard signal from a thoracic belt. Signals were recorded from eight healthy volunteers during an experimental protocol comprising sitting and standing postures and a controlled respiration task. Parabola and cubic-spline interpolation significantly increased IBIs accuracy at 32, 16, and 8 Hz sampling rates. Concerning breath signal extraction, the method holding higher accuracy was based on PPG bandpass filtering. Our results support the efficacy of parabola and spline interpolations to improve the accuracy of the IBIs obtained from low-sampling rate PPG signals, and also indicate a robust method for breath signal extraction.
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Davies HJ, Bachtiger P, Williams I, Molyneaux PL, Peters NS, Mandic DP. Wearable In-Ear PPG: Detailed Respiratory Variations Enable Classification of COPD. IEEE Trans Biomed Eng 2022; 69:2390-2400. [PMID: 35077352 DOI: 10.1109/tbme.2022.3145688] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
An ability to extract detailed spirometry-like breath-ing waveforms from wearable sensors promises to greatly improve respiratory health monitoring. Photoplethysmography (PPG) has been researched in depth for estimation of respiration rate, given that it varies with respiration through overall intensity, pulse amplitude and pulse interval. We compare and contrast the extraction of these three respiratory modes from both the ear canal and finger and show a marked improvement in the respiratory power for respiration induced intensity variations and pulse amplitude variations when recording from the ear canal. We next employ a data driven multi-scale method, noise assisted multivariate empirical mode decomposition (NA-MEMD), which allows for simultaneous analysis of all three respiratory modes to extract detailed respiratory waveforms from in-ear PPG. For rigour, we considered in-ear PPG recordings from healthy subjects, both older and young, patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) and healthy subjects with artificially obstructed breathing. Specific in-ear PPG waveform changes are observed for COPD, such as a decreased inspiratory duty cycle and an increased inspiratory magnitude, when compared with expiratory magnitude. These differences are used to classify COPD from healthy and IPF waveforms with a sensitivity of 87% and an overall accuracy of 92%. Our findings indicate the promise of in-ear PPG for COPD screening and unobtrusive respiratory monitoring in ambulatory scenarios and in consumer wearables.
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18
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Analysis of phase interactions between heart rate variability, respiration and peripheral microhemodynamics oscillations of upper and lower extremities in human. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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19
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Deng S, Wang Q, Fan J, Yang X, Mei J, Lu J, Chen G, Yang Y, Liu W, Wang R, Han Y, Sheng R, Wang W, Ba L, Ding F. Correlation of Circadian Rhythms of Heart Rate Variability Indices with Stress, Mood, and Sleep Status in Female Medical Workers with Night Shifts. Nat Sci Sleep 2022; 14:1769-1781. [PMID: 36225321 PMCID: PMC9549795 DOI: 10.2147/nss.s377762] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 09/12/2022] [Indexed: 12/02/2022] Open
Abstract
PURPOSE Heart rate variability (HRV) indices have been used as stress indicators. Rare studies investigated the associations of circadian rhythms of the HRV indices with the stress, mood, and sleep conditions in populations under stress. METHODS In total 257 female participants (203 shift workers and 54 non-shift workers) were included. All the participants completed a structured questionnaire to assess the stress, mood, and sleep conditions and performed 24-hour Holter electrocardiogram monitoring on the day away from shifts. Using epochs of 1-min or 5-min beat-to-beat intervals, the HRV indices (SDNN, RMSSD, LF, HF, LF/HF, and LFnu, SD1, SD2, SD1/SD2) were plotted as a function of time and fitted into cosine periodic curves, respectively. Three mathematical parameters based on the cosine periodic curves were extracted, MESOR (M, overall averages of the cosine curve), amplitude (A, amplitude of the peak of the cosine curve), and acrophase (θ, latency to the peak) to quantify the circadian rhythms of the HRV indices. Multivariable linear regression models were used to reveal the associations of these parameters with the clinical assessments of stress, mood, or sleep conditions, as well as with the 24-h averages of the HRV indices. RESULTS The parameters M and A of SDNN, RMSSD, LF, and HF, and θ of LF/HF and LFnu significantly differ between shift and non-shift workers. The parameter θ of LF/HF positively correlates with the severity of stress and anxiety. The parameter A of LF/HF and LFnu also positively correlates with daytime sleepiness and sleep fragmentation. In addition, the parameters M and A instead of θ of SDNN, RMSSD, LF, LF/HF, and LFnu significantly correlate with the 24-h averages of HRV indices. CONCLUSION The circadian rhythms of the HRV indices over 24 hours can, to some extent, predict the severity of stress, emotion and sleep conditions in female populations under stress.
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Affiliation(s)
- Saiyue Deng
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China
| | - Quan Wang
- School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People's Republic of China
| | - Jingjing Fan
- Cardiac Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China
| | - Xiaoyun Yang
- Cardiac Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China
| | - Junhua Mei
- Department of Neurology, Wuhan No.1 Hospital, Wuhan, 430022, People's Republic of China
| | - Jiajia Lu
- Cardiac Unit, Wuhan No.1 Hospital, Wuhan, 430022, People's Republic of China
| | - Guohua Chen
- Department of Neurology, Wuhan No.1 Hospital, Wuhan, 430022, People's Republic of China
| | - Yuan Yang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China
| | - Wenhua Liu
- Department of Clinical Research Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People's Republic of China
| | - Runsen Wang
- Huawei Technologies Co, Shenzhen, People's Republic of China
| | - Yujia Han
- Huawei Technologies Co, Shenzhen, People's Republic of China
| | - Rong Sheng
- Huawei Technologies Co, Shenzhen, People's Republic of China
| | - Wei Wang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China
| | - Li Ba
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China
| | - Fengfei Ding
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China.,Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, 200032, People's Republic of China
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20
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Mendelson AA, Rajaram A, Bainbridge D, Lawrence KS, Bentall T, Sharpe M, Diop M, Ellis CG. Dynamic tracking of microvascular hemoglobin content for continuous perfusion monitoring in the intensive care unit: pilot feasibility study. J Clin Monit Comput 2021; 35:1453-1465. [PMID: 33104968 PMCID: PMC7586414 DOI: 10.1007/s10877-020-00611-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 10/20/2020] [Indexed: 12/25/2022]
Abstract
PURPOSE There is a need for bedside methods to monitor oxygen delivery in the microcirculation. Near-infrared spectroscopy commonly measures tissue oxygen saturation, but does not reflect the time-dependent variability of microvascular hemoglobin content (MHC) that attempts to match oxygen supply with demand. The objective of this study is to determine the feasibility of MHC monitoring in critically ill patients using high-resolution near-infrared spectroscopy to assess perfusion in the peripheral microcirculation. METHODS Prospective observational cohort of 36 patients admitted within 48 h at a tertiary intensive care unit. Perfusion was measured on the quadriceps, biceps, and/or deltoid, using the temporal change in optical density at the isosbestic wavelength of hemoglobin (798 nm). Continuous wavelet transform was applied to the hemoglobin signal to delineate frequency ranges corresponding to physiological oscillations in the cardiovascular system. RESULTS 31/36 patients had adequate signal quality for analysis, most commonly affected by motion artifacts. MHC signal demonstrates inter-subject heterogeneity in the cohort, indicated by different patterns of variability and frequency composition. Signal characteristics were concordant between muscle groups in the same patient, and correlated with systemic hemoglobin levels and oxygen saturation. Signal power was lower for patients receiving vasopressors, but not correlated with mean arterial pressure. Mechanical ventilation directly impacts MHC in peripheral tissue. CONCLUSION MHC can be measured continuously in the ICU with high-resolution near-infrared spectroscopy, and reflects the dynamic variability of hemoglobin distribution in the microcirculation. Results suggest this novel hemodynamic metric should be further evaluated for diagnosing microvascular dysfunction and monitoring peripheral perfusion.
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Affiliation(s)
- Asher A Mendelson
- Department of Medical Biophysics, Western University, London, ON, Canada
- Centre for Critical Illness Research, Lawson Health Research Institute, London, ON, Canada
| | - Ajay Rajaram
- Department of Medical Biophysics, Western University, London, ON, Canada
- Imaging Program, Lawson Health Research Institute, London, ON, Canada
| | - Daniel Bainbridge
- Department of Anesthesia and Peri-operative Medicine, Western University, London, ON, Canada
- Division of Critical Care, Department of Medicine, Western University, London, ON, Canada
| | - Keith St Lawrence
- Department of Medical Biophysics, Western University, London, ON, Canada
- Imaging Program, Lawson Health Research Institute, London, ON, Canada
| | - Tracey Bentall
- Division of Critical Care, Department of Medicine, Western University, London, ON, Canada
| | - Michael Sharpe
- Department of Anesthesia and Peri-operative Medicine, Western University, London, ON, Canada
- Division of Critical Care, Department of Medicine, Western University, London, ON, Canada
| | - Mamadou Diop
- Department of Medical Biophysics, Western University, London, ON, Canada
- Imaging Program, Lawson Health Research Institute, London, ON, Canada
| | - Christopher G Ellis
- Department of Medical Biophysics, Western University, London, ON, Canada.
- Centre for Critical Illness Research, Lawson Health Research Institute, London, ON, Canada.
- Robarts Research Institute, Rm 3205, London, ON, N6A 5B7, Canada.
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21
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Validity of a novel respiratory rate monitor comprising stretchable strain sensors during a 6-min walking test in patients with chronic pulmonary obstructive disease. Respir Med 2021; 190:106675. [PMID: 34768076 DOI: 10.1016/j.rmed.2021.106675] [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: 06/22/2021] [Revised: 09/18/2021] [Accepted: 10/30/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Breathing frequency is rarely measured during a field walking test since the current monitoring system using a face mask is cumbersome for older adults. For effective clinical application, we aimed to validate the new respiratory monitor using wearable strain sensors during a 6-min walk test (6MWT) in young adults and patients with chronic obstructive pulmonary disease (COPD). METHODS The study included young adults and patients with stable COPD voluntarily recruited from three hospitals. Breathing frequency during 6MWT were measured by the strain sensor and a nasal capnometer. Total breathing frequencies were measured by the capnometer. The Bland-Altman method was used to estimate the mean limit of agreement for breathing frequency. RESULTS A total of 23 young adults (age = 23.1 ± 3.7, mean ± SD) and 50 patients with COPD (age = 75.2 ± 7.2, %FEV1 = 59.1 ± 19.7) were analyzed. During the entire test period, the total breathing frequencies were measured based on an average of 252 ± 46 breaths, and the total breathing frequency was higher in patients with COPD than in young adults (mean difference = -3.349, p < 0.0013). The mean difference in breathing frequency between the strain sensors and capnometer was -0.28 (95%CI: 0.75 to 0.20), and the limit of agreement ranged from -4.1 to 3.6. The CI of the limit of agreement included the limit of equivalence (4 counts/min). CONCLUSIONS The novel respiratory monitor with wearable sensors achieved the target accuracy in both young adults and patients with COPD in the 6MWT.
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Ali M, Elsayed A, Mendez A, Savaria Y, Sawan M. Contact and Remote Breathing Rate Monitoring Techniques: A Review. IEEE SENSORS JOURNAL 2021; 21:14569-14586. [PMID: 35789086 PMCID: PMC8769001 DOI: 10.1109/jsen.2021.3072607] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 06/01/2023]
Abstract
Breathing rate monitoring is a must for hospitalized patients with the current coronavirus disease 2019 (COVID-19). We review in this paper recent implementations of breathing monitoring techniques, where both contact and remote approaches are presented. It is known that with non-contact monitoring, the patient is not tied to an instrument, which improves patients' comfort and enhances the accuracy of extracted breathing activity, since the distress generated by a contact device is avoided. Remote breathing monitoring allows screening people infected with COVID-19 by detecting abnormal respiratory patterns. However, non-contact methods show some disadvantages such as the higher set-up complexity compared to contact ones. On the other hand, many reported contact methods are mainly implemented using discrete components. While, numerous integrated solutions have been reported for non-contact techniques, such as continuous wave (CW) Doppler radar and ultrawideband (UWB) pulsed radar. These radar chips are discussed and their measured performances are summarized and compared.
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Affiliation(s)
- Mohamed Ali
- Department of Electrical EngineeringPolytechnique MontréalMontrealQCH3T IJ4Canada
- Department of MicroelectronicsElectronics Research InstituteCairo12622Egypt
| | - Ali Elsayed
- Nanotechnology and Nanoelectronics ProgramUniversity of Science and Technology, Zewail City of Science, Technology and InnovationGiza12578Egypt
| | - Arnaldo Mendez
- Department of Electrical EngineeringPolytechnique MontréalMontrealQCH3T IJ4Canada
| | - Yvon Savaria
- Department of Electrical EngineeringPolytechnique MontréalMontrealQCH3T IJ4Canada
| | - Mohamad Sawan
- Department of Electrical EngineeringPolytechnique MontréalMontrealQCH3T IJ4Canada
- School of EngineeringWestlake Institute for Advanced Study, Westlake UniversityHangzhou310024China
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Photoplethysmography in Normal and Pathological Sleep. SENSORS 2021; 21:s21092928. [PMID: 33922042 PMCID: PMC8122413 DOI: 10.3390/s21092928] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/19/2021] [Accepted: 04/20/2021] [Indexed: 01/20/2023]
Abstract
This article presents an overview of the advancements that have been made in the use of photoplethysmography (PPG) for unobtrusive sleep studies. PPG is included in the quickly evolving and very popular landscape of wearables but has specific interesting properties, particularly the ability to capture the modulation of the autonomic nervous system during sleep. Recent advances have been made in PPG signal acquisition and processing, including coupling it with accelerometry in order to construct hypnograms in normal and pathologic sleep and also to detect sleep-disordered breathing (SDB). The limitations of PPG (e.g., oxymetry signal failure, motion artefacts, signal processing) are reviewed as well as technical solutions to overcome these issues. The potential medical applications of PPG are numerous, including home-based detection of SDB (for triage purposes), and long-term monitoring of insomnia, circadian rhythm sleep disorders (to assess treatment effects), and treated SDB (to ensure disease control). New contact sensor combinations to improve future wearables seem promising, particularly tools that allow for the assessment of brain activity. In this way, in-ear EEG combined with PPG and actigraphy could be an interesting focus for future research.
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Yüksek A. Utility of the Pleth Variability Index in predicting anesthesia-induced hypotension in geriatric patients. Turk J Med Sci 2021; 51:134-139. [PMID: 32892541 PMCID: PMC7991892 DOI: 10.3906/sag-1912-132] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 08/22/2020] [Indexed: 11/13/2022] Open
Abstract
Background/aim Anesthesia-induced hypotension may have negative consequences in geriatric patients. Therefore, predicting hypotension remains an important topic for anesthesiologists. Pleth Variability Index (PVI) measurement provides information about the fluid status and vascular tonus of patients. In this study, the ability of the Pleth Variability Index to predict hypotension after general anesthesia induction was evaluated. Materials and methods PVI values obtained from pulse oximetry were recorded, in addition to preoperative standard anesthesia monitoring. The correlation between the PVI value and mean arterial pressure (MAP), systolic arterial blood pressure (SAP) changes, and the power of PVI values to predict the incidence of hypotension after anesthesia induction (>20% MAP decrease) was tested. Results Eighty patients over 65 years of age who were operated under general anesthesia were included in the study. Hypotension was observed in 20 patients (25%). PVI values were mild and positively correlated with MAP changes (r = 0.195 and P = 0.041). According to receiver operating characteristic (ROC) analysis, the incidence of hypotension increased in patients with PVI values above 15.45%. We also found the following diagnostic results for PVI value for predicting hypotension: P = 0.044 and area under the ROC curve of 0.651 ± 0.073 (95% confidence interval (CI): 0.507–0.794), 40% sensitivity, 80% specificity, a PPV of 40%, an NPV of 80%, a cut-off value of 15.45, a positive likelihood ratio of 2, a negative likelihood ratio of 0.75, and a Youden Index of 0.2. Conclusion Predicting hypotension in geriatric patients is an important issue for anesthesiologists. As an easily applicable test, the Pleth Variability Index is useful in predicting MAP reduction in patients. This practical technique can be used routinely in all geriatric patient groups.
