Cited by 175Wireless Body Area NetworksNon-Invasive Vital Sign MonitoringECG Monitoring and Analysis

The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.

Novel Wireless Devices for Cardiac Monitoring

Open access

Walsh, Joseph A., Topol, Eric J., Steinhubl, Steven R.·2014·Circulation

DOI 10.1161/circulationaha.114.009024PMC PMC4135373

Open this paper in CoChat — free account

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1161/circulationaha.114.009024

Cites

41 of 41 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Heart Disease and Stroke Statistics—2010 Update: A Report From the American Heart Association
WRITING GROUP MEMBERS, Lloyd-Jones, D., Adams, R. J., Brown, T. M., Carnethon, M., Dai, S., De Simone, G., Ferguson, T. B., Ford, E., Furie, K., et al. (2010) · Circulation · doi:10.1161/circulationaha.109.192667 · Cited by 5,700
Heart Disease and Stroke Statistics—2009 Update
WRITING GROUP MEMBERS, Lloyd‐Jones, D. M., Adams, R. J., Carnethon, M. R., SIMONE, G. D., Ferguson, T. B., Flegal, K. M., Ford, E. S., Furie, K. L., Go, A. S., et al. (2009) · Circulation · doi:10.1161/circulationaha.108.191259 · Cited by 3,915
2009 Focused Update Incorporated Into the ACC/AHA 2005 Guidelines for the Diagnosis and Management of Heart Failure in Adults
Hunt, S. A., Abraham, W. T., Chin, M. H., Feldman, A. M., Francis, G. S., Ganiats, T. G., Jessup, M. L., Konstam, M. A., MANCINI, D. M., Michl, K., et al. (2009) · Circulation · doi:10.1161/circulationaha.109.192065 · Cited by 3,739
Heart Disease and Stroke Statistics—2009 Update: A Report From the American Heart Association Statistics Committee and Stroke Statistics Subcommittee
WRITING GROUP MEMBERS, Lloyd-Jones, D., Adams, R., Carnethon, M., De Simone, G., Ferguson, T. B., Flegal, K., Ford, E., Furie, K., Go, A., et al. (2009) · Circulation · doi:10.1161/circulationaha.108.191261 · Cited by 3,140
Characteristics and outcomes of patients hospitalized for heart failure in the United States: Rationale, design, and preliminary observations from the first 100,000 cases in the Acute Decompensated Heart Failure National Registry (ADHERE)
Adams, K. F., Fonarow, G. C., Emerman, C. L., LeJemtel, T. H., Costanzo, M. R., Abraham, W. T., Berkowitz, R. L., Galvao, M., & Horton, D. P. (2005) · American Heart Journal · doi:10.1016/j.ahj.2004.08.005 · Cited by 2,111
Exercise-based cardiac rehabilitation for coronary heart disease
Heran, B. S., Chen, J. M., Ebrahim, S., Moxham, T., Oldridge, N., Rees, K., Thompson, D. R., & Taylor, R. S. (2011) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd001800.pub2 · Cited by 1,844
AHA/ACCF Secondary Prevention and Risk Reduction Therapy for Patients With Coronary and Other Atherosclerotic Vascular Disease: 2011 Update: A Guideline From the American Heart Association and American College of Cardiology Foundation
Smith, S. C., Benjamin, E. J., Bonow, R. O., Braun, L. T., Creager, M. A., Franklin, B. A., Gibbons, R. J., Grundy, S. M., Hiratzka, L. F., Jones, D. W., et al. (2011) · Circulation · doi:10.1161/cir.0b013e318235eb4d · Cited by 1,759
Wireless pulmonary artery haemodynamic monitoring in chronic heart failure: a randomised controlled trial
Abraham, W. T., Adamson, P. B., Bourge, R. C., Aaron, M. F., Costanzo, M. R., Stevenson, L. W., Strickland, W., Neelagaru, S., Raval, N., Krueger, S., et al. (2011) · The Lancet · doi:10.1016/s0140-6736(11)60101-3 · Cited by 1,744
Time Delay to Treatment and Mortality in Primary Angioplasty for Acute Myocardial Infarction
Luca, G. D., Suryapranata, H., Ottervanger, J. P., & Antman, E. M. (2004) · Circulation · doi:10.1161/01.cir.0000121424.76486.20 · Cited by 1,541
Use of Cardiac Rehabilitation by Medicare Beneficiaries After Myocardial Infarction or Coronary Bypass Surgery
Suaya, J. A., Shepard, D. S., Normand, S. T., Ades, P. A., Prottas, J. M., & Stason, W. B. (2007) · Circulation · doi:10.1161/circulationaha.107.701466 · Cited by 827

