The DOI matches its Crossref record; 206 of the 206 references it cites were found in a registry or an index.
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, 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]
Citations
Cites
Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association
Benjamin, E. J., Blaha, M. J., Chiuve, S. E., Cushman, M., Das, S. R., Deo, R., de Ferranti, S. D., Floyd, J., Fornage, M., Gillespie, C., et al. (2017) · Circulation · doi:10.1161/cir.0000000000000485 · Cited by 12,591
A review of wearable sensors and systems with application in rehabilitation
Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2012) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-9-21 · Cited by 2,396
Lab-on-Skin: A Review of Flexible and Stretchable Electronics for Wearable Health Monitoring
Liu, Y., Pharr, M., & Salvatore, G. A. (2017) · ACS Nano · doi:10.1021/acsnano.7b04898 · Cited by 1,725
Smart wearable systems: Current status and future challenges
Chan, M., Estève, D., Fourniols, J.-Y., Escriba, C., & Campo, E. (2012) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2012.09.003 · Cited by 953
Electronic Health Records: Then, Now, and in the Future
Evans, R. S. (2016) · Yearbook of Medical Informatics · doi:10.15265/iys-2016-s006 · Cited by 816
A direct comparison of wet, dry and insulating bioelectric recording electrodes
Searle, A., & Kirkup, L. (2000) · Physiological Measurement · doi:10.1088/0967-3334/21/2/307 · Cited by 736
Heat Generation and Transport in Nanometer-Scale Transistors
Pop, E., Sinha, S., & Goodson, K. E. (2006) · Proceedings of the IEEE · doi:10.1109/jproc.2006.879794 · Cited by 712
(2015) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2015.2417514 · Cited by 712
Middleton, B., Bloomrosen, M., Dente, M. A., Hashmat, B., Koppel, R., Overhage, J. M., Payne, T. H., Rosenbloom, S. T., Weaver, C., & Zhang, J. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001458 · Cited by 618
Research works printed but not linked: 5
- Benjamin, 2017, Heart disease and stroke statistics—2017 update, Circulation, 135, e146, 10.1161/CIR.0000000000000485 · DOI · Paper page
- 1985, CSE Working Party. Recommendations for measurement standards in quantitative electrocardiography, Eur. Heart J., 6, 815
- Ioannou, 2014, Ambulatory electrocardiography: the contribution of Norman jefferis holter, Brit Col Med Jour., 56, 86
- Romero, 2013, Ambulatory electrocardiology, Cardiol. Rev., 21, 239, 10.1097/CRD.0b013e31828a8294 · DOI
- Assambo, 2012, An optimized high-impedance amplifier for dry- electrode ECG recording, International Journal of Circuits Systems and Signal Processing, 6, 10
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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
Metadata
- 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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