This will create a high tendency for congestion, causing severe performance degradation. Tejedor et al. Intermittent Review of cEEG, provided 24/7 by remote R. EEG T technologists, at different intervals . Gusev M., Stojmenski A., Guseva A. ECGalert: A Heart Attack Alerting System; Proceedings of the 9th International Conference; Skopje, Macedonia. Cleaning and transformation are also performed during the preprocessing stage [91]. An official website of the United States government. Aljuaid M., Marashly Q., AlDanaf J., Tawhari I., Barakat M., Barakat R., Zobell B., Cho W., Chelu M.G., Marrouche N.F. Sun F., Yi C., Li W., Li Y. Xiong Y., Chen S., Dong X., Peng Z., Zhang W. Accurate measurement in doppler radar vital sign detection based on parameterized demodulation. Prognosis is one of the main objectives of ECG monitoring systems attracting much research interest. Yang B., Teo S.K., Hoeben B., Monterola C., Su Y. As a library, NLM provides access to scientific literature. [279] highlighted a few challenges in handling visualization for continuous ECG monitoring. Wu W., Pirbhulal S., Sangaiah A.K., Mukhopadhyay S.C., Li G. Optimization of signal quality over comfortability of textile electrodes for ECG monitoring in fog computing based medical applications. 15. Pirbhulal S., Samuel O.W., Wu W., Sangaiah A.K., Li G. A joint resource-aware and medical data security framework for wearable healthcare systems. . [115] proposed a mobile personal elderly health monitoring for automated classification of ECG signals using machine learning techniques. TheECG247 TM Smart Heart Sensor is a new, mobile, long-term patch ECG monitoring device that has undergone extensive testing in a home health care setting (Sandberg et al., 2021; Jortveit and . Kundu M., Nasipuri M., Basu D.K. Holter A Holter is a remote cardiac monitoring device that tracks a patient's heart rhythm with the help of small electrodes attached to the skin. Bouwstra S., Chen W., Feijs L., Oetomo S.B. 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. Both categories of systems have been implemented for monitoring, for example, heartbeats, to detect patterns that might point to arrhythmia in diverse contexts, such as ambulatory and home settings. Gieratowski J.J., Ciuchciski K., Grzegorczyk I., Kona K., Soliski M., Podziemski P. Heart rate variability discovery: Algorithm for detection of heart rate from noisy, multimodal recordings; Proceedings of the Computing in Cardiology 2014; Cambridge, MA, USA. Exploring Eng. ECG monitoring should document symptoms such as syncope and palpitations, but 24 hours is often too short a period, therefore other devices have been introduced. Another way of reducing energy consumption is optimizing processing techniques and proposing new enhanced algorithms for signal processing [222,233,236,237]. Pregnancy telemonitoring with smart control of algorithms for signal analysis. To avoid this, the Piavet System enables remote ECG monitoring of cardiac arrhythmias. Therefore, hybrid filtering is rather more adaptive to raw ECG signals and, thus, was introduced in some research work to improve filtering results [89,90]. Wang Y., Doleschel S., Wunderlich R., Heinen S. A wearable wireless ECG monitoring system With dynamic transmission power control for long-term homecare. Deriche M., Aljabri S., Al-Akhras M., Siddiqui M., Deriche N. 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. It can, for example, integrate IoT devices and regulate the IoT devices behavior automatically. Most researchers focus on a subset of key processes; however, they neglect other very important supporting processes. Multiple physiological signals fusion techniques for improving heartbeat detection: A review. 1719 October 2019; pp. 19 November 2015; [. 2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry. 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. This accounts for 45% of all deaths in Europe and 37% of all deaths in the EU [3]. An automated detection of CAD using the method of signal decomposition and non linear entropy using heart signals. Monitoring and detection platform to prevent anomalous situations in home care. The noise is classified, in the literature, into five main groups: powerline interference, baseline wander, electrode contact noise, electrode motion artifacts, and muscle contractions. [. In real-time setups, patients can measure ECG signals while doing normal real-life activities [161]. It contributes significantly to cardiac disease diagnoses, as it retrieves the most representative set of features from the preprocessed ECG, which allows better heartbeat detection. Monitoring logs are continuously analyzed and improvement measures are taken to react to any quality degradation. We define performance-based monitoring systems as those that address performance advances in different aspects and characteristics. 2022 February 2019; [. However, these studies lack comprehensiveness and completeness. IoT-Based Real-Time Remote ECG Monitoring System Samik Basu, Anwesha Sengupta, Anindita Das, Mahasweta Ghosh & Soma Barman (Mandal) Conference paper First Online: 04 February 2021 497 Accesses Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 147) Abstract Piuzzi E., Pisa S., Pittella E., Podest L., Sangiovanni S. Low-cost and portable impedance plethysmography system for the simultaneous detection of respiratory and heart activities. Phan D., Siong L.Y., Pathirana P.N., Seneviratne A. Smartwatch: Performance evaluation for long-term heart rate monitoring; Proceedings of the 4th International Symposium on Bioelectronics and Bioinformatics ISBB; Beijing, China. 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. [. The main feature extraction methods are Wavelet Transform-based feature extraction, the autocorrelation function-based feature extraction method (periodic information of ECG signals), principal component analysis-based feature extraction method (finding periodic information in time series signals), and normal feature extraction method (Fast Fourier Transform (FFT)) [92]. Implants offer a practical solution for long-term monitoring, given that continuous external monitoring for such a long period of time can be unfeasible. Therefore, we will provide an across-the-board description and classification of primary and supporting processes that should be implemented within an ECG monitoring system, as depicted in Figure 2. Most of the research work reviewed in this study focuses on ECG signal monitoring that generally requires touch-based sensing of the patients skin. Detecting and diagnosing atrial fibrillation (D 2 AF): study protocol for a cluster randomised controlled trial. Real-time signal quality-aware ECG telemetry system for IoT-based health care monitoring. One of the most important processes is data acquisition;it involves measuring and recording the hearts activity using different sensors. 1D-CADCapsNet: One dimensional deep capsule networks for coronary artery disease detection using ECG signals. official website and that any information you provide is encrypted [. Electrocardiogram (ECG) classification based on dynamic beats segmentation. Several reviewed ECG monitoring systems proposed solutions for lower energy consumption by reducing signal transmission, processing, and supporting signal compression. Valchinov E., Antoniou A., Rotas K., Pallikarakis N. 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. These include, but are not limited to signal quality assessment, ECG signal classification, heartbeat detection and delay correction, peak detection, and training. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Additionally, the data compression process is required for many purposes, including storage capacity reduction and faster file transfer, which eventually contributes to efficient bandwidth utilization and cost reduction, especially in the case of continuous ECG monitoring and data streaming. A cryptographic key management solution for HIPAA privacy/security regulations. Our proposed architecture is designed to fit into contexts of use in which various actors interact with the ECG monitoring system by providing inputs and receiving some sort of output. Increasingly, remote ECG monitoring is used by clinics in the United States as a cost-effective solution to review a patient's heart activity without their need to travel to a clinic. It can serve as reference for various researchers and stakeholders in the field to compare, understand, and value ECG monitoring system features. 16. The framework evaluates the systems capability to provide continuous monitoring, ubiquitous connectivity, extended device integration, reliability, and security and privacy support. Received 2020 Feb 29; Accepted 2020 Mar 19. Accessibility With advances in sensor technology, communication infrastructure, data processing, and modeling as well as analytics algorithms the risk of impairments could be better addressed more than ever done before. 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. 69 June 2017; [, Nguyen Gia T., Jiang M., Sarker V.K., Rahmani A.M., Westerlund T., Liljeberg P., Tenhunen H. 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. Gouttebarge V., Andersen T.E., Cowie C., Goedhart E., Jorstad H., Kemp S., Knigs M., Maas M., Orhant E., Rantanen J., et al. The processing and analysis stage requires the application of various optimization techniques to achieve higher accuracy, precision and quality results. Data mining for wearable sensors in health monitoring systems: A review of recent trends and challenges. [29] addressed the comfort of monitored patients and designed a non-invasive textile electrode that guarantees excellent quality of ECG reading and offers comfort to patient while they are being monitored. Finally, best practices for hospital ECG monitoring have been proposed in [116] and a set of recommendations are made, which included indications, timeframes, and strategies to improve the diagnostic accuracy of cardiac arrhythmia, ischemia, and QT interval monitoring. Figure 3 presents ECG monitoring systems divided into four main clusters, in addition to the fifth cluster, which is considered the future generation of ECG monitoring systems. The site is secure. Wang H., Peng D., Wang W., Sharif H., Chen H.H., Khoynezhad A. Resource-aware secure ECG healthcare monitoring through body sensor networks. Careers, Unable to load your collection due to an error. Zhang H., Wang Z., Dong K., Ng S.H., Lin Z. As a library, NLM provides access to scientific literature. The involvement of mobile devices in continuous ECG monitoring makes them less effective for computational, data-intensive processing. Ma T., Shrestha P.L., Hempel M., Peng D., Sharif H., Chen H.-H. Assurance of energy efficiency and data security for ECG transmission in BASNs. 1Department of Information Systems and Security, College of Information Technology, UAE University, Al Ain 15551, United Arab Emirates; ea.ca.ueau@281075102. For instance, Giancaterino et al. 100% of the ECG data, not just events is transmitted live, and the automated analysis is performed on the full-disclosure data. 2426 April 2019; pp. Octaviani V., Kurniawan A., Suprapto Y.K., Zaini A. 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. These challenges were addressed in [281], in which special dashboard functionalities were integrated with visualization features, such as zoom-in and zoom-out, and filtering. Fensli R., Gunnarson E., Gundersen T. 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. One of the most common devices with remote ECG capabilities is the Apple Watch, which provides single-lead ECG functionality that can identify atrial fibrillation. Moreover, water sports monitoring was discussed in [36]. Various data compression techniques were proposed in [84,85,88]. It relies on the analytics of evidence-based data collected from sensors, as well as the massive data collected from social networks. Continuous EEG Services. Yu B., Xu L., Li Y. Bluetooth Low Energy (BLE) based mobile electrocardiogram monitoring system; Proceedings of the 2012 IEEE International Conference on Information and Automation ICIA; Shenyang, China. Another body of work in [110] proposed the use of mobile Cloud computing to overcome issues related to the computational requirement of the large amount of data processing resulting from continuous ECG monitoring. 30 June6 July 2018; [. Full disclosure analysis allows for highly accurate arrhythmia detection. Such systems include a remote health monitoring system for detecting varying cardiac disorders, including, for instance, arrhythmia and myocardial conditions, as proposed in [129]. Exploiting prior knowledge in compressed sensing wireless ECG systems. Keeping the good reliability of data and the quality of the signal are also challenges facing smartphone-integrated ECG monitoring systems; such a case was handled in [94] by enhancing the feature extraction process. Also, in [14] a textile-based, contactless ECG monitoring system with sensors embedded in non-ICU environments was proposed. This group is classified into two categories: (1) the enabling technologies which involve IoT, Cloud, and Fog and (2) the monitoring devices which comprise mobile devices, wearable devices, and sensor devices. Li X., Sun Y. 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. Chamadiya B., Mankodiya K., Wagner M., Hofmann U.G. [71] a cloud-based system has been developed to assess the usefulness of the ECG data collected from patients themselves using either mobile devices or web applications. 2324 October 2019; pp. . EN S.Y., ZKURT N. ECG arrhythmia classification by using convolutional neural network and spectrogram; Proceedings of the 2019 Innovations in Intelligent Systems and Applications Conference (ASYU); Izmir, Turkey. 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. Wireless ECG monitoring system using IoT based signal conditioning module for real time signal acquisition. Numerous ECG monitoring systems have been developed for diagnosing specific or multiple diseases. 35 July 2019; [. Others studied the possibility of having a robot assistant providing medical feedback, diagnosis, and notifications [267,268]. 12. Data cleansing was also defined as a discrete process in [71]. Abrar S., Aziz U.S., Choudhry F., Mansoor A. Lip G.Y.H., Hunter T.D., Quiroz M.E., Ziegler P.D., Turakhia M.P. However, these processes are not distinctly defined in the literature; some overlap and others are better merged. 7679. It facilitates the integration of interactive television to moderate activity with the user under monitoring. Based on the proposed taxonomy, architecture, and common process model, we conduct an extensive, thorough analysis of the literature surrounding ECG monitoring systems, highlighting systems categories, attributes, functions, challenges, and current trends, leading to a panorama of ECG monitoring systems. Likewise, Tewary et al. [(accessed on 16 March 2020)]; Scutti S. Nearly Half of US Adults Have Cardiovascular Disease, Study Says. Alternatively, some researchers investigated implanted sensor technology for durable and long-term continuous monitoring [263,264]. Classification of selected service-based ECG monitoring systems. Similarly, in the work of Wang et al. On the other hand, advancements in robotics introduced new opportunities for cardiac healthcare, especially with the great challenge of limited medical resources. This diversity and variability of ECG monitoring system contexts and components impose a number of challenges that have been highlighted by several researchers. Liu N., Koh Z.X., Chua E.C.-P., Tan L.M.-L., Lin Z., Mirza B., Ong M.E.H. Interconnection framework for mHealth and remote monitoring based on the internet of things. The architecture encompasses four layers: the bottom layer is the acquisition layer, which offers various sensing platforms and devices, such as ECG sensors, IoT sensors, Wireless Body Area Network (WBAN) sensors, mobile sensors, and wearable sensors. Another piece of work reported in [32] combined an Arduino microcontroller with an Android-based smartphone to develop an intelligent healthcare system and provide elderly patients with medical services at home. Recent research in the literature adopts Neural Network (NN) and decision trees for the diagnosis of different cardiac diseases, the assessment of cardiac health conditions, the detection of chronic problems, sleeping issues including apnea, and mood and emotion recognition [55]. The proposed framework details the hardware and software components along with the underlying network and protocol used, including 6LoWPAN and YOAPY protocols to support secure and scalable integration and deployment of sensors within the patients environment. Drew B.J., Califf R.M., Funk M., Kaufman E.S., Krucoff M.W., Laks M.M., Macfarlane P.W., Sommargren C., Swiryn S., Van Hare G.F. 2325 May 2011; pp. Finally, smartness is another property of the ECG monitoring systems where various intelligent features could be implemented across all layers from data inception to visualization. [79] presented a thorough literature survey on data compression methods, as well as quality assessment techniques applied after compression. Barrett P.M., Komatireddy R., Haaser S., Topol S., Sheard J., Encinas J., Fought A.J., Topol E.J. Hsieh S.-T., Lin C.-L. Craven D., McGinley B., Kilmartin L., Glavin M., Jones E. Energy-efficient Compressed Sensing for ambulatory ECG monitoring. [283] discussed opportunities for the seamless integration of remote monitoring systems with other smart home systems over an IoT infrastructure. the contents by NLM or the National Institutes of Health. Jara A.J., Zamora-Izquierdo M.A., Skarmeta A.F. Kim K. Europace Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography. M.A.S., H.T.E.K., and H.I. Wearable medical devices will not only detect the wearer's psychological and physiological parameters, but also make regulations to the body according to the collected information. because during syncope the patient is unable to activate the device. Furthermore, the European Health Network European Cardiovascular Disease Statistics 2017 edition revealed that CVDs cause 3.9 million deaths in Europe and over 1.8 million deaths in the European Union (EU) yearly. 59 August 2011; pp. Use our services for full-time EEG monitoring or gap coverage when needed. This work is supported by Zayed Health Center at UAE University under Fund code 31R227. For example, Wang et al. Satija U., Ramkumar B., Manikandan S.M. The number of ECG monitoring systems in the literature is expanding exponentially. Different approaches lead to cost reduction, including the use of low-cost devices, such as smartphones [232,244,245,246]. Fast acquisition of heart rate in noncontact vital sign radar measurement using time-window-variation technique. The work must be attributed back to the original author and commercial use is not permitted without specific permission. A home-based monitoring system with low-cost data acquisition was proposed in [251]. An automatic classification of ST morphology provides valuable information for physicians in the diagnosis of myocardial ischemia, especially in long-term and remote ECG monitoring environments. Classification of selected futuristic ECG monitoring systems. Pathak S., Kumar M., Mohan A., Kumar B. Several research works on wearable ECG monitoring have been developed in the literature [25,29,125,126,127,128]. 244251. Other solutions, such as in [132], go beyond the adoption of traditional IoT-based ECG monitoring systems and further incorporate intelligent wireless sensors within a personal area network to handle data acquisition and limited processing, which helped in improving monitoring efficiency and urgent reactions in cases of emergency. Somanna J., Joshi D., Gundu H., Srinivasa G. Automated classification of sleep apnea and hypopnea on polysomnography data; Proceedings of the 2019 12th Biomedical Engineering International Conference (BMEiCON); Laos, Thailand. On one hand, hospital ECG acquisition devices are usually big in size and support high-precision and long-term monitoring. 105109. Also, Cloud infrastructure offers storage and processing services at various stages of the ECG monitoring lifecycle. The pre-processing algorithm will demonstrate effective noise removal, accurate QRS wave detection, and strong anti-infection and robustness when used for the detection of unusually tall P waves and RR intervals in a large variety of abnormal waves, and also successfully suppress the effects of tall T waves, big P wave misdetection of R waves, ventricular tachycardia, and ventricular fibrillation. Sensor 2. ); Health monitoring and its related technologies is an attractive research area. 2325 September 2015; pp. For example, the signal selection process is performed only in systems using multiple physiological types of signals for heartbeat detection [58,70] or R-peak detection [62]. 302307. In some cases, cardiologists may recommend 24-hour Holter monitoring for patient monitoring. 407412. Jovanov E., Raskovic D., Price J., Chapman J., Moore A., Krishnamurthy A. ECG signals can be processed in a constant setup that we refer to as continuous monitoring, a one-time setup that we refer to as ad hoc monitoring, or a recurring, prescheduled, and preplanned set up, which we refer to as episodic monitoring.. The application included data charting, electrode state, and animation storyboard functionalities. [. [1] The wireless physiological information collection nodes of the wearable network will be connected to the patient's portable terminal, such as a personal digital assistant (PDA), smart phone, or other communication device, to send data. 47 March 2018; pp. Dziubiski M. PocketECG: A new continuous and real-time ambulatory arrhythmia diagnostic method. Perego P., Moltani A., Andreoni G. Sport monitoring with smart wearable system. At present, the application of ECG automatic diagnosis technology is not very extensive; it still lacks a complete set of suitable algorithms. Each stakeholder requires a different reporting context. [. Thorn A., Rawshani A., Herlitz J., Engdahl J., Kahan T., Djrv T. ECG monitoring in in-hospital cardiac arrest (IHCA), Mahdy L.N., Ezzat K.A., Tan Q. Real-time display is also required to be automatically customized according to the visualizing devices screen size and even the device battery level. Each cluster focuses on one dimension of ECG monitoring systems, detailing the features and attributes of these systems in that dimension. The right silo provides processing and storage services to all processes in the four horizontal layers of the architecture. General health status and activity prediction were proposed in [105,216]. They do not consider the latest technological trends [49,50,51], and they target very narrow research niches, such as wearable sensors [52,53,54,55], mobile sensors [56], disease diagnosis [57], heartbeat detection [58], emotion recognition [59], or ECG compression methods [60]. In addition to our experts taxonomy, the proposed ECG monitoring systems layered architecture depicts essential structural components and elements of ECG monitoring systems, their interfaces, and the data inputs/outputs of each layer. Event monitor. Tychkov A., Alimuradov A., Churakov P. 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. They propose a compressed sensing architecture, combining a redundancy removal scheme with quantization and Huffman entropy coding, to effectively improve the compression ratio. For real-time monitoring, it is important to use energy-efficient devices and communication technologies to allow for long-term monitoring. 16. This system proves its feasibility of extended monitoring without disturbing daily activities. Alternatively, episodic monitoring was adopted in several researches to limit the causes of motion artifacts and constrain the amount of generated ECG signal data, allowing for easier processing and analysis. Prescribe and configure per patient needs. Holter monitor. On the other hand, some studies attempted to analyze ECG monitoring systems attributes and provide classification taxonomies, supporting better analysis and understanding of the ECG systems reported in the literature. Typically, IoT-based monitoring systems adopt most of the primary processes [12,13,71,72]. How to develop an ECG monitoring system or get help with this type of project. A convenient and reliable touch-free alternative is radar cardiography. Future wearable equipment will pay more attention to the wearer's psychology and emotional state. The methodology and results demonstrated that it is possible to overcome most of the design barriers that have thus far prevented wearable sensor systems from being used in everyday clinical practice. 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. While the authors in [21,125] proposed an ECG monitoring device for wireless monitoring of atrial arrhythmia, and Fung et al. Remote monitoring with Philips MCOT gives physicians access to critical data about patients' day-to-day life like atrial fibrillation burden, event duration, activity level, and symptoms. Steinhubl S.R., Edwards A.M., Waalen J., Zambon R., Mehta R., Ariniello L., Ebner G., Baca-Motes K., Carter C., Felicione E., et al. [. Licensee MDPI, Basel, Switzerland. A Holter monitor is a 12-lead medical device that records the heartbeat and checks for unusual signs. 2830 November 2016; [, Ahouandjinou A.S.R.M., Assogba K., Motamed C. 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. 14. Long-term ECG monitoring using an implantable loop recorder for the detection of atrial fibrillation after cavotricuspid isthmus ablation in patients with atrial flutter. [82] proposed a design for web application visualization to display data from the ECG device. Remote cardiac telemetry was developed to allow home ECG monitoring of patients with suspected cardiac arrhythmias. 2529 August 2015; pp. 25 May 2019; [.
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