Show all 40 references

Sorted by citations

Binodal, wireless epidermal electronic systems with in-sensor analytics for neonatal intensive care
Chung, H. U., Kim, B. H., Lee, J. Y., Lee, J., Xie, Z., Ibler, E. M., Lee, K., Banks, A., Jeong, J. Y., Kim, J., et al. (2019) · Science · doi:10.1126/science.aau0780 · Cited by 807
Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention: A Scientific Statement From the American Heart Association
Burke, L. E., Ma, J., Azar, K. M. J., Bennett, G. G., Peterson, E. D., Zheng, Y., Riley, W., Stephens, J., Shah, S. H., Suffoletto, B., et al. (2015) · Circulation · doi:10.1161/cir.0000000000000232 · Cited by 516
2017 ACC/AHA/HRS Guideline for the Evaluation and Management of Patients With Syncope
Shen, W.-K., Sheldon, R. S., Benditt, D. G., Cohen, M. I., Forman, D. E., Goldberger, Z. D., Grubb, B. P., Hamdan, M. H., Krahn, A. D., Link, M. S., et al. (2017) · Heart Rhythm · doi:10.1016/j.hrthm.2017.03.004 · Cited by 478
Mobile technology and the digitization of healthcare
Bhavnani, S. P., Narula, J., & Sengupta, P. P. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehv770 · Cited by 460
The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise
Nicolò, A., Massaroni, C., Schena, E., & Sacchetti, M. (2020) · Sensors · doi:10.3390/s20216396 · Cited by 440
2017 ACC/AHA/HRS Guideline for the Evaluation and Management of Patients With Syncope: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society
Shen, W.-K., Sheldon, R. S., Benditt, D. G., Cohen, M. I., Forman, D. E., Goldberger, Z. D., Grubb, B. P., Hamdan, M. H., Krahn, A. D., Link, M. S., et al. (2017) · Circulation · doi:10.1161/cir.0000000000000499 · Cited by 463
2017 ACC/AHA/HRS Guideline for the Evaluation and Management of Patients With Syncope: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society
Shen, W.-K., Sheldon, R. S., Benditt, D. G., Cohen, M. I., Forman, D. E., Goldberger, Z. D., Grubb, B. P., Hamdan, M. H., Krahn, A. D., Link, M. S., et al. (2017) · Circulation · doi:10.1161/cir.0000000000000498 · Cited by 411
Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review
Charlton, P. H., Birrenkott, D. A., Bonnici, T., Pimentel, M. A. F., Johnson, A. E. W., Alastruey, J., Tarassenko, L., Watkinson, P. J., Beale, R., & Clifton, D. A. (2018) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2017.2763681 · Cited by 379
Self-Powered, One-Stop, and Multifunctional Implantable Triboelectric Active Sensor for Real-Time Biomedical Monitoring
Ma, Y., Zheng, Q., Liu, Y., Shi, B., Xue, X., Ji, W., Liu, Z., Jin, Y., Zou, Y., An, Z., et al. (2016) · Nano Letters · doi:10.1021/acs.nanolett.6b01968 · Cited by 367
Wearable Devices for Ambulatory Cardiac Monitoring
Sana, F., Isselbacher, E. M., Singh, J. P., Heist, E. K., Pathik, B., & Armoundas, A. A. (2020) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2020.01.046 · Cited by 362
2017 ACC/AHA/HRS Guideline for the Evaluation and Management of Patients With Syncope
Shen, W.-K., Sheldon, R. S., Benditt, D. G., Cohen, M. I., Forman, D. E., Goldberger, Z. D., Grubb, B. P., Hamdan, M. H., Krahn, A. D., Link, M. S., et al. (2017) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2017.03.003 · Cited by 327
High-Definition Medicine
Torkamani, A., Andersen, K. G., Steinhubl, S. R., & Topol, E. J. (2017) · Cell · doi:10.1016/j.cell.2017.08.007 · Cited by 253
Self-citation
Exercise therapy and cardiovascular toxicity in cancer
Scott, J. M., Nilsen, T. S., Gupta, D., & Jones, L. W. (2018) · Circulation · doi:10.1161/circulationaha.117.024671 · Cited by 239
A Chest‐Laminated Ultrathin and Stretchable E‐Tattoo for the Measurement of Electrocardiogram, Seismocardiogram, and Cardiac Time Intervals
Ha, T., Tran, J., Liu, S., Jang, H., Jeong, H., Mitbander, R., Huh, H., Qiu, Y., Duong, J., Wang, R. L., et al. (2019) · Advanced Science · doi:10.1002/advs.201900290 · Cited by 220
Big data from electronic health records for early and late translational cardiovascular research: challenges and potential
Hemingway, H., Asselbergs, F. W., Danesh, J., Dobson, R., Maniadakis, N., Maggioni, A. P., van Thiel, G. J. M. W., Cronin, M., Brobert, G., Vardas, P. E., et al. (2017) · European Heart Journal · doi:10.1093/eurheartj/ehx487 · Cited by 218
mHealth in Cardiovascular Health Care
Chow, C. K., Ariyarathna, N., Islam, S. M. S., Thiagalingam, A., & Redfern, J. (2016) · Heart Lung and Circulation · doi:10.1016/j.hlc.2016.04.009 · Cited by 205
Gyrocardiography: A New Non-invasive Monitoring Method for the Assessment of Cardiac Mechanics and the Estimation of Hemodynamic Variables
Tadi, M. J., Lehtonen, E., Saraste, A., Tuominen, J., Koskinen, J., Teräs, M., Airaksinen, J. K. E., Pänkäälä, M., & Koivisto, T. (2017) · Scientific Reports · doi:10.1038/s41598-017-07248-y · Cited by 179
Handheld Echocardiography
Chamsi‐Pasha, M. A., Sengupta, P. P., & Zoghbi, W. A. (2017) · Circulation · doi:10.1161/circulationaha.117.026622 · Cited by 170
Portable microfluidic and smartphone-based devices for monitoring of cardiovascular diseases at the point of care
Hu, J., Cui, X., Gong, Y. M., Xu, X., Gao, B., Wen, T., Lu, T. J., & Xu, F. (2016) · Biotechnology Advances · doi:10.1016/j.biotechadv.2016.02.008 · Cited by 158
Arrhythmia Classification with ECG signals based on the Optimization-Enabled Deep Convolutional Neural Network
Atal, D. K., & Singh, M. (2020) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2020.105607 · Cited by 146
Artificial intelligence algorithm for detecting myocardial infarction using six-lead electrocardiography
Cho, Y., Kwon, J., Kim, K., Medina‐Inojosa, J. R., Jeon, K., Cho, S., Lee, S. Y., Park, J., & Oh, B. (2020) · Scientific Reports · doi:10.1038/s41598-020-77599-6 · Cited by 148
Evaluation of remote dielectric sensing (ReDS) technology-guided therapy for decreasing heart failure re-hospitalizations
Amir, O., Gal, T. B., Weinstein, J. M., Schliamser, J. E., Burkhoff, D., Abbo, A., & Abraham, W. T. (2017) · International Journal of Cardiology · doi:10.1016/j.ijcard.2017.02.120 · Cited by 137
An Automatic Cardiac Arrhythmia Classification System With Wearable Electrocardiogram
Xia, Y., Zhang, H., Xu, L., Gao, Z., Zhang, H., Liu, H., & Li, S. (2018) · IEEE Access · doi:10.1109/access.2018.2807700 · Cited by 127
Internet of things, smart sensors, and pervasive systems: Enabling connected and pervasive healthcare
Pramanik, P. K. D., Upadhyaya, B. K., Pal, S., & Pal, T. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-815368-0.00001-4 · Cited by 122
Artificial Intelligence (AI) and Cardiovascular Diseases: An Unexpected Alliance
Romiti, S., Vinciguerra, M., Saade, W., Cortajarena, I. A., & Greco, E. (2020) · Cardiology Research and Practice · doi:10.1155/2020/4972346 · Cited by 109
Autonomic dysfunction in early breast cancer: Incidence, clinical importance, and underlying mechanisms
Gilchrist, S. C., Jones, L. W., Krone, R. J., Stein, P. K., & Scott, J. M. (2015) · American Heart Journal · doi:10.1016/j.ahj.2015.05.014 · Cited by 103
Wearable and implantable bioelectronics as eco‐friendly and patient‐friendly integrated nanoarchitectonics for next‐generation smart healthcare technology
Kim, S., Baek, S., Sluyter, R., Konstantinov, K., Kim, J. H., Kim, S., & Kim, J. H. (2023) · EcoMat · doi:10.1002/eom2.12356 · Cited by 105
Automated Detection of Atrial Fibrillation Based on Time–Frequency Analysis of Seismocardiograms
Hurnanen, T., Lehtonen, E., Tadi, M. J., Kuusela, T., Kiviniemi, T., Saraste, A., Vasankari, T., Airaksinen, J. K. E., Koivisto, T., & Pänkäälä, M. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2621887 · Cited by 91
Incidence of Idiopathic Ventricular Arrhythmias
Sirichand, S., Killu, A. M., Padmanabhan, D., Hodge, D. O., Chamberlain, A. M., Brady, P. A., Kapa, S., Noseworthy, P. A., Packer, D. L., Munger, T. M., et al. (2017) · Circulation Arrhythmia and Electrophysiology · doi:10.1161/circep.116.004662 · Cited by 85
Artificial Intelligence Assessment for Early Detection of Heart Failure with Preserved Ejection Fraction Based on Electrocardiographic Features
Kwon, J.-M., Kim, K.-H., Eisen, H. J., Cho, Y., Jeon, K.-H., Lee, S. Y., Park, J., & Oh, B.-H. (2021) · European Heart Journal - Digital Health · doi:10.1093/ehjdh/ztaa015 · Cited by 82
Use of smartphone technology in cardiology
Nguyen, H. H., & Silva, J. N. A. (2015) · Trends in Cardiovascular Medicine · doi:10.1016/j.tcm.2015.11.002 · Cited by 79
ECG by mobile technologies
Guzik, P., & Malík, M. (2016) · Journal of Electrocardiology · doi:10.1016/j.jelectrocard.2016.07.030 · Cited by 81
Wireless and battery-free platforms for collection of biosignals
Stuart, T., Cai, L., Burton, A., & Gutruf, P. (2021) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2021.113007 · Cited by 78
Strain‐Isolating Materials and Interfacial Physics for Soft Wearable Bioelectronics and Wireless, Motion Artifact‐Controlled Health Monitoring
Rodeheaver, N., Herbert, R., Kim, Y., Mahmood, M., Kim, H., Jeong, J., & Yeo, W. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202104070 · Cited by 76
Eco-friendly in-situ gap generation of no-spacer triboelectric nanogenerator for monitoring cardiovascular activities
Zhao, D., Zhuo, J., Chen, Z., Wu, J., Ma, R., Zhang, X., Zhang, Y., Wang, X., Wei, X., Liu, L., et al. (2021) · Nano Energy · doi:10.1016/j.nanoen.2021.106580 · Cited by 76
2021 ISHNE/HRS/EHRA/APHRS Expert Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society
Varma, N., Cygankiewicz, I., Turakhia, M. P., Heidbuchel, H., Hu, Y.-F., Chen, L. Y., Couderc, J.-P., Cronin, E. M., Estep, J. D., Grieten, L., et al. (2021) · Circulation: Arrhythmia and Electrophysiology · doi:10.1161/circep.120.009204 · Cited by 74
A Robust Fusion Model for Estimating Respiratory Rate From Photoplethysmography and Electrocardiography
Birrenkott, D. A., Pimentel, M. A. F., Watkinson, P. J., & Clifton, D. A. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2778265 · Cited by 71
Moving From Digitalization to Digitization in Cardiovascular Care
Steinhubl, S. R., & Topol, E. J. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.08.006 · Cited by 75
Self-citation
Skin‐Integrated Devices with Soft, Holey Architectures for Wireless Physiological Monitoring, With Applications in the Neonatal Intensive Care Unit
Kwak, S. S., Yoo, S., Avila, R. O., Chung, H. U., Jeong, H., Liu, C. Y., Vogl, J. L., Kim, J., Yoon, H., Park, Y., et al. (2021) · Advanced Materials · doi:10.1002/adma.202103974 · Cited by 70
Smart medical device selection based on intuitionistic fuzzy Choquet integral
Büyüközkan, G., & Göçer, F. (2018) · Soft Computing · doi:10.1007/s00500-018-3563-5 · Cited by 67
Digital healthcare: Historical development, applications, and future research directions
Sharma, R., & Kshetri, N. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102105 · Cited by 67
A digital health industry cohort across the health continuum
Cohen, A. B., Dorsey, E. R., Mathews, S. C., Bates, D. W., & Safavi, K. C. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0276-9 · Cited by 66
Feasibility of Using Wideband Microwave System for Non-Invasive Detection and Monitoring of Pulmonary Oedema
Rezaeieh, S. A., Zamani, A., Bialkowski, K. S., Mahmoud, A. A. O., & Abbosh, A. M. (2015) · Scientific Reports · doi:10.1038/srep14047 · Cited by 61
Single Drop Whole Blood Diagnostics: Portable Biomedical Sensor for Cardiac Troponin I Detection
Sarangadharan, I., Wang, S.-L., Sukesan, R., Chen, P., Dai, T.-Y., Pulikkathodi, A. K., Hsu, C.-P., Chiang, H.-H. K., Liu, L. Y., & Wang, Y. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.7b05018 · Cited by 60
Comparison of diagnostic value using a small, single channel, P-wave centric sternal ECG monitoring patch with a standard 3-lead Holter system over 24 hours
Smith, W., Riddell, F., Madon, M., & Gleva, M. J. (2016) · American Heart Journal · doi:10.1016/j.ahj.2016.11.006 · Cited by 59
A sneak peek into digital innovations and wearable sensors for cardiac monitoring
Michard, F. (2016) · Journal of Clinical Monitoring and Computing · doi:10.1007/s10877-016-9925-6 · Cited by 56
The genetics of congenital central hypoventilation syndrome: clinical implications
Bishara, J., Keens, T. G., & Perez, I. A. (2018) · The Application of Clinical Genetics · doi:10.2147/tacg.s140629 · Cited by 52
Remote Cardiac Rhythm Monitoring in the Era of Smart Wearables: Present Assets and Future Perspectives
Xintarakou, A., Sousonis, V., Asvestas, D., Vardas, P. E., & Tzeis, S. E. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.853614 · Cited by 58
2021 ISHNE/ HRS/ EHRA/ APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals
Varma, N., Cygankiewicz, I., Turakhia, M. P., Heidbüchel, H., Hu, Y., Chen, L. Y., Couderc, J., Cronin, E. M., Estep, J. D., Grieten, L., et al. (2021) · Annals of Noninvasive Electrocardiology · doi:10.1111/anec.12795 · Cited by 51
Congenital central hypoventilation syndrome: diagnosis and management
Maloney, M. A., Kun, S. S., Keens, T. G., & Perez, I. A. (2018) · Expert Review of Respiratory Medicine · doi:10.1080/17476348.2018.1445970 · Cited by 49
Multiclass Classifier based Cardiovascular Condition Detection Using Smartphone Mechanocardiography
Iftikhar, Z., Lahdenoja, O., Tadi, M. J., Hurnanen, T., Vasankari, T., Kiviniemi, T., Airaksinen, J. K. E., Koivisto, T., & Pänkäälä, M. (2018) · Scientific Reports · doi:10.1038/s41598-018-27683-9 · Cited by 48
Evaluation of a Smartphone Electrocardiograph in Healthy Horses: Comparison With Standard Base-apex Electrocardiography
Vezzosi, T., Sgorbini, M., Bonelli, F., Buralli, C., Pillotti, M., Meucci, V., & Tognetti, R. (2018) · Journal of Equine Veterinary Science · doi:10.1016/j.jevs.2018.03.006 · Cited by 44
First-In-Human Experience With Integration of Wireless Intracranial Pressure Monitoring Device Within a Customized Cranial Implant
Mitchell, K.-A. S., Anderson, W. S., Shay, T., Huang, J., Luciano, M. G., Suárez, J. I., Manson, P. N., Brem, H., & Gordon, C. R. (2020) · Operative Neurosurgery · doi:10.1093/ons/opz431 · Cited by 44
Atrial Fibrillation Detection
Thijs, V. (2017) · Stroke · doi:10.1161/strokeaha.117.017083 · Cited by 43
Diagnostic accuracy of a smartphone electrocardiograph in dogs: Comparison with standard 6-lead electrocardiography
Vezzosi, T., Buralli, C., Marchesotti, F., Porporato, F., Tognetti, R., Zini, E., & Domenech, O. (2016) · The Veterinary Journal · doi:10.1016/j.tvjl.2016.06.013 · Cited by 42
Comparison of Holter With Zio Patch Electrocardiography Monitoring in Children
Bolourchi, M., Silver, E. S., Muwanga, D., Mendez, E., & Liberman, L. (2019) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2019.11.028 · Cited by 41
ECG-derived spatial QRS-T angle is associated with ICD implantation, mortality and heart failure admissions in patients with LV systolic dysfunction
Gleeson, S., Liao, Y.-W., Dugo, C., Cave, A., Zhou, L., Ayar, Z., Christiansen, J., Scott, T., Dawson, L., Gavin, A., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0171069 · Cited by 40
Comprehensive Analysis of Cardiogenic Vibrations for Automated Detection of Atrial Fibrillation Using Smartphone Mechanocardiograms
Tadi, M. J., Mehrang, S., Kaisti, M., Lahdenoja, O., Hurnanen, T., Jaakkola, J., Jaakkola, S., Vasankari, T., Kiviniemi, T., Airaksinen, J. K. E., et al. (2018) · IEEE Sensors Journal · doi:10.1109/jsen.2018.2882874 · Cited by 38
2021 ISHNE/HRS/EHRA/APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals
Varma, N., Cygankiewicz, I., Turakhia, M. P., Heidbüchel, H., Hu, Y., Chen, L. Y., Couderc, J., Cronin, E. M., Estep, J. D., Grieten, L., et al. (2021) · Journal of Arrhythmia · doi:10.1002/joa3.12461 · Cited by 37