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Affiliation(s)
- Ahmet Yüksek
- Department of Anesthesiology and Reanimation, Bozok University, Yozgat, Turkey
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25
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Razavi MK, Flanigan DPT, White SM, Rice TB. A Real-Time Blood Flow Measurement Device for Patients with Peripheral Artery Disease. J Vasc Interv Radiol 2021; 32:453-458. [PMID: 33454181 DOI: 10.1016/j.jvir.2020.09.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 09/03/2020] [Accepted: 09/05/2020] [Indexed: 01/22/2023] Open
Abstract
PURPOSE To evaluate the feasibility of a new optical device that measures peripheral blood flow as a diagnostic and monitoring tool for patients with peripheral artery disease (PAD). MATERIALS AND METHODS In this prospective study, 167 limbs of 90 patients (mean age, 76 y; 53% men) with suspected PAD were evaluated with the FlowMet device, which uses a new type of dynamic light-scattering technology to assess blood flow in real time. Measurements of magnitude and phasicity of blood flow were combined into a single-value flow-waveform score and compared vs ankle-brachial index (ABI), toe-brachial index (TBI), and clinical presentation of patients per Rutherford category (RC). Receiver operating characteristic curves were constructed to predict RC. Area under the curve (AUC), sensitivity, and specificity were compared among flow-waveform score, ABI, and TBI. RESULTS Qualitatively, the FlowMet waveforms were analogous to Doppler velocity measurements, and degradation of waveform phasicity and amplitude were observed with increasing PAD severity. Quantitatively, the flow, waveform, and composite flow-waveform scores decreased significantly with decreasing TBI. In predicting RC ≥ 4, the flow-waveform score (AUC = 0.83) showed a linear decrease with worsening patient symptoms and power comparable to that of TBI (AUC = 0.82) and better than that of ABI (AUC = 0.71). Optimal sensitivity and specificity pairs were found to be 56%/83%, 72%/81%, and 89%/74% for ABI, TBI, and flow-waveform score, respectively. CONCLUSIONS The technology tested in this pilot study showed a high predictive value for diagnosis of critical limb ischemia. The device showed promise as a diagnostic tool capable of providing clinical feedback in real time.
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Affiliation(s)
- Mahmood K Razavi
- Vascular & Interventional Specialists of Orange County, 1140 W. La Veta Ave., no. 850, Orange, CA 92868.
| | - D Preston T Flanigan
- Vascular & Interventional Specialists of Orange County, 1140 W. La Veta Ave., no. 850, Orange, CA 92868
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Estimating Surgical Blood Loss Volume Using Continuously Monitored Vital Signs. SENSORS 2020; 20:s20226558. [PMID: 33212858 PMCID: PMC7698368 DOI: 10.3390/s20226558] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 11/13/2020] [Accepted: 11/16/2020] [Indexed: 11/17/2022]
Abstract
Background: There are currently no effective and accurate blood loss volume (BLV) estimation methods that can be implemented in operating rooms. To improve the accuracy and reliability of BLV estimation and facilitate clinical implementation, we propose a novel estimation method using continuously monitored photoplethysmography (PPG) and invasive arterial blood pressure (ABP). Methods: Forty anesthetized York Pigs (31.82 ± 3.52 kg) underwent a controlled hemorrhage at 20 mL/min until shock development was included. Machine-learning-based BLV estimation models were proposed and tested on normalized features derived by vital signs. Results: The results showed that the mean ± standard deviation (SD) for estimating BLV against the reference BLV of our proposed random-forest-derived BLV estimation models using PPG and ABP features, as well as the combination of ABP and PPG features, were 11.9 ± 156.2, 6.5 ± 161.5, and 7.0 ± 139.4 mL, respectively. Compared with traditional hematocrit computation formulas (estimation error: 102.1 ± 313.5 mL), our proposed models outperformed by nearly 200 mL in SD. Conclusion: This is the first attempt at predicting quantitative BLV from noninvasive measurements. Normalized PPG features are superior to ABP in accurately estimating early-stage BLV, and normalized invasive ABP features could enhance model performance in the event of a massive BLV.
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Papini GB, Fonseca P, Gilst MMV, Bergmans JW, Vullings R, Overeem S. Respiratory activity extracted from wrist-worn reflective photoplethysmography in a sleep-disordered population. Physiol Meas 2020; 41:065010. [PMID: 32428875 DOI: 10.1088/1361-6579/ab9481] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Respiratory activity is an essential parameter to monitor healthy and disordered sleep, and unobtrusive measurement methods have important clinical applications in diagnostics of sleep-related breathing disorders. We propose a respiratory activity surrogate extracted from wrist-worn reflective photoplethysmography validated on a heterogeneous dataset of 389 sleep recordings. APPROACH The surrogate was extracted by interpolating the amplitude of the PPG pulses after evaluation of pulse morphological quality. Subsequent multistep post-processing was applied to remove parts of the surrogate with low quality and high motion levels. In addition to standard respiration rate performance, we evaluated the similarity between surrogate respiratory activity and reference inductance plethysmography of the thorax, using Spearman's correlations and spectral coherence, and assessed the influence of PPG signal quality, motion levels, sleep stages and obstructive sleep apnea. MAIN RESULTS Prior to post-processing, the surrogate already had a strong similarity with the reference (correlation = 0.54, coherence = 0.81), and reached respiration rate estimation performance in line with the literature (estimation error = 0.76± 2.11 breaths/min). Detrimental effects of low PPG quality, high motion levels and sleep-dependent physiological phenomena were significantly mitigated by the proposed post-processing steps (correlation = 0.62, coherence = 0.88, estimation error = 0.53± 1.85 breaths/min). SIGNIFICANCE Wrist-worn PPG can be used to extract respiratory activity, thus allowing respiration monitoring in real-world sleep medicine applications using (consumer) wearable devices.
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Affiliation(s)
- Gabriele B Papini
- Department of Electrical Engineering, Eindhoven University of Technology, Den Dolech 2, 5612 AZ Eindhoven, The Netherlands. Philips Research, High Tech Campus, 5656 AE Eindhoven, The Netherlands. Sleep Medicine Center Kempenhaeghe, P.O. Box 61, 5590 AB Heeze, The Netherlands
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Chand T, Li M, Jamalabadi H, Wagner G, Lord A, Alizadeh S, Danyeli LV, Herrmann L, Walter M, Sen ZD. Heart Rate Variability as an Index of Differential Brain Dynamics at Rest and After Acute Stress Induction. Front Neurosci 2020; 14:645. [PMID: 32714132 PMCID: PMC7344021 DOI: 10.3389/fnins.2020.00645] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 05/25/2020] [Indexed: 11/17/2022] Open
Abstract
The brain continuously receives input from the internal and external environment. Using this information, the brain exerts its influence on both itself and the body to facilitate an appropriate response. The dynamic interplay between the brain and the heart and how external conditions modulate this relationship deserves attention. In high-stress situations, synchrony between various brain regions such as the prefrontal cortex and the heart may alter. This flexibility is believed to facilitate transitions between functional states related to cognitive, emotional, and especially autonomic activity. This study examined the dynamic temporal functional association of heart rate variability (HRV) with the interaction between three main canonical brain networks in 38 healthy male subjects at rest and directly after a psychosocial stress task. A sliding window approach was used to estimate the functional connectivity (FC) among the salience network (SN), central executive network (CEN), and default mode network (DMN) in 60-s windows on time series of blood-oxygen-level dependent (BOLD) signal. FC between brain networks was calculated by Pearson correlation. A multilevel linear mixed model was conducted to examine the window-by-window association between the root mean square of successive differences between normal heartbeats (RMSSD) and FC of network-pairs across sessions. Our findings showed that the minute-by-minute correlation between the FC and RMSSD was significantly stronger between DMN and CEN than for SN and CEN in the baseline session [b = 4.36, t(5025) = 3.20, p = 0.006]. Additionally, this differential relationship between network pairs and RMSSD disappeared after the stress task; FC between DMN and CEN showed a weaker correlation with RMSSD in comparison to baseline [b = −3.35, t(5025) = −3.47, p = 0.006]. These results suggest a dynamic functional interplay between HRV and the functional association between brain networks that varies depending on the needs created by changing conditions.
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Affiliation(s)
- Tara Chand
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.,Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.,Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
| | - Meng Li
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Anton Lord
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany.,QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah Alizadeh
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
| | - Lena V Danyeli
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany.,Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Luisa Herrmann
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.,Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.,Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.,Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany.,Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Zumrut D Sen
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.,Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.,Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
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A new approach to complicated and noisy physiological waveforms analysis: peripheral venous pressure waveform as an example. J Clin Monit Comput 2020; 35:637-653. [PMID: 32529454 DOI: 10.1007/s10877-020-00524-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Accepted: 05/05/2020] [Indexed: 10/24/2022]
Abstract
We introduce a recently developed nonlinear-type time-frequency analysis tool, synchrosqueezing transform (SST), to quantify complicated and noisy physiological waveform that has time-varying amplitude and frequency. We apply it to analyze a peripheral venous pressure (PVP) signal recorded during a seven hours aortic valve replacement procedure. In addition to showing the captured dynamics, we also quantify how accurately we can estimate the instantaneous heart rate from the PVP signal.
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30
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Tankanag AV, Grinevich AA, Tikhonova IV, Chemeris NK. An Analysis of Phase Relationships between Oscillatory Processes in the Human Cardiovascular System. Biophysics (Nagoya-shi) 2020. [DOI: 10.1134/s0006350920010194] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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31
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A pilot study: Wavelet cross-correlation of cardiovascular oscillations under controlled respiration in humans. Microvasc Res 2020; 130:103993. [PMID: 32194083 DOI: 10.1016/j.mvr.2020.103993] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 03/10/2020] [Accepted: 03/10/2020] [Indexed: 12/16/2022]
Abstract
The influence of deep controlled respiration on cardiovascular oscillations in 13 healthy young volunteers was studied. A measurement system comprising electrocardiography, laser Doppler flowmetry (LDF) and photoplethysmography (PPG) was used to estimate heart rate variability (HRV), tissue blood volume and skin blood perfusion at spontaneous respiration and during three tests at controlled conditions. In the latter case, respiration was controlled in both rate (0.04, 0.1 and 0.25 Hz) and depth. During respiration at 0.04 and 0.1 Hz, the amplification of a respiratory-related component in the spectra of HRV and PPG signals turned out to be more significant than that at spontaneous respiration, and at 0.25 Hz this component remained unchanged. Controlled respiration caused a significant increase in correlation in HRV-PPG, HRV-LDF and PPG-LDF pairs of signals compared to spontaneous one. At 0.25 Hz controlled respiration, no significant increase in correlation in these pairs of signals was found. The differences observed in this study can be attributed to the effects of the sympathetic nerve activity on vascular tone regulation.
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Hoff IE, Hisdal J, Landsverk SA, Røislien J, Kirkebøen KA, Høiseth LØ. Respiratory variations in pulse pressure and photoplethysmographic waveform amplitude during positive expiratory pressure and continuous positive airway pressure in a model of progressive hypovolemia. PLoS One 2019; 14:e0223071. [PMID: 31560715 PMCID: PMC6764667 DOI: 10.1371/journal.pone.0223071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 09/12/2019] [Indexed: 11/18/2022] Open
Abstract
PURPOSE Respiratory variations in pulse pressure (dPP) and photoplethysmographic waveform amplitude (dPOP) are used for evaluation of volume status in mechanically ventilated patients. Amplification of intrathoracic pressure changes may enable their use also during spontaneous breathing. We investigated the association between the degree of hypovolemia and dPP and dPOP at different levels of two commonly applied clinical interventions; positive expiratory pressure (PEP) and continuous positive airway pressure (CPAP). METHODS 20 healthy volunteers were exposed to progressive hypovolemia by lower body negative pressure (LBNP). PEP of 0 (baseline), 5 and 10 cmH2O was applied by an expiratory resistor and CPAP of 0 (baseline), 5 and 10 cmH2O by a facemask. dPP was obtained non-invasively with the volume clamp method and dPOP from a pulse oximeter. Central venous pressure was measured in 10 subjects. Associations between changes were examined using linear mixed-effects regression models. RESULTS dPP increased with progressive LBNP at all levels of PEP and CPAP. The LBNP-induced increase in dPP was amplified by PEP 10 cmH20. dPOP increased with progressive LBNP during PEP 5 and PEP 10, and during all levels of CPAP. There was no additional effect of the level of PEP or CPAP on dPOP. Progressive hypovolemia and increasing levels of PEP were reflected by increasing respiratory variations in CVP. CONCLUSION dPP and dPOP reflected progressive hypovolemia in spontaneously breathing healthy volunteers during PEP and CPAP. An increase in PEP from baseline to 10 cmH2O augmented the increase in dPP, but not in dPOP.
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Affiliation(s)
- Ingrid Elise Hoff
- Norwegian Air Ambulance Foundation, Sentrum, Oslo, Norway
- Department of Anesthesiology, Oslo University Hospital, Nydalen, Oslo, Norway
- * E-mail:
| | - Jonny Hisdal
- Section of Vascular Investigations, Department of Vascular Surgery, Oslo University Hospital, Nydalen, Oslo, Norway
- Faculty of Medicine, University of Oslo, Blindern, Oslo, Norway
| | | | - Jo Røislien
- Norwegian Air Ambulance Foundation, Sentrum, Oslo, Norway
| | | | - Lars Øivind Høiseth
- Department of Anesthesiology, Oslo University Hospital, Nydalen, Oslo, Norway
- Section of Vascular Investigations, Department of Vascular Surgery, Oslo University Hospital, Nydalen, Oslo, Norway
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Allen J. Quantifying the Delays Between Multi-Site Photoplethysmography Pulse and Electrocardiogram R-R Interval Changes Under Slow-Paced Breathing. Front Physiol 2019; 10:1190. [PMID: 31607946 PMCID: PMC6774289 DOI: 10.3389/fphys.2019.01190] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 09/03/2019] [Indexed: 12/05/2022] Open
Abstract
Objective: Objective assessment of autonomic function is important, including the investigation of slow-paced breathing to induce associated periodic changes in the cardiovascular system – such as blood pressure and heart rate. However, pulse changes across a range of peripheral body sites have seldom been explored with this challenge. The primary aim of this pilot study was to utilize multi-site photoplethysmography (MPPG) technology to quantify the phase delays, i.e., correlation lags, between changes in heart rate and changes in key pulse features with slow-paced breathing (0.1 Hz). Methods: Waveforms were collected simultaneously from the right and left ear lobes, thumbs, and great toes of 18 healthy adult subjects. Cross correlation lags between reference beat-to-beat changes in electrocardiogram (ECG) R-R wave interval and changes in pulse arrival time (foot of pulse; PATf) and also for pulse amplitude (foot-to-peak; AMP) were determined. Results: Relative to R-R changes, the median ear, thumb, and toe PATf correlation lags were 3.4, 2.9, and 2.1 beats, respectively; contrasting to AMP with 5.7, 6.0, and 6.9 beats, respectively. These PATf correlation lags in beats were significantly lower than for the AMP measure. Segmental differences between sites and timing measure variability have also been quantified. Conclusion: This pilot study has indicated bilateral similarity plus segmental differences for relative delays in PPG pulse timing and amplitude measures relative to R-R interval changes with paced breathing. These correlation and variability data are now available for comparison with cardiovascular patient groups to support development of autonomic function assessment techniques.
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Affiliation(s)
- John Allen
- Microvascular Diagnostics, Northern Medical Physics and Clinical Engineering Department, Freeman Hospital, Newcastle upon Tyne, United Kingdom.,Faculty of Medical Sciences, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
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Mulcahy JS, Larsson DEO, Garfinkel SN, Critchley HD. Heart rate variability as a biomarker in health and affective disorders: A perspective on neuroimaging studies. Neuroimage 2019; 202:116072. [PMID: 31386920 DOI: 10.1016/j.neuroimage.2019.116072] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 07/28/2019] [Accepted: 08/02/2019] [Indexed: 12/30/2022] Open
Abstract
The dynamic embodiment of psychological processes is evident in the association of health outcomes, behavioural traits and psychological functioning with Heart Rate Variability (HRV). The dominant high-frequency component of HRV is an index of the central neural control of heart rhythm, mediated via the parasympathetic vagus nerve. HRV provides a potential objective measure of action policies for the adaptive and predictive allostatic regulation of homeostasis within the cardiovascular system. In its support, a network of brain regions (referred to as the 'central autonomic network') maps internal state, and controls autonomic responses. This network includes regions of prefrontal cortex, anterior cingulate cortex, insula, amygdala, periaqueductal grey, pons and medulla. Human neuroimaging studies of neural activation and functional connectivity broadly endorse this architecture, and its link with cardiac regulation at rest and dysregulation in clinical states that include affective disorders. In this review, we appraise neuroimaging research and related evidence for HRV as an informative marker of autonomic integration with affect and cognition, taking a perspective on function and organisation. We consider evidence for the utility of HRV as a metric to inform targeted interventions to improve autonomic and affective dysregulation, and suggest research questions for further investigation.
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Affiliation(s)
- James S Mulcahy
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, BN1 9RY, UK.
| | | | - Sarah N Garfinkel
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, BN1 9RY, UK; Sackler Centre for Consciousness Science, University of Sussex, Falmer, BN1 9RR, UK; Sussex Partnership NHS Foundation Trust, Brighton, BN2 3EW, UK
| | - Hugo D Critchley
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, BN1 9RY, UK; Sackler Centre for Consciousness Science, University of Sussex, Falmer, BN1 9RR, UK; Sussex Partnership NHS Foundation Trust, Brighton, BN2 3EW, UK
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35
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Scholkmann F, Wolf U. The Pulse-Respiration Quotient: A Powerful but Untapped Parameter for Modern Studies About Human Physiology and Pathophysiology. Front Physiol 2019; 10:371. [PMID: 31024336 PMCID: PMC6465339 DOI: 10.3389/fphys.2019.00371] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Accepted: 03/18/2019] [Indexed: 01/06/2023] Open
Abstract
A specific and unique aspect of cardiorespiratory activity can be captured by dividing the heart rate (HR) by the respiration rate (RR), giving the pulse-respiration quotient (PRQ = HR/RR). In this review article, we summarize the main findings of studies using and investigating the PRQ. We describe why the PRQ is a powerful parameter that captures complex regulatory states of the cardiorespiratory system, and we highlight the need to re-introduce the use of this parameter into modern studies about human physiology and pathophysiology. In particular, we show that the PRQ (i) changes during human development, (ii) is time-dependent (ultradian, circadian, and infradian rhythms), (iii) shows specific patterns during sleep, (iv) changes with physical activity and body posture, (v) is linked with psychophysical and cognitive activity, (vi) is sex-dependent, and (vii) is determined by the individual physiological constitution. Furthermore, we discuss the medical aspects of the PRQ in terms of applications for disease classification and monitoring. Finally, we explain why there should be a revival in the use of the PRQ for basic research about human physiology and for applications in medicine, and we give recommendations for the use of the PRQ in studies and medical applications.
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Affiliation(s)
- Felix Scholkmann
- Institute of Complementary and Integrative Medicine, University of Bern, Bern, Switzerland
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de Souza Kock K, Marques JLB. Use of photoplethysmography to predict mortality in intensive care units. Vasc Health Risk Manag 2018; 14:311-320. [PMID: 30464494 PMCID: PMC6217313 DOI: 10.2147/vhrm.s172643] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
PURPOSE The aim of this study was to evaluate and compare the capacity to predict hemodynamic variables obtained with photoplethysmography (PPG) and Acute Physiology and Chronic Health Evaluation (APACHE II) in patients hospitalized in the intensive care unit (ICU). MATERIALS AND METHODS A prospective cohort study was conducted in the adult ICU of Hospital Nossa Senhora da Conceição, located in Tubarão, Santa Catarina, Brazil. The data collected included the diagnosis for hospitalization, age, gender, clinical or surgical profile, PPG pulse curve signal, and APACHE II score in the first 24 hours. A bivariate and a multivariate logistic regressions were performed, with death as an outcome. A mortality model using artificial neural networks (ANNs) was proposed. RESULTS A total of 190 individuals were evaluated. Most of them were males (6:5), with a median age of 67 (54-75) years, and the main reasons for hospitalization were cardiovascular and neurological causes; half of them were surgical cases. APACHE II median score was 14 (8-19), with a median length of stay of 6 (3-15) days, and 28.4% of the patients died. The following factors were associated with mortality: age (OR=1.023; 95% CI 1.001-1.044; P=0.039), clinical profile (OR=5.481; 95% CI 2.646-11.354; P<0.001), APACHE II (OR=1.168; 95% CI 1.106-1.234; P<0.001), heart rate in the first 24 hours (OR=1.020; 95% CI 1.001-1.039; P=0.036), and time between the systolic and diastolic peak (∆T) intervals obtained with PPG (OR=0.989; 95% CI 0.979-0.998; P=0.015). Compared with the accuracy (area under the receiver-operating characteristic curve) 0.780 of APACHE II (95% CI 0.711-0.849; P<0.001), the multivariate logistic model showed a larger area of 0.858 (95% CI 0.803-0.914; P<0.001). In the model using ANNs, the accuracy was 0.895 (95% CI 0.851-0.940; P<0.001). CONCLUSION The mortality models using variables obtained with PPG, with the inclusion of epidemiological parameters, are very accurate and, if associated to APACHE II, improve prognostic accuracy. The use of ANN was even more accurate, indicating that this tool is important to help in the clinical judgment of the intensivist.
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Affiliation(s)
- Kelser de Souza Kock
- Graduate Program in Medical Sciences, Federal University of Santa Catarina, Florianópolis, SC, Brazil,
| | - Jefferson Luiz Brum Marques
- Institute of Biomedical Engineering, Department of Electrical and Electronic Engineering, Federal University of Santa Catarina, Florianópolis, SC, Brazil
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Lee JH, Yang S, Park J, Kim HC, Kim EH, Jang YE, Kim JT, Kim HS. Time to consider the contact force during photoplethysmography measurement during pediatric anesthesia: A prospective, nonrandomized interventional study. Paediatr Anaesth 2018; 28:660-667. [PMID: 29920853 DOI: 10.1111/pan.13415] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/30/2018] [Indexed: 12/15/2022]
Abstract
BACKGROUND Respiratory variations in photoplethysmography amplitude enable volume status assessment. However, the contact force between the measurement site and sensor can affect photoplethysmography waveforms. We aimed to evaluate contact force effects on respiratory variations in photoplethysmography waveforms in children under general anesthesia. METHODS Children aged 3-5 years were enrolled. After anesthetic induction, mechanical ventilation commenced at a tidal volume of 10 mL/kg. Photoplethysmographic signals were obtained in the supine position from the index finger using a force sensor-integrated clip-type photoplethysmography sensor that increased the contact force from 0-1.4 N for 20 respiratory cycles at each force. The AC amplitude (pulsatile component), DC amplitude (nonpulsatile component), AC/DC ratio, and respiratory variations in photoplethysmography amplitude were calculated. RESULTS Data from 34 children were analyzed. Seven contact forces at 0.2-N increments were evaluated for each patient. The normalized AC amplitude increased maximally at a contact force of 0.4-0.6 N and decreased with increasing contact force. However, the normalized DC amplitude increased with a contact force exceeding 0.4 N. ΔPOP decreased slightly and increased from the point when the AC amplitude started to decrease as contact force increased. In a 0.2-1.2 N contact force range, significant changes in the normalized AC amplitude, normalized DC amplitude, AC/DC ratio, and respiratory variations in photoplethysmography amplitude were observed. CONCLUSION Respiratory variations in photoplethysmography amplitude changed according to variable contact forces; therefore, these measurements may not reflect respiration-induced stroke volume variations. Clinicians should consider contact force bias when interpreting morphological data from photoplethysmography signals.
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Affiliation(s)
- Ji-Hyun Lee
- Department of Anaesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Seungman Yang
- Interdisciplinary Program for Bioengineering, Seoul National University Graduate School, Seoul, Korea
| | - Jonghyun Park
- Interdisciplinary Program for Bioengineering, Seoul National University Graduate School, Seoul, Korea
| | - Hee Chan Kim
- Interdisciplinary Program for Bioengineering, Seoul National University Graduate School, Seoul, Korea.,Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea
| | - Eun-Hee Kim
- Department of Anaesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Young-Eun Jang
- Department of Anaesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Jin-Tae Kim
- Department of Anaesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Hee-Soo Kim
- Department of Anaesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
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The value of dynamic preload variables during spontaneous ventilation. Curr Opin Crit Care 2018; 23:310-317. [PMID: 28614095 DOI: 10.1097/mcc.0000000000000430] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW To discuss the physiological significance and clinical value of dynamic preload variables in spontaneously breathing patients. RECENT FINDINGS Dynamic preload variables reflect the response of the cardiac output to a modification of preload and can therefore be used to assess fluid responsiveness. Continuous dynamic parameters that are calculated from the variations in the arterial and plethysmographic waveforms following a mechanical breath have been shown to predict fluid responsiveness much better than static preload parameters. These parameters are displayed on many patient monitors though their use is limited to mechanically ventilated patients. However, spontaneous breathing may also induce significant hemodynamic changes because of the repetitive negative swings in the pleural pressure. By better understanding the physiological basis of these changes, the same 'dynamic parameters' can be used to gain unique physiological insights during spontaneous breathing. These include the ability to identify and/or monitor respiratory rate, respiratory effort (e.g., patient-ventilator asynchrony), fluid responsiveness (to some degree), pulsus paradoxus (e.g. asthma, cardiac tamponade), and, importantly, upper airway obstruction. SUMMARY Although originally intended to be used only during mechanical ventilation, 'dynamic parameters' may offer valuable clinical information in spontaneously breathing patients.
