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Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review

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Abstract

Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2–11%. For the roughly 75% of OHCAs that are unwitnessed, survival is approximately 2–4.4%, as there are no bystanders present to provide life-saving interventions and alert Emergency Medical Services. Sensor technologies may reduce the number of unwitnessed OHCAs through automated detection of OHCA-associated physiological changes. However, no technologies are widely available for OHCA detection. This review identifies research and commercial technologies developed for cardiopulmonary monitoring that may be best suited for use in the context of OHCA, and provides recommendations for technology development, testing, and implementation. We conducted a systematic review of published studies along with a search of grey literature to identify technologies that were able to provide cardiopulmonary monitoring, and could be used to detect OHCA. We searched MEDLINE, EMBASE, Web of Science, and Engineering Village using MeSH keywords. Following inclusion, we summarized trends and findings from included studies. Our searches retrieved 6945 unique publications between January, 1950 and May, 2023. 90 studies met the inclusion criteria. In addition, our grey literature search identified 26 commercial technologies. Among included technologies, 52% utilized electrocardiography (ECG) and 40% utilized photoplethysmography (PPG) sensors. Most wearable devices were multi-modal (59%), utilizing more than one sensor simultaneously. Most included devices were wearable technologies (84%), with chest patches (22%), wrist-worn devices (18%), and garments (14%) being the most prevalent. ECG and PPG sensors are heavily utilized in devices for cardiopulmonary monitoring that could be adapted to OHCA detection. Developers seeking to rapidly develop methods for OHCA detection should focus on using ECG- and/or PPG-based multimodal systems as these are most prevalent in existing devices. However, novel sensor technology development could overcome limitations in existing sensors and could serve as potential additions to or replacements for ECG- and PPG-based devices.

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  1. Sensors integrated into clothing

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Funding

MK is funded by Mitacs and the Michael Smith Health Research BC, JH is funded by Mitacs, and the research team is funded by the UBC VPRI Research Excellence Cluster.

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Author notes

  1. Saud Lingawi, Jacob Hutton, and Mahsa Khalili have contributed equally to this work and are co-first authors.

Authors and Affiliations

  1. British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada

    Saud Lingawi, Jacob Hutton, Mahsa Khalili, Babak Shadgan, Jim Christenson, Brian Grunau & Calvin Kuo

  2. School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada

    Saud Lingawi, Babak Shadgan & Calvin Kuo

  3. Centre for Aging SMART, University of British Columbia, 2635 Laurel St., Vancouver, BC, V5Z 1M9, Canada

    Saud Lingawi, Mahsa Khalili & Calvin Kuo

  4. British Columbia Emergency Health Services, Vancouver, Canada

    Jacob Hutton, Jim Christenson & Brian Grunau

  5. Department of Emergency Medicine, University of British Columbia and St. Paul’s Hospital, Vancouver, BC, Canada

    Jacob Hutton, Mahsa Khalili, Jim Christenson & Brian Grunau

  6. Centre for Advancing Health Outcomes, University of British Columbia, Vancouver, BC, Canada

    Jacob Hutton, Mahsa Khalili, Jim Christenson & Brian Grunau

  7. Department of Orthopedic Surgery, University of British Columbia, Vancouver, BC, Canada

    Babak Shadgan

  8. International Collaboration on Repair Discoveries, Vancouver, BC, Canada

    Babak Shadgan

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Appendix: Search Terms and Search Strategy

Appendix: Search Terms and Search Strategy

The search strategy is provided below. The search databases include MEDLINE, EMBASE, Web of Science, and Engineering Village. The search was restricted to articles in English within the date range of January 1, 1950 to May 19, 2023. Full-text case reports, clinical trials, and technical reports were included in the search.

Search Terms

The terms used in this search fell under four classifying categories: (1) terms for continuous monitoring and detection of physiological parameters, (2) terms for broad categories of sensors, (3) terms for the primary disease states associated with cardiac arrest, and (4) terms for cardiac arrest-associated physiological parameters. The exact search terms within each classifying category are listed below (Table 3).

Table 3 Literature search terms
Full size table

When necessary, keywords were shortened and truncated with an asterisk (e.g. detect*) to retrieve unlimited suffix variations (e.g. detect, detecting, detectable, etc.). The search terms were combined according to the following strategy:

$$Category 1 AND \left[\left(Category 2\right) AND (Category 3 OR category 4)\right]$$

MEDLINE Example Search

On MEDLINE, all of the search terms used, with the exception of “prevent”, “detect”, “monitor”, “cardiac arrest”, and “implant” were Medical Subject Headings (MeSH). Broader MeSH were selected to encompass relevant subcategories when necessary. Below is a more detailed representation of this search strategy (Table 4).

Table 4 MEDLINE example search strategy
Full size table

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Lingawi, S., Hutton, J., Khalili, M. et al. Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review. Ann Biomed Eng 52, 1136–1158 (2024). https://doi.org/10.1007/s10439-024-03442-y

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