{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T15:23:26Z","timestamp":1782573806987,"version":"3.54.5"},"reference-count":283,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,24]],"date-time":"2020-03-24T00:00:00Z","timestamp":1585008000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006013","name":"United Arab Emirates University","doi-asserted-by":"publisher","award":["31R227"],"award-info":[{"award-number":["31R227"]}],"id":[{"id":"10.13039\/501100006013","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Health monitoring and its related technologies is an attractive research area. The electrocardiogram (ECG) has always been a popular measurement scheme to assess and diagnose cardiovascular diseases (CVDs). The number of ECG monitoring systems in the literature is expanding exponentially. Hence, it is very hard for researchers and healthcare experts to choose, compare, and evaluate systems that serve their needs and fulfill the monitoring requirements. This accentuates the need for a verified reference guiding the design, classification, and analysis of ECG monitoring systems, serving both researchers and professionals in the field. In this paper, we propose a comprehensive, expert-verified taxonomy of ECG monitoring systems and conduct an extensive, systematic review of the literature. This provides evidence-based support for critically understanding ECG monitoring systems\u2019 components, contexts, features, and challenges. Hence, a generic architectural model for ECG monitoring systems is proposed, an extensive analysis of ECG monitoring systems\u2019 value chain is conducted, and a thorough review of the relevant literature, classified against the experts\u2019 taxonomy, is presented, highlighting challenges and current trends. Finally, we identify key challenges and emphasize the importance of smart monitoring systems that leverage new technologies, including deep learning, artificial intelligence (AI), Big Data and Internet of Things (IoT), to provide efficient, cost-aware, and fully connected monitoring systems.<\/jats:p>","DOI":"10.3390\/s20061796","type":"journal-article","created":{"date-parts":[[2020,3,24]],"date-time":"2020-03-24T13:04:04Z","timestamp":1585055044000},"page":"1796","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":304,"title":["ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7001-3710","authenticated-orcid":false,"given":"Mohamed Adel","family":"Serhani","sequence":"first","affiliation":[{"name":"Department of Information Systems and Security, College of Information Technology, UAE University, Al Ain 15551, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hadeel","family":"T. El Kassabi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, College of Information Technology, UAE University, Al Ain 15551, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7891-9872","authenticated-orcid":false,"given":"Heba","family":"Ismail","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, College of Information Technology, UAE University, Al Ain 15551, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2787-523X","authenticated-orcid":false,"given":"Alramzana","family":"Nujum Navaz","sequence":"additional","affiliation":[{"name":"Department of Information Systems and Security, College of Information Technology, UAE University, Al Ain 15551, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,24]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2020, March 16). Cardiovascular Diseases. Available online: www.who.int\/health-topics\/cardiovascular-diseases\/#tab=tab_1."},{"key":"ref_2","unstructured":"Scutti, S. (2020, March 15). Nearly Half of US Adults Have Cardiovascular Disease, Study Says. Available online: www.cnn.com\/2019\/01\/31\/health\/heart-disease-statistics-report\/index.html."},{"key":"ref_3","unstructured":"(2017). European Cardiovascular Disease Statistics 2017, The European Heart Network (EHN). Available online: http:\/\/www.ehnheart.org\/cvd-statistics.html."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Hassan, M.F.U., Lai, D., and Bu, Y. (2019, January 17\u201319). Characterization of Single Lead Continuous ECG Recording with Various Dry Electrodes. Proceedings of the 2019 3rd International Conference on Computational Biology and Bioinformatics, Nagoya, Japan.","DOI":"10.1145\/3365966.3365974"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Preejith, S.P., Dhinesh, R., Joseph, J., and Sivaprakasam, M. (2016, January 16\u201320). Wearable ECG platform for continuous cardiac monitoring. Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Lake Buena Vista, FL, USA.","DOI":"10.1109\/EMBC.2016.7590779"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1109\/TITB.2010.2087386","article-title":"Apnea MedAssist: Real-time sleep apnea monitor using single-lead ECG","volume":"15","author":"Bsoul","year":"2011","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Azariadi, D., Tsoutsouras, V., Xydis, S., and Soudris, D. (2016, January 12\u201314). ECG signal analysis and arrhythmia detection on IoT wearable medical devices. Proceedings of the 2016 5th International Conference on Modern Circuits and Systems Technologies, MOCAST, Thessaloniki, Greece.","DOI":"10.1109\/MOCAST.2016.7495143"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1109\/JIOT.2017.2670022","article-title":"Real-time signal quality-aware ECG telemetry system for IoT-based health care monitoring","volume":"4","author":"Satija","year":"2017","journal-title":"IEEE Intern. Things J."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Scrugli, M.A., Loi, D., Raffo, L., and Meloni, P. (May, January 30). A runtime-adaptive cognitive IoT node for healthcare monitoring. Proceedings of the ACM International Conference on Computing Frontiers 2019, CF 2019\u2013Proceedings, Alghero, Italy.","DOI":"10.1145\/3310273.3323160"},{"key":"ref_10","first-page":"70","article-title":"An IoT Based Low-Cost ECG Monitoring System for Remote Patient","volume":"3","author":"Sanghavi","year":"2018","journal-title":"Int. J. Res. Trends Innov."},{"key":"ref_11","unstructured":"Kim, K. (2018). Europace Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography. Europace, 1\u20138."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Bansal, M., and Gandhi, B. (2019, January 14\u201316). IoT big data in smart healthcare (ECG monitoring). Proceedings of the International Conference on Machine Learning, Big Data, Cloud and Parallel Computing: Trends, Prespectives and Prospects, COMITCon, Faridabad, India.","DOI":"10.1109\/COMITCon.2019.8862197"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Taher, N.C., Mallat, I., Agoulmine, N., and El-Mawass, N. (2019, January 22\u201326). An IoT-Cloud based solution for real-time and batch processing of big data: Application in healthcare. Proceedings of the 2019 3rd International Conference on Bio-engineering for Smart Technologies BioSMART, Paris, France.","DOI":"10.1109\/BIOSMART.2019.8734185"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Chamadiya, B., Mankodiya, K., Wagner, M., and Hofmann, U.G. (2013). Textile-based, contactless ECG monitoring for non-ICU clinical settings. J. Ambient Intell. Humaniz. Comput., 4.","DOI":"10.1007\/s12652-012-0153-8"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zagan, I., Gaitan, V.G., Iuga, N., and Brezulianu, A. (2018, January 24\u201326). M-GreenCARDIO embedded system designed for out-of-hospital cardiac patients. Proceedings of the 2018 14th International Conference on Development and Application Systems, DAS, Suceava, Romania.","DOI":"10.1109\/DAAS.2018.8396063"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Navaz, A.N., Mohammed, E., Serhani, M.A., and Zaki, N. (2016, January 28\u201330). The use of data mining techniques to predict mortality and length of stay in an ICU. Proceedings of the 2016 12th International Conference on Innovations in Information Technology IIT, Al-Ain, United Arab Emirates.","DOI":"10.1109\/INNOVATIONS.2016.7880045"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ahouandjinou, A.S.R.M., Assogba, K., and Motamed, C. (2016, January 4\u20137). Smart and pervasive ICU based-IoT for improving intensive health care. Proceedings of the 2016 International Conference on Bio-Engineering for Smart Technologies BioSMART, Dubai, United Arab Emirates.","DOI":"10.1109\/BIOSMART.2016.7835599"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1001\/jama.2018.8102","article-title":"Effect of a home-Based wearable continuous ECG monitoring patch on detection of undiagnosed atrial fibrillation the mSToPS randomized clinical trial","volume":"320","author":"Steinhubl","year":"2018","journal-title":"JAMA J. Am. Med. Assoc."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Benhamida, A., Zouaoui, A., Sz\u00f3cska, G., Kar\u00f3czkai, K., Slimani, G., and Kozlovszky, M. (2019, January 24\u201326). Problems in archiving long-term continuous ECG data - A review. Proceedings of the SAMI 2019 - IEEE 17th World Symposium on Applied Machine Intelligence and Informatics, Herlany, Slovakia.","DOI":"10.1109\/SAMI.2019.8782737"},{"key":"ref_20","unstructured":"Shakthi Murugan, K.H., Sriram, T.J., Jerold, P.M., Peeran, A.S.A., and Abisheik, P. (2019, January 20\u201322). Wearable ECG electrodes for detection of heart rate and arrhythmia classification. Proceedings of the 2019 3rd IEEE International Conference on Electrical, Computer and Communication Technologies ICECCT, Coimbatore, India."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.jelectrocard.2014.12.005","article-title":"A modified Lewis ECG lead system for ambulatory monitoring of atrial arrhythmias","volume":"48","author":"Petrenas","year":"2015","journal-title":"J. Electrocardiol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"149","DOI":"10.3389\/fphys.2015.00149","article-title":"Electrocardiographic patch devices and contemporary wireless cardiac monitoring","volume":"6","author":"Fung","year":"2015","journal-title":"Front. Physiol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2456","DOI":"10.1109\/TBME.2011.2156795","article-title":"Compressed sensing for real-time energy-efficient ECG compression on wireless body sensor nodes","volume":"58","author":"Mamaghanian","year":"2011","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Guan, K., Shao, M., and Wu, S. (2017). A remote health monitoring system for the elderly based on smart home gateway. J. Healthc. Eng., 2017.","DOI":"10.1155\/2017\/5843504"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Akrivopoulos, O., Antoniou, A., Amaxilatis, D., and Chatzigiannakis, I. (2017, January 6\u20138). Design and evaluation of a person-centric heart monitoring system over fog computing infrastructure. Proceedings of the HumanSys 2017 - 1st International Workshop on Human-Centered Sensing, Networking, and Systems, Part of SenSys, Delft, The Netherlands.","DOI":"10.1145\/3144730.3144736"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.future.2019.10.043","article-title":"HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments","volume":"104","author":"Tuli","year":"2020","journal-title":"Futur. Gener. Comput. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Neyja, M., Mumtaz, S., Huq, K.M.S., Busari, S.A., Rodriguez, J., and Zhou, Z. (2017, January 4\u20138). An IoT-based e-health monitoring system using ECG signal. Proceedings of the GLOBECOM 2017 IEEE Global Communications Conference, Singapore.","DOI":"10.1109\/GLOCOM.2017.8255023"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"237","DOI":"10.3233\/AIS-190523","article-title":"Utilising fog computing for developing a person-centric heart monitoring system","volume":"11","author":"Akrivopoulos","year":"2019","journal-title":"J. Ambient Intell. Smart Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/j.future.2018.04.024","article-title":"Optimization of signal quality over comfortability of textile electrodes for ECG monitoring in fog computing based medical applications","volume":"86","author":"Wu","year":"2018","journal-title":"Futur. Gener. Comput. Syst."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1007\/978-3-642-23508-5_244","article-title":"Wearable patient home monitoring based on ECG and ACC sensors","volume":"37","author":"Augustyniak","year":"2011","journal-title":"IFMBE Proc."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Yusof, M.A., and Hau, Y.W. (2018, January 3\u20136). Mini home-based vital sign monitor with android mobile application (myVitalGear). Proceedings of the 2018 IEEE EMBS Conference on Biomedical Engineering and Science IECBES, Sarawak, Malaysia.","DOI":"10.1109\/IECBES.2018.8626639"},{"key":"ref_32","first-page":"9940","article-title":"Intelligent healthcare system using an arduino microcontroller and an android-based smartphone","volume":"28","author":"Hsieh","year":"2017","journal-title":"BioMed Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.snb.2009.04.040","article-title":"Wireless sensor network based wearable smart shirt for ubiquitous health and activity monitoring","volume":"140","author":"Lee","year":"2009","journal-title":"Sens. Actuators B Chem."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Pirozzi, M., Pietroni, F., Casaccia, S., Scalise, L., and Revel, G.M. (2018, January 11\u201313). Cardiac activity classification using an E-health app for a wearable device. Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications MeMeA, Rome, Italy.","DOI":"10.1109\/MeMeA.2018.8438674"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Schneider, J., Schroth, M., Ottenbacher, J., and Stork, W. (2018, January 12\u201314). A novel wearable sensor device for continuous monitoring of cardiac activity during sleep. Proceedings of the 2018 IEEE Sensors Applications Symposium SAS, Seoul, Korea.","DOI":"10.1109\/SAS.2018.8336725"},{"key":"ref_36","first-page":"202","article-title":"12-lead Holter monitoring in diving and water sports: A preliminary investigation","volume":"44","author":"Bosco","year":"2014","journal-title":"Diving Hyperb. Med."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Rakovi\u0107, P., and Lutovac, B. (2015, January 14\u201318). A cloud computing architecture with wireless body area network for professional athletes health monitoring in sports organizations\u2014Case study of Montenegro. Proceedings of the 2015 4th Mediterranean Conference on Embedded Computing (MECO), Budva, Montenegro.","DOI":"10.1109\/MECO.2015.7181950"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Octaviani, V., Kurniawan, A., Suprapto, Y.K., and Zaini, A. (2017, January 19\u201321). Alerting system for sport activity based on ECG signals using proportional integral derivative. Proceedings of the 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), Yogyakarta, Indonesia.","DOI":"10.1109\/EECSI.2017.8239104"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.jad.2016.04.051","article-title":"Nighttime heart rate predicts response to depression treatment in patients with coronary heart disease","volume":"200","author":"Carney","year":"2016","journal-title":"J. Affect. Disord."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1034","DOI":"10.1109\/JBHI.2016.2554546","article-title":"Predicting mood changes in bipolar disorder through heartbeat nonlinear dynamics","volume":"20","author":"Valenza","year":"2016","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Migliorini, M., Mariani, S., Bertschy, G., Kosel, M., and Bianchi, A.M. (2015, January 25\u201329). Can home-monitoring of sleep predict depressive episodes in bipolar patients?. Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Milano, Italy.","DOI":"10.1109\/EMBC.2015.7318831"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1743","DOI":"10.1088\/0967-3334\/36\/8\/1743","article-title":"RS slope detection algorithm for extraction of heart rate from noisy, multimodal recordings","volume":"36","author":"Grzegorczyk","year":"2015","journal-title":"Physiol. Meas."},{"key":"ref_43","unstructured":"Ghosh, S., Feng, M., Nguyen, H., and Li, J. (2014, January 7\u201310). Predicting heart beats using co-occurring constrained sequential patterns. Proceedings of the Computing in Cardiology 2014, Cambridge, MA, USA."},{"key":"ref_44","unstructured":"Yang, B., Teo, S.K., Hoeben, B., Monterola, C., and Su, Y. (2014, January 7\u201310). Robust identification of heartbeats with blood pressure signals and noise detection. Proceedings of the Computing in Cardiology 2014, Cambridge, MA, USA."},{"key":"ref_45","unstructured":"Giera\u0142towski, J.J., Ciuchci\u0144ski, K., Grzegorczyk, I., Ko\u015bna, K., Soli\u0144ski, M., and Podziemski, P. (2014, January 7\u201310). Heart rate variability discovery: Algorithm for detection of heart rate from noisy, multimodal recordings. Proceedings of the Computing in Cardiology 2014, Cambridge, MA, USA."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"64003","DOI":"10.1088\/1361-6579\/aac76c","article-title":"A low-complexity algorithm for detection of atrial fibrillation using an ECG","volume":"39","author":"Sadr","year":"2018","journal-title":"Physiol. Meas."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/JBHI.2017.2686436","article-title":"Automated ECG noise detection and classification system for unsupervised healthcare monitoring","volume":"22","author":"Satija","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_48","unstructured":"Bhattacherjee, P., Ganguly, D., and Chatterjee, K. (2019, January 5\u20136). A review of Steganography techniques suitable for ECG signal. Proceedings of the International Conference on Emerging Technologies for Sustainable Development (ICETSD \u201919), Kolkata, India."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1109\/51.248164","article-title":"Intelligent patient monitoring and management systems: A review","volume":"12","author":"Mora","year":"1993","journal-title":"IEEE Eng. Med. Biol. Mag."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/S0031-3203(99)00065-5","article-title":"Knowledge-based ECG interpretation: A critical review","volume":"33","author":"Kundu","year":"2000","journal-title":"Pattern Recognit."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Sohn, H., Farrar, C.R., Hemez, F.M., Shunk, D.D., Stinemates, D.W., Nadler, B.R., and Czarnecki, J.J. (2003). A Review of Structural Health Monitoring Literature: 1996\u20132001.","DOI":"10.1117\/12.434158"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Windmiller, J.R., and Wang, J. (2013). Wearable electrochemical sensors and biosensors: A review. Electroanalysis, 25.","DOI":"10.1002\/elan.201200349"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1007\/s11517-012-1021-6","article-title":"A comprehensive survey of wearable and wireless ECG monitoring systems for older adults","volume":"51","author":"Baig","year":"2013","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s10916-017-0760-1","article-title":"A systematic review of wearable patient monitoring systems\u2013current challenges and opportunities for clinical adoption","volume":"41","author":"Baig","year":"2017","journal-title":"J. Med. Syst."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"17472","DOI":"10.3390\/s131217472","article-title":"Data mining for wearable sensors in health monitoring systems: A review of recent trends and challenges","volume":"13","author":"Banaee","year":"2013","journal-title":"Sensors"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Marston, H.R., Hadley, R., Banks, D., and Duro, M.D.C.M. (2019). Mobile self-monitoring ECG devices to diagnose arrhythmia that coincide with palpitations: A scoping review. Healthcare, 7.","DOI":"10.2196\/preprints.13251"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/S1474-4422(15)70027-X","article-title":"Diagnosis of atrial fibrillation after stroke and transient ischaemic attack: A systematic review and meta-analysis","volume":"14","author":"Sposato","year":"2015","journal-title":"Lancet Neurol."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Tejedor, J., Garc\u00eda, C.A., M\u00e1rquez, D.G., Raya, R., and Otero, A. (2019). Multiple physiological signals fusion techniques for improving heartbeat detection: A review. Sensors, 19.","DOI":"10.3390\/s19214708"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.entcs.2019.04.009","article-title":"Emotion recognition from physiological signal analysis: A review","volume":"343","author":"Egger","year":"2019","journal-title":"Electron. Notes Theor. Comput. Sci."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.bspc.2014.07.002","article-title":"Wavelet-based electrocardiogram signal compression methods and their performances: A prospective review","volume":"14","author":"Dandapat","year":"2014","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Jeong, D.-U., and Kim, S.-J. (2008, January 11\u201313). Development of a technique for cancelling motion artifact in ambulatory ECG monitoring system. Proceedings of the 2008 Third International Conference on Convergence and Hybrid Information Technology, Busan, Korea.","DOI":"10.1109\/ICCIT.2008.315"},{"key":"ref_62","unstructured":"De Cooman, T., Goovaerts, G., Varon, C., Widjaja, D., and Van Huffel, S. (2014, January 7\u201310). Heart beat detection in multimodal data using signal recognition and beat location estimation. Proceedings of the Computing in Cardiology 2014, Cambridge, MA, USA."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Li, Z., Derksen, H., Gryak, J., Ghanbari, H., Gunaratne, P., and Najarian, K. (2018, January 18\u201321). A novel atrial fibrillation prediction algorithm applicable to recordings from portable devices. Proceedings of the 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HA, USA.","DOI":"10.1109\/EMBC.2018.8513006"},{"key":"ref_64","unstructured":"Ding, Q., Bai, Y., Erol, Y.B., Salas-Boni, R., Zhang, X., Li, L., and Hu, X. (2014, January 7\u201310). Multimodal information fusion for robust heart beat detection. Proceedings of the Computing in Cardiology 2014, Cambridge, MA, USA."},{"key":"ref_65","unstructured":"Vollmer, M. (2014, January 7\u201310). Robust detection of heart beats using dynamic thresholds and moving windows. Proceedings of the Computing in Cardiology 2014, Cambridge, MA, USA."},{"key":"ref_66","unstructured":"Yusuf, S.A.A., and Hidayat, R. (2019, January 26\u201327). MFCC feature extraction and KNN classification in ECG signals. Proceedings of the 2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE), Semarang, Indonesia."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Kora, P., Kumari, C.U., Swaraja, K., and Meenakshi, K. (2019, January 20\u201322). Atrial Fibrillation detection using Discrete Wavelet Transform. Proceedings of the 2019 3rd IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), Coimbatore, India.","DOI":"10.1109\/ICECCT.2019.8869498"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Vernekar, S., Vijaysenan, D., and Ranjan, R. (2016, January 11\u201314). A novel approach for Robust Detection of Heart Beats in Multimodal Data using neural networks and boosted trees. Proceedings of the 2016 Computing in Cardiology Conference (CinC), Vancouver, BC, Canada.","DOI":"10.22489\/CinC.2016.325-127"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Zhang, H., Wang, Z., Dong, K., Ng, S.H., and Lin, Z. (2017, January 11\u201315). Towards precise tracking of electric-mechanical cardiac time intervals through joint ECG and BCG sensing and signal processing. Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Seogwipo, Korea.","DOI":"10.1109\/EMBC.2017.8036933"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1088\/0967-3334\/36\/8\/1691","article-title":"Heart beat detection in multimodal data using automatic relevant signal detection","volume":"36","author":"Goovaerts","year":"2015","journal-title":"Physiol. Meas."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.cmpb.2012.11.008","article-title":"Cloud-ECG for real time ECG monitoring and analysis","volume":"110","author":"Xia","year":"2013","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1111\/anec.12204","article-title":"Cloud-based privacy-preserving remote ECG monitoring and surveillance","volume":"20","author":"Page","year":"2015","journal-title":"Ann. Noninvasive Electrocardiol."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/TBCAS.2013.2260159","article-title":"A configurable and low-power mixed signal SoC for portable ECG monitoring applications","volume":"8","author":"Kim","year":"2014","journal-title":"IEEE Trans. Biomed. Circ. Syst."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Mart\u00edn-Yebra, A., Landreani, F., Casellato, C., Pavan, E., Frigo, C., Migeotte, P., and Caiani, E.G. (2015, January 6\u20139). Studying heart rate variability from ballistocardiography acquired by force platform: Comparison with conventional ECG. Proceedings of the 2015 Computing in Cardiology Conference (CinC), Nice, France.","DOI":"10.1109\/CIC.2015.7411064"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Mohaar, G., Maleque, M., and Singh, R. (2015, January 24\u201327). Framework for stochastic modelling of multi-dimensional real-time sensor data. Proceedings of the 2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), Taipei, Taiwan.","DOI":"10.1109\/ISKE.2015.63"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Serhani, M.A., Benharref, A., and Nujum, A.R. (2014, January 26\u201330). Intelligent remote health monitoring using evident-based DSS for automated assistance. Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, IL, USA.","DOI":"10.1109\/EMBC.2014.6944173"},{"key":"ref_77","first-page":"178","article-title":"ECG based human authentication: A review","volume":"2","author":"Nawal","year":"2014","journal-title":"Int. J. Emerg. Eng. Res. Technol."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Gusev, M., Stojmenski, A., and Guseva, A. (2017, January 18\u201323). ECGalert: A Heart Attack Alerting System. Proceedings of the 9th International Conference, Skopje, Macedonia.","DOI":"10.1007\/978-3-319-67597-8_3"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"N\u011bmcov\u00e1, A., Sm\u00ed\u0161ek, R., Mar\u0161\u00e1nov\u00e1, L., Smital, L., and V\u00edtek, M. (2018). A comparative analysis of methods for evaluation of ECG signal quality after compression. BioMed Res. Int., 2018.","DOI":"10.1155\/2018\/1868519"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Villegas, A., McEneaney, D., and Escalona, O. (2019). Arm-ECG wireless sensor system for wearable long-term surveillance of heart arrhythmias. Electronics, 8.","DOI":"10.3390\/electronics8111300"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Llanas, A., Guill\u00e9n, J., Cardiel, E., and Hern\u00e1ndez, P.-R. (2018, January 5\u20137). Development of an interactive system for the visualization of a cardiac model activated by the R-Wave of ECG in a 3D CAVE. Proceedings of the 2018 15th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), Mexico City, Mexico.","DOI":"10.1109\/ICEEE.2018.8533919"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Motalova, L., Krejcar, O., Polak, T., Janckulik, D., and Cernohorsky, J. (2011, January 21\u201324). ECG data visualisation in web application using MS Silverlight. Proceedings of the 2011 1st Middle East Conference on Biomedical Engineering, Sharjah, United Arab Emirates.","DOI":"10.1109\/MECBME.2011.5752137"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1109\/TITB.2010.2047865","article-title":"A wearable smartphone-based platform for real-time cardiovascular disease detection via electrocardiogram processing","volume":"14","author":"Oresko","year":"2010","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"S\u00f6rnmo, L., and Laguna, P. (2006). Electrocardiogram (ECG) signal processing. Wiley Encycl. Biomed. Eng.","DOI":"10.1002\/9780471740360.ebs1482"},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Ding, H., Sun, H., and Hou, K. (2011, January 9\u201311). Abnormal ECG signal detection based on compressed sampling in Wearable ECG sensor. Proceedings of the 2011 International Conference on Wireless Communications and Signal Processing (WCSP), Nanjing, China.","DOI":"10.1109\/WCSP.2011.6096677"},{"key":"ref_86","first-page":"797","article-title":"An exploration of ECG signal feature selection and classification using machine learning techniques","volume":"9","author":"Shankar","year":"2020","journal-title":"Int. J. Innovative Technol. Exploring Eng. Regul. Issue"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"188","DOI":"10.32622\/ijrat.732019143","article-title":"A study on ECG signal analysis and ECG databases","volume":"7","author":"Karnewar","year":"2019","journal-title":"Int. J. Res. Advent Technol."},{"key":"ref_88","first-page":"206","article-title":"A survey of data mining algorithms used in cardiovascular disease diagnosis from multi-lead ECG data","volume":"42","author":"Moses","year":"2015","journal-title":"Kuwait J. Sci."},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Ghodake, S., Ghumbre, S., and Deshmukh, S. (2020). Electrocardiogram Signal Denoising Using Hybrid Filtering for Cardiovascular Diseases Prediction. Techno-Societal 2018, Springer.","DOI":"10.1007\/978-3-030-16848-3_26"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"30","DOI":"10.5815\/ijigsp.2019.02.04","article-title":"An automated detection of CAD using the method of signal decomposition and non linear entropy using heart signals","volume":"11","author":"Padmavathi","year":"2019","journal-title":"Int. J. Image Graph. Signal Process."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Tychkov, A., Alimuradov, A., and Churakov, P. (2019, January 9\u201311). The emperical mode decomposition for ECG signal preprocessing. Proceedings of the 2019 3rd School on Dynamics of Complex Networks and their Application in Intellectual Robotics, DCNAIR, Innopolis, Russia.","DOI":"10.1109\/DCNAIR.2019.8875613"},{"key":"ref_92","unstructured":"Wang, Y. (2018). An automated ECG Signal Quality Assessment Method with Supervised Learning Algorithm, Delft University of Technology."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Deriche, M., Aljabri, S., Al-Akhras, M., Siddiqui, M., and Deriche, N. (2019, January 21\u201324). An optimal set of features for multi-class heart beat abnormality classification. Proceedings of the 2019 16th International Multi-Conference on Systems, Signals & Devices (SSD), Istanbul, Turkey.","DOI":"10.1109\/SSD.2019.8893151"},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Kwon, S., Lee, D., Kim, J., Lee, Y., Kang, S., Seo, S., and Park, K. (2016). Sinabro: A smartphone-integrated opportunistic electrocardiogram monitoring system. Sensors, 16.","DOI":"10.3390\/s16030361"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"276","DOI":"10.3844\/ajassp.2008.276.281","article-title":"ECG signal denoising by wavelet transform thresholding","volume":"5","author":"Alfaouri","year":"2008","journal-title":"Am. J. Appl. Sci."},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Valupadasu, R., and Chunduri, B.R.R. (2019, January 2\u20135). Automatic classification of cardiac disorders using MLP algorithm. Proceedings of the 2019 Prognostics and System Health Management Conference PHM-Paris, Paris, France.","DOI":"10.1109\/PHM-Paris.2019.00050"},{"key":"ref_97","first-page":"75","article-title":"Electrocardiogram (ECG) classification based on dynamic beats segmentation","volume":"09-11-May-","author":"Tantawi","year":"2016","journal-title":"ACM Int. Conf. Proc. Ser."},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wang, L., Zhang, W., and Yao, J. (2018, January 3\u20136). A signal quality assessment method for electrocardiography acquired by mobile device. Proceedings of the 2018 IEEE International Conference on Bioinformatics and Biomedicine BIBM, Madrid, Spain.","DOI":"10.1109\/BIBM.2018.8621160"},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"100286","DOI":"10.1016\/j.imu.2019.100286","article-title":"Quality analysis of heart rate derived from functional near-infrared spectroscopy in stress assessment","volume":"18","author":"Mirbagheri","year":"2019","journal-title":"Inform. Med. Unlocked"},{"key":"ref_100","doi-asserted-by":"crossref","unstructured":"Satija, U., Ramkumar, B., and Manikandan, M.S. (2015, January 19\u201320). A simple method for detection and classification of ECG noises for wearable ECG monitoring devices. Proceedings of the 2nd International Conference on Signal Processing and Integrated Networks SPIN, Noida, India.","DOI":"10.1109\/SPIN.2015.7095425"},{"key":"ref_101","doi-asserted-by":"crossref","unstructured":"Lamba, P., and Rawal, K. (2019, January 24\u201326). A survey of algorithms for feature extraction and feature classification methods. Proceedings of the 2019 International Conference on Automation, Computational and Technology Management (ICACTM), London, UK.","DOI":"10.1109\/ICACTM.2019.8776804"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ejmp.2020.01.007","article-title":"1D-CADCapsNet: One dimensional deep capsule networks for coronary artery disease detection using ECG signals","volume":"70","author":"Butun","year":"2020","journal-title":"Phys. Medica"},{"key":"ref_103","doi-asserted-by":"crossref","unstructured":"\u015eEN, S.Y., and \u00d6ZKURT, N. (November, January 31). ECG arrhythmia classification by using convolutional neural network and spectrogram. Proceedings of the 2019 Innovations in Intelligent Systems and Applications Conference (ASYU), Izmir, Turkey.","DOI":"10.1109\/ASYU48272.2019.8946417"},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Shashikumar, S.P., Shah, A.J., Li, Q., Clifford, G.D., and Nemati, S. (2017, January 16\u201319). A deep learning approach to monitoring and detecting atrial fibrillation using wearable technology. Proceedings of the 2017 IEEE EMBS International Conference on Biomedical and Health Informatics BHI, Orlando, FL, USA.","DOI":"10.1109\/BHI.2017.7897225"},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.jpdc.2018.08.010","article-title":"A wearable sensor-based activity prediction system to facilitate edge computing in smart healthcare system","volume":"123","author":"Uddin","year":"2019","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_106","doi-asserted-by":"crossref","unstructured":"Carnevale, L., Celesti, A., Fazio, M., and Villari, M. (2020). A Big Data Analytics Approach for the Development of Advanced Cardiology Applications. Information, 11.","DOI":"10.3390\/info11020060"},{"key":"ref_107","doi-asserted-by":"crossref","unstructured":"Krejcar, O., Janckulik, D., Motalova, L., Musil, K., and Penhaker, M. (2010). Real time measurement and visualization of ECG on mobile monitoring stations of biotelemetric system. Advances in Intelligent Information and Database Systems, Springer.","DOI":"10.1007\/978-3-642-12090-9_6"},{"key":"ref_108","unstructured":"(2020, February 10). Medical Expo, the Online Medical Device Exhibition. Available online: https:\/\/www.medicalexpo.com\/medical-manufacturer\/electrocardiography-software-16421.html."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"481","DOI":"10.4338\/ACI-2010-12-RA-0078","article-title":"Near field communication-based telemonitoring with integrated ECG recordings","volume":"2","author":"Morak","year":"2011","journal-title":"Appl. Clin. Inform."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.bspc.2018.04.013","article-title":"Mobile cloud computing for ECG telemonitoring and real-time coronary heart disease risk detection","volume":"44","author":"Venkatesan","year":"2018","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1109\/JBHI.2013.2286157","article-title":"Enabling smart personalized healthcare: A hybrid mobile-cloud approach for ECG telemonitoring","volume":"18","author":"Wang","year":"2014","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_112","doi-asserted-by":"crossref","unstructured":"Benini, A., Donati, M., Iacopetti, F., and Fanucci, L. (2014, January 2\u20134). User-friendly single-lead ECG device for home telemonitoring applications. Proceedings of the International Symposium on Medical Information and Communication Technology ISMICT, Firenze, Italy.","DOI":"10.1109\/ISMICT.2014.6825206"},{"key":"ref_113","doi-asserted-by":"crossref","unstructured":"Al Hemairy, M., Serhani, M., Amin, S., and Alahmad, M. (2018). A Comprehensive Framework for Elderly Healthcare Monitoring in Smart Environment, Springer.","DOI":"10.1007\/978-3-319-60137-3_6"},{"key":"ref_114","unstructured":"Wang, Y.H., Chung, C.G., Lin, C.C., and Lin, C.M. (July, January 30). The study of the electrocardiography monitoring for the elderly based on smart clothes. Proceedings of the 8th International Conference on Information Science and Technology ICIST, Cordoba, Spain."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"9128054","DOI":"10.1155\/2018\/9128054","article-title":"Mobile personal health monitoring for automated classification of electrocardiogram signals in elderly","volume":"2018","author":"Mena","year":"2018","journal-title":"Comput. Math. Methods Med."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"2721","DOI":"10.1161\/01.CIR.0000145144.56673.59","article-title":"Practice standards for electrocardiographic monitoring in hospital settings: An American Heart Association scientific statement from the councils on cardiovascular nursing, clinical cardiology, and cardiovascular disease in the young","volume":"110","author":"Drew","year":"2004","journal-title":"Circulation"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"e13","DOI":"10.1016\/j.resuscitation.2019.06.040","article-title":"ECG monitoring in in-hospital cardiac arrest (IHCA)","volume":"142","author":"Rawshani","year":"2019","journal-title":"Resuscitation"},{"key":"ref_118","doi-asserted-by":"crossref","unstructured":"Mahdy, L.N., Ezzat, K.A., and Tan, Q. (2018, January 1\u20133). Smart ECG Holter monitoring system using smartphone. Proceedings of the 2018 IEEE International Conference on Internet of Things and Intelligence System IOTAIS, Bali, Indonesia.","DOI":"10.1109\/IOTAIS.2018.8600891"},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"3357","DOI":"10.1161\/STROKEAHA.113.001884","article-title":"Improved detection of silent atrial fibrillation using 72-hour holter ecg in patients with ischemic stroke: A prospective multicenter cohort study","volume":"44","author":"Grond","year":"2013","journal-title":"Stroke"},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"95.e11","DOI":"10.1016\/j.amjmed.2013.10.003","article-title":"Comparison of 24-hour Holter monitoring with 14-day novel adhesive patch electrocardiographic monitoring","volume":"127","author":"Barrett","year":"2014","journal-title":"Am. J. Med."},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.ahj.2014.06.018","article-title":"Finding atrial fibrillation in stroke patients: Randomized evaluation of enhanced and prolonged Holter monitoring\u2014Find-AFRANDOMISED\u2014Rationale and design","volume":"168","author":"Gelbrich","year":"2014","journal-title":"Am. Heart J."},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"e55","DOI":"10.1016\/j.hrthm.2017.03.038","article-title":"2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring\/telemetry","volume":"14","author":"Steinberg","year":"2017","journal-title":"Heart Rhythm"},{"key":"ref_123","first-page":"1580","article-title":"Real time physiological status monitorinig through telemetry system for on-spot-accident patients using IoT","volume":"3","author":"Jebin","year":"2019","journal-title":"Int. J. Trend Sci. Res. Dev."},{"key":"ref_124","doi-asserted-by":"crossref","unstructured":"Yama, Y., Ueno, A., and Uchikawa, Y. (2007, January 23\u201326). Development of a wireless capacitive sensor for ambulatory ECG monitoring over clothes. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology, Lyon, France.","DOI":"10.1109\/IEMBS.2007.4353647"},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.jelectrocard.2019.02.012","article-title":"The quality of ECG data acquisition, and diagnostic performance of a novel adhesive patch for ambulatory cardiac rhythm monitoring in arrhythmia detection","volume":"54","author":"Yurtseven","year":"2019","journal-title":"J. Electrocardiol."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"1112","DOI":"10.1109\/TBCAS.2016.2519523","article-title":"Wearable noncontact armband for mobile ECG monitoring system","volume":"10","author":"Rachim","year":"2016","journal-title":"IEEE Trans. Biomed. Circ. Syst."},{"key":"ref_127","doi-asserted-by":"crossref","unstructured":"Wang, Y., Doleschel, S., Wunderlich, R., and Heinen, S. (2015). A wearable wireless ECG monitoring system With dynamic transmission power control for long-term homecare. J. Med. Syst., 39.","DOI":"10.1007\/s10916-015-0223-5"},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"S24","DOI":"10.1016\/j.cjca.2018.07.411","article-title":"A novel form of wearable ecg sensors for continuous ambulatory rhythm monitoring: Proof of concept and assessment of signal quality","volume":"34","author":"Steinberg","year":"2018","journal-title":"Can. J. Cardiol."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1049\/iet-syb.2015.0012","article-title":"Remote health monitoring system for detecting cardiac disorders","volume":"9","author":"Bansal","year":"2015","journal-title":"IET Syst. Biol."},{"key":"ref_130","doi-asserted-by":"crossref","unstructured":"Tewary, S., Chakraborty, S., Majumdar, J., Majumder, R., Kundu, D., Ghosh, S., and Das Gupta, S. (2016, January 5\u20136). A novel approach towards designing a wearable Smart Health Monitoring System measuring the vital parameters and emergency situations in real-time and providing the necessary medical care through telemedicine. Proceedings of the 2016 IEEE Students\u2019 Conference on Electrical, Electronics and Computer Science, SCEECS, Bhopal, India.","DOI":"10.1109\/SCEECS.2016.7509332"},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1007\/s40031-014-0084-1","article-title":"Cardiac care assistance using self configured sensor network\u2014A remote patient monitoring system","volume":"95","author":"Kanagachidambaresan","year":"2014","journal-title":"J. Inst. Eng. Ser. B"},{"key":"ref_132","first-page":"373","article-title":"Patient monitoring using personal area networks of wireless intelligent sensors","volume":"37","author":"Jovanov","year":"2001","journal-title":"Biomed. Sci. Instrum."},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1109\/JBHI.2014.2325017","article-title":"Exploiting prior knowledge in compressed sensing wireless ECG systems","volume":"19","author":"Polania","year":"2015","journal-title":"IEEE J. Biomed. Heath Inform."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compbiomed.2016.01.013","article-title":"Energy-efficient Compressed Sensing for ambulatory ECG monitoring","volume":"71","author":"Craven","year":"2016","journal-title":"Comput. Biol. Med."},{"key":"ref_135","doi-asserted-by":"crossref","unstructured":"Kanoun, K., Mamaghanian, H., Khaled, N., and Atienza, D. (2011, January 14\u201318). A real-time compressed sensing-based personal electrocardiogram monitoring system. Proceedings of the 2011 Design, Automation and Test in Europe, Grenoble, France.","DOI":"10.1109\/DATE.2011.5763140"},{"key":"ref_136","doi-asserted-by":"crossref","unstructured":"Rahman, A., Rahman, T., Ghani, N.H., Hossain, S., and Uddin, J. (2019, January 10\u201312). IoT Based patient monitoring system using ECG sensor. Proceedings of the 1st International Conference on Robotics, Electrical and Signal Processing Techniques ICREST, Dhaka, Bangladesh.","DOI":"10.1109\/ICREST.2019.8644065"},{"key":"ref_137","doi-asserted-by":"crossref","unstructured":"Singh, P., and Jasuja, A. (2017, January 5\u20136). IoT based low-cost distant patient ECG monitoring system. Proceedings of the IEEE International Conference on Computing, Communication and Automation ICCCA, Greater Noida, India.","DOI":"10.1109\/CCAA.2017.8230003"},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"294","DOI":"10.5958\/0976-5506.2018.00457.6","article-title":"Wireless ECG monitoring system using IoT based signal conditioning module for real time signal acquisition","volume":"9","author":"Sobya","year":"2018","journal-title":"Indian J. Public Health Res. Dev."},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1109\/JSAC.2013.SUP.0513005","article-title":"Interconnection framework for mHealth and remote monitoring based on the internet of things","volume":"31","author":"Jara","year":"2013","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_140","first-page":"337","article-title":"IoT based patient monitoring system using raspberry pi 3 and Lab view","volume":"14","author":"Mohanraj","year":"2017","journal-title":"Pak. J. Biotechnol."},{"key":"ref_141","first-page":"181","article-title":"IoT platform for real-time multichannel ECG monitoring and classification with neural networks","volume":"310","author":"Granados","year":"2018","journal-title":"Lect. Notes Bus. Inf. Process."