Health Informatics via Machine Learning for the Clinical Management of Patients
Niehaus, K. E., Charlton, P. H., Colopy, G. W., & Clifton, D. A. (2015) · Yearbook of Medical Informatics · doi:10.15265/iy-2015-014 · Cited by 39
Are heart rate monitors valuable tools for diagnosing arrhythmias in endurance athletes?
Gajda, R., Biernacka, E. K., & Drygas, W. (2017) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.12917 · Cited by 37
Anthracycline induced cardiotoxicity: biomarkers and “Omics” technology in the era of patient specific care
Moazeni, S., Cadeiras, M., Yang, E. H., Deng, M. C.-H. K., & Nguyen, K. (2017) · Clinical and Translational Medicine · doi:10.1186/s40169-017-0148-3 · Cited by 36
Cardio-Oncology rehabilitation- challenges and opportunities to improve cardiovascular outcomes in cancer patients and survivors
Sase, K., Kida, K., & Furukawa, Y. (2020) · Journal of Cardiology · doi:10.1016/j.jjcc.2020.07.014 · Cited by 39
Deep learning-based electrocardiogram rhythm and beat features for heart abnormality classification
Darmawahyuni, A., Nurmaini, S., Rachmatullah, M. N., Tutuko, B., Sapitri, A. I., Firdaus, F., Fansyuri, A., & Predyansyah, A. (2022) · PeerJ Computer Science · doi:10.7717/peerj-cs.825 · Cited by 40
An Algorithm for Heart Rate Extraction From Acoustic Recordings at the Neck
Sharma, P., Imtiaz, S. A., & Rodriguez–Villegas, E. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2836187 · Cited by 34
Comparison of Continuous ECG Monitoring by Wearable Patch Device and Conventional Telemonitoring Device
Choi, W., Kim, S., Lee, W., Kang, S., Yoon, C., Youn, T., & Chae, I. (2020) · Journal of Korean Medical Science · doi:10.3346/jkms.2020.35.e363 · Cited by 30
Establishing reference ranges for ambulatory electrocardiography parameters: meta-analysis
Williams, C., Andrade, J. G., Hawkins, N. M., Cheung, C. C., Krahn, A. D., Laksman, Z., Bennett, M. T., Heilbron, B. G., Chakrabarti, S., Yeung‐Lai‐Wah, J. A., et al. (2020) · Heart · doi:10.1136/heartjnl-2020-316925 · Cited by 29
AI-enhanced reconstruction of the 12-lead electrocardiogram via 3-leads with accurate clinical assessment
Mason, F., Pandey, A. C., Gadaleta, M., Topol, E. J., Muse, E. D., & Quer, G. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01193-7 · Cited by 30
Self-citation
A Novel Point-of-Care Smartphone Based System for Monitoring the Cardiac and Respiratory Systems
Sohn, K., Merchant, F. M., Sayadi, O., Puppala, D., Doddamani, R., Sahani, A. K., Singh, J. P., Heist, E. K., Isselbacher, E. M., & Armoundas, A. A. (2017) · Scientific Reports · doi:10.1038/srep44946 · Cited by 28
Stability, Consistency and Performance of Distribution Entropy in Analysing Short Length Heart Rate Variability (HRV) Signal
Karmakar, C. K., Udhayakumar, R. K., Li, P., Venkatesh, S., & Palaniswami, M. S. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.00720 · Cited by 28
Clinically recorded heart rate and incidence of 12 coronary, cardiac, cerebrovascular and peripheral arterial diseases in 233,970 men and women: A linked electronic health record study
Archangelidi, O., Pujades‐Rodríguez, M., Timmis, A., Jouven, X., Denaxas, S., & Hemingway, H. (2018) · European Journal of Preventive Cardiology · doi:10.1177/2047487318785228 · Cited by 27
Simulation of Daily Snapshot Rhythm Monitoring to Identify Atrial Fibrillation in Continuously Monitored Patients with Stroke Risk Factors
Yano, Y., Greenland, P., Lloyd‐Jones, D. M., Daoud, E. G., Koehler, J. L., & Ziegler, P. (2016) · PLoS ONE · doi:10.1371/journal.pone.0148914 · Cited by 25
Detecting heart failure using wearables: a pilot study
Shah, A. J., Isakadze, N., Levantsevych, O. M., Vest, A. N., Clifford, G. D., & Nemati, S. (2020) · Physiological Measurement · doi:10.1088/1361-6579/ab7f93 · Cited by 25
Breathable, Wireless, Thin-Film Wearable Biopatch Using Noise-Reduction Mechanisms
Rodeheaver, N., Kim, H., Herbert, R., Seo, H., & Yeo, W. (2022) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.1c01107 · Cited by 25
The Future of Arrhythmias and Electrophysiology
Albert, C. M., & Stevenson, W. G. (2016) · Circulation · doi:10.1161/circulationaha.116.023519 · Cited by 25
The Digital Outcome Measure
Cohen, A. B., & Mathews, S. C. (2018) · Digital Biomarkers · doi:10.1159/000492396 · Cited by 24
Flexible and wearable energy technologies: A lithium-ion battery perspective
YARAR, G., AKYÜZ, E. S., Aydın, Ö., Telli, E., & Farsak, M. (2025) · Journal of Alloys and Compounds · doi:10.1016/j.jallcom.2025.180103 · Cited by 26
Feasibility and performance of a device for automatic self-detection of symptomatic acute coronary artery occlusion in outpatients with coronary artery disease: a multicentre observational study
Heuverswyn, F. V., Buyzere, M. D., Coeman, M., Pooter, J. D., Drieghe, B., Duytschaever, M. F., Gevaert, S., Kayaert, P., Vandekerckhove, Y. R., Voet, J., et al. (2019) · The Lancet Digital Health · doi:10.1016/s2589-7500(19)30026-3 · Cited by 24
From wearables to THINKables: artificial intelligence-enabled sensors for health monitoring
Mirmomeni, M., Fazio, T., von Cavallar, S., & Harrer, S. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819246-7.00012-7 · Cited by 23
An IoT Assisted Real-Time High CMRR Wireless Ambulatory ECG Monitoring System with Arrhythmia Detection
Ali, H., Naing, H. H., & Yaqub, R. (2021) · Electronics · doi:10.3390/electronics10161871 · Cited by 22
The Digital Neurologic Examination
Cohen, A. B., & Nahed, B. V. (2021) · Digital Biomarkers · doi:10.1159/000515577 · Cited by 22
Perspective: Advancing Understanding of Population Nutrient–Health Relations via Metabolomics and Precision Phenotypes
Andraos, S., Wake, M. A., Saffery, R., Burgner, D. P., Kussmann, M., & O'Sullivan, J. M. (2019) · Advances in Nutrition · doi:10.1093/advances/nmz045 · Cited by 20
A Deep Learning Framework for Heart Disease Classification in an IoTs-Based System
Nguyen, T.-H., Nguyen, T.-N., & Nguyen, T.-T. (2019) · Intelligent systems reference library · doi:10.1007/978-3-030-23983-1_9 · Cited by 19
IoT: Electrocardiogram (ECG) Monitoring System
Ortiz, K. J. P., Davalos, J. P. O., Eusebio, E. S., & Tucay, D. M. (2018) · Indonesian Journal of Electrical Engineering and Computer Science · doi:10.11591/ijeecs.v10.i2.pp480-489 · Cited by 19
Evaluation of a new portable 1-lead digital cardiac monitor (eKuore) compared with standard base-apex electrocardiography in healthy horses
Vitale, V., Vezzosi, T., Tognetti, R., Fraschetti, C., & Sgorbini, M. (2021) · PLoS ONE · doi:10.1371/journal.pone.0255247 · Cited by 18
Evaluation of a new smartphone-based digital stethoscope featuring phonocardiography and electrocardiography in dogs and cats
Vezzosi, T., Alibrandi, L., Grosso, G., & Tognetti, R. (2023) · The Veterinary Journal · doi:10.1016/j.tvjl.2023.105987 · Cited by 18
Cardiac Diagnosis with Machine Learning: A Paradigm Shift in Cardiac Care
Laad, M. S., Kotecha, K. V., Patil, K. R., & Pise, R. N. (2022) · Applied Artificial Intelligence · doi:10.1080/08839514.2022.2031816 · Cited by 17
Using big data for non-communicable disease surveillance
Balicer, R. D., Luengo-Oroz, M. A., Cohen-Stavi, C. J., Loyola, E., Mantingh, F., Romanoff, L., & Galea, G. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(17)30372-8 · Cited by 17
A Real-Time Vital-Sign Monitoring in the Physical Domain on a Mixed-Signal Reconfigurable Platform
Shah, S. S., Töreyin, H., Güngör, C. B., & Hasler, J. (2019) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2019.2949778 · Cited by 18
The Role of Contemporary Wearable and Handheld Devices in the Diagnosis and Management of Cardiac Arrhythmias
Garikapati, K., Turnbull, S., Bennett, R. G., Campbell, T. G., Kanawati, J., Wong, M. S., Thomas, S. P., Chow, C. K., & Kumar, S. (2022) · Heart Lung and Circulation · doi:10.1016/j.hlc.2022.08.001 · Cited by 18
mCardia: A Context-Aware ECG Collection System for Ambulatory Arrhythmia Screening
Kumar, D., Maharjan, R., Maxhuni, A., Domínguez, H., Frølich, A., & Bardram, J. E. (2022) · ACM Transactions on Computing for Healthcare · doi:10.1145/3494581 · Cited by 16
2021 ISHNE/HRS/EHRA/APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals
Varma, N., Cygankiewicz, I., Turakhia, M. P., Heidbuchel, H., Hu, Y., Chen, L. Y., Couderc, J.-P., Cronin, E. M., Estep, J. D., Grieten, L., et al. (2021) · Cardiovascular Digital Health Journal · doi:10.1016/j.cvdhj.2020.11.004 · Cited by 16
Wireless body sensor for electrocardiographic monitoring in dogs and cats
Brložnik, M., Likar, S., Krvavica, A., Avbelj, V., & Petrič, A. D. (2018) · Journal of Small Animal Practice · doi:10.1111/jsap.12963 · Cited by 15
Smart Medical Device Selection Based on Interval Valued Intuitionistic Fuzzy VIKOR
Büyüközkan, G., & Göçer, F. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-66830-7_28 · Cited by 15
Estimating Heart Rate and Respiratory Rate from a Single Lead Electrocardiogram Using Ensemble Empirical Mode Decomposition and Spectral Data Fusion
Chung, I.-Q., Yu, J.-T., & Hu, W.-C. (2021) · Sensors · doi:10.3390/s21041184 · Cited by 14
Validation of a new wearable device for type 3 sleep test without flowmeter
Contini, M. C., Sarmento, A., Gugliandolo, P., Leonardi, A. D. C., Longinotti-Buitoni, G., Minella, C., Vignati, C., Mapelli, M., Aliverti, A., & Agostoni, P. (2021) · PLoS ONE · doi:10.1371/journal.pone.0249470 · Cited by 14
2021 ISHNE / HRS / EHRA / APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals
Varma, N., Cygankiewicz, I., Turakhia, M. P., Heidbüchel, H., Hu, Y., Chen, L. Y., Couderc, J., Cronin, E. M., Estep, J. D., Grieten, L., et al. (2021) · European Heart Journal - Digital Health · doi:10.1093/ehjdh/ztab001 · Cited by 17
Digital health technology to support care and improve outcomes of chronic kidney disease patients: as a case illustration, the Withings toolkit health sensing tools
Canaud, B., Kooman, J. P., Davenport, A., Campo, D., Carreel, E., Morena-Carrere, M., & Cristol, J. (2023) · Frontiers in Nephrology · doi:10.3389/fneph.2023.1148565 · Cited by 13
Big Data: What Is It and What Does It Mean for Cardiovascular Research and Prevention Policy
Pah, A. R., Rasmussen‐Torvik, L. J., Goel, S., Greenland, P., & Kho, A. (2014) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-014-0424-3 · Cited by 14
Health care in a technological world
Meetoo, D. D., Rylance, R., & Abuhaimid, H. A. (2018) · British Journal of Nursing · doi:10.12968/bjon.2018.27.20.1172 · Cited by 13

Authors: Walsh, J. A., Topol, E. J., & Steinhubl, S. R.
Affiliations: Scripps Green Hospital (US)
ORCID: Topol, Eric J.
Steinhubl, Steven R.
Venue: Circulation
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2014-08-12
Volume: 130
Issue: 7
Pages: 573-581
ISSN: 0009-7322 (ISSN-L)
1524-4539
DOI: 10.1161/circulationaha.114.009024
PMC: PMC4135373
OpenAlex: W1972902097
Cited by: 175
References: 40
Citations by year: 2026: 2 · 2025: 6 · 2024: 3 · 2023: 9 · 2022: 19 · 2021: 23 · 2020: 18 · 2019: 15 · 2018: 23 · 2017: 30 · 2016: 17 · 2015: 8 · 2014: 2
FWCI: 9.87
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Circulation (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health (UL1TR001114)
National Center for Advancing Translational Sciences
Topics: Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
Keywords: wireless devices, cardiac monitoring, biomedical implants, remote patient monitoring, cardiac implantable electronic devices
MeSH terms: Cardiovascular Diseases, Humans, Electrocardiography, Ambulatory, Cell Phone, Wireless Technology

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Novel Wireless Devices for Cardiac Monitoring

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks