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2226 April 2019; pp. 1114 September 2016; pp. 1113 November 2012; pp. 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]. PDF Starting a Continuous Glucose Monitor - Kaiser Permanente Yusof M.A., Hau Y.W. These actions were performed automatically based on the continuous analysis of signal quality and evaluation of the reliability of the quantitative descriptive parameters determined for the recorded signals. At the same time, it will also be capable of uploads, backup, analysis, and feedback of data to a remote medical service center through the internet or mobile communications network. 16. Grond M., Jauss M., Hamann G., Stark E., Veltkamp R., Nabavi D., Horn M., Weimar C., Khrmann M., Wachter R., et al. 640648. Coronary heart disease risk is identified using feature extraction and an adaptive neuro-fuzzy inference system-based classification has been used. Nevertheless, in some ECG monitoring systems, real-time and continuous ECG sensor acquisition is handled. In addition to the five clusters, a horizontal underneath level represents the communication protocol and the wireless technology used by all the categories of monitoring systems to transport the ECG signals from sensors to the underlying servers and/or devices under which the ECG is processed and visualized. Also, personalized monitoring systems should be raised to the next level in terms of being highly customized according to patients needs and interactive to allow special configurations and adaptations to users requirements for a better quality of life. In this paper, to the best of our knowledge, we tried to generalize a complete lifecycle, including all main processes starting from data acquisition, preprocessing, feature extraction, processing and, finally, visualization. Wireless ECG monitoring system using IoT based signal conditioning module for real time signal acquisition. 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. Biagini E., Pazzi C., Olivotto I., Musumeci B., Limongelli G., Boriani G., Pacileo G., Mastromarino V., Reggiani M.L.B., Lorenzini M. Usefulness of electrocardiographic patterns at presentation to predict long-term risk of cardiac death in patients with hypertrophic cardiomyopathy. They also employ a wide range of technologies such as IoT [25,26,27], edge computing [28,29], and mobile computing [30,31,32]. The authors in [27,136,137], and [138] proposed an IoT-based patient-continuous monitoring system using the ECG sensor. 2530. 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. 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. The data comes from the context into input layer, moves through the system, then goes back to the context through the visualization layer. In this system, the ECG data are stored as model parameters rather than data samples to reduce the storage space, and only the abnormal sensed ECG signals are transmitted to reduce energy [232]. Developing evolutionary, efficient, and accurate automatic diagnostic techniques have been always an open area of research to overcome many challenges, among which are medical device capabilities, ECG diagnostics overlapping patterns, and other ECG signal-related issues throughout the systems lifecycle. 2426 May 2018; [, Navaz A.N., Mohammed E., Serhani M.A., Zaki N. 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. Bianchi et al. Lee W.B., Lee C.D. Carnevale L., Celesti A., Fazio M., Villari M. A Big Data Analytics Approach for the Development of Advanced Cardiology Applications. 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. Fast acquisition of heart rate in noncontact vital sign radar measurement using time-window-variation technique. Individual sensor monitors specific physiological signals, communicates with other sensors and connects to a personal server. Jovanov E., Raskovic D., Price J., Chapman J., Moore A., Krishnamurthy A. Summary of the most common literature referring to ECG monitoring systems lifecycles, primary and supporting processes. Another exercise evaluation platform has been developed by Sun et al. ECG monitoring systems have been studied thoroughly in the literature; however, the multi-dimensional aspects of these systems make it difficult for researchers, medical practitioners, and others to select, among these systems, those that fulfill their monitoring needs, match the context of their use, and support the required disease monitoring requirements. Different machine learning algorithms have been applied in IoT Cloud-based monitoring systems in [13] and Cloud-based cardiology services in [106]. 261264. One of the most important processes is data acquisition;it involves measuring and recording the hearts activity using different sensors. 