Automated detection of premature ventricular contraction in ECG signals using enhanced template matching algorithm

Malek, Abdel Salam; Elnahrawy, Ashraf; Anwar, Hamed; Naeem, Mohamed

doