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Review
. 2023 Dec 15;6(1):231.
doi: 10.1038/s41746-023-00973-x.

Challenges and prospects of visual contactless physiological monitoring in clinical study

Bin Huang  1   2 , Shen Hu  3   4 , Zimeng Liu  5 , Chun-Liang Lin  6 , Junfeng Su  7   8 , Changchen Zhao  9 , Li Wang  10 , Wenjin Wang  11
Affiliations
Review

Challenges and prospects of visual contactless physiological monitoring in clinical study

Bin Huang et al. NPJ Digit Med. .

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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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. An overview of physiological principle of VCPM technologies of multiple physiological parameters monitoring.
a A schematic representation of the cardiopulmonary circulation system. Due to the interaction of oxygen between the heart and lungs, respiratory rate information is implicitly reflected in hemodynamics. b The skin reflection model of the blood volume pulse (BVP) signal monitoring and the hemodynamics varying with the heartbeat. c Different body sites employed to extract PPG signals. d PPG signals from various body sites with RGB channels. e The vital signs derived from PPG waveforms. f The AI model for cardiopulmonary status assessment, and disease diagnosis. Subgraphs (a–c and e) are designed by Freepik.
Fig. 2
Fig. 2
The pipeline of the future direction topics.
Fig. 3
Fig. 3. The skin segmentation results of SAM online demo on clinical scenarios.
a The facial region of our ICU patients' recording image. b Full image automatic segmentation. c The results of automatic segmentation solution. d The interactive manual segmentation process. The rectangle box denotes the selected region, and dots represent the areas to be removed or retained. e The results of interactive segmentation. The source images are designed by Freepik.
Fig. 4
Fig. 4. The VCPM-based telemedicine/telehealth system is employed to personalized disease diagnosis and public health management.
a The two typical application scenarios. The VCPM relies solely on ubiquitous cameras to capture video data. b The internet infrastructure, including both wireless and wired networks, facilitates the transmission and storage of data across the globe. c The AI model of physiological monitoring based on individual video data, and the AI model for large-scale decision-making, incorporating multi-source information fusion based on global patient data. d The upper subgraph denotes the personal health care in a telemedicine system, while the lower subgraph depicts the decision-making of public health policies based on global patient information and horizontal relationships. The elements of sub-figures are designed by Freepik.
Fig. 5
Fig. 5. The development trend of the vital-sign monitoring of neonates or preterm infants.
a The conventional contact monitoring approach with hard-wired devices and rigid sensors that adhere to neonatal skin. b The wireless, non-invasive soft biosensors employed to monitor physiological signals in NICU or pediatric ICU (PICU) settings, e.g., the research of literature. c The video-based non-contact vital-sign monitoring solution utilized in the NICU, such as the study of Oxford University.
Fig. 6
Fig. 6. The digital medicine and telemedicine systems based on VCPM technologies.
a The hierarchical advantages and characteristics of the VCPM methodology. b The relationships of concepts of digital medicine, telehealth, telemedicine, RPM, home-based monitoring or self-monitoring. The VCPM technology is a fundamental and suitable tool to support telemedicine, particularly in home-based monitoring.
Fig. 7
Fig. 7. Application scenarios of VCPM.
Sub-figure (a) is designed by our team, and (b–i) are designed by Freepik.
Fig. 8
Fig. 8
The distinct types of abnormal PPG waveforms.
Fig. 9
Fig. 9
Flowchart for literature search and screening.
Fig. 10
Fig. 10
The relationship between the number of subjects and videos’ length.
See this image and copyright information in PMC

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References

    1. Curran T, Liu X, McDuff D, Patel S, Yang E. Camera-based remote photoplethysmography to measure heart rate and blood pressure in ambulatory patients with cardiovascular disease: Preliminary analysis. J. Am. Coll. Cardiol. 2023;81:2301–2301.
    1. Wu B-F, Wu B-J, Tsai B-R, Hsu C-P. A facial-image-based blood pressure measurement system without calibration. IEEE Trans. Instrum. Measur. 2022;71:1–13.
    1. Wang, W. & Wang, X. Contactless vital signs monitoring (Academic Press, 2021).
    1. Frey L, Menon C, Elgendi M. Blood pressure measurement using only a smartphone. npj Digital Med. 2022;5:86. - PMC - PubMed
    1. Shabaan M, et al. Survey: smartphone-based assessment of cardiovascular diseases using ecg and ppg analysis. BMC Med. Inform. Decision Making. 2020;20:1–16. - PMC - PubMed
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