1215 October 2017; pp. 16. Many studies that are related to daily monitoring and activities during sleep, proposed different designs and specifications for wearable devices, such as shirts [33,34,35]. The use of wireless body sensor networks (WBSN) in the medical field aims at providing continuous monitoring of patients' physiological data. The overall architecture of electrocardiogram (ECG) monitoring systems. A wireless emergency telemedicine system for patients monitoring and diagnosis. Jovanov E., Milenkovic A. It is able to detect various abnormalities, such as high blood pressure, low blood pressure, fever, tachycardia and bradycardia; it also sends notifications in case of unexpected events. Uittenbogaart S.B., Verbiest-van Gurp N., Erkens P.M.G., Lucassen W.A.M., Knottnerus J.A., Winkens B., van Weert H.C.P.M., Stoffers H.E.J.H. This accentuates the need for automatic analysis and interpretation of signal data for these monitoring setups in order to generate useful notifications for patients as well as health caregivers. A cloud computing architecture with wireless body area network for professional athletes health monitoring in sports organizationsCase study of Montenegro; Proceedings of the 2015 4th Mediterranean Conference on Embedded Computing (MECO); Budva, Montenegro. Sudha G., Karthik S., Kumar N.S. 16. The https:// ensures that you are connecting to the An ECG is considered the best method for detecting heart abnormalities. These systems were developed to reduce the economic burden on hospitals and involve patients in their continuous health monitoring with the comfort of being at home and are designed for people with lifelong and chronic disease or elderly people that require permanent assistance, surveillance and monitoring. The latter is responsible for handling operations such as ECG noise and artifact filtering, QRS detection, ECG wave delineation, transformation, and compression. In Oster's studies, a model-based ECG filtering approach to ECG data from healthy subjects was applied to facilitate accurate online filtering and analysis of physiological signals. For example, Ravanshar et al. Hence, alarm and screening reminder needs to be considered when designing home manual monitoring systems. 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. The work must be attributed back to the original author and commercial use is not permitted without specific permission. Wearable devices are remotely trained to interpret heart abnormalities and the Fog extends the Cloud by migrating data-processing closer to the production site, thus accelerating the systems responsiveness to events. exercising, doing sporting activities, and/or working), which does not necessary require his/her presence at home. This makes the available ECG monitoring system processes and architectures hard to generalize and reuse. This process acquires its importance throughout the value chain as it helps the human brain to better understand and analyze patterns, and detect abnormalities, especially with large datasets. Steganography is defined as: the art of hiding secret information inside another type of data called host data [278]. Various data compression techniques were proposed in [84,85,88]. [283] discussed opportunities for the seamless integration of remote monitoring systems with other smart home systems over an IoT infrastructure. Mainly, the problems were related to handling different refreshing rate requirements via multiple platforms installed on displaying devices with low processing requirements. Lee et al. [111] a hybrid mobile-Cloud ECG telemonitoring method has been proposed to allow more effective personalized medical monitoring and convey processing to the Cloud whenever heavy processing is required and cannot be handled by mobile devices. Innovative Technol. Hybrid intelligent methods for arrhythmia detection and geriatric depression diagnosis. These are clustered based on the monitoring context for which they are developed, the involved ECG technologies and devices that characterize these systems, the monitoring scheme and frequency adopted, the monitoring target and purpose for which these systems were implemented, and finally, the futuristic monitoring system that leverages new technologies, such as AI, robotics, and nanotechnology, to shape emerging ECG monitoring systems. This challenge was highlighted and addressed in [149,17]. Our remote ECG monitoring professionals increase patient compliance through 24/7 support and oversight. Remote patient monitoring devices tap digital health technology to send communications between patients and providers. Federal government websites often end in .gov or .mil. Get the report Corporate. In order to provide more accurate and efficient ST morphology classifications for these applications, Xu, et al. [, Shin H.S., Jung S.J., Kim J.J., Chung W.Y. 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]. [. Xu MF, Wei SS, Qin XW, et al. Other activities, such as driving, was tackled in the literature in [189,190,191,192,193,194,195]. Banaee H., Ahmed M., Loutfi A. 11371140. Section 3 describes the experts taxonomy of ECG monitoring systems. Span E., Di Pascoli S., Iannaccone G. Low-power wearable ECG monitoring system for multiple-patient remote monitoring. 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]. FOIA Licensee MDPI, Basel, Switzerland. 