A mobile application for ECG detection and feature extraction

Stojmenski, Aleksandar; Gušev, Marjan; Chorbev, Ivan

doi:10.20544/aiit2016.37

Cited by 7 publications

(10 citation statements)

References 11 publications

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“…Interestingly, research on ES and DSS for ECG interpretation and diagnosis has witnessed tremendous growth over the past few years. Researchers have investigated and explored the possible use of mobile application development to reduce the stress in ECG data acquisition and diagnosis [24][25][26][27]. Cloud-based models [4,14], ontology framework [28,29], wearable sensors [10,30] and a XML rule-based repository [31], as well as Internet-of-Things (IoT) [4], among others, have been considered to aid in the diagnosis of heart diseases.…”

Section: Review Methodologymentioning

confidence: 99%

“…Some applications carry out basic interpretation processes such as QRS detection, R-R interval detection and heart rate measures on the mobile interface [20,48,121] so that users can have a quick grasp of their condition before transmission to cloud processing center for in-depth analysis or in the event of unavailability of cloud services. Most ECG mobile applications employ red-oriented colors for designing mock-ups or ECG traces to portray heart feelings [3,24,26]. Visualization is also implemented on the web application to be used by the cardiac patient and medical staff.…”

Section: Design Architecture Of Ecg Mobile Applicationsmentioning

confidence: 99%

“…Users receive the reports as an alert on the mobile application. An example of an analysis report alert on an ECG mobile application is presented in [24].…”

Section: Design Architecture Of Ecg Mobile Applicationsmentioning

confidence: 99%

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Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

et al. 2022

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Electrocardiography (ECG) is one of the most widely used recordings in clinical medicine. ECG deals with the recording of electrical activity that is generated by the heart through the surface of the body. The electrical activity generated by the heart is measured using electrodes that are attached to the body surface. The use of ECG in the diagnosis and management of cardiovascular disease (CVD) has been in existence for over a decade, and research in this domain has recently attracted large attention. Along this line, an expert system (ES) and decision support system (DSS) have been developed for ECG interpretation and diagnosis. However, despite the availability of a lot of literature, access to recent and more comprehensive review papers on this subject is still a challenge. This paper presents a comprehensive review of the application of ES and DSS for ECG interpretation and diagnosis. Researchers have proposed a number of features and methods for ES and DSS development that can be used to monitor a patient’s health condition through ECG recordings. In this paper, a taxonomy of the features and methods for ECG interpretation and diagnosis were presented. The significance of the features and methods, as well as their limitations, were analyzed. This review further presents interesting theoretical concepts in this domain, as well as identifies challenges and open research issues on ES and DSS development for ECG interpretation and diagnosis that require substantial research effort. In conclusion, this paper identifies important future research areas with the purpose of advancing the development of ES and DSS for ECG interpretation and diagnosis.

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Section: Review Methodologymentioning

confidence: 99%

Section: Design Architecture Of Ecg Mobile Applicationsmentioning

confidence: 99%

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Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

et al. 2022

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“…Authors in [13] present a system architecture design based on three layers. The Edge layer is implemented by utilizing the Savvy ECG sensor in order to capture the ECG signal.…”

Section: Related Workmentioning

confidence: 99%

From edge to cloud: Design and implementation of a healthcare Internet of Things infrastructure

Masouros

Bakolas

Tsoutsouras

et al. 2017

2017 27th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS)

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Lately, the advancement in circuit technology combined with the design of low cost embedded devices have resulted in an infiltration of the latter into everyday humans' lives. To exploit the full potential of ubiquitous embedded devices, a network is used for their inter-communication, offering advanced real-time monitoring. This paradigm, known as Internet of Things (IoT), is steadily consolidated and promises to offer a wide variety of applications. However, with the adoption of IoT, new challenges arise, such as the design of architectures able to support the requirements of the new applications. Towards this goal, we explore a three layered architecture, able to acquire, process and store Healthcare data as well as to provide real-time decision making. We use ECG signal arrhythmia detection as our use case evaluation scenario, and compare different techniques for wireless communication, storage and data classification. Experimental results show that, our architecture provides realtime decision making, with an average delay of 15 μs and that different communication technologies achieved to provide up to 10% lower power consumption on the monitoring devices. 1

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“…In our earlier paper [15] we presented a proof-of-concept system for analysis of heart operation and heart attack detection using ECG sensor. In this paper, we elaborate the challenges we have met and solved in the development of the mHealth solution based on a mobile application that monitors the heart.…”

Section: Introductionmentioning

confidence: 99%

Challenges for development of an ECG m-Health solution

Gušev¹,

Stojmenski²,

Chorbev³

2016

ERSICT

Self Cite

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Abstract. This paper presents the challenges to develop a system for early detection and alerting of the onset of a heart attack. The system consists of a wireless, easily wearable and mobile ECG biosensor, a cloud-based data centre, smartphone and web application. A significant part of the system is the 24h health monitoring and care provided by expert cardiac physicians. The system predicts potential heart attack and sends risk alerts to the medical experts for assessment. If a potential heart attack risk exists, an emergency ambulance is being called with the coordinates of the cardiac patient wearing the sensor. The timely reaction can prevent serious tissue damage or even death to the users of the system. Our goal in this paper is to elaborate the challenges we met and solutions we have developed for development of an m-Health mobile application for detection of abnormalities in the ECG and alerting of a heart attack. The problems analyzed address Low Power Bluetooth connections, number conversion and transmission, decision making on what to be locally processed and what computations to be offloaded to cloud, software architecture, type of initial filtering for obtaining sufficient quality of the ECG signal, and visualization approach with relatively small processing requirements.

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A mobile application for ECG detection and feature extraction

Cited by 7 publications

References 11 publications

Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

From edge to cloud: Design and implementation of a healthcare Internet of Things infrastructure

Challenges for development of an ECG m-Health solution

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