Ambulatory cardiac bio-signals: From mirage to clinical reality through a decade of progress
Abstract
Background Health monitoring is shifting towards continuous, ambulatory and clinically comparable wearable devices. Telemedicine and remote diagnosis could harness the capability of mobile cardiac health information, as the technology on bio-physical signal monitoring has improved significantly.Objectives The purpose of this review article is (1) to systematically assess the viability of ambulatory electrocardiography (ECG), (2) to provide a systems level understanding of a broad spectrum of wearable heart signal monitoring approaches and (3) to identify areas of improvement in the existing technology needed to attain clinical grade diagnosis.Results Based on the included literature, we have identified (1) that the developments in ECG monitoring through wearable devices are reaching feasibility, and are capable of delivering diagnostic and prognostic information, (2) that reliable sensing is the major bottleneck in the entire process of ambulatory monitoring, (3) that there is a strong need for artificial intelligence and machine learning techniques to parse and infer the biosignals and (4) that aspects of wearer comfort has largely been ignored in the prevailing developments, which can become a key factor for consumer acceptance.Conclusions Cardiac health information is crucial for diagnosis and prevention of several disease onsets. Mobile and continuous monitoring can aid avoiding risks involved with acute symptoms. The health information obtained through continuous monitoring can serve as the BigData of heart signals, and can facilitate new treatment methods and devise effective health policies.
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Recently, in addition to Holter monitoring, patch-type, watch-type, ring-type, and clothing-type monitoring systems have been approved by the FDA.
“Recently, in addition to Holter monitoring, which has been traditionally used, the use of patch-type, watch-type, ring-type, and clothing-type monitoring systems have been approved by the FDA.138”
From Artificial intelligence for detection of cardiovascular-related diseases from wearable devices: A systematic review and meta-analysis (2022) · cites this paper as [138]
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Lee, S., Chu, Y., Ryu, J., Park, Y. J., Yang, S., & Koh, S. B. (2022) · Yonsei Medical Journal · doi:10.3349/ymj.2022.63.s93 · Cited by 88 · see citing works
- Authors
- Periyaswamy, T., & Balasubramanian, M.
- Affiliations
- Central Michigan University (US)
- University of Arkansas at Fayetteville (US)
- Corresponding author
- Periyaswamy, Thamizhisai
- Venue
- International Journal of Medical Informatics
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 130
- Pages
- 103928
- ISSN
- 1386-5056 (ISSN-L)
- OpenAlex
- W2958092670
- Cited by
- 14
- References
- 206
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 1 · 2023: 1 · 2022: 3 · 2021: 4 · 2020: 1
- FWCI
- 0.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Medical Informatics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Keywords
- Holter monitoring, wearable cardiac monitoring, remote diagnosis, telemedicine, wearable comfort, continuous cardiac monitoring
- MeSH terms
- Wearable Electronic Devices, Arrhythmias, Cardiac, Humans, Electrocardiography, Ambulatory, Telemedicine, Monitoring, Ambulatory
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