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. Such systems include a remote health monitoring system for detecting varying cardiac disorders, including, for instance, arrhythmia and myocardial conditions, as proposed in [129]. In the following sub-sections, we describe and analyze each of the abovementioned clusters and we provide a comprehensive review of each cluster in terms of integrated ECG monitoring systems and solutions. 621625. Benini A., Donati M., Iacopetti F., Fanucci L. User-friendly single-lead ECG device for home telemonitoring applications; Proceedings of the International Symposium on Medical Information and Communication Technology ISMICT; Firenze, Italy. 1School of Automation, Beijing Institute of Technology, Beijing, China, 2Department of Cardiology Internal Medicine, Nanlou Branch of Chinese PLA General Hospital, Beijing, China. Gusev M., Stojmenski A., Guseva A. ECGalert: A Heart Attack Alerting System; Proceedings of the 9th International Conference; Skopje, Macedonia. The device is worn for about 24-48 hours and is . 37603763. Different diseases require different types of recordings, which should be supported by the selected electrode. 1416 February 2019; [, Taher N.C., Mallat I., Agoulmine N., El-Mawass N. 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. Table 7 summarizes selected research works related to these five categories. Intensive research was devoted to improve the efficiency of processing and analysis of ECG signals to achieve high diagnostic accuracy. Moreover, in [141], Granados et al. [82] proposed a design for web application visualization to display data from the ECG device. However, exiting reviews related to ECG monitoring in the literature can be intuitive and incomprehensive [48]. Wearable noncontact armband for mobile ECG monitoring system. Eventually, the multi-guide synchronous ECG detection system and the twelve-guide synchronous ECG detection system will replace the current application of a wide range of single-guide ECG detection systems. Touati F., Erdene-Ochir O., Mehmood W., Hassan A., Mnaouer A.B., Gaabab B., Rasid M.F.A., Khriji L. An experimental performance evaluation and compatibility study of the Bluetooth low energy based platform for ECG monitoring in WBANs. Barison A., Del Torto A., Chiappino S., Aquaro G.D., Todiere G., Vergaro G., Passino C., Lombardi M., Emdin M., Masci P.G. 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. Ad hoc (i.e., one-time), immotile monitoring has been deployed in many research studies to address various healthcare situations using different types of ECG sensors and monitoring platforms. 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. Connect via Bluetooth to the patient's smartphone and perform a 2-leads high-resolution ECG recordings and/or remote heart and lung recordings as required. Kwon S., Lee D., Kim J., Lee Y., Kang S., Seo S., Park K. Sinabro: A smartphone-integrated opportunistic electrocardiogram monitoring system. Mirbagheri M., Hakimi N., Ebrahimzadeh E., Setarehdan S.K. 1618 February 2017; [, Krachunov S., Beach C., Casson A.J., Pope J., Fafoutis X., Piechocki R.J., Craddock I. In this section, we classify the service-based ECG monitoring systems into three main categories: diagnoses, activities, and prognoses. These may include vision-enhancing devices and technology as well as visual skills and related training. 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. Go to: Abstract Health monitoring and its related technologies is an attractive research area. These studies proposed ECG monitoring for the purpose of observing drivers health and emotions, with the ultimate goal of enhancing transport safety on the roads. ECG portable devices: example of e-Health strength and threats The data storage process is defined as a standalone process in [13,71,76], and for encrypted data storage in [72]. 47 March 2018; pp. 16. Mahmud M.S., Wang H., Esfar-E-Alam A.M., Fang H. A wireless health monitoring system using mobile phone accessories. ECG signals in the time domain, frequency domain, and wavelet domain of feature information will be extracted. The Wavelet Transform was also used in [7,60,67,95,96]. Moreover, Karaouz et al. 378382. The Piavet Measuring Device is a palm-sized, multi-sensor electrode that fits securely into a surcingle-like belt . Further future research directions include exploring the use of the fast-growing IoT and smart connected devices for preventive healthcare and supporting the detection of patients unusual medical problems or a change in behavioral patterns. 30 April2 May 2019; [. One-month ECG loop recording use [3] increased the . Due to the continuous expansion in the number of ECG monitoring systems proposed in the literature, it is very hard for researchers in this field to analyze and classify these systems into distinct, cohesive clusters of interrelated works. It provides a high level of transparency to ensure security and privacy. Event monitor. 21762181. For real-time monitoring, it is important to use energy-efficient devices and communication technologies to allow for long-term monitoring. 22152218. Ankhili A., Tao X., Cochrane C., Coulon D., Koncar V. Washable and reliable textile electrodes embedded into underwear fabric for electrocardiography (ECG) monitoring. At present, the application of ECG automatic diagnosis technology is not very extensive; it still lacks a complete set of suitable algorithms. Int. They propose a compressed sensing architecture, combining a redundancy removal scheme with quantization and Huffman entropy coding, to effectively improve the compression ratio. [255] proposed resource-aware Body Sensor Network (BSN) architecture for real-time healthcare monitoring. Energy-efficient long-term continuous personal health monitoring. Zhang Z.-X., Tian X.-W., Lim J.S. Furthermore, Jovanov et al. Egger M., Ley M., Hanke S. Emotion recognition from physiological signal analysis: A review. Yang B., Teo S.K., Hoeben B., Monterola C., Su Y. Disease prevention is another perspective in reducing monitoring costs. Smartphone ECG monitoring system helps lower emergency room and clinic visits in postatrial fibrillation ablation patients. In Table 5, we further classify the systems focusing on disease diagnosis into two main categories: (1) general CVDs, having three subcategories including Arrhythmia, AF, and other abnormalities, such as, such as left ventricular hypertrophy [11]; unexplained syncope [162]; long QT syndrome [163]; depression [164] and coronary heart disease [165], and (2) sleep apnea. Full disclosure analysis allows for highly accurate arrhythmia detection. A switching Kalman filter approach was introduced to enable the automatic selection of the most likely mode (beat type), while simultaneously filtering the signal using appropriate prior knowledge. Storage and transmission improvements were proposed in a resource-efficient ECG monitoring system named Generative Model-Driven Resource Efficient ECG Monitoring (GeM-REM). [262] utilized insertable cardiac monitors (ICMs) which are small, medically implanted devices to offer continuous ambulatory ECG monitoring with a lifespan of up to three years. Additionally, prediction based on ECG monitoring was addressed in various aspects of health status, such as survival chances, mood and behavior, and health status. In this paper, we propose a comprehensive, expert-verified taxonomy of ECG monitoring systems and conduct an extensive, systematic review of the literature. The third category of home-based ECG monitoring involves elderly monitoring; several systems have been developed, among which include [24,113,114,115]. [. Other systems support the objective of monitoring user activities; examples include sports, driving, daily activities, and elderly activities. A review of the literature on ECG monitoring systems has differentially defined the processes/stages of the ECG monitoring systems lifecycle, as depicted in Table 1. Pregnancy telemonitoring with smart control of algorithms for signal analysis. [6] Wrobel, et al. Few of the researches specified additional supporting processes, such as data storage or encryption. 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. This is why most of the research work devotes huge efforts to the preprocessing stage. 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. CVDs are disorders affecting the blood vessels and the heart. [6] An extension of this approach was proposed, which modeled not only normal and ventricular heartbeats, but also morphologies not previously encountered. [265] used an implantable loop recorder (ILR), which is a small devices with integrated leads that are implanted in a small subcutaneous pocket after a simple surgery, with a dedicated AF detection algorithm for long-term ECG monitoring in patients with atrial flutter. We intend to identify research gaps in defining the complete lifecycle of ECG monitoring systems and highlight the existing models, which include processes that overlap, or processes that are merged. 710 September 2014; pp. 1719 October 2019; pp. 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. Allows for remote transition from Holter to Extended Holter or Mobile Cardiac Telemetry, allowing for continuity of care and ease of use. Sensor 2. Few other studies used alternative wireless methods to reduce transmission and eventually reduce power consumption [234,235]. 652660. 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. El-Saadawy H., Tantawi M., Shedeed H.A., Tolba M.F. Milis M., Michaelides K., Kounoudes A., Ansaloni G., Atienza D., Giroud F., Ruedi P.-F., Masson F. 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. Kumari P., Mathew L., Syal P. Increasing trend of wearables and multimodal interface for human activity monitoring: A review. CVDs involving the blood vessels are known as vascular diseases, such as coronary artery disease. 2022 February 2019; [. Congestion may lead to a high number of packet loss and delays, which are dangerous and may lead to incorrect diagnoses.

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