},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"9900","DOI":"10.3390\/s140609900","article-title":"Monitoring and detection platform to prevent anomalous situations in home care","volume":"14","author":"Villarrubia","year":"2014","journal-title":"Sensors"},{"key":"ref_143","doi-asserted-by":"crossref","unstructured":"Akrivopoulos, O., Amaxilatis, D., Mavrommati, I., and Chatzigiannakis, I. (2018, January 25\u201328). Utilising fog computing for developing a person-centric heart monitoring system. Proceedings of the 2018 International Conference on Intelligent Environments IE, Rome, Italy.","DOI":"10.1109\/IE.2018.00010"},{"key":"ref_144","doi-asserted-by":"crossref","unstructured":"Ji, C., Liu, F., Wang, Z., Li, Y., Qi, C., and Li, Z. (2017, January 12\u201315). Mobile cloud ECG intelligent monitoring and data processing system. Proceedings of the 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services Healthcom, Dalian, China.","DOI":"10.1109\/HealthCom.2017.8210812"},{"key":"ref_145","doi-asserted-by":"crossref","unstructured":"Chatzigiannakis, I., Valchinov, E.S., Antoniou, A., Kalogeras, A., Alexakos, C., and Konstantinopoulos, P. (2016, January 6\u20139). Advanced observation and telemetry heart system utilizing wearable ECG device and a Cloud platform. Proceedings of the IEEE Symposium on Computers and Communications, Larnaca, Cyprus.","DOI":"10.1109\/ISCC.2015.7405449"},{"key":"ref_146","doi-asserted-by":"crossref","unstructured":"Aljuaid, M., Marashly, Q., AlDanaf, J., Tawhari, I., Barakat, M., Barakat, R., Zobell, B., Cho, W., Chelu, M.G., and Marrouche, N.F. (2020). Smartphone ECG monitoring system helps lower emergency room and clinic visits in post\u2013atrial fibrillation ablation patients. Clin. Med. Insights Cardiol., 14.","DOI":"10.1177\/1179546820901508"},{"key":"ref_147","doi-asserted-by":"crossref","unstructured":"Phan, D., Siong, L.Y., Pathirana, P.N., and Seneviratne, A. (2015, January 14\u201317). Smartwatch: Performance evaluation for long-term heart rate monitoring. Proceedings of the 4th International Symposium on Bioelectronics and Bioinformatics ISBB, Beijing, China.","DOI":"10.1109\/ISBB.2015.7344944"},{"key":"ref_148","doi-asserted-by":"crossref","unstructured":"Li, X., and Sun, Y. (2017, January 17\u201319). NCMB-Button: A wearable non-contact system for long-term multiple biopotential monitoring. Proceedings of the 2017 2nd IEEE\/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Philadelphia, PA, USA.","DOI":"10.1109\/CHASE.2017.118"},{"key":"ref_149","first-page":"2488","article-title":"Designing for reliable textile neonatal ECG monitoring using multi-sensor recordings Medical Simulations View project DOCHANGE View project","volume":"2011","author":"Feijs","year":"2011","journal-title":"IEEE Eng. Med. Biol. Soc."},{"key":"ref_150","doi-asserted-by":"crossref","unstructured":"Bouwstra, S., Chen, W., Feijs, L., and Oetomo, S.B. (2009, January 3\u20135). Smart jacket design for neonatal monitoring with wearable sensors. Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks, Berkeley, CA, USA.","DOI":"10.1109\/BSN.2009.40"},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1007\/s10877-014-9616-0","article-title":"Electrocardiogram characteristics prior to in-hospital cardiac arrest","volume":"29","author":"Attin","year":"2015","journal-title":"J. clin. Monit. Comput."},{"key":"ref_152","doi-asserted-by":"crossref","unstructured":"Rafiq, S., Alam, A.H.M.Z., and Islam, M.R. (2017, January 23\u201325). Development of ECG home monitoring system. Proceedings of the 2017 IEEE Regional Symposium on Micro and Nanoelectronics RSM, Penang, Malaysia.","DOI":"10.1109\/RSM.2017.8069119"},{"key":"ref_153","doi-asserted-by":"crossref","first-page":"3454","DOI":"10.1109\/JSEN.2015.2485210","article-title":"Wearable heart rate sensor systems for wireless canine health monitoring","volume":"16","author":"Brugarolas","year":"2015","journal-title":"IEEE Sens. J."},{"key":"ref_154","doi-asserted-by":"crossref","first-page":"741","DOI":"10.1109\/TITB.2010.2049025","article-title":"Processing of signals recorded through smart devices: Sleep-quality assessment central nervous system view project LINK-Linking excellence in biomedical knowledge and computational intelligence research for personalized management of CVD within PHC View p","volume":"14","author":"Bianchi","year":"2010","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_155","doi-asserted-by":"crossref","first-page":"1700309","DOI":"10.1002\/admt.201700309","article-title":"Bluetooth low energy-based washable wearable activity motion and electrocardiogram textronic monitoring and communicating system","volume":"3","author":"Tao","year":"2018","journal-title":"Adv. Mater. Technol."},{"key":"ref_156","doi-asserted-by":"crossref","unstructured":"Ankhili, A., Tao, X., Cochrane, C., Coulon, D., and Koncar, V. (2018). Washable and reliable textile electrodes embedded into underwear fabric for electrocardiography (ECG) monitoring. Materials, 11.","DOI":"10.3390\/ma11020256"},{"key":"ref_157","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s10916-008-9186-0","article-title":"Non-constrained blood pressure monitoring using ECG and PPG for personal healthcare","volume":"33","author":"Yoon","year":"2009","journal-title":"J. Med. Syst."},{"key":"ref_158","unstructured":"Lee, H.E., Wang, W.C., Lu, S.W., Wu, B.Y., and Ko, L.W. (\u2013, January 30). Home-based mobile cardio-pulmonary rehabilitation consultant system. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBC, Boston, MA, USA."},{"key":"ref_159","doi-asserted-by":"crossref","unstructured":"Ravanshad, N., and Rezaee-Dehsorkh, H. (2017, January 2\u20134). An event-based ECG-monitoring and QRS-detection system based on level-crossing sampling. Proceedings of the 2017 25th Iranian Conference on Electrical Engineering ICEE, Tehran, Iran.","DOI":"10.1109\/IranianCEE.2017.7985460"},{"key":"ref_160","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1109\/JBHI.2013.2274809","article-title":"A level-crossing based QRS-detection algorithm for wearable ECG sensors","volume":"18","author":"Ravanshad","year":"2014","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_161","unstructured":"Fensli, R., Gunnarson, E., and Gundersen, T. (2005, January 23\u201324). A wearable ECG-recording system for continuous arrhythmia monitoring in a wireless tele-home-care situation. Proceedings of the IEEE Symposium on Computer-Based Medical Systems, Dublin, Ireland."},{"key":"ref_162","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.pcad.2013.08.007","article-title":"ECG monitoring in syncope","volume":"56","author":"Ruwald","year":"2013","journal-title":"Prog. Cardiovasc. Dis."},{"key":"ref_163","doi-asserted-by":"crossref","first-page":"1955","DOI":"10.1016\/j.jacc.2009.12.015","article-title":"The response of the QT interval to the brief tachycardia provoked by standing: a bedside test for diagnosing long QT syndrome","volume":"55","author":"Viskin","year":"2010","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_164","doi-asserted-by":"crossref","unstructured":"Zhang, Z.-X., Tian, X.-W., and Lim, J.S. (2011, January 3\u20135). New algorithm for the depression diagnosis using HRV: A neuro-fuzzy approach. Proceedings of the International Symposium on Bioelectronics and Bioinformations, Suzhou, China.","DOI":"10.1109\/ISBB.2011.6107702"},{"key":"ref_165","unstructured":"Yin, L., Chen, Y., and Ji, W. (2011, January 18\u201321). A novel method of diagnosing coronary heart disease by analysing ECG signals combined with motion activity. Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, Santander, Spain."},{"key":"ref_166","unstructured":"Garudadri, H., Chi, Y., Baker, S., Majumdar, S., Baheti, P.K., and Ballard, D. (\u2013, January 30). Diagnostic grade wireless ECG monitoring. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS, Boston, USA."},{"key":"ref_167","first-page":"380787","article-title":"A wireless emergency telemedicine system for patients monitoring and diagnosis","volume":"2014","author":"Ahmed","year":"2014","journal-title":"Int. J. Telemed. Appl."},{"key":"ref_168","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1109\/MIS.2012.4","article-title":"A remote diagnosis service platform for wearable ECG monitors","volume":"27","author":"Dong","year":"2012","journal-title":"IEEE Intell. Syst."},{"key":"ref_169","doi-asserted-by":"crossref","first-page":"S86","DOI":"10.1016\/j.jelectrocard.2019.08.006","article-title":"SPICED-ACS: Study of the potential impact of a computer-generated ECG diagnostic algorithmic certainty index in STEMI diagnosis: Towards transparent AI","volume":"57","author":"Knoery","year":"2019","journal-title":"J. Electrocardiol."},{"key":"ref_170","doi-asserted-by":"crossref","unstructured":"Calzone, R., Pagana, G., Perez, M.D., and Augustine, R. (2019, January 9\u201313). Innovations in biomedicine: Measuring physiological parameters becomes as simple as applying a plaster on the body. Proceedings of the 2019 21st International Conference on Electromagnetics in Advanced Applications ICEAA, Granada, Spain.","DOI":"10.1109\/ICEAA.2019.8879184"},{"key":"ref_171","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1016\/j.medengphy.2013.03.002","article-title":"Clinical evaluation of a wireless ECG sensor system for arrhythmia diagnostic purposes","volume":"35","author":"Fensli","year":"2013","journal-title":"Med. Eng. Phys."},{"key":"ref_172","first-page":"4","article-title":"CardioSounds: Real-time auditory assistance for supporting cardiac diagnostic and monitoring","volume":"Part F1319","author":"Grautoff","year":"2017","journal-title":"ACM Int. Conf. Proc. Ser."},{"key":"ref_173","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1109\/JSSC.2014.2364036","article-title":"An injectable 64 nW ECG mixed-signal SoC in 65 nm for arrhythmia monitoring","volume":"50","author":"Chen","year":"2015","journal-title":"IEEE J. Solid State Circ."},{"key":"ref_174","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.asoc.2013.09.021","article-title":"Hybrid intelligent methods for arrhythmia detection and geriatric depression diagnosis","volume":"14","author":"Huang","year":"2014","journal-title":"Appl. Soft Comput."},{"key":"ref_175","doi-asserted-by":"crossref","unstructured":"Chen, X., Ji, J., Loparo, K., and Li, P. (2017, January 16\u201319). Real-time personalized cardiac arrhythmia detection and diagnosis: A cloud computing architecture. Proceedings of the 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Orlando, FL, USA.","DOI":"10.1109\/BHI.2017.7897240"},{"key":"ref_176","first-page":"454","article-title":"PocketECG: A new continuous and real-time ambulatory arrhythmia diagnostic method","volume":"18","year":"2011","journal-title":"Cardiol. J."},{"key":"ref_177","doi-asserted-by":"crossref","first-page":"e002864","DOI":"10.1161\/CIRCOUTCOMES.116.002864","article-title":"Atrial fibrillation diagnosis timing, ambulatory ECG monitoring utilization, and risk of recurrent stroke","volume":"10","author":"Lip","year":"2017","journal-title":"Circ. Cardiovasc. Qual. Outcomes"},{"key":"ref_178","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1186\/s13063-015-1006-5","article-title":"Detecting and diagnosing atrial fibrillation (D 2 AF): study protocol for a cluster randomised controlled trial","volume":"16","author":"Uittenbogaart","year":"2015","journal-title":"Trials"},{"key":"ref_179","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1159\/000457809","article-title":"First diagnosis of atrial fibrillation at the time of stroke","volume":"43","author":"Borowsky","year":"2017","journal-title":"Cerebrovasc. Dis."},{"key":"ref_180","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1109\/TITB.2010.2094197","article-title":"Diagnosis of cardiovascular abnormalities from compressed ECG: A data mining-based approach","volume":"15","author":"Sufi","year":"2010","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_181","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1109\/JBHI.2014.2321515","article-title":"An interoperable system for automated diagnosis of cardiac abnormalities from electrocardiogram data","volume":"19","author":"Tinnakornsrisuphap","year":"2014","journal-title":"IEEE J. Biomed. Health inform."},{"key":"ref_182","doi-asserted-by":"crossref","unstructured":"Hadjem, M., Salem, O., and Nait-Abdesselam, F. (2014, January 15\u201318). An ECG monitoring system for prediction of cardiac anomalies using WBAN. Proceedings of the 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services Healthcom, Natal, Brazil.","DOI":"10.1109\/HealthCom.2014.7001883"},{"key":"ref_183","first-page":"224","article-title":"Sport monitoring with smart wearable system","volume":"177","author":"Perego","year":"2012","journal-title":"Stud. Health Technol. Inform."},{"key":"ref_184","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1016\/j.jelectrocard.2015.07.010","article-title":"Smartphone ECG aids real time diagnosis of palpitations in the competitive college athlete","volume":"48","author":"Peritz","year":"2015","journal-title":"J. Electrocardiol."},{"key":"ref_185","doi-asserted-by":"crossref","unstructured":"Xia, W., Zhou, Y., Fang, Y., and Liu, H. (2018, January 7\u201310). ECG-Enhanced multi-sensor solution for wearable sports devices. Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics SMC, Miyazaki, Japan.","DOI":"10.1109\/SMC.2018.00335"},{"key":"ref_186","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compind.2017.06.004","article-title":"A wearable H-shirt for exercise ECG monitoring and individual lactate threshold computing","volume":"92\u201393","author":"Sun","year":"2017","journal-title":"Comput. Ind."},{"key":"ref_187","doi-asserted-by":"crossref","unstructured":"Pollonini, L., Re, R., Simpson, R.J., and Dacso, C.C. (September, January 28). Integrated device for the measurement of systemic and local oxygen transport during physical exercise. Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, CA, USA.","DOI":"10.1109\/EMBC.2012.6346785"},{"key":"ref_188","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1136\/bmjsem-2019-000680","article-title":"Monitoring the health of transitioning professional footballers: Protocol of an observational prospective cohort study","volume":"5","author":"Gouttebarge","year":"2019","journal-title":"BMJ Open Sport Exerc. Med."},{"key":"ref_189","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1049\/iet-its.2012.0032","article-title":"Driver fatigue and drowsiness monitoring system with embedded electrocardiogram sensor on steering wheel","volume":"8","author":"Jung","year":"2014","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_190","doi-asserted-by":"crossref","unstructured":"Matsuda, T., and Makikawa, M. (2008, January 20\u201325). ECG monitoring of a car driver using capacitively-coupled electrodes. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS\u201908\u2014\u201cPersonalized Healthcare through Technology, Vancouver, BC, Canada.","DOI":"10.1109\/IEMBS.2008.4649406"},{"key":"ref_191","doi-asserted-by":"crossref","first-page":"1923","DOI":"10.1109\/JBHI.2014.2305403","article-title":"An innovative nonintrusive driver assistance system for vital signal monitoring","volume":"18","author":"Sun","year":"2014","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_192","doi-asserted-by":"crossref","unstructured":"Zeng, C., Wang, W., Chen, C., Zhang, C., and Cheng, B. Poincar\u00e9 plot indices of heart rate variability for monitoring driving fatigue. Proceedings of the CICTP 2019: Transportation in China\u2014Connecting the World - Proceedings of the 19th COTA International Conference of Transportation Professionals.","DOI":"10.1061\/9780784482292.059"},{"key":"ref_193","unstructured":"Shin, H.S., Jung, S.J., Kim, J.J., and Chung, W.Y. (2010, January 1\u20134). Real time car driver\u2019s condition monitoring system. Proceedings of the IEEE Sensors, Kona, HI, USA."},{"key":"ref_194","doi-asserted-by":"crossref","unstructured":"Trenta, F., Conoci, S., Rundo, F., and Battiato, S. (2019, January 14\u201318). Advanced motion-tracking system with multi-layers deep learning framework for innovative car-driver drowsiness monitoring. Proceedings of the Proceedings - 14th IEEE International Conference on Automatic Face and Gesture Recognition FG, Lille, France.","DOI":"10.1109\/FG.2019.8756566"},{"key":"ref_195","doi-asserted-by":"crossref","unstructured":"De Nadai, S., D\u2019Inc\u00e0, M., Parodi, F., Benza, M., Trotta, A., Zero, E., Zero, L., and Sacile, R. (2016, January 12\u201316). Enhancing safety of transport by road by on-line monitoring of driver emotions. Proceedings of the 2016 11th System of Systems Engineering Conference (SoSE), Kongsberg, Norway.","DOI":"10.1109\/SYSOSE.2016.7542941"},{"key":"ref_196","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1016\/j.bios.2016.12.001","article-title":"Increasing trend of wearables and multimodal interface for human activity monitoring: A review","volume":"90","author":"Kumari","year":"2017","journal-title":"Biosens. Bioelectron."},{"key":"ref_197","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.ijmedinf.2008.07.005","article-title":"Ubiquitous healthcare service using Zigbee and mobile phone for elderly patients","volume":"78","author":"Lee","year":"2009","journal-title":"Int. J. Med. Inform."},{"key":"ref_198","doi-asserted-by":"crossref","unstructured":"Fan, X., Zhao, Y., Wang, H., and Tsui, K.L. (2019). Forecasting one-day-forward wellness conditions for community-dwelling elderly with single lead short electrocardiogram signals. BMC Med. Inform. Decis. Mak., 19.","DOI":"10.1186\/s12911-019-1012-8"},{"key":"ref_199","doi-asserted-by":"crossref","unstructured":"Valchinov, E., Antoniou, A., Rotas, K., and Pallikarakis, N. (2014, January 3\u20135). Wearable ECG system for health and sports monitoring. Proceedings of the 2014 4th International Conference on Wireless Mobile Communication and Healthcare-Transforming Healthcare Through Innovations in Mobile and Wireless Technologies (MOBIHEALTH), Athens, Greece.","DOI":"10.4108\/icst.mobihealth.2014.257236"},{"key":"ref_200","doi-asserted-by":"crossref","unstructured":"Walinjkar, A., and Woods, J. (2017, January 19\u201320). ECG classification and prognostic approach towards personalized healthcare. Proceedings of the 2017 International Conference On Social Media, Wearable And Web Analytics, Social Media, London, UK.","DOI":"10.1109\/SOCIALMEDIA.2017.8057360"},{"key":"ref_201","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.pcad.2013.07.005","article-title":"Prognostic significance of ambulatory ECG monitoring for ventricular arrhythmias","volume":"56","author":"Katritsis","year":"2013","journal-title":"Prog. Cardiovasc. Dis."},{"key":"ref_202","doi-asserted-by":"crossref","unstructured":"Benchaira, K., Bitam, S., Mellouk, A., Tahri, A., and Okbi, R. (2019, January 23\u201324). AfibPred: A Novel Atrial Fibrillation Prediction Approach Based on Short Single-Lead ECG Using Deep Transfer Knowledge. Proceedings of the 4th International Conference on Big Data and Internet of Things, Tangier-Tetuan, Morocco.","DOI":"10.1145\/3372938.3372964"},{"key":"ref_203","doi-asserted-by":"crossref","unstructured":"El Halabi, N., Daou, R.A.Z., Achkar, R., Hayek, A., and Borcsok, J. (2019, January 3\u20135). Monitoring system for prediction and detection of epilepsy seizure. Proceedings of the 2019 4th International Conference on Advances in Computational Tools for Engineering Applications ACTEA, Beirut, Lebanon.","DOI":"10.1109\/ACTEA.2019.8851094"},{"key":"ref_204","doi-asserted-by":"crossref","first-page":"795","DOI":"10.3233\/THC-161225","article-title":"Prediction of epileptic seizures based on heart rate variability","volume":"24","author":"Behbahani","year":"2016","journal-title":"Technol. Health Care"},{"key":"ref_205","doi-asserted-by":"crossref","first-page":"681","DOI":"10.2459\/JCM.0000000000000275","article-title":"Prognostic significance of myocardial extracellular volume fraction in nonischaemic dilated cardiomyopathy","volume":"16","author":"Barison","year":"2015","journal-title":"J. Cardiovasc. Med."},{"key":"ref_206","doi-asserted-by":"crossref","first-page":"e010485","DOI":"10.1136\/bmjopen-2015-010485","article-title":"Prognosis assessment of persistent left bundle branch block after TAVI by an electrophysiological and remote monitoring risk-adapted algorithm: Rationale and design of the multicentre LBBB\u2013TAVI study","volume":"6","author":"Bordachar","year":"2016","journal-title":"BMJ Open"},{"key":"ref_207","doi-asserted-by":"crossref","first-page":"1894","DOI":"10.1109\/JBHI.2014.2303481","article-title":"Risk scoring for prediction of acute cardiac complications from imbalanced clinical data","volume":"18","author":"Liu","year":"2014","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_208","doi-asserted-by":"crossref","unstructured":"Liu, N., Koh, Z.X., Goh, J., Lin, Z., Haaland, B., Ting, B.P., and Ong, M.E.H. (2014). Prediction of adverse cardiac events in emergency department patients with chest pain using intelligent variable selection and heart rate variability. BMC Med. Inform. Decis. Mak., 14.","DOI":"10.1186\/1472-6947-14-75"},{"key":"ref_209","doi-asserted-by":"crossref","unstructured":"Nikolaiev, S., and Timoshenko, Y. (2015, January 7\u20139). Reinvention of the cardiovascular diseases prevention and prediction due to ubiquitous convergence of mobile apps and machine learning. Proceedings of the 2015 Information Technologies in Innovation Business Conference (ITIB), Kharkiv, Ukraine.","DOI":"10.1109\/ITIB.2015.7355066"},{"key":"ref_210","doi-asserted-by":"crossref","unstructured":"Forkan, A.R.M., and Hu, W. (2016, January 11\u201314). A context-aware, predictive and protective approach for wellness monitoring of cardiac patients. Proceedings of the 2016 Computing in Cardiology Conference (CinC), Vancouver, BC, Canada.","DOI":"10.22489\/CinC.2016.108-324"},{"key":"ref_211","doi-asserted-by":"crossref","unstructured":"Bazan, J.G., Buregwa-Czuma, S., Pardel, P.W., Bazan-Socha, S., Soko\u0142owska, B., and Dziedzina, S. (2015). Predicting the presence of serious coronary artery disease based on 24 hour Holter ECG monitoring. Transactions on Rough Sets XIX, Springer.","DOI":"10.1007\/978-3-662-47815-8_7"},{"key":"ref_212","doi-asserted-by":"crossref","first-page":"1242","DOI":"10.1016\/j.jocn.2011.12.008","article-title":"Role of the combined CHADS2 score and echocardiographic abnormalities in predicting stroke in patients with paroxysmal atrial fibrillation","volume":"19","author":"Gupta","year":"2012","journal-title":"J. Clin. Neurosci."},{"key":"ref_213","first-page":"199","article-title":"Prognostic factors for death and survival with or without complications in cardiac arrest patients receiving CPR within 24 hours of anesthesia for emergency surgery","volume":"7","author":"Siriphuwanun","year":"2014","journal-title":"Risk Manag. Healthc. Policy"},{"key":"ref_214","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.artmed.2019.06.001","article-title":"A deep survival analysis method based on ranking","volume":"98","author":"Jing","year":"2019","journal-title":"Artif. Intell. Med."},{"key":"ref_215","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/j.amjcard.2016.05.023","article-title":"Usefulness of electrocardiographic patterns at presentation to predict long-term risk of cardiac death in patients with hypertrophic cardiomyopathy","volume":"118","author":"Biagini","year":"2016","journal-title":"Am. J. Cardiol."},{"key":"ref_216","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.jnca.2019.02.029","article-title":"An approach for predicting health status in IoT health care","volume":"134","author":"Zamanifar","year":"2019","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_217","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/rcs.1975","article-title":"A comprehensive multimodality heart motion prediction algorithm for robotic-assisted beating heart surgery","volume":"15","author":"Mansouri","year":"2019","journal-title":"Int. J. Med. Robot. Comput. Assist. Surg."},{"key":"ref_218","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.neucom.2016.06.074","article-title":"Smart assisted diagnosis solution with multi-sensor Holter","volume":"220","author":"Bie","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_219","doi-asserted-by":"crossref","unstructured":"Somanna, J., Joshi, D., Gundu, H., and Srinivasa, G. (2019, January 18\u201321). Automated classification of sleep apnea and hypopnea on polysomnography data. Proceedings of the 2019 12th Biomedical Engineering International Conference (BMEiCON), Laos, Thailand.","DOI":"10.1109\/BMEiCON47515.2019.8990338"},{"key":"ref_220","doi-asserted-by":"crossref","unstructured":"Fahruzi, I., Purnama, I.K.E., and Purnomo, M.H. (2019, January 19\u201320). Screening of non-overlapping apnea and non-apnea from single lead ECG-apnea recordings using time-frequency approach. Proceedings of the 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM), Surabaya City, Indonesia.","DOI":"10.1109\/CENIM48368.2019.8973250"},{"key":"ref_221","doi-asserted-by":"crossref","unstructured":"Chen, Z., Tian, F., Zhao, Q., and Hu, B. (2019, January 5\u20139). A Non-contact and unconstrained sleep health monitoring system. Proceedings of the International Conference on Human Centered Computing, \u010ca\u010dak, Serbia.","DOI":"10.1007\/978-3-030-37429-7_6"},{"key":"ref_222","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.future.2019.01.008","article-title":"A joint resource-aware and medical data security framework for wearable healthcare systems","volume":"95","author":"Pirbhulal","year":"2019","journal-title":"Futur. Gener. Comput. Syst."},{"key":"ref_223","doi-asserted-by":"crossref","unstructured":"Yu, B., Xu, L., and Li, Y. (2012, January 6\u20138). Bluetooth Low Energy (BLE) based mobile electrocardiogram monitoring system. Proceedings of the 2012 IEEE International Conference on Information and Automation ICIA, Shenyang, China.","DOI":"10.1109\/ICInfA.2012.6246921"},{"key":"ref_224","doi-asserted-by":"crossref","first-page":"2009","DOI":"10.1109\/JIOT.2016.2645125","article-title":"A wireless health monitoring system using mobile phone accessories","volume":"4","author":"Mahmud","year":"2017","journal-title":"IEEE Intern. Things J."},{"key":"ref_225","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1109\/TMSCS.2015.2494021","article-title":"Energy-efficient long-term continuous personal health monitoring","volume":"1","author":"Nia","year":"2015","journal-title":"IEEE Trans. Multi Scale Comput. Syst."},{"key":"ref_226","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.1109\/TBME.2011.2182196","article-title":"Assurance of energy efficiency and data security for ECG transmission in BASNs","volume":"59","author":"Ma","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_227","doi-asserted-by":"crossref","unstructured":"Altini, M., Polito, S., Penders, J., Kim, H., Van Helleputte, N., Kim, S., and Yazicioglu, F. (2011, January 5\u20139). An ECG patch combining a customized ultra-low-power ECG SoC with Bluetooth low energy for long term ambulatory monitoring. Proceedings of the 2nd Conference on Wireless Health, San Diego, CA, USA.","DOI":"10.1145\/2077546.2077564"},{"key":"ref_228","unstructured":"Zhou, B., Chen, X., Hu, X., Ren, R., Tan, X., Fang, Z., and Xia, S. (2013, January 9\u201312). A Bluetooth low energy approach for monitoring electrocardiography and respiration. Proceedings of the 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013), Lisbon, Portugal."},{"key":"ref_229","doi-asserted-by":"crossref","first-page":"645781","DOI":"10.1155\/2015\/645781","article-title":"An experimental performance evaluation and compatibility study of the Bluetooth low energy based platform for ECG monitoring in WBANs","volume":"11","author":"Touati","year":"2015","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_230","unstructured":"Chen, X., Xie, J., Fang, Z., and Xia, S. (2015, January 19). Low power electrocardiography and impedance cardiography detection system based on labview and bluetooth low energy. Proceedings of the 2015 IET International Conference on Biomedical Image and Signal Processing (ICBISP 2015), Beijing, China."},{"key":"ref_231","doi-asserted-by":"crossref","unstructured":"Pandya, U.T., and Desai, U.B. (March, January 28). Feasibility study of filtering algorithms for low cost wireless physiological monitoring system. Proceedings of the 2011 2nd International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE), Chennai, India.","DOI":"10.1109\/WIRELESSVITAE.2011.5940914"},{"key":"ref_232","doi-asserted-by":"crossref","unstructured":"Nabar, S., Banerjee, A., Gupta, S.K.S., and Poovendran, R. (2011, January 23\u201325). GeM-REM: Generative model-driven resource efficient ECG monitoring in body sensor networks. Proceedings of the 2011 International Conference on Body Sensor Networks, Dallas, TX, USA.","DOI":"10.1109\/BSN.2011.29"},{"key":"ref_233","doi-asserted-by":"crossref","unstructured":"Samie, F., Tsoutsouras, V., Xydis, S., Bauer, L., Soudris, D., and Henkel, J. (2016, January 11\u201316). Distributed QoS management for internet of things under resource constraints. Proceedings of the Eleventh IEEE\/ACM\/IFIP International Conference on Hardware\/Software Codesign and System Synthesis, Pittsburgh, PA, USA.","DOI":"10.1145\/2968456.2974005"},{"key":"ref_234","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.procs.2015.10.055","article-title":"Energy optimization of zigBee based WBAN for patient monitoring","volume":"70","author":"Pathak","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"ref_235","doi-asserted-by":"crossref","unstructured":"Milis, M., Michaelides, K., Kounoudes, A., Ansaloni, G., Atienza, D., Giroud, F., Ruedi, P.-F., and Masson, F. (2012, January 11\u201313). IcyHeart: Highly integrated ultra-low-power SoC solution for unobtrusive and energy efficient wireless cardiac monitoring: Research project for the benefit of specific groups (FP7, Capacities). Proceedings of the 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE), Chania, Greece.","DOI":"10.1109\/BIBE.2012.6399716"},{"key":"ref_236","doi-asserted-by":"crossref","first-page":"167","DOI":"10.3233\/THC-140782","article-title":"Activity aware energy efficient priority based multi patient monitoring adaptive system for body sensor networks","volume":"22","author":"Sudha","year":"2014","journal-title":"Technol. Health Care"},{"key":"ref_237","doi-asserted-by":"crossref","unstructured":"Aldammas, M.A., Tabbabi, E., and Soudani, A. (2019, January 1\u20133). Low-Energy ECG Processing for Accurate Features\u2019 Extraction in Wireless Body Sensor Networks. Proceedings of the 2nd International Conference on Computer Applications and Information Security ICCAIS, Riyadh, Saudi Arabia.","DOI":"10.1109\/CAIS.2019.8769544"},{"key":"ref_238","doi-asserted-by":"crossref","unstructured":"Ferretti, L., Ansaloni, G., Pozzi, L., Aminifar, A., Atienza, D., Cammoun, L., and Ryvlin, P. (2019, January 25\u201329). Tailoring SVM inference for resource-efficient ECG-based epilepsy monitors. Proceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition DATE, Florence, Italy.","DOI":"10.23919\/DATE.2019.8714858"},{"key":"ref_239","first-page":"1","article-title":"Energy-Efficient ECG Signal Compression for User Data Input in Cyber-Physical Systems by Leveraging Empirical Mode Decomposition","volume":"3","author":"Huang","year":"2019","journal-title":"ACM Trans. Cyber Phys. Syst."},{"key":"ref_240","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1109\/TBME.2012.2226175","article-title":"Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning","volume":"60","author":"Zhang","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_241","doi-asserted-by":"crossref","unstructured":"Bortolotti, D., Bartolini, A., Mangia, M., Rovatti, R., Setti, G., and Benini, L. (2015, January 23\u201325). Energy-aware bio-signal compressed sensing reconstruction: FOCUSS on the WBSN-gateway. Proceedings of the 2015 IEEE 9th International Symposium on Embedded Multicore\/Many-core Systems-on-Chip, Turin, Italy.","DOI":"10.1109\/MCSoC.2015.34"},{"key":"ref_242","doi-asserted-by":"crossref","unstructured":"Biswas, D., Mazomenos, E.B., and Maharatna, K. (2012, January 3\u20135). ECG compression for remote healthcare systems using selective thresholding based on energy compaction. Proceedings of the 2012 International Symposium on Signals, Systems, and Electronics (ISSSE), Potsdam, Germany.","DOI":"10.1109\/ISSSE.2012.6374306"},{"key":"ref_243","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1109\/TETC.2016.2564361","article-title":"Energy-aware bio-signal compressed sensing reconstruction on the WBSN-gateway","volume":"6","author":"Bortolotti","year":"2016","journal-title":"IEEE Trans. Emerg. Top. Comput."},{"key":"ref_244","doi-asserted-by":"crossref","unstructured":"Gavriel, C., Parker, K.H., and Faisal, A.A. (2015, January 23\u201325). Smartphone as an ultra-low cost medical tricorder for real-time cardiological measurements via ballistocardiography. Proceedings of the 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN), Turin, Italy.","DOI":"10.1109\/BSN.2015.7299425"},{"key":"ref_245","doi-asserted-by":"crossref","unstructured":"Rebolledo-Nandi, Z., Chavez-Olivera, A., Cuevas-Valencia, R.E., Alarcon-Paredes, A., and Alonso, G.A. (2015, January 23\u201328). Design of a versatile low cost mobile health care monitoring system using an android application. Proceedings of the 2015 Pan American Health Care Exchanges (PAHCE), Vina del Mar, Chile.","DOI":"10.1109\/PAHCE.2015.7173334"},{"key":"ref_246","doi-asserted-by":"crossref","unstructured":"Abrar, S., Aziz, U.S., Choudhry, F., and Mansoor, A. (2012, January 20\u201322). Design and implementation of an embedded system for transmitting human ECG and web server for emergency services and remote health monitoring: A low cost ECG signal simulator and its transmitter, to send and store data in electronic databases, in remote l. Proceedings of the 2012 International Conference on Open Source Systems and Technologies, Lahore, Pakistan.","DOI":"10.1109\/ICOSST.2012.6472828"},{"key":"ref_247","doi-asserted-by":"crossref","unstructured":"Deb, S., Islam, S.M.R., Robaiatmou, J., and Islam, M.T. (2017, January 16\u201318). Design and implementation of low Cost ECG monitoring system for the patient using smart device. Proceedings of the ECCE 2017\u2014International Conference on Electrical, Computer and Communication Engineering, Cox\u2019s Bazar, Bangladesh.","DOI":"10.1109\/ECACE.2017.7913007"},{"key":"ref_248","doi-asserted-by":"crossref","unstructured":"Krachunov, S., Beach, C., Casson, A.J., Pope, J., Fafoutis, X., Piechocki, R.J., and Craddock, I. (2017, January 6\u20139). Energy efficient heart rate sensing using a painted electrode ECG wearable. Proceedings of the GIoTS 2017\u2014Global Internet of Things Summit, Geneva, Switzerland.","DOI":"10.1109\/GIOTS.2017.8016260"},{"key":"ref_249","doi-asserted-by":"crossref","unstructured":"Nguyen Gia, T., Jiang, M., Sarker, V.K., Rahmani, A.M., Westerlund, T., Liljeberg, P., and Tenhunen, H. (2017, January 26\u201330). Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes. Proceedings of the 2017 13th International Wireless Communications and Mobile Computing Conference IWCMC, Valencia, Spain.","DOI":"10.1109\/IWCMC.2017.7986551"},{"key":"ref_250","doi-asserted-by":"crossref","unstructured":"Preu\u010dil, T., and Novotn\u00fd, M. (2019, January 10\u201314). Low-cost portable ECG. Proceedings of the 2019 8th Mediterranean Conference on Embedded Computing MECO, Budva, Montenegro.","DOI":"10.1109\/MECO.2019.8760086"},{"key":"ref_251","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1016\/j.tele.2017.12.004","article-title":"Patient monitoring at home using 32-channel cost-effective data acquisition device","volume":"35","author":"Alhalabi","year":"2018","journal-title":"Telemat. Inform."},{"key":"ref_252","doi-asserted-by":"crossref","first-page":"2735","DOI":"10.1109\/JSEN.2018.2887303","article-title":"Low-cost and portable impedance plethysmography system for the simultaneous detection of respiratory and heart activities","volume":"19","author":"Piuzzi","year":"2018","journal-title":"IEEE Sens. J."},{"key":"ref_253","doi-asserted-by":"crossref","first-page":"2380","DOI":"10.1161\/STROKEAHA.115.011979","article-title":"Potential Cost-Effectiveness of Ambulatory Cardiac Rhythm Monitoring after Cryptogenic Stroke","volume":"47","author":"Yong","year":"2016","journal-title":"Stroke"},{"key":"ref_254","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1016\/S0735-1097(19)30904-0","article-title":"Healthcare resource UTILIZATION associated with electrocardiograph (ECG) sensor patch screening for atrial fibrillation (AF): Results from the mhealth screening to prevent strokes (MSTOPS) trial","volume":"73","author":"Steinhubl","year":"2019","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_255","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1109\/MWC.2010.5416345","article-title":"Resource-aware secure ECG healthcare monitoring through body sensor networks","volume":"17","author":"Wang","year":"2010","journal-title":"IEEE Wirel. Commun."},{"key":"ref_256","doi-asserted-by":"crossref","unstructured":"Majhi, R.R., Chattopadhyay, S., Chattopadhyay, S., and Ghosh, A. (2015, January 12\u201313). Analysis of electro-cardiogram by radar and DWT based Kurtosis comparison. Proceedings of the IET Conference Publications, Kolkata, India.","DOI":"10.1049\/cp.2015.1704"},{"key":"ref_257","doi-asserted-by":"crossref","first-page":"1847","DOI":"10.1109\/TMTT.2014.2343934","article-title":"Noise and sensitivity of harmonic radar architecture for remote sensing and detection of vital signs","volume":"62","author":"Chioukh","year":"2014","journal-title":"IEEE Trans. Microw. Theory Tech."},{"key":"ref_258","doi-asserted-by":"crossref","first-page":"1332","DOI":"10.1118\/1.3267038","article-title":"Medical applications of shortwave FM radar: Remote monitoring of cardiac and respiratory motion","volume":"37","author":"Mostov","year":"2010","journal-title":"Med. Phys."},{"key":"ref_259","doi-asserted-by":"crossref","first-page":"2093","DOI":"10.1109\/TMTT.2013.2247055","article-title":"Six-port radar sensor for remote respiration rate and heartbeat vital-sign monitoring","volume":"61","author":"Vinci","year":"2013","journal-title":"IEEE Trans. Microw. Theory Tech."},{"key":"ref_260","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1109\/TIM.2015.2479103","article-title":"Fast acquisition of heart rate in noncontact vital sign radar measurement using time-window-variation technique","volume":"65","author":"Tu","year":"2016","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_261","doi-asserted-by":"crossref","first-page":"4483","DOI":"10.1109\/TMTT.2017.2684138","article-title":"Accurate measurement in doppler radar vital sign detection based on parameterized demodulation","volume":"65","author":"Xiong","year":"2017","journal-title":"IEEE Trans. Microw. Theory Tech."},{"key":"ref_262","doi-asserted-by":"crossref","first-page":"1383","DOI":"10.1016\/j.jacep.2018.06.001","article-title":"Current and future use of insertable cardiac monitors","volume":"4","author":"Giancaterino","year":"2018","journal-title":"JACC Clin. Electrophysiol."},{"key":"ref_263","first-page":"1","article-title":"Miniaturized human insertable cardiac monitoring system with wireless power transmission technique","volume":"2016","author":"Lee","year":"2016","journal-title":"J. Sens."},{"key":"ref_264","doi-asserted-by":"crossref","first-page":"1163","DOI":"10.1007\/s11517-007-0264-0","article-title":"Wireless and inductively powered implant for measuring electrocardiogram","volume":"45","author":"Riistama","year":"2007","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_265","doi-asserted-by":"crossref","first-page":"1598","DOI":"10.1016\/j.hrthm.2013.07.044","article-title":"Long-term ECG monitoring using an implantable loop recorder for the detection of atrial fibrillation after cavotricuspid isthmus ablation in patients with atrial flutter","volume":"10","author":"Mittal","year":"2013","journal-title":"Heart Rhythm"},{"key":"ref_266","doi-asserted-by":"crossref","first-page":"322","DOI":"10.5761\/atcs.ra.15-00145","article-title":"Robot-assisted cardiac surgery","volume":"21","author":"Ishikawa","year":"2015","journal-title":"Ann. Thorac. Cardiovasc. Surg."},{"key":"ref_267","first-page":"1295","article-title":"Robot and cloud-assisted multi-modal healthcare system Enabling comfortable sports therapy for patient: A novel lightweight durable and portable ECG monitoring system View project VENDNET: Vehicular Named Data Network View project Robot and cloud-assisted","volume":"18","author":"Ma","year":"2015","journal-title":"Comput. Netw."},{"key":"ref_268","doi-asserted-by":"crossref","unstructured":"Deng, Z.Y., Li, H.C., Chiang, H.H., and Lee, T.T. (2018, January 7\u201310). Robotic Aids for ECG Monitoring and Diagnosis in Assisted Living Environments. Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC, Miyazaki, Japan.","DOI":"10.1109\/SMC.2018.00374"},{"key":"ref_269","doi-asserted-by":"crossref","unstructured":"Hattori, K., Asamoto, M., Otsuji, M., Ito, N., Kasahara, S., Hashimoto, Y., and Yamada, Y. (2019). Quantitative evaluation of stress in Japanese anesthesiology residents based on heart rate variability and psychological testing. J. Clin. Monit. Comput., 1\u20137.","DOI":"10.1007\/s10877-019-00305-z"},{"key":"ref_270","unstructured":"Sarkar, P., and Etemad, A. (2020). Self-supervised ecg representation learning for emotion recognition under review. arXiv."},{"key":"ref_271","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.bspc.2018.08.002","article-title":"Self-adjustable domain adaptation in personalized ECG monitoring integrated with IR-UWB radar","volume":"47","author":"Yin","year":"2019","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_272","first-page":"557","article-title":"PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification","volume":"33","author":"Golany","year":"2019","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_273","first-page":"66","article-title":"ECG steganography to secure patient data in an E-healthcare system","volume":"21\u201322","author":"Meghani","year":"2016","journal-title":"ACM Int. Conf. Proc. Ser."},{"key":"ref_274","doi-asserted-by":"crossref","unstructured":"Yang, C.-Y., Cheng, L.-T., and Wang, W.-F. (2018, January 13\u201314). Effective reversible data hiding in electrocardiogram based on fast discrete cosine transform. Proceedings of the Future Technologies Conference, Vancouver, BC, Canada.","DOI":"10.1007\/978-3-030-02686-8_48"},{"key":"ref_275","doi-asserted-by":"crossref","first-page":"3322","DOI":"10.1109\/TBME.2013.2264539","article-title":"Wavelet-based ECG steganography for protecting patient confidential information in point-of-care systems","volume":"60","author":"Ibaida","year":"2013","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_276","doi-asserted-by":"crossref","unstructured":"Malasri, K., and Wang, L. (2007, January 11). Addressing security in medical sensor networks. Proceedings of the HealthNet\u201907: 1st ACM SIGMOBILE International Workshop on Systems and Networking Support for Healthcare and Assisted Living Environments, San Juan, Puerto Rico.","DOI":"10.1145\/1248054.1248058"},{"key":"ref_277","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/TITB.2007.906101","article-title":"A cryptographic key management solution for HIPAA privacy\/security regulations","volume":"12","author":"Lee","year":"2008","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_278","doi-asserted-by":"crossref","first-page":"1075","DOI":"10.1109\/83.777088","article-title":"Spread spectrum image steganography","volume":"8","author":"Marvel","year":"1999","journal-title":"IEEE Trans. Image Process."},{"key":"ref_279","doi-asserted-by":"crossref","first-page":"25","DOI":"10.20544\/ERSICT.02.16.P03","article-title":"Challenges for development of an ECG m-Health solution ECGalert View project SIARS (Smart I (eye) Advisory Rescue System) View project Challenges for development of an ECG m-Health solution","volume":"1","author":"Gusev","year":"2016","journal-title":"J. Emerging Res. Solutions"},{"key":"ref_280","doi-asserted-by":"crossref","unstructured":"Jarchi, D., Mahdi, A., Tarassenko, L., and Clifton, D.A. (2018, January 4\u20137). Visualisation of long-term ECG signals applied to post-intensive care patients. Proceedings of the 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN), Las Vegas, NV, USA.","DOI":"10.1109\/BSN.2018.8329684"},{"key":"ref_281","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.cmpb.2018.10.008","article-title":"Towards an efficient and Energy-Aware mobile big health data architecture","volume":"166","author":"Navaz","year":"2018","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_282","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1007\/s10916-011-9661-x","article-title":"Body area networks for ubiquitous healthcare applications: Opportunities and challenges","volume":"35","author":"Jovanov","year":"2011","journal-title":"J. Med. Syst."},{"key":"ref_283","doi-asserted-by":"crossref","first-page":"5452","DOI":"10.1109\/JSEN.2016.2564995","article-title":"Low-power wearable ECG monitoring system for multiple-patient remote monitoring","volume":"16","author":"Iannaccone","year":"2016","journal-title":"IEEE Sens. J."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/6\/1796\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:11:08Z","timestamp":1760173868000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/6\/1796"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,24]]},"references-count":283,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["s20061796"],"URL":"https:\/\/doi.org\/10.3390\/s20061796","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,24]]}}}