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Choi BM, Park C, Lee YH, Shin H, Lee SH, Jeong S, Noh GJ, Lee B. Development of a new analgesic index using nasal photoplethysmography. Anaesthesia 2018; 73:1123-1130. [PMID: 29790159 DOI: 10.1111/anae.14327] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/16/2018] [Indexed: 11/29/2022]
Abstract
Although surrogate measures to quantify pain intensity have been commercialised, there is a need to develop a new index with improved accuracy. The aim of this study was to develop a new analgesic index using nasal photoplethysmography data. The specially designed sensor was placed between the columella and the nasal septum to acquire nasal photoplethysmography in surgical patients. Nasal photoplethysmography and Surgical Pleth Index® (GE Healthcare) data were obtained for 14 min both in the absence (pre-operatively) or presence (postoperatively) of pain in a group of surgical patients, each patient acting as their own control. Various dynamic photoplethysmography variables were extracted to quantify pain intensity; the most accurate index was selected using logistic regression as a classifier. The area under the curve of the receiver-operating characteristic curve was measured to evaluate the accuracy of final model predictions. In total, 12,012 heart beats from 89 patients were used to develop a new Nasal Photoplethysmography Index for analgesic depth quantification. The two-variable model (a combination of diastolic peak point variation and heart beat interval variation) was most accurate in discriminating between the presence and absence of pain (numerical rating scale (NRS) ≥ 3). The accuracy and area under the curve of the receiver-operating characteristic curve for the Nasal Photoplethysmography Index were 75.3% and 0.8018, respectively, and 64.8% and 0.7034, respectively, for the Surgical Pleth Index. The Nasal Photoplethysmography Index clearly distinguished pain (NRS ≥ 3) in awake surgical patients with postoperative pain. The Nasal Photoplethysmography Index performed better than the Surgical Pleth Index. Further validation studies are needed to evaluate its feasibility to quantify pain intensity during general anaesthesia.
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Affiliation(s)
- B M Choi
- Department of Anaesthesiology and Pain Medicine, Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - C Park
- School of Mechanical Engineering, Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju, South Korea
| | - Y H Lee
- Department of Anaesthesiology and Pain Medicine, Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - H Shin
- Department of Biomedical Engineering, Chonnam National University, Yeosu, South Korea
| | - S H Lee
- New Drug Development Center, Osong Medical Innovation Foundation, Chungcheongbuk-do, Korea
| | - S Jeong
- Department of Anesthesiology and Pain Medicine, Chonnam National University Medical School, Gwangju, Korea
| | - G J Noh
- Department of Anesthesiology and Pain Medicine and Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - B Lee
- Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju, South Korea
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Kuwata S, Suehiro K, Juri T, Tsujimoto S, Mukai A, Tanaka K, Yamada T, Mori T, Nishikawa K. Pleth variability index can predict spinal anaesthesia-induced hypotension in patients undergoing caesarean delivery. Acta Anaesthesiol Scand 2018; 62:75-84. [PMID: 29034983 DOI: 10.1111/aas.13012] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Accepted: 09/24/2017] [Indexed: 12/30/2022]
Abstract
BACKGROUND Spinal anaesthesia carries a risk of hypotension. We hypothesized that pleth variability index and perfusion index would assess maternal volume status, and thus, allow identification of patients at higher risk of developing hypotension after spinal anaesthesia for caesarean delivery. METHODS Fifty patients undergoing elective caesarean delivery were enrolled. All patients received spinal anaesthesia with 0.5% hyperbaric bupivacaine (10 mg) and fentanyl (10 mcg). Blood pressure was measured every minute. Pleth variability index and perfusion index were automatically measured throughout the procedure using pulse oximetry on the index finger. In case of hypotension (systolic blood pressure below 90 mmHg or 80% of the baseline value), ephedrine 5 mg was administered. Receiver-operating characteristic and multivariate logistic regression analyses for spinal anaesthesia-induced hypotension were performed. RESULTS Hypotension occurred in 32 patients (64%). The areas under the receiver-operating characteristic curve were 0.751 (95% confidence interval: 0.597-0.904) for pleth variability index before anaesthesia, 0.793 (95% confidence interval: 0.655-0.930) for pleth variability index after anaesthesia and 0.731 (95% confidence interval: 0.570-0.892) for perfusion index change (percent change in perfusion index induced by spinal anaesthesia). The optimal threshold value of pleth variability index (after anaesthesia) for predicting hypotension was 18% (sensitivity: 78.1%, specificity: 83.3%). Pleth variability index after spinal anaesthesia was an independent factor for hypotension (odds ratio: 1.21, P = 0.041). CONCLUSIONS Pleth variability index after spinal anaesthesia was a good predictor of spinal anaesthesia-induced hypotension in patients undergoing caesarean delivery. In addition, perfusion index change after spinal anaesthesia has the potential to predict hypotension.
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Affiliation(s)
- S. Kuwata
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
| | - K. Suehiro
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
| | - T. Juri
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
| | - S. Tsujimoto
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
| | - A. Mukai
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
| | - K. Tanaka
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
| | - T. Yamada
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
| | - T. Mori
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
| | - K. Nishikawa
- Department of Anaesthesiology; Osaka City University Graduate School of Medicine; Osaka Japan
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41
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Fonseca P, Weysen T, Goelema MS, Møst EIS, Radha M, Lunsingh Scheurleer C, van den Heuvel L, Aarts RM. Validation of Photoplethysmography-Based Sleep Staging Compared With Polysomnography in Healthy Middle-Aged Adults. Sleep 2017; 40:3868868. [PMID: 28838130 DOI: 10.1093/sleep/zsx097] [Citation(s) in RCA: 86] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Study Objectives To compare the accuracy of automatic sleep staging based on heart rate variability measured from photoplethysmography (PPG) combined with body movements measured with an accelerometer, with polysomnography (PSG) and actigraphy. Methods Using wrist-worn PPG to analyze heart rate variability and an accelerometer to measure body movements, sleep stages and sleep statistics were automatically computed from overnight recordings. Sleep-wake, 4-class (wake/N1 + N2/N3/REM) and 3-class (wake/NREM/REM) classifiers were trained on 135 simultaneously recorded PSG and PPG recordings of 101 healthy participants and validated on 80 recordings of 51 healthy middle-aged adults. Epoch-by-epoch agreement and sleep statistics were compared with actigraphy for a subset of the validation set. Results The sleep-wake classifier obtained an epoch-by-epoch Cohen's κ between PPG and PSG sleep stages of 0.55 ± 0.14, sensitivity to wake of 58.2 ± 17.3%, and accuracy of 91.5 ± 5.1%. κ and sensitivity were significantly higher than with actigraphy (0.40 ± 0.15 and 45.5 ± 19.3%, respectively). The 3-class classifier achieved a κ of 0.46 ± 0.15 and accuracy of 72.9 ± 8.3%, and the 4-class classifier, a κ of 0.42 ± 0.12 and accuracy of 59.3 ± 8.5%. Conclusions The moderate epoch-by-epoch agreement and, in particular, the good agreement in terms of sleep statistics suggest that this technique is promising for long-term sleep monitoring, although more evidence is needed to understand whether it can complement PSG in clinical practice. It also offers an improvement in sleep/wake detection over actigraphy for healthy individuals, although this must be confirmed on a larger, clinical population.
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Affiliation(s)
- Pedro Fonseca
- Philips Group Innovation Research, Eindhoven, The Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Tim Weysen
- Philips Group Innovation Research, Eindhoven, The Netherlands
| | - Maaike S Goelema
- Philips Group Innovation Research, Eindhoven, The Netherlands.,Department of Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Els I S Møst
- Philips Group Innovation Research, Eindhoven, The Netherlands
| | - Mustafa Radha
- Philips Group Innovation Research, Eindhoven, The Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Charlotte Lunsingh Scheurleer
- Philips Group Innovation Research, Eindhoven, The Netherlands.,Department of Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands
| | | | - Ronald M Aarts
- Philips Group Innovation Research, Eindhoven, The Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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BHAT SHREYA, ADAM MUHAMMAD, HAGIWARA YUKI, NG EDDIEY. THE BIOPHYSICAL PARAMETER MEASUREMENTS FROM PPG SIGNAL. J MECH MED BIOL 2017. [DOI: 10.1142/s021951941740005x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Early investigation on blood circulation by Hertzman (1937) leads to the observation of vital body signs such as respiration rate, heart rate (HR), blood oxygenation and vascular assessment using photoplethysmographic (PPG) device. PPG is a noninvasive, painless optical technique used to monitor the pulsations linked to alteration in the blood volume. The PPG waveform is a summation of pulsatile and nonpulsatile components and contains useful information about the physiological systems. With the breakthrough in technology and development of powerful analytical tools, PPG devices are constantly being used in advanced medical equipments such as smart-watches and smart-wristbands for HR monitoring, pulse oximeters for measuring respiratory rate and noncontact PPG device for blood oxygen saturation measurement. This paper presents description on PPG and its characteristic waveform and working principle. It also includes brief explanation on nonlinear analysis of PPG signals and salient applications of PPG followed by its advantages and limitations.
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Affiliation(s)
- SHREYA BHAT
- Department of Psychiatry, St John’s Research Institute, Bangalore, India
| | - MUHAMMAD ADAM
- Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore
| | - YUKI HAGIWARA
- Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore
| | - EDDIE Y. K. NG
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
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43
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Cicone A, Wu HT. How Nonlinear-Type Time-Frequency Analysis Can Help in Sensing Instantaneous Heart Rate and Instantaneous Respiratory Rate from Photoplethysmography in a Reliable Way. Front Physiol 2017; 8:701. [PMID: 29018352 PMCID: PMC5615790 DOI: 10.3389/fphys.2017.00701] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2017] [Accepted: 08/30/2017] [Indexed: 11/13/2022] Open
Abstract
Despite the population of the noninvasive, economic, comfortable, and easy-to-install photoplethysmography (PPG), it is still lacking a mathematically rigorous and stable algorithm which is able to simultaneously extract from a single-channel PPG signal the instantaneous heart rate (IHR) and the instantaneous respiratory rate (IRR). In this paper, a novel algorithm called deppG is provided to tackle this challenge. deppG is composed of two theoretically solid nonlinear-type time-frequency analyses techniques, the de-shape short time Fourier transform and the synchrosqueezing transform, which allows us to extract the instantaneous physiological information from the PPG signal in a reliable way. To test its performance, in addition to validating the algorithm by a simulated signal and discussing the meaning of "instantaneous," the algorithm is applied to two publicly available batch databases, the Capnobase and the ICASSP 2015 signal processing cup. The former contains PPG signals relative to spontaneous or controlled breathing in static patients, and the latter is made up of PPG signals collected from subjects doing intense physical activities. The accuracies of the estimated IHR and IRR are compared with the ones obtained by other methods, and represent the state-of-the-art in this field of research. The results suggest the potential of deppG to extract instantaneous physiological information from a signal acquired from widely available wearable devices, even when a subject carries out intense physical activities.
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Affiliation(s)
- Antonio Cicone
- Department of Information Engineering, Computer Science and Mathematics, Universitá degli Studi dell'AquilaL'Aquila, Italy
| | - Hau-Tieng Wu
- Department of Mathematics and Statistical Science, Duke UniversityDurham, NC, United States.,Mathematics Division, National Center for Theoretical SciencesTaipei, Taiwan
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44
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Huvanandana J, Thamrin C, Tracy MB, Hinder M, Nguyen CD, McEwan AL. Advanced analyses of physiological signals in the neonatal intensive care unit. Physiol Meas 2017; 38:R253-R279. [DOI: 10.1088/1361-6579/aa8a13] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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45
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Touw HRW, Verheul MH, Tuinman PR, Smit J, Thöne D, Schober P, Boer C. Photoplethysmography respiratory rate monitoring in patients receiving procedural sedation and analgesia for upper gastrointestinal endoscopy. J Clin Monit Comput 2017; 31:747-754. [PMID: 27236561 PMCID: PMC5500676 DOI: 10.1007/s10877-016-9890-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2016] [Accepted: 05/20/2016] [Indexed: 02/07/2023]
Abstract
The value of capnography during procedural sedation and analgesia (PSA) for the detection of hypoxaemia during upper gastrointestinal (UGI) endoscopic procedures is limited. Photoplethysmography respiratory rate (RRp) monitoring may provide a useful alternative, but the level of agreement with capnography during PSA is unknown. We therefore investigated the level of agreement between the RRp and capnography-based RR (RRc) during PSA for UGI endoscopy. This study included patients undergoing PSA for UGI endoscopy procedures. Pulse oximetry (SpO2) and RRc were recorded in combination with Nellcor 2.0 (RRp) monitoring (Covidien, USA). Bland-Altman analysis was used to evaluate the level of agreement between RRc and RRp. Episodes of apnoea, defined as no detection of exhaled CO2 for minimal 36 s, and hypoxaemia, defined as an SpO2 < 92 %, were registered. A total of 1054 min of data from 26 patients were analysed. Bland-Altman analysis between the RRc and RRp revealed a bias of 2.25 ± 5.41 breath rate per minute (brpm), with limits of agreement from -8.35 to 12.84 brpm for an RR ≥ 4 brpm. A total of 67 apnoea events were detected. In 21 % of all apnoea events, the patient became hypoxaemic. Hypoxaemia occurred 42 times with a median length of 34 (19-141) s, and was preceded in 34 % of the cases by apnoea and in 64 % by an RRc ≥ 8 brpm. In 81 % of all apnoea events, photoplethysmography registered an RRp ≥ 4 brpm. We found a low level of agreement between capnography and the plethysmography respiratory rate during procedural sedation for UGI endoscopy. Moreover, respiratory rate derived from both the capnogram and photoplethysmogram showed a limited ability to provide warning signs for a hypoxaemic event during the sedation procedure.
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Affiliation(s)
- Hugo R W Touw
- Department of Anaesthesiology, Institute for Cardiovascular Research, VU University Medical Centre, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Milou H Verheul
- Department of Anaesthesiology, Institute for Cardiovascular Research, VU University Medical Centre, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Pieter R Tuinman
- Department of Intensive Care Medicine, Institute for Cardiovascular Research, VU University Medical Centre, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Jeroen Smit
- Department of Anaesthesiology, Institute for Cardiovascular Research, VU University Medical Centre, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Deirdre Thöne
- Department of Anaesthesiology, Institute for Cardiovascular Research, VU University Medical Centre, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Patrick Schober
- Department of Anaesthesiology, Institute for Cardiovascular Research, VU University Medical Centre, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Christa Boer
- Department of Anaesthesiology, Institute for Cardiovascular Research, VU University Medical Centre, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
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Bergese SD, Mestek ML, Kelley SD, McIntyre R, Uribe AA, Sethi R, Watson JN, Addison PS. Multicenter Study Validating Accuracy of a Continuous Respiratory Rate Measurement Derived From Pulse Oximetry: A Comparison With Capnography. Anesth Analg 2017; 124:1153-1159. [PMID: 28099286 PMCID: PMC5367492 DOI: 10.1213/ane.0000000000001852] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Published ahead of print January 17, 2017. BACKGROUND: Intermittent measurement of respiratory rate via observation is routine in many patient care settings. This approach has several inherent limitations that diminish the clinical utility of these measurements because it is intermittent, susceptible to human error, and requires clinical resources. As an alternative, a software application that derives continuous respiratory rate measurement from a standard pulse oximeter has been developed. We sought to determine the performance characteristics of this new technology by comparison with clinician-reviewed capnography waveforms in both healthy subjects and hospitalized patients in a low-acuity care setting. METHODS: Two independent observational studies were conducted to validate the performance of the Medtronic NellcorTM Respiration Rate Software application. One study enrolled 26 healthy volunteer subjects in a clinical laboratory, and a second multicenter study enrolled 53 hospitalized patients. During a 30-minute study period taking place while participants were breathing spontaneously, pulse oximeter and nasal/oral capnography waveforms were collected. Pulse oximeter waveforms were processed to determine respiratory rate via the Medtronic Nellcor Respiration Rate Software. Capnography waveforms reviewed by a clinician were used to determine the reference respiratory rate. RESULTS: A total of 23,243 paired observations between the pulse oximeter-derived respiratory rate and the capnography reference method were collected and examined. The mean reference-based respiratory rate was 15.3 ± 4.3 breaths per minute with a range of 4 to 34 breaths per minute. The Pearson correlation coefficient between the Medtronic Nellcor Respiration Rate Software values and the capnography reference respiratory rate is reported as a linear correlation, R, as 0.92 ± 0.02 (P < .001), whereas Lin’s concordance correlation coefficient indicates an overall agreement of 0.85 ± 0.04 (95% confidence interval [CI] +0.76; +0.93) (healthy volunteers: 0.94 ± 0.02 [95% CI +0.91; +0.97]; hospitalized patients: 0.80 ± 0.06 [95% CI +0.68; +0.92]). The mean bias of the Medtronic Nellcor Respiration Rate Software was 0.18 breaths per minute with a precision (SD) of 1.65 breaths per minute (healthy volunteers: 0.37 ± 0.78 [95% limits of agreement: –1.16; +1.90] breaths per minute; hospitalized patients: 0.07 ± 1.99 [95% limits of agreement: –3.84; +3.97] breaths per minute). The root mean square deviation was 1.35 breaths per minute (healthy volunteers: 0.81; hospitalized patients: 1.60). CONCLUSIONS: These data demonstrate the performance of the Medtronic Nellcor Respiration Rate Software in healthy subjects and patients hospitalized in a low-acuity care setting when compared with clinician-reviewed capnography. The observed performance of this technology suggests that it may be a useful adjunct to continuous pulse oximetry monitoring by providing continuous respiratory rate measurements. The potential patient safety benefit of using combined continuous pulse oximetry and respiratory rate monitoring warrants assessment.
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Affiliation(s)
- Sergio D Bergese
- From the Departments of *Anesthesiology and †Neurological Surgery, The Ohio State University Wexner Medical Center, Columbus, Ohio; ‡Respiratory & Monitoring Solutions, Medtronic, Boulder, Colorado; §Department of Surgery, University of Colorado Hospital, Aurora, Colorado; and ‖Respiratory & Monitoring Solutions, Medtronic, Edinburgh, United Kingdom
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Caballero-Gaudes C, Reynolds RC. Methods for cleaning the BOLD fMRI signal. Neuroimage 2017; 154:128-149. [PMID: 27956209 PMCID: PMC5466511 DOI: 10.1016/j.neuroimage.2016.12.018] [Citation(s) in RCA: 325] [Impact Index Per Article: 46.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 12/05/2016] [Accepted: 12/08/2016] [Indexed: 01/13/2023] Open
Abstract
Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has rapidly become a popular technique for the investigation of brain function in healthy individuals, patients as well as in animal studies. However, the BOLD signal arises from a complex mixture of neuronal, metabolic and vascular processes, being therefore an indirect measure of neuronal activity, which is further severely corrupted by multiple non-neuronal fluctuations of instrumental, physiological or subject-specific origin. This review aims to provide a comprehensive summary of existing methods for cleaning the BOLD fMRI signal. The description is given from a methodological point of view, focusing on the operation of the different techniques in addition to pointing out the advantages and limitations in their application. Since motion-related and physiological noise fluctuations are two of the main noise components of the signal, techniques targeting their removal are primarily addressed, including both data-driven approaches and using external recordings. Data-driven approaches, which are less specific in the assumed model and can simultaneously reduce multiple noise fluctuations, are mainly based on data decomposition techniques such as principal and independent component analysis. Importantly, the usefulness of strategies that benefit from the information available in the phase component of the signal, or in multiple signal echoes is also highlighted. The use of global signal regression for denoising is also addressed. Finally, practical recommendations regarding the optimization of the preprocessing pipeline for the purpose of denoising and future venues of research are indicated. Through the review, we summarize the importance of signal denoising as an essential step in the analysis pipeline of task-based and resting state fMRI studies.
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Affiliation(s)
| | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA
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48
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A Novel Remote Rehabilitation System with the Fusion of Noninvasive Wearable Device and Motion Sensing for Pulmonary Patients. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2017; 2017:5823740. [PMID: 28553367 PMCID: PMC5434462 DOI: 10.1155/2017/5823740] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Revised: 03/23/2017] [Accepted: 04/10/2017] [Indexed: 11/18/2022]
Abstract
Chronic obstructive pulmonary disease is a type of lung disease caused by chronically poor airflow that makes breathing difficult. As a chronic illness, it typically worsens over time. Therefore, pulmonary rehabilitation exercises and patient management for extensive periods of time are required. This paper presents a remote rehabilitation system for a multimodal sensors-based application for patients who have chronic breathing difficulties. The process involves the fusion of sensory data-captured motion data by stereo-camera and photoplethysmogram signal by a wearable PPG sensor-that are the input variables of a detection and evaluation framework. In addition, we incorporated a set of rehabilitation exercises specific for pulmonary patients into the system by fusing sensory data. Simultaneously, the system also features medical functions that accommodate the needs of medical professionals and those which ease the use of the application for patients, including exercises for tracking progress, patient performance, exercise assignments, and exercise guidance. Finally, the results indicate the accurate determination of pulmonary exercises from the fusion of sensory data. This remote rehabilitation system provides a comfortable and cost-effective option in the healthcare rehabilitation system.
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49
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Zhang X, Ding Q. Respiratory rate estimation from the photoplethysmogram via joint sparse signal reconstruction and spectra fusion. Biomed Signal Process Control 2017. [DOI: 10.1016/j.bspc.2017.02.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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50
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Zhang X, Kassem MAM, Zhou Y, Shabsigh M, Wang Q, Xu X. A Brief Review of Non-invasive Monitoring of Respiratory Condition for Extubated Patients with or at Risk for Obstructive Sleep Apnea after Surgery. Front Med (Lausanne) 2017; 4:26. [PMID: 28337439 PMCID: PMC5340767 DOI: 10.3389/fmed.2017.00026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2016] [Accepted: 02/20/2017] [Indexed: 11/21/2022] Open
Abstract
Obstructive sleep apnea (OSA) is one of the important risk factors contributing to postoperative airway complications. OSA alters the respiratory physiology and increases the sensitivity of muscle tone of the upper airway after surgery to residual anesthetic medication. In addition, the prevalence of OSA was reported to be much higher among surgical patients than the general population. Therefore, appropriate monitoring to detect early respiratory impairment in postoperative extubated patients with possible OSA is challenging. Based on the comprehensive clinical observation, several equipment have been used for monitoring the respiratory conditions of OSA patients after surgery, including the continuous pulse oximetry, capnography, photoplethysmography (PPG), and respiratory volume monitor (RVM). To date, there has been no consensus on the most suitable device as a recommended standard of care. In this review, we describe the advantages and disadvantages of some possible monitoring strategies under certain clinical conditions. According to the literature, the continuous pulse oximetry, with its high sensitivity, is still the most widely used device. It is also cost-effective and convenient to use but has low specificity and does not reflect ventilation. Capnography is the most widely used device for detection of hypoventilation, but it may not provide reliable data for extubated patients. Even normal capnography cannot exclude the existence of hypoxia. PPG shows the state of both ventilation and oxygenation, but its sensitivity needs further improvement. RVM provides real-time detection of hypoventilation, quantitative precise demonstration of respiratory rate, tidal volume, and MV for extubated patients, but no reflection of oxygenation. Altogether, the sole use of any of these devices is not ideal for monitoring of extubated patients with or at risk for OSA after surgery. However, we expect that the combined use of continuous pulse oximetry and RVM may be promising for these patients due to their complementary function, which need further study.
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Affiliation(s)
- Xuezheng Zhang
- Anesthesiology Department, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China; Anesthesiology Department, Wexner Medical Center of Ohio State University, Columbus, OH, USA
| | | | - Ying Zhou
- Pulmonary Medicine, The First Affiliated Hospital of Wenzhou Medical University , Wenzhou , China
| | - Muhammad Shabsigh
- Anesthesiology Department, Wexner Medical Center of Ohio State University , Columbus, OH , USA
| | - Quanguang Wang
- Anesthesiology Department, The First Affiliated Hospital of Wenzhou Medical University , Wenzhou , China
| | - Xuzhong Xu
- Anesthesiology Department, The First Affiliated Hospital of Wenzhou Medical University , Wenzhou , China
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