ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

Serhani, Mohamed Adel; Kassabi, Hadeel T. El; Ismail, Heba; Navaz, Alramzana Nujum

doi:10.3390/s20061796

Cited by 231 publications

(135 citation statements)

References 257 publications

(453 reference statements)

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“…Both feature extraction and classification approaches are the critical successes of any automatic ECG classification. There are plenty of applications that ECG analysis and classification involve, such as ischemic heart disease, arrhythmia, and myocardial infarction [3].…”

Section: Introductionmentioning

confidence: 99%

CNN-LSTM Based Model for ECG Arrhythmias and Myocardial Infarction Classification

Abdullah¹,

Al-Ani²

2020

Adv. sci. technol. eng. syst. j.

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ECG analysis is commonly used by medical practitioners and cardiologists for monitoring cardiac health. A high-performance automatic ECG classification system is a challenging area because there is difficulty in detecting and clustering various waveforms in the signal, especially in the manual analysis of electrocardiogram (ECG) signals. In this paper, an accurate (ECG) classification and monitoring system are proposed using the implementation of 1D Convolutional Neural Networks (CNNs) and Long Short Term Memory (LSTM). The learned features are captured from the CNN model, and then fed to the LSTM model. No handcraft features are required for the model for the ECG classification. The result of the CNN-LSTM model has demonstrated superior performance than several state-of-the-arts that cited in the result section. The proposed models are evaluated on MIT-BIH arrhythmia and PTB Diagnostics datasets. Based on the obtained results, the CNN-LSTM method can improve the accuracy rate, such that 98.1 % and 98.66 % on Myocardial Infarction (MI) and arrhythmia classification, respectively.

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Section: Introductionmentioning

confidence: 99%

CNN-LSTM Based Model for ECG Arrhythmias and Myocardial Infarction Classification

Abdullah¹,

Al-Ani²

2020

Adv. sci. technol. eng. syst. j.

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“…Regarding the regulatory environment, a recent survey performed by the World Health Organization [67], reveals that out of all the member states, only 58% have an eHealth policy, 55% have legislation to protect electronic patient data and 87% have at least one or more national initiatives to promote eHealth and mHealth services. In Europe, massive progress has been achieved since the early 1990s when the European Commission started to promote the adoption of eHealth practices in the member states.…”

Section: Fostering Mhealth and Ehealth Solutionsmentioning

confidence: 99%

Benefits of Home-Based Solutions for Diagnosis and Treatment of Acute Coronary Syndromes on Health Care Costs: A Systematic Review

Redon

Shahzad

Iqbal

et al. 2020

Sensors

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Diagnosing and treating acute coronary syndromes consumes a significant fraction of the healthcare budget worldwide. The pressure on resources is expected to increase with the continuing rise of cardiovascular disease, other chronic diseases and extended life expectancy, while expenditure is constrained. The objective of this review is to assess if home-based solutions for measuring chemical cardiac biomarkers can mitigate or reduce the continued rise in the costs of ACS treatment. A systematic review was performed considering published literature in several relevant public databases (i.e., PUBMED, Cochrane, Embase and Scopus) focusing on current biomarker practices in high-risk patients, their cost-effectiveness and the clinical evidence and feasibility of implementation. Out of 26,000 references screened, 86 met the inclusion criteria after independent full-text review. Current clinical evidence highlights that home-based solutions implemented in primary and secondary prevention reduce health care costs by earlier diagnosis, improved patient outcomes and quality of life, as well as by avoidance of unnecessary use of resources. Economical evidence suggests their potential to reduce health care costs if the incremental cost-effectiveness ratio or the willingness-to-pay does not surpass £20,000/QALY or €50,000 limit per 20,000 patients, respectively. The cost-effectiveness of these solutions increases when applied to high-risk patients.

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“…As we know day by day the number of death increasing caused by chronic and cardiovascular diseases (CVDs) throughout the society. According to WHO, 17.9 million death every year caused by CVDs [30]. IoT-driven Electrocardiogram monitoring can play a significant role in improving safety and well-being along with quality medical care.…”

Section: Ecg Monitoringmentioning

confidence: 99%

Pharma 4.0–IMPACT of the Internet of Things on Health Care

2020

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The IoT in health care is currently booming in the world of health care in particular. Industry has risen from generation 1.0 to 4.0 during the Internet of things period. As we remember, we came across the exact submission of the traditional health care system. Each time the patient has needed to visit the clinic/hospitals, even for small complications that may affect the patient's medical costs along with time and energy. One more significant factor is also an emergency; otherwise, she/he/older population was unable to demand urgent assistance from the older system of healthcare. And yet somehow, the situation has changed with the use of the cyber-physical world; we are heading out of the 4th phase of the health care industry means smart health care network. This paper offers an insight into different facets of how healthcare systems such as doctors, hospitals, and of course, patients are powered by the internet of things and how can it track and ensure fast, quality, and efficient use of less time also in a smart way. Here, a patient knows how to track patients by using a collection of different wearable sensor nodes for real-time monitoring and examination of specific patient criteria. One of the most boosting subjects characterizes the development of medical technology within their own homes, enabling older or physically weak people to stay as long as possible at home while being medically cared for and monitored. We searched literature and guidelines in Pubmed, Web of Science, Google Scholar, Scopus, CNKI, and Embase databases up to 2019. The following search terms alone or matched with the Boolean operators ‘AND’ or ‘OR’ were used: "Nanoparticles", “Anticancer treatment", ‘Bioflavonoids’, ‘Plant origin drugs’, ‘Nano formulations’, ‘Cancer’ and ‘Novel drug delivery systems’. We focused on full-text articles, but abstracts were considered if relevant.

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ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

Cited by 231 publications

References 257 publications

CNN-LSTM Based Model for ECG Arrhythmias and Myocardial Infarction Classification

CNN-LSTM Based Model for ECG Arrhythmias and Myocardial Infarction Classification

Benefits of Home-Based Solutions for Diagnosis and Treatment of Acute Coronary Syndromes on Health Care Costs: A Systematic Review

Pharma 4.0–IMPACT of the Internet of Things on Health Care

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