Abstract
Wireless cardiac devices offer a novel method for remote monitoring of cardiac patients. Diagnosing the work of the heart, in the most basic approach, is mainly based on observing the hear rhythm.
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References
AlGhatrif, M., Lindsay, J.: A brief review: history to understand fundamentals of electrocardiography, J. Community Hosp. Intern. Med. Perspect. 2(1) (2012). https://doi.org/10.3402/jchimp.v2i1.14383. PMID: 23882360
Brugada J., et al.: 2019 ESC Guidelines for the management of patients with supraventricular tachycardia. The Task Force for the management of patients with supraventricular tachycardia of the European Society of Cardiology (ESC). Eur. Heart J. 41(5), 655–720 (2020). https://doi.org/10.1093/EURHEARTJ/EHZ467
Bernstein, R.A., et al.: Effect of long-term continuous cardiac monitoring vs usual care on detection of atrial fibrillation in patients with stroke attributed to large- or small-vessel disease: the STROKE-AF randomized clinical trial. JAMA 325(21), 2169–2177 (2021). https://doi.org/10.1001/JAMA.2021.6470
Charitakis, E., et al.: Comparing efficacy and safety in catheter ablation strategies for atrial fibrillation: a network meta-analysis. BMC Med. 20(1), 193 (2022). https://doi.org/10.1186/s12916-022-02385-2. PMID: 35637488; PMCID: PMC9153169
da Costa, F.A., et al.: Awareness campaigns of atrial fibrillation as an opportunity for early detection by pharmacists: an international cross-sectional study. J. Thromb. Thrombolysis 49(4), 606–617 (2019). https://doi.org/10.1007/s11239-019-02000-x
ECG Database: Lobachevsky University electrocardiography database. https://physionet.org/content/ludb/1.0.1/
ECG Database: MIT-BIH arrhythmia database. https://physionet.org/content/mitdb/1.0.0/
ECG Database: Mendeley, ECG signals. https://data.mendeley.com/datasets/7dybx7wyfn/3
Gladstone, D.J., et al.: Screening for atrial fibrillation in the older population: a randomized clinical trial. JAMA Cardiol. 6(5), 558–567 (2021). https://doi.org/10.1001/JAMACARDIO.2021.0038
Gautham, A., Venkitaraman, K.R.: Designing of a single arm single lead ECG system for wet and dry electrode: a comparison with traditional system. Biomed. Eng. Appl. Basis Commun. 28(03), 1650021 (2016). https://doi.org/10.4015/S1016237216500216
Hindricks G., et al.: 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS), The Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology (ESC) Developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC. Eur. Heart J. 42(5), 373–498 (2021). Erratum. In: Eur Heart J. 2021 Feb 1;42(5):507. Erratum in: Eur Heart J. 2021 Feb 1;42(5):546–547. Erratum in: Eur Heart J. 2021 Oct 21;42(40):4194. https://doi.org/10.1093/eurheartj/ehaa612. PMID: 32860505
Kazemi, M., Krishnan, M.B., Howe, T.A.: Frequency analysis of capnogram signals to differentiate asthmatic and non-asthmatic conditions using radial basis function neural networks Iran. J. Allergy Asthma Immunol. 12(3), 236–246 (2013). PMID: 23893807
Kim, N.H., Ko, J.S.: Introduction of wearable device in cardiovascular field for monitoring arrhythmia. Chonnam Med. J. 57(1), 1–6 (2021). https://doi.org/10.4068/CMJ.2021.57.1.1
Klempous, R., Nikodem, J., Kluwak, K., Jagielski, D.: Electrocardiographic shoulder device and the method of measuring the electrocardiographic signal. Patent: PL439675, WIPO ST 10/C, November 2021. (in polish)
Koyama, T., Kobayashi, M., Ichikawa, T., Wakabayashi, Y., Abe, H.: Application of capnography waveform analyses for evaluation of recovery process in a patient with heart failure: a case report. Arch. Clin. Med. Case Rep. 4(5), 779–787 (2020). https://doi.org/10.26502/acmcr.96550265
Mesin, L.: Heartbeat monitoring from adaptively down-sampled electrocardiogram. Comput. Biol. Med. 84(5), 217–225 (2017). https://doi.org/10.1016/J.COMPBIOMED.2017.03.023
Raj, P.S., Hatzinakos, D.: Feasibility of single-arm single-lead ECG biometrics. In: Proceeding of 22nd European Signal Processing Conference (EUSPICO), vol. 2525 (2014)
Shdefat, A., Joo, M., Kim, H.: A method of analyzing ECG to diagnose heart abnormality utilizing SVM and DWT. J. Multimed. Inf. Syst. 3(2), 35–42 (2016). https://doi.org/10.9717/JMIS.2016.3.2.35
Villegas, A., McEneaney, D., Escalona, O.: Arm-ECG wireless sensor system for wearable long-term surveillance of heart arrhythmias. Electronics 8(11), 1300 (2019). https://doi.org/10.3390/electronics8111300
Wilson, F.N., et al.: Recommendations for standardization of electrocardiographic and vectorcardiographic leads. Circulation 10(4), 564–573 (1954)
Acknowledgement
We want to thank Poliband Active Sp.z o.o. for partial financing of the implementation of this publication. We want to thank EMTEL Śliwa Sp.k. for providing the software enabling the export of ECG records to CSV files.
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Nikodem, J. et al. (2022). A Novel Approach to Continuous Heart Rhythm Monitoring for Arrhythmia Detection. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2022. EUROCAST 2022. Lecture Notes in Computer Science, vol 13789. Springer, Cham. https://doi.org/10.1007/978-3-031-25312-6_60
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