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Cay G, Solanki D, Al Rumon MA, Ravichandran V, Fapohunda KO, Mankodiya K. SolunumWear: A smart textile system for dynamic respiration monitoring across various postures. iScience 2024; 27:110223. [PMID: 39040071 PMCID: PMC11261107 DOI: 10.1016/j.isci.2024.110223] [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: 02/22/2024] [Revised: 05/27/2024] [Accepted: 06/06/2024] [Indexed: 07/24/2024] Open
Abstract
We introduce SolunumWear, a multi-sensory e-textile system designed for respiration in daily life settings, addressing the gap in continuous, real-world respiration event monitoring. Leveraging a textile pressure sensor belt to capture chest movements and a wireless data acquisition system, SolunumWear offers a promising solution for both medical and wellness applications. The system's efficacy was evaluated through a human study involving 10 healthy adults (six female and four male) across various breathing rates and postures, demonstrating a strong correlation (R value = 0.836) with the gold-standard system. The study highlights the system's computational and communication efficiencies, with latencies of approximately 4.84 s and 2.13 ms, respectively. These findings highlight the efficacy of SolunumWear as a wireless, wearable technology for respiration monitoring in daily settings. This research contributes to the expanding body of knowledge on smart textile-based health monitoring technologies, demonstrating its potential to provide reliable respiratory data in real-world environments.
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Affiliation(s)
- Gozde Cay
- Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA
| | - Dhaval Solanki
- Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA
| | - Md Abdullah Al Rumon
- Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA
| | - Vignesh Ravichandran
- Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA
| | | | - Kunal Mankodiya
- Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA
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Svoboda L, Sperrhake J, Nisser M, Taphorn L, Proquitté H. Contactless assessment of heart rate in neonates within a clinical environment using imaging photoplethysmography. Front Pediatr 2024; 12:1383120. [PMID: 38681773 PMCID: PMC11045999 DOI: 10.3389/fped.2024.1383120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 04/01/2024] [Indexed: 05/01/2024] Open
Abstract
Introduction In neonatology, the accurate determination of vital parameters plays a pivotal role in monitoring critically ill newborns and premature infants, as well as aiding in disease diagnosis. In response to the limitations associated with contact-based measurement methods, substantial efforts have been directed toward developing contactless measurement techniques, particularly over the past decade. Methods Building upon the insights gained from our pilot study, we realized a new investigation to assess the precision of our imaging photoplethysmography-based system within a clinical environment of the neonatal intermediate care unit. We conducted measurements in 20 preterm infants or newborns requiring therapeutic interventions. As a point of reference, we employed a conventional pulse oximeter. To analytically predict measurement artifacts, we analyzed the potential influence of confounding factors, such as motion artifacts, illumination fluctuations (under- and overexposure), and loss of region of interest prior to heart rate evaluation. This reduced the amount of data we evaluated for heart rate to 56.1% of its original volume. Results In artifact-free time segments, the mean difference between the pulse oximetry and the imaging photoplethysmography-based system for 1 s sampling intervals resulted in -0.2 bpm (95% CI -0.8 to 0.4, LOA ± 12.2). For the clinical standard of 8 s averaging time, the mean difference resulted in -0.09 bpm (95% CI -0.7 to 0.6, LOA ± 10.1). These results match the medical standards. Discussion While further research is needed to increase the range of measurable vital parameters and more diverse patient collectives need to be considered in the future, we could demonstrate very high accuracy for non-contact heart rate measurement in newborn infants in the clinical setting, provided artifacts are excluded. In particular, performing a priori signal assessment helps make clinical measurements safer by identifying unreliable readings.
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Affiliation(s)
- Libor Svoboda
- Department of Pediatric and Adolescent Medicine, University Hospital Jena, Jena, Germany
| | | | | | - Luca Taphorn
- Department of Pediatric and Adolescent Medicine, University Hospital Jena, Jena, Germany
| | - Hans Proquitté
- Department of Pediatric and Adolescent Medicine, University Hospital Jena, Jena, Germany
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3
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Huang B, Hu S, Liu Z, Lin CL, Su J, Zhao C, Wang L, Wang W. Challenges and prospects of visual contactless physiological monitoring in clinical study. NPJ Digit Med 2023; 6:231. [PMID: 38097771 PMCID: PMC10721846 DOI: 10.1038/s41746-023-00973-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Accepted: 11/21/2023] [Indexed: 12/17/2023] Open
Abstract
The monitoring of physiological parameters is a crucial topic in promoting human health and an indispensable approach for assessing physiological status and diagnosing diseases. Particularly, it holds significant value for patients who require long-term monitoring or with underlying cardiovascular disease. To this end, Visual Contactless Physiological Monitoring (VCPM) is capable of using videos recorded by a consumer camera to monitor blood volume pulse (BVP) signal, heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and blood pressure (BP). Recently, deep learning-based pipelines have attracted numerous scholars and achieved unprecedented development. Although VCPM is still an emerging digital medical technology and presents many challenges and opportunities, it has the potential to revolutionize clinical medicine, digital health, telemedicine as well as other areas. The VCPM technology presents a viable solution that can be integrated into these systems for measuring vital parameters during video consultation, owing to its merits of contactless measurement, cost-effectiveness, user-friendly passive monitoring and the sole requirement of an off-the-shelf camera. In fact, the studies of VCPM technologies have been rocketing recently, particularly AI-based approaches, but few are employed in clinical settings. Here we provide a comprehensive overview of the applications, challenges, and prospects of VCPM from the perspective of clinical settings and AI technologies for the first time. The thorough exploration and analysis of clinical scenarios will provide profound guidance for the research and development of VCPM technologies in clinical settings.
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Affiliation(s)
- Bin Huang
- AI Research Center, Hangzhou Innovation Institute, Beihang University, 99 Juhang Rd., Binjiang Dist., Hangzhou, Zhejiang, China.
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China.
| | - Shen Hu
- Department of Obstetrics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Department of Epidemiology, The Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zimeng Liu
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Chun-Liang Lin
- College of Electrical Engineering and Computer Science, National Chung Hsing University, 145 Xingda Rd., South Dist., Taichung, Taiwan.
| | - Junfeng Su
- Department of General Intensive Care Unit, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Early Warning and Intervention of Multiple Organ Failure, China National Ministry of Education, Hangzhou, Zhejiang, China
| | - Changchen Zhao
- AI Research Center, Hangzhou Innovation Institute, Beihang University, 99 Juhang Rd., Binjiang Dist., Hangzhou, Zhejiang, China
| | - Li Wang
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenjin Wang
- Department of Biomedical Engineering, Southern University of Science and Technology, 1088 Xueyuan Ave, Nanshan Dist., Shenzhen, Guangdong, China.
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Bautista M, Cave D, Downey C, Bentham JR, Jayne D. Clinical applications of contactless photoplethysmography for vital signs monitoring in pediatrics: A systematic review and meta-analysis. J Clin Transl Sci 2023; 7:e144. [PMID: 37396820 PMCID: PMC10310860 DOI: 10.1017/cts.2023.557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 05/11/2023] [Accepted: 05/11/2023] [Indexed: 07/04/2023] Open
Abstract
Background Contactless photoplethysmography (PPG) potentially affords the ability to obtain vital signs in pediatric populations without disturbing the child. Most validity studies have been conducted in laboratory settings or with healthy adult volunteers. This review aims to evaluate the current literature on contactless vital signs monitoring in pediatric populations and within a clinical setting. Methods OVID, Webofscience, Cochrane library, and clinicaltrials.org were systematically searched by two authors for research studies which used contactless PPG to assess vital signs in children and within a clinical setting. Results Fifteen studies were included with a total of 170 individuals. Ten studies were included in a meta-analysis for neonatal heart rate (HR), which demonstrated a pooled mean bias of -0.25 (95% limits of agreement (LOA), -1.83 to 1.32). Four studies assessed respiratory rate (RR) in neonates, and meta-analysis demonstrated a pooled mean bias of 0.65 (95% LOA, -3.08 to 4.37). All studies were small, and there were variations in the methods used and risk of bias. Conclusion Contactless PPG is a promising tool for vital signs monitoring in children and accurately measures neonatal HR and RR. Further research is needed to assess children of different age groups, the effects of skin type variation, and the addition of other vital signs.
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Affiliation(s)
- Melissa Bautista
- University of Leeds, Leeds, West Yorkshire, UK
- General Surgery Department, St James’s University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, West Yorkshire, UK
| | - Daniel Cave
- University of Leeds, Leeds, West Yorkshire, UK
- Leeds Children’s Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, West Yorkshire, UK
| | - Candice Downey
- University of Leeds, Leeds, West Yorkshire, UK
- General Surgery Department, St James’s University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, West Yorkshire, UK
| | - James R. Bentham
- University of Leeds, Leeds, West Yorkshire, UK
- Leeds Children’s Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, West Yorkshire, UK
| | - David Jayne
- University of Leeds, Leeds, West Yorkshire, UK
- General Surgery Department, St James’s University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, West Yorkshire, UK
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5
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Han Q, Hao D, Yang L, Yang Y, Li G. Non-Contact Monitoring of Fetal Movement Using Abdominal Video Recording. SENSORS (BASEL, SWITZERLAND) 2023; 23:4753. [PMID: 37430667 DOI: 10.3390/s23104753] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 05/09/2023] [Accepted: 05/10/2023] [Indexed: 07/12/2023]
Abstract
Fetal movement (FM) is an important indicator of fetal health. However, the current methods of FM detection are unsuitable for ambulatory or long-term observation. This paper proposes a non-contact method for monitoring FM. We recorded abdominal videos from pregnant women and then detected the maternal abdominal region within each frame. FM signals were acquired by optical flow color-coding, ensemble empirical mode decomposition, energy ratio, and correlation analysis. FM spikes, indicating the occurrence of FMs, were recognized using the differential threshold method. FM parameters including number, interval, duration, and percentage were calculated, and good agreement was found with the manual labeling performed by the professionals, achieving true detection rate, positive predictive value, sensitivity, accuracy, and F1_score of 95.75%, 95.26%, 95.75%, 91.40%, and 95.50%, respectively. The changes in FM parameters with gestational week were consistent with pregnancy progress. In general, this study provides a novel contactless FM monitoring technology for use at home.
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Affiliation(s)
- Qiao Han
- Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
| | - Dongmei Hao
- Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
| | - Lin Yang
- Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
| | - Yimin Yang
- Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
| | - Guangfei Li
- Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
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6
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Walker SB, Badke CM, Carroll MS, Honegger KS, Fawcett A, Weese-Mayer DE, Sanchez-Pinto LN. Novel approaches to capturing and using continuous cardiorespiratory physiological data in hospitalized children. Pediatr Res 2023; 93:396-404. [PMID: 36329224 DOI: 10.1038/s41390-022-02359-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 08/16/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
Abstract
Continuous cardiorespiratory physiological monitoring is a cornerstone of care in hospitalized children. The data generated by monitoring devices coupled with machine learning could transform the way we provide care. This scoping review summarizes existing evidence on novel approaches to continuous cardiorespiratory monitoring in hospitalized children. We aimed to identify opportunities for the development of monitoring technology and the use of machine learning to analyze continuous physiological data to improve the outcomes of hospitalized children. We included original research articles published on or after January 1, 2001, involving novel approaches to collect and use continuous cardiorespiratory physiological data in hospitalized children. OVID Medline, PubMed, and Embase databases were searched. We screened 2909 articles and performed full-text extraction of 105 articles. We identified 58 articles describing novel devices or approaches, which were generally small and single-center. In addition, we identified 47 articles that described the use of continuous physiological data in prediction models, but only 7 integrated multidimensional data (e.g., demographics, laboratory results). We identified three areas for development: (1) further validation of promising novel devices; (2) more studies of models integrating multidimensional data with continuous cardiorespiratory data; and (3) further dissemination, implementation, and validation of prediction models using continuous cardiorespiratory data. IMPACT: We performed a comprehensive scoping review of novel approaches to capture and use continuous cardiorespiratory physiological data for monitoring, diagnosis, providing care, and predicting events in hospitalized infants and children, from novel devices to machine learning-based prediction models. We identified three key areas for future development: (1) further validation of promising novel devices; (2) more studies of models integrating multidimensional data with continuous cardiorespiratory data; and (3) further dissemination, implementation, and validation of prediction models using cardiorespiratory data.
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Affiliation(s)
- Sarah B Walker
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. .,Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
| | - Colleen M Badke
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.,Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Michael S Carroll
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.,Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Kyle S Honegger
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.,Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Andrea Fawcett
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.,Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Debra E Weese-Mayer
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.,Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - L Nelson Sanchez-Pinto
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.,Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
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7
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Grech N, Agius JC, Sciberras S, Micallef N, Camilleri K, Falzon O. Non-contact Vital Signs Monitoring in Paediatric Anaesthesia - Current Challenges and Future Direction. ACTA MEDICA (HRADEC KRALOVE) 2023; 66:39-46. [PMID: 37930092 DOI: 10.14712/18059694.2023.14] [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] [Indexed: 11/07/2023]
Abstract
Non-contact vital sign monitoring is an area of increasing interest in the clinical scenario since it offers advantages over traditional monitoring using leads and wires. These advantages include reduction in transmission of infection and more freedom of movement. Yet there is a paucity of studies available in the clinical setting particularly in paediatric anaesthesia. This scoping review aims to investigate why contactless monitoring, specifically with red-green-blue cameras, is not implemented in mainstream practise. The challenges, drawbacks and limitations of non-contact vital sign monitoring, will be outlined, together with future direction on how it can potentially be implemented in the setting of paediatric anaesthesia, and in the critical care scenario.
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Affiliation(s)
- Nicole Grech
- Department of Anaesthesia and Intensive Care Medicine, Mater Dei Hospital, Malta.
| | - Jean Calleja Agius
- Department of Anatomy, Faculty of Medicine and Surgery, University of Malta
| | - Stephen Sciberras
- Department of Anaesthesia and Intensive Care Medicine, Mater Dei Hospital, Malta
| | - Neil Micallef
- Centre for Biomedical Cybernetics, Faculty of Engineering, University of Malta
| | - Kenneth Camilleri
- Centre for Biomedical Cybernetics, Faculty of Engineering, University of Malta
| | - Owen Falzon
- Centre for Biomedical Cybernetics, Faculty of Engineering, University of Malta
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8
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Maurya L, Zwiggelaar R, Chawla D, Mahapatra P. Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates. J Clin Monit Comput 2022; 37:815-828. [PMID: 36463541 PMCID: PMC10175339 DOI: 10.1007/s10877-022-00945-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 11/05/2022] [Indexed: 12/07/2022]
Abstract
AbstractRespiratory rate (RR) monitoring is essential in neonatal intensive care units. Despite its importance, RR is still monitored intermittently by manual counting instead of continuous monitoring due to the risk of skin damage with prolonged use of contact electrodes in preterm neonates and false signals due to displacement of electrodes. Thermal imaging has recently gained significance as a non-contact method for RR detection because of its many advantages. However, due to the lack of information in thermal images, the selection and tracking of the region of interest (ROI) in thermal images for neonates are challenging. This paper presents the integration of visible (RGB) and thermal (T) image sequences for the selection and tracking of ROI for breathing rate extraction. The deep-learning based tracking-by-detection approach is employed to detect the ROI in the RGB images, and it is mapped to the thermal images using the RGB-T image registration. The mapped ROI in thermal spectrum sequences gives the respiratory rate. The study was conducted first on healthy adults in different modes, including steady, motion, talking, and variable respiratory order. Subsequently, the method is tested on neonates in a clinical settings. The findings have been validated with a contact-based reference method.The average absolute error between the proposed and belt-based contact method in healthy adults reached 0.1 bpm and for more challenging conditions was approximately 1.5 bpm and 1.8 bpm, respectively. In the case of neonates, the average error is 1.5 bpm, which are promising results. The Bland–Altman analysis showed a good agreement of estimated RR with the reference method RR and this pilot study provided the evidence of using the proposed approach as a contactless method for the respiratory rate detection of neonates in clinical settings.
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Affiliation(s)
- Lalit Maurya
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
- CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Sector 30-C, Chandigarh, 160030, India.
- Department of Computer Science, Aberystwyth University, Ceredigion, SY23 3DB, UK.
| | - Reyer Zwiggelaar
- Department of Computer Science, Aberystwyth University, Ceredigion, SY23 3DB, UK
| | - Deepak Chawla
- Department of Neonatology, Government Medical College & Hospital (GMCH), Chandigarh, 160030, India
| | - Prasant Mahapatra
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
- CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Sector 30-C, Chandigarh, 160030, India
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9
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Selvaraju V, Spicher N, Wang J, Ganapathy N, Warnecke JM, Leonhardt S, Swaminathan R, Deserno TM. Continuous Monitoring of Vital Signs Using Cameras: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:4097. [PMID: 35684717 PMCID: PMC9185528 DOI: 10.3390/s22114097] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 05/18/2022] [Accepted: 05/18/2022] [Indexed: 02/04/2023]
Abstract
In recent years, noncontact measurements of vital signs using cameras received a great amount of interest. However, some questions are unanswered: (i) Which vital sign is monitored using what type of camera? (ii) What is the performance and which factors affect it? (iii) Which health issues are addressed by camera-based techniques? Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement, we conduct a systematic review of continuous camera-based vital sign monitoring using Scopus, PubMed, and the Association for Computing Machinery (ACM) databases. We consider articles that were published between January 2018 and April 2021 in the English language. We include five vital signs: heart rate (HR), respiratory rate (RR), blood pressure (BP), body skin temperature (BST), and oxygen saturation (SpO2). In total, we retrieve 905 articles and screened them regarding title, abstract, and full text. One hundred and four articles remained: 60, 20, 6, 2, and 1 of the articles focus on HR, RR, BP, BST, and SpO2, respectively, and 15 on multiple vital signs. HR and RR can be measured using red, green, and blue (RGB) and near-infrared (NIR) as well as far-infrared (FIR) cameras. So far, BP and SpO2 are monitored with RGB cameras only, whereas BST is derived from FIR cameras only. Under ideal conditions, the root mean squared error is around 2.60 bpm, 2.22 cpm, 6.91 mm Hg, 4.88 mm Hg, and 0.86 °C for HR, RR, systolic BP, diastolic BP, and BST, respectively. The estimated error for SpO2 is less than 1%, but it increases with movements of the subject and the camera-subject distance. Camera-based remote monitoring mainly explores intensive care, post-anaesthesia care, and sleep monitoring, but also explores special diseases such as heart failure. The monitored targets are newborn and pediatric patients, geriatric patients, athletes (e.g., exercising, cycling), and vehicle drivers. Camera-based techniques monitor HR, RR, and BST in static conditions within acceptable ranges for certain applications. The research gaps are large and heterogeneous populations, real-time scenarios, moving subjects, and accuracy of BP and SpO2 monitoring.
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Affiliation(s)
- Vinothini Selvaraju
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, D-38106 Braunschweig, Germany; (V.S.); (N.S.); (J.W.); (N.G.); (J.M.W.)
- Non-Invasive Imaging and Diagnostic Laboratory, Biomedical Engineering, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai 600036, India;
| | - Nicolai Spicher
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, D-38106 Braunschweig, Germany; (V.S.); (N.S.); (J.W.); (N.G.); (J.M.W.)
| | - Ju Wang
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, D-38106 Braunschweig, Germany; (V.S.); (N.S.); (J.W.); (N.G.); (J.M.W.)
| | - Nagarajan Ganapathy
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, D-38106 Braunschweig, Germany; (V.S.); (N.S.); (J.W.); (N.G.); (J.M.W.)
| | - Joana M. Warnecke
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, D-38106 Braunschweig, Germany; (V.S.); (N.S.); (J.W.); (N.G.); (J.M.W.)
| | - Steffen Leonhardt
- Chair for Medical Information Technology, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, D-52074 Aachen, Germany;
| | - Ramakrishnan Swaminathan
- Non-Invasive Imaging and Diagnostic Laboratory, Biomedical Engineering, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai 600036, India;
| | - Thomas M. Deserno
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, D-38106 Braunschweig, Germany; (V.S.); (N.S.); (J.W.); (N.G.); (J.M.W.)
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10
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Khanam FTZ, Al-Naji A, Perera AG, Gibson K, Chahl J. Non-contact automatic vital signs monitoring of neonates in NICU using video camera imaging. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING: IMAGING & VISUALIZATION 2022. [DOI: 10.1080/21681163.2022.2069598] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
| | - Ali Al-Naji
- UniSA STEM, University of South Australia, Adelaide, Australia
- Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq
| | | | - Kim Gibson
- Clinical and Health Sciences, Rosemary Bryant AO Research Centre, University of South Australia, Adelaide, Australia
| | - Javaan Chahl
- UniSA STEM, University of South Australia, Adelaide, Australia
- Joint and Operations Analysis Division, Defence Science and Technology Group, Melbourne, Australia
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11
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Contactless radar-based breathing monitoring of premature infants in the neonatal intensive care unit. Sci Rep 2022; 12:5150. [PMID: 35338172 PMCID: PMC8956695 DOI: 10.1038/s41598-022-08836-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 03/03/2022] [Indexed: 01/18/2023] Open
Abstract
Vital sign monitoring systems are essential in the care of hospitalized neonates. Due to the immaturity of their organs and immune system, premature infants require continuous monitoring of their vital parameters and sensors need to be directly attached to their fragile skin. Besides mobility restrictions and stress, these sensors often cause skin irritation and may lead to pressure necrosis. In this work, we show that a contactless radar-based approach is viable for breathing monitoring in the Neonatal intensive care unit (NICU). For the first time, different scenarios common to the NICU daily routine are investigated, and the challenges of monitoring in a real clinical setup are addressed through different contributions in the signal processing framework. Rather than just discarding measurements under strong interference, we present a novel random body movement mitigation technique based on the time-frequency decomposition of the recovered signal. In addition, we propose a simple and accurate frequency estimator which explores the harmonic structure of the breathing signal. As a result, the proposed radar-based solution is able to provide reliable breathing frequency estimation, which is close to the reference cabled device values most of the time. Our findings shed light on the strengths and limitations of this technology and lay the foundation for future studies toward a completely contactless solution for vital signs monitoring.
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12
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Svoboda L, Sperrhake J, Nisser M, Zhang C, Notni G, Proquitté H. Contactless heart rate measurement in newborn infants using a multimodal 3D camera system. Front Pediatr 2022; 10:897961. [PMID: 36016880 PMCID: PMC9395962 DOI: 10.3389/fped.2022.897961] [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: 03/16/2022] [Accepted: 07/20/2022] [Indexed: 11/13/2022] Open
Abstract
Newborns and preterm infants require accurate and continuous monitoring of their vital parameters. Contact-based methods of monitoring have several disadvantages, thus, contactless systems have increasingly attracted the neonatal communities' attention. Camera-based photoplethysmography is an emerging method of contactless heart rate monitoring. We conducted a pilot study in 42 healthy newborn and near-term preterm infants for assessing the feasibility and accuracy of a multimodal 3D camera system on heart rates (HR) in beats per min (bpm) compared to conventional pulse oximetry. Simultaneously, we compared the accuracy of 2D and 3D vision on HR measurements. The mean difference in HR between pulse oximetry and 2D-technique added up to + 3.0 bpm [CI-3.7 - 9.7; p = 0.359, limits of agreement (LOA) ± 36.6]. In contrast, 3D-technique represented a mean difference in HR of + 8.6 bpm (CI 2.0-14.9; p = 0.010, LOA ± 44.7) compared to pulse oximetry HR. Both, intra- and interindividual variance of patient characteristics could be eliminated as a source for the results and the measuring accuracy achieved. Additionally, we proved the feasibility of this emerging method. Camera-based photoplethysmography seems to be a promising approach for HR measurement of newborns with adequate precision; however, further research is warranted.
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Affiliation(s)
- Libor Svoboda
- Department of Pediatric and Adolescent Medicine, University Hospital Jena, Jena, Germany
| | - Jan Sperrhake
- Abbe Center of Photonics, Institute of Applied Physics, Friedrich Schiller University Jena, Jena, Germany
| | - Maria Nisser
- Department of Pediatric and Adolescent Medicine, University Hospital Jena, Jena, Germany
| | - Chen Zhang
- Group for Quality Assurance and Industrial Image Processing, Ilmenau University of Technology, Ilmenau, Germany
| | - Gunter Notni
- Group for Quality Assurance and Industrial Image Processing, Ilmenau University of Technology, Ilmenau, Germany.,Fraunhofer Institute for Applied Optics and Precision Engineering IOF, Jena, Germany
| | - Hans Proquitté
- Department of Pediatric and Adolescent Medicine, University Hospital Jena, Jena, Germany
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13
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Cubík J, Kepak S, Wiedermannova H, Vrtkova A, Burckova H, Zarubova P, Fernandez C, Pavlicek J, Jargus J, Vasinek V. Measuring respiratory and heart rate using a fiber optic interferometer: A pilot study in a neonate model. Front Pediatr 2022; 10:957835. [PMID: 36545663 PMCID: PMC9760927 DOI: 10.3389/fped.2022.957835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 11/07/2022] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION The study aim was to test the safety and efficacy of a pad with optic fibers developed for monitoring newborn respiratory rate (RR) and heart rate (HR). METHODS Thirty New Zealand White rabbits were included, divided by weight into three groups. RR and HR were measured using two methods for each rabbit: ECG electrodes as the reference method and a newly developed pad with an experimental fiber optic system (EFOS) as the experimental method. RESULTS Analysis was performed on data for 29 rabbits (10 female, 34%; 19 male, 66%). EFOS performed better at measuring RR compared with HR. RR values did not differ significantly between the methods for the whole group (p = 0.151) or within each sex (female: p > 0.999; male: p = 0.075). Values for HR, however, did differ between methods for the whole group of animals (p < 0.001) and also within groups by sex (female: p < 0.001; male: p = 0.006). CONCLUSION The results of this preclinical study demonstrate the potential of this non-invasive method using a fiber optic pad to measure HR and RR.
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Affiliation(s)
- Jakub Cubík
- Department of Telecommunications, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic
| | - Stanislav Kepak
- Department of Telecommunications, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic
| | - Hana Wiedermannova
- Department of Neonatology, University Hospital Ostrava, Ostrava, Czech Republic.,Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Adela Vrtkova
- Department of Applied Mathematics, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic.,Department of the Deputy Director for Science, Research, and Education, University Hospital Ostrava, Ostrava, Czech Republic
| | - Hana Burckova
- Department of Neonatology, University Hospital Ostrava, Ostrava, Czech Republic
| | - Pavla Zarubova
- Department of Neonatology, University Hospital Ostrava, Ostrava, Czech Republic
| | - Carlos Fernandez
- Centre for Cardiovascular Research and Development, American Heart Poland Inc, Kostkowice, Poland
| | - Jan Pavlicek
- Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic.,Department of Pediatrics and Prenatal Cardiology, University Hospital Ostrava, Ostrava, Czech Republic.,Biomedical Research Center, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic
| | - Jan Jargus
- Department of Telecommunications, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic
| | - Vladimir Vasinek
- Department of Telecommunications, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic
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14
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Tohma A, Nishikawa M, Hashimoto T, Yamazaki Y, Sun G. Evaluation of Remote Photoplethysmography Measurement Conditions toward Telemedicine Applications. SENSORS 2021; 21:s21248357. [PMID: 34960451 PMCID: PMC8704576 DOI: 10.3390/s21248357] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 12/02/2021] [Accepted: 12/10/2021] [Indexed: 11/16/2022]
Abstract
Camera-based remote photoplethysmography (rPPG) is a low-cost and casual non-contact heart rate measurement method suitable for telemedicine. Several factors affect the accuracy of measuring the heart rate and heart rate variability (HRV) using rPPG despite HRV being an important indicator for healthcare monitoring. This study aimed to investigate the appropriate setup for precise HRV measurements using rPPG while considering the effects of possible factors including illumination, direction of the light, frame rate of the camera, and body motion. In the lighting conditions experiment, the smallest mean absolute R–R interval (RRI) error was obtained when light greater than 500 lux was cast from the front (among the following conditions—illuminance: 100, 300, 500, and 700 lux; directions: front, top, and front and top). In addition, the RRI and HRV were measured with sufficient accuracy at frame rates above 30 fps. The accuracy of the HRV measurement was greatly reduced when the body motion was not constrained; thus, it is necessary to limit the body motion, especially the head motion, in an actual telemedicine situation. The results of this study can act as guidelines for setting up the shooting environment and camera settings for rPPG use in telemedicine.
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Affiliation(s)
- Akito Tohma
- Department of Mechanical Engineering, Tokyo University of Science, Tokyo 162-8601, Japan;
| | - Maho Nishikawa
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo 182-0033, Japan; (M.N.); (G.S.)
| | - Takuya Hashimoto
- Department of Mechanical Engineering, Tokyo University of Science, Tokyo 162-8601, Japan;
- Correspondence:
| | - Yoichi Yamazaki
- Department of Home Electronics, Kanagawa Institute of Technology, Kanagawa 243-0292, Japan;
| | - Guanghao Sun
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo 182-0033, Japan; (M.N.); (G.S.)
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15
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Wang W, Vosters L, den Brinker AC. Modified Camera Setups for Day-and-Night Pulse-rate Monitoring. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:1744-1748. [PMID: 34891624 DOI: 10.1109/embc46164.2021.9630497] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Camera systems have been studied as a means for ubiquitous remote photoplethysmography. It was first considered for daytime applications using ambient light. However, main applications for continuous monitoring are in dark or low-light conditions (e.g. sleep monitoring) and, more recently, suitable light sources and simple camera adaptations have been considered for infrared-based solutions. This paper explores suitable camera configurations for pulse-rate monitoring during both day and night (24/7). Various configurations differing in the recorded spectral range are defined, i.e. straight-forward adaptations of a standard RGB camera by choosing proper optical filters. These systems have been studied in a benchmark involving day and night monitoring with various degrees of motion disturbances. The results indicate that, for the 24/7 monitoring, it is best to deploy the full spectral band of an RGB camera, and this can be done without compromising the monitoring performance at night.
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16
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Cheng CH, Wong KL, Chin JW, Chan TT, So RHY. Deep Learning Methods for Remote Heart Rate Measurement: A Review and Future Research Agenda. SENSORS (BASEL, SWITZERLAND) 2021; 21:6296. [PMID: 34577503 PMCID: PMC8473186 DOI: 10.3390/s21186296] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/13/2021] [Accepted: 09/16/2021] [Indexed: 01/05/2023]
Abstract
Heart rate (HR) is one of the essential vital signs used to indicate the physiological health of the human body. While traditional HR monitors usually require contact with skin, remote photoplethysmography (rPPG) enables contactless HR monitoring by capturing subtle light changes of skin through a video camera. Given the vast potential of this technology in the future of digital healthcare, remote monitoring of physiological signals has gained significant traction in the research community. In recent years, the success of deep learning (DL) methods for image and video analysis has inspired researchers to apply such techniques to various parts of the remote physiological signal extraction pipeline. In this paper, we discuss several recent advances of DL-based methods specifically for remote HR measurement, categorizing them based on model architecture and application. We further detail relevant real-world applications of remote physiological monitoring and summarize various common resources used to accelerate related research progress. Lastly, we analyze the implications of research findings and discuss research gaps to guide future explorations.
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Affiliation(s)
- Chun-Hong Cheng
- Department of Computer Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China;
- PanopticAI, Hong Kong Science and Technology Parks, New Territories, Hong Kong, China; (J.-W.C.); (T.-T.C.); (R.H.Y.S.)
| | - Kwan-Long Wong
- PanopticAI, Hong Kong Science and Technology Parks, New Territories, Hong Kong, China; (J.-W.C.); (T.-T.C.); (R.H.Y.S.)
- Department of Bioengineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Jing-Wei Chin
- PanopticAI, Hong Kong Science and Technology Parks, New Territories, Hong Kong, China; (J.-W.C.); (T.-T.C.); (R.H.Y.S.)
- Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Tsz-Tai Chan
- PanopticAI, Hong Kong Science and Technology Parks, New Territories, Hong Kong, China; (J.-W.C.); (T.-T.C.); (R.H.Y.S.)
- Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Richard H. Y. So
- PanopticAI, Hong Kong Science and Technology Parks, New Territories, Hong Kong, China; (J.-W.C.); (T.-T.C.); (R.H.Y.S.)
- Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
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17
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Khanam FTZ, Perera AG, Al-Naji A, Gibson K, Chahl J. Non-Contact Automatic Vital Signs Monitoring of Infants in a Neonatal Intensive Care Unit Based on Neural Networks. J Imaging 2021; 7:122. [PMID: 34460758 PMCID: PMC8404938 DOI: 10.3390/jimaging7080122] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/18/2021] [Accepted: 07/19/2021] [Indexed: 12/28/2022] Open
Abstract
Infants with fragile skin are patients who would benefit from non-contact vital sign monitoring due to the avoidance of potentially harmful adhesive electrodes and cables. Non-contact vital signs monitoring has been studied in clinical settings in recent decades. However, studies on infants in the Neonatal Intensive Care Unit (NICU) are still limited. Therefore, we conducted a single-center study to remotely monitor the heart rate (HR) and respiratory rate (RR) of seven infants in NICU using a digital camera. The region of interest (ROI) was automatically selected using a convolutional neural network and signal decomposition was used to minimize the noise artefacts. The experimental results have been validated with the reference data obtained from an ECG monitor. They showed a strong correlation using the Pearson correlation coefficients (PCC) of 0.9864 and 0.9453 for HR and RR, respectively, and a lower error rate with RMSE 2.23 beats/min and 2.69 breaths/min between measured data and reference data. A Bland-Altman analysis of the data also presented a close correlation between measured data and reference data for both HR and RR. Therefore, this technique may be applicable in clinical environments as an economical, non-contact, and easily deployable monitoring system, and it also represents a potential application in home health monitoring.
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Affiliation(s)
- Fatema-Tuz-Zohra Khanam
- UniSA STEM, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia; (A.G.P.); (A.A.-N.); (J.C.)
| | - Asanka G. Perera
- UniSA STEM, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia; (A.G.P.); (A.A.-N.); (J.C.)
| | - Ali Al-Naji
- UniSA STEM, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia; (A.G.P.); (A.A.-N.); (J.C.)
- Electrical Engineering Technical College, Middle Technical University, Baghdad 10022, Iraq
| | - Kim Gibson
- Clinical and Health Sciences, City East Campus, University of South Australia, North Terrace, Adelaide, SA 5000, Australia;
| | - Javaan Chahl
- UniSA STEM, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia; (A.G.P.); (A.A.-N.); (J.C.)
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18
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Kodama Y, Okamoto J, Imai K, Asano H, Uchiyama A, Masamune K, Wada M, Muragaki Y. Video-based neonatal state assessment method for timing of procedures. Pediatr Int 2021; 63:685-692. [PMID: 33034092 DOI: 10.1111/ped.14501] [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: 06/08/2020] [Revised: 09/09/2020] [Accepted: 09/28/2020] [Indexed: 11/28/2022]
Abstract
BACKGROUND Procedures should be performed when an infant is most receptive to disruptions in order to reduce the stress on the infant. However, frequent direct observations place a heavy burden on medical staff. There is therefore a need for a method for quantitatively and automatically evaluating the neonatal state. METHODS Ten infants in our hospital were enrolled in this study. The states of the infants were assessed by medical staff using the Brazelton Neonatal Behavioral Assessment Scale and were recorded on video at the same time. The recorded states were reclassified as activity levels, a new state classification method that includes middle activity, which is the appropriate time for a procedure. Using image analysis, motions of the infant were quantified as two indices: activity and pause time. Activity and pause time were compared for each activity level. The cutoff values of the indices were calculated, and the sensitivity and specificity of the middle activity were calculated. RESULTS There was a significant difference between all groups of activity level (P < 0.01). The maximum sensitivity and specificity of middle activity were 71.7% and 51.2%, respectively. CONCLUSIONS The neonatal state of infants can be quantitatively and automatically evaluated using video cameras, and the activity level can be used to determine an appropriate time for procedures in infants. This will reduce the burden on medical staff and lead to less stressful procedures for infants.
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Affiliation(s)
- Yu Kodama
- Institute of Advanced Biomedical Engineering & Science, Tokyo Women's Medical University, Tokyo, Japan.,Human Resources and General Affairs Department, Atom Medical Corporation, Tokyo, Japan
| | - Jun Okamoto
- Institute of Advanced Biomedical Engineering & Science, Tokyo Women's Medical University, Tokyo, Japan
| | - Ken Imai
- Department of Neonatology, Tokyo Women's Medical University, Tokyo, Japan
| | - Hidetsugu Asano
- Institute of Advanced Biomedical Engineering & Science, Tokyo Women's Medical University, Tokyo, Japan.,Technical Department, Atom Medical Corporation, Tokyo, Japan
| | - Atsushi Uchiyama
- Department of Neonatology, Tokyo Women's Medical University, Tokyo, Japan.,Department of Pediatrics, Tokai University School of Medicine, Kanagawa, Japan
| | - Ken Masamune
- Institute of Advanced Biomedical Engineering & Science, Tokyo Women's Medical University, Tokyo, Japan
| | - Masaki Wada
- Department of Neonatology, Tokyo Women's Medical University, Tokyo, Japan
| | - Yoshihiro Muragaki
- Institute of Advanced Biomedical Engineering & Science, Tokyo Women's Medical University, Tokyo, Japan.,Department of Neurosurgery, Neurological Institute, Tokyo Women's Medical University, Tokyo, Japan
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19
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Yu X, Laurentius T, Bollheimer C, Leonhardt S, Antink CH. Noncontact Monitoring of Heart Rate and Heart Rate Variability in Geriatric Patients Using Photoplethysmography Imaging. IEEE J Biomed Health Inform 2021; 25:1781-1792. [PMID: 32816681 DOI: 10.1109/jbhi.2020.3018394] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Geriatric patients, especially those with dementia or in a delirious state, do not accept conventional contact-based monitoring. Therefore, we propose to measure heart rate (HR) and heart rate variability (HRV) of geriatric patients in a noncontact and unobtrusive way using photoplethysmography imaging (PPGI). METHODS PPGI video sequences were recorded from 10 geriatric patients and 10 healthy elderly people using a monochrome camera operating in the near-infrared spectrum and a colour camera operating in the visible spectrum. PPGI waveforms were extracted from both cameras using superpixel-based regions of interests (ROI). A classifier based on bagged trees was trained to automatically select artefact-free ROIs for HR estimation. HRV was calculated in the time-domain and frequency-domain. RESULTS an RMSE of 1.03 bpm and a correlation of 0.8 with the reference was achieved using the NIR camera for HR estimation. Using the RGB camera, RMSE and correlation improved to 0.48 bpm and 0.95, respectively. Correlation for HRV in the frequency-domain (LF/HF-ratio) was 0.50 using the NIR camera and 0.70 using the RGB camera. CONCLUSION We were able to demonstrate that PPGI is very suitable to measure HR and HRV in geriatric patients. We strongly believe that PPGI will become clinically relevant in monitoring of geriatric patients. SIGNIFICANCE we are the first group to measure both HR and HRV in awake geriatric patients using PPGI. Moreover, we systematically evaluate the effects of the spectrum (near-infrared vs. visible), ROI, and additional motion artefact reduction algorithms on the accuracy of estimated HR and HRV.
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20
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Maurya L, Kaur P, Chawla D, Mahapatra P. Non-contact breathing rate monitoring in newborns: A review. Comput Biol Med 2021; 132:104321. [PMID: 33773194 DOI: 10.1016/j.compbiomed.2021.104321] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 03/04/2021] [Accepted: 03/04/2021] [Indexed: 02/07/2023]
Abstract
The neonatal period - the first 4 weeks of life - is the most critical time for a child's survival. Breathing rate is a vital indicator of the health condition and requires continuous monitoring in case of sickness or preterm birth. Breathing movements can be counted by contact and non-contact methods. In the case of newborn infants, the non-contact breathing rate monitoring need is high, as a contact-based approach may interfere while providing care and is subject to interference by non-breathing movements. This review article delivers a factual summary, and describes the methods and processing involved in non-contact based breathing rate monitoring. The article also provides the advantages, limitations, and clinical applications of these methods. Additionally, signal processing, feasibility, and future direction of different non-contact neonatal breathing rate monitoring are discussed.
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Affiliation(s)
- Lalit Maurya
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Sector 30-C, Chandigarh, 160030, India.
| | - Pavleen Kaur
- CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Sector 30-C, Chandigarh, 160030, India; Department of Biomedical Engineering, SRM University Delhi NCR, Sonepat, Haryana, India.
| | - Deepak Chawla
- Department of Neonatology, Government Medical College & Hospital (GMCH), Chandigarh, 160030, India.
| | - Prasant Mahapatra
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Sector 30-C, Chandigarh, 160030, India.
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21
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Khanam FTZ, Chahl LA, Chahl JS, Al-Naji A, Perera AG, Wang D, Lee Y, Ogunwa TT, Teague S, Nguyen TXB, McIntyre TD, Pegoli SP, Tao Y, McGuire JL, Huynh J, Chahl J. Noncontact Sensing of Contagion. J Imaging 2021; 7:28. [PMID: 34460627 PMCID: PMC8321279 DOI: 10.3390/jimaging7020028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 02/02/2021] [Accepted: 02/02/2021] [Indexed: 12/28/2022] Open
Abstract
The World Health Organization (WHO) has declared COVID-19 a pandemic. We review and reduce the clinical literature on diagnosis of COVID-19 through symptoms that might be remotely detected as of early May 2020. Vital signs associated with respiratory distress and fever, coughing, and visible infections have been reported. Fever screening by temperature monitoring is currently popular. However, improved noncontact detection is sought. Vital signs including heart rate and respiratory rate are affected by the condition. Cough, fatigue, and visible infections are also reported as common symptoms. There are non-contact methods for measuring vital signs remotely that have been shown to have acceptable accuracy, reliability, and practicality in some settings. Each has its pros and cons and may perform well in some challenges but be inadequate in others. Our review shows that visible spectrum and thermal spectrum cameras offer the best options for truly noncontact sensing of those studied to date, thermal cameras due to their potential to measure all likely symptoms on a single camera, especially temperature, and video cameras due to their availability, cost, adaptability, and compatibility. Substantial supply chain disruptions during the pandemic and the widespread nature of the problem means that cost-effectiveness and availability are important considerations.
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Affiliation(s)
- Fatema-Tuz-Zohra Khanam
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Loris A. Chahl
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW 2308, Australia;
| | - Jaswant S. Chahl
- The Chahl Medical Practice, P.O. Box 2300, Dangar, NSW 2309, Australia;
| | - Ali Al-Naji
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
- Electrical Engineering Technical College, Middle Technical University, Al Doura, Baghdad 10022, Iraq
| | - Asanka G. Perera
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Danyi Wang
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Y.H. Lee
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Titilayo T. Ogunwa
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Samuel Teague
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Tran Xuan Bach Nguyen
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Timothy D. McIntyre
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Simon P. Pegoli
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Yiting Tao
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - John L. McGuire
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Jasmine Huynh
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Javaan Chahl
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
- Joint and Operations Analysis Division, Defence Science and Technology Group, Melbourne, VIC 3207, Australia
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22
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Antink CH, Ferreira JCM, Paul M, Lyra S, Heimann K, Karthik S, Joseph J, Jayaraman K, Orlikowsky T, Sivaprakasam M, Leonhardt S. Fast body part segmentation and tracking of neonatal video data using deep learning. Med Biol Eng Comput 2020; 58:3049-3061. [PMID: 33094430 PMCID: PMC7679364 DOI: 10.1007/s11517-020-02251-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Accepted: 08/20/2020] [Indexed: 12/11/2022]
Abstract
Photoplethysmography imaging (PPGI) for non-contact monitoring of preterm infants in the neonatal intensive care unit (NICU) is a promising technology, as it could reduce medical adhesive-related skin injuries and associated complications. For practical implementations of PPGI, a region of interest has to be detected automatically in real time. As the neonates' body proportions differ significantly from adults, existing approaches may not be used in a straightforward way, and color-based skin detection requires RGB data, thus prohibiting the use of less-intrusive near-infrared (NIR) acquisition. In this paper, we present a deep learning-based method for segmentation of neonatal video data. We augmented an existing encoder-decoder semantic segmentation method with a modified version of the ResNet-50 encoder. This reduced the computational time by a factor of 7.5, so that 30 frames per second can be processed at 960 × 576 pixels. The method was developed and optimized on publicly available databases with segmentation data from adults. For evaluation, a comprehensive dataset consisting of RGB and NIR video recordings from 29 neonates with various skin tones recorded in two NICUs in Germany and India was used. From all recordings, 643 frames were manually segmented. After pre-training the model on the public adult data, parts of the neonatal data were used for additional learning and left-out neonates are used for cross-validated evaluation. On the RGB data, the head is segmented well (82% intersection over union, 88% accuracy), and performance is comparable with those achieved on large, public, non-neonatal datasets. On the other hand, performance on the NIR data was inferior. By employing data augmentation to generate additional virtual NIR data for training, results could be improved and the head could be segmented with 62% intersection over union and 65% accuracy. The method is in theory capable of performing segmentation in real time and thus it may provide a useful tool for future PPGI applications. Graphical Abstract This work presents the development of a customized, real-time capable Deep Learning architecture for segmenting of neonatal videos recorded in the intensive care unit. In addition to hand-annotated data, transfer learning is exploited to improve performance.
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Affiliation(s)
- Christoph Hoog Antink
- Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074, Aachen, Germany.
| | - Joana Carlos Mesquita Ferreira
- Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074, Aachen, Germany
| | - Michael Paul
- Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074, Aachen, Germany
| | - Simon Lyra
- Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074, Aachen, Germany
| | - Konrad Heimann
- Section of Neonatology, RWTH Aachen University, Pauwelsstr. 30, 52074, Aachen, Germany
| | - Srinivasa Karthik
- Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai, 600036, Tamil Nadu, India
| | - Jayaraj Joseph
- Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai, 600036, Tamil Nadu, India
| | - Kumutha Jayaraman
- Saveetha Medical College, Kanchipuram, Saveetha Nagar, Chennai, 602 105, India
| | - Thorsten Orlikowsky
- Section of Neonatology, RWTH Aachen University, Pauwelsstr. 30, 52074, Aachen, Germany
| | - Mohanasankar Sivaprakasam
- Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai, 600036, Tamil Nadu, India
| | - Steffen Leonhardt
- Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074, Aachen, Germany
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23
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Rossol SL, Yang JK, Toney-Noland C, Bergin J, Basavaraju C, Kumar P, Lee HC. Non-Contact Video-Based Neonatal Respiratory Monitoring. CHILDREN-BASEL 2020; 7:children7100171. [PMID: 33036226 PMCID: PMC7600716 DOI: 10.3390/children7100171] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 10/01/2020] [Accepted: 10/03/2020] [Indexed: 12/25/2022]
Abstract
Respiratory rate (RR) has been shown to be a reliable predictor of cardio-pulmonary deterioration, but standard RR monitoring methods in the neonatal intensive care units (NICU) with contact leads have been related to iatrogenic complications. Video-based monitoring is a potential non-contact system that could improve patient care. This iterative design study developed a novel algorithm that produced RR from footage analyzed from stable NICU patients in open cribs with corrected gestational ages ranging from 33 to 40 weeks. The final algorithm used a proprietary technique of micromotion and stationarity detection (MSD) to model background noise to be able to amplify and record respiratory motions. We found significant correlation—r equals 0.948 (p value of 0.001)—between MSD and the current hospital standard, electrocardiogram impedance pneumography. Our video-based system showed a bias of negative 1.3 breaths and root mean square error of 6.36 breaths per minute compared to standard continuous monitoring. Further work is needed to evaluate the ability of video-based monitors to observe clinical changes in a larger population of patients over extended periods of time.
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Affiliation(s)
- Scott L. Rossol
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USA; (J.K.Y.); (C.T.-N.); (J.B.); (H.C.L.)
- Correspondence:
| | - Jeffrey K. Yang
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USA; (J.K.Y.); (C.T.-N.); (J.B.); (H.C.L.)
| | - Caroline Toney-Noland
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USA; (J.K.Y.); (C.T.-N.); (J.B.); (H.C.L.)
| | - Janine Bergin
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USA; (J.K.Y.); (C.T.-N.); (J.B.); (H.C.L.)
| | | | - Pavan Kumar
- CocoonCam, Sunnyvale, CA 94089, USA; (C.B.); (P.K.)
| | - Henry C. Lee
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USA; (J.K.Y.); (C.T.-N.); (J.B.); (H.C.L.)
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24
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Chiera M, Cerritelli F, Casini A, Barsotti N, Boschiero D, Cavigioli F, Corti CG, Manzotti A. Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review. Front Neurosci 2020; 14:561186. [PMID: 33071738 PMCID: PMC7544983 DOI: 10.3389/fnins.2020.561186] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 08/28/2020] [Indexed: 12/18/2022] Open
Abstract
Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often time-consuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a non-invasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby’s overall wellbeing and neurological development to detect stress-/pain-related behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby’s stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant’s HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant’s clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients’ health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.
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Affiliation(s)
- Marco Chiera
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy.,Research Commission on Manual Therapies and Mind-Body Disciplines, Societ Italiana di Psico Neuro Endocrino Immunologia, Rome, Italy
| | - Francesco Cerritelli
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
| | - Alessandro Casini
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
| | - Nicola Barsotti
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy.,Research Commission on Manual Therapies and Mind-Body Disciplines, Societ Italiana di Psico Neuro Endocrino Immunologia, Rome, Italy
| | | | - Francesco Cavigioli
- Neonatal Intensive Care Unit, "V. Buzzi" Children's Hospital, Azienda Socio Sanitaria Territoriale Fatebenefratelli-Sacco, Milan, Italy
| | - Carla G Corti
- Pediatric Cardiology Unit-Pediatric Department, Azienda Socio Sanitaria Territoriale Fatebenefratelli-Sacco, Milan, Italy
| | - Andrea Manzotti
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy.,Neonatal Intensive Care Unit, "V. Buzzi" Children's Hospital, Azienda Socio Sanitaria Territoriale Fatebenefratelli-Sacco, Milan, Italy.,Research Department, SOMA, Istituto Osteopatia Milano, Milan, Italy
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25
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Continuous-Spectrum Infrared Illuminator for Camera-PPG in Darkness. SENSORS 2020; 20:s20113044. [PMID: 32471224 PMCID: PMC7309009 DOI: 10.3390/s20113044] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 05/10/2020] [Accepted: 05/20/2020] [Indexed: 11/17/2022]
Abstract
Many camera-based remote photoplethysmography (PPG) applications require sensing in near infrared (NIR). The performance of PPG systems benefits from multi-wavelength processing. The illumination source in such system is explored in this paper. We demonstrate that multiple narrow-band LEDs have inferior color homogeneity compared to broadband light sources. Therefore, we consider the broadband option based on phosphor material excited by LEDs. A first prototype was realized and its details are discussed. It was tested within a remote-PPG monitoring scenario in darkness and the full system demonstrates robust pulse-rate measurement. Given its accuracy in pulse rate extraction, the proposed illumination principle is considered a valuable asset for large-scale NIR-PPG applications as it enables multi-wavelength processing, lightweight set-ups with relatively low-power infrared light sources.
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26
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Le Bris A, Mazille-Orfanos N, Simonot P, Luherne M, Flamant C, Gascoin G, ÓLaighin G, Harte R, Pladys P. Parents' and healthcare professionals' perceptions of the use of live video recording in neonatal units: a focus group study. BMC Pediatr 2020; 20:143. [PMID: 32238158 PMCID: PMC7110620 DOI: 10.1186/s12887-020-02041-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 03/20/2020] [Indexed: 01/05/2023] Open
Abstract
Background The emerging use of video in neonatology units raises ethical and practical questions. This study aims to gain a better understanding of the suitability, limitations and constraints concerning the use of live video as a tool in neonatal clinical practice. The perceptions of parents and healthcare professionals in regard to live video were examined. Methods Nine focus groups were conducted in four neonatal units involving 20 healthcare professionals and 19 parents. Data were triangulated using transcripts and field notes and analyzed using inductive and semantic thematic analysis. Results The seven major themes that emerged from the healthcare professionals focus groups were (i) the impact of video recording on healthcare professionals’ behavior; (ii) the impact on parents; (iii) forensic issues;(iv) guarantee of use; (v) benefits for the newborn; (vi) methodology of use; and (vii) technical considerations & feasibility. The five major themes that emerged from parents focus groups were (i) benefits for the newborn and care enhancement; (ii) impact on parents and potential benefits in case of newborn child/parent separation; (iii) informed consent and guarantee of use;(iv) concern about a possible disruptive impact on healthcare professionals; and (v) data protection. Conclusion Both parents and healthcare professionals found video recording useful and acceptable if measures were taken to protect the data and mitigate any negative impacts on healthcare professionals.
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Affiliation(s)
- Aude Le Bris
- Department of Neonatology, University Hospital of Rennes, 35000, Rennes, France.
| | | | - Pauline Simonot
- Department of Neonatology, University Hospital of Caen, Caen, France
| | - Maude Luherne
- Research and Innovation Department, Paediatric Department, University Hospital of Rennes and GCS HUGO, Rennes, France
| | - Cyril Flamant
- Department of Neonatology, University Hospital of Nantes, Nantes, France
| | - Geraldine Gascoin
- Department of Neonatology, University Hospital of Angers, Angers, France
| | | | - Richard Harte
- CURAM, Human Movement Laboratory, NUI Galway, Galway, Ireland
| | - Patrick Pladys
- Department of Neonatology, University Hospital of Rennes, 35000, Rennes, France.,Research and Innovation Department, Paediatric Department, University Hospital of Rennes and GCS HUGO, Rennes, France
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27
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Paul M, Karthik S, Joseph J, Sivaprakasam M, Kumutha J, Leonhardt S, Hoog Antink C. Non-contact sensing of neonatal pulse rate using camera-based imaging: a clinical feasibility study. Physiol Meas 2020; 41:024001. [PMID: 32148333 DOI: 10.1088/1361-6579/ab755c] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Neonates and infants are patients who would benefit from less invasive vital sign sensing, especially from fewer cables and the avoidance of adhesive electrodes. Photoplethysmography imaging (PPGI) has been studied for medical applications in recent years: it is possible to assess various vital signs remotely, non-invasively, and without contact by using video cameras and light. However, studies on infants and especially on neonates in clinical settings are still rare. Hence, we conducted a single-center study to assess heart activity by estimating the pulse rate (PR) of 19 neonates. APPROACH Time series were generated from tracked regions of interest (ROIs) and PR was estimated via a joint time-frequency analysis using a short-time Fourier transform. Artifacts, for example, induced by movement, were detected and flagged by applying a signal quality index in the frequency domain. MAIN RESULTS The feasibility of PR estimation was demonstrated using visible light and near-infrared light at 850 nm and 940 nm, respectively: the estimated PR was as close as 3 heartbeats per minute in artifact-free time segments. Furthermore, an improvement could be shown when selecting the best performing ROI compared to the ROI containing the whole body. The main challenges are artifacts from motion, light sources, medical devices, and the detection and tracking of suitable regions for signal retrieval. Nonetheless, the PR extracted was found to be comparable to the contact-based photoplethysmography reference and is, therefore, a viable replacement if robust signal retrieval is ensured. SIGNIFICANCE Neonates are seldom measured by PPGI and studies reporting measurements on darker skin tones are rare. In this work, not only a single camera was used, but a synchronized camera setup using multiple wavelengths. Various ROIs were used for signal extraction to examine the capabilities of PPGI. In addition, qualitative observations regarding camera parameters and noise sources were reported and discussed.
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Affiliation(s)
- M Paul
- Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstr. 20, Aachen, 52074, Germany
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28
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Moreno-Castillo M, Meza R, Romero-Vaca J, Huidobro N, Méndez-Fernández A, Martínez-Castillo J, Mabil P, Flores A, Manjarrez E. The Hemodynamic Mass Action of a Central Pattern Generator. Front Neurosci 2020; 14:38. [PMID: 32076397 PMCID: PMC7006454 DOI: 10.3389/fnins.2020.00038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 01/13/2020] [Indexed: 12/12/2022] Open
Abstract
The hemodynamic response is a neurovascular and metabolic process in which there is rapid delivery of blood flow to a neuronal tissue in response to neuronal activation. The functional magnetic resonance imaging (fMRI) and the functional near-infrared spectroscopy (fNIRS), for instance, are based on the physiological principles of such hemodynamic responses. Both techniques allow the mapping of active neuronal regions in which the neurovascular and metabolic events are occurring. However, although both techniques have revolutionized the neurosciences, they are mostly employed for neuroimaging of the human brain but not for the spinal cord during functional tasks. Moreover, little is known about other techniques measuring the hemodynamic response in the spinal cord. The purpose of the present study was to show for the first time that a simple optical system termed direct current photoplethysmography (DC-PPG) can be employed to detect hemodynamic responses of the spinal cord and the brainstem during the functional activation of the spinal central pattern generator (CPG). In particular, we positioned two DC-PPG systems directly on the brainstem and spinal cord during fictive scratching in the cat. The optical DC-PPG systems allowed the trial-by-trial recording of massive hemodynamic signals. We found that the “strength” of the flexor-plus-extensor motoneuron activities during motor episodes of fictive scratching was significantly correlated to the “strengths” of the brainstem and spinal DC-PPG signals. Because the DC-PPG was robustly detected in real-time, we claim that such a functional signal reflects the hemodynamic mass action of the brainstem and spinal cord associated with the CPG motor action. Our findings shed light on an unexplored hemodynamic observable of the spinal CPGs, providing a proof of concept that the DC-PPG can be used for the assessment of the integrity of the human CPGs.
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Affiliation(s)
| | - Roberto Meza
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - Jesús Romero-Vaca
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - Nayeli Huidobro
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | | | - Jaime Martínez-Castillo
- Centro de Investigación en Micro y Nanotecnología, Universidad Veracruzana, Veracruz, Mexico
| | - Pedro Mabil
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - Amira Flores
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - Elias Manjarrez
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
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29
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Abstract
Multi-wavelength cameras play an essential role in remote photoplethysmography (PPG). Whereas these are readily available for visible light, this is not the case for near infrared (NIR). We propose to modify existing RGB cameras to make them suited for NIR-PPG. In particular, we exploit the spectral leakage of the RGB channels in infrared in combination with a narrow dual-band optical filter. Such camera modification is simple, cost-effective, easy to implement, and it is shown to attain a pulse-rate extraction performance comparable to that of multiple narrow-band NIR cameras.
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30
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Remote Monitoring of Vital Signs in Diverse Non-Clinical and Clinical Scenarios Using Computer Vision Systems: A Review. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9204474] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Techniques for noncontact measurement of vital signs using camera imaging technologies have been attracting increasing attention. For noncontact physiological assessments, computer vision-based methods appear to be an advantageous approach that could be robust, hygienic, reliable, safe, cost effective and suitable for long distance and long-term monitoring. In addition, video techniques allow measurements from multiple individuals opportunistically and simultaneously in groups. This paper aims to explore the progress of the technology from controlled clinical scenarios with fixed monitoring installations and controlled lighting, towards uncontrolled environments, crowds and moving sensor platforms. We focus on the diversity of applications and scenarios being studied in this topic. From this review it emerges that automatic multiple regions of interest (ROIs) selection, removal of noise artefacts caused by both illumination variations and motion artefacts, simultaneous multiple person monitoring, long distance detection, multi-camera fusion and accepted publicly available datasets are topics that still require research to enable the technology to mature into many real-world applications.
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31
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Abstract
Near-infrared (NIR) remote photoplethysmography (PPG) promises attractive applications in darkness, as it involves unobtrusive, invisible light. However, since the PPG strength (AC/DC) is much lower in the NIR spectrum than in the RGB spectrum, robust vital signs monitoring is more challenging. In this paper, we propose a new PPG-extraction method, DIScriminative signature based extraction (DIS), to significantly improve the pulse-rate measurement in NIR. Our core idea is to use both the color signals containing blood absorption variations and additional disturbance signals as input for PPG extraction. By defining a discriminative signature, we use one-step least-squares regression (joint optimization) to retrieve the pulsatile component from color signals and suppress disturbance signals simultaneously. A large-scale lab experiment, recorded in NIR with heavy body motions, shows the significant improvement of DIS over the state-of-the-art method, whereas its principle is simple and generally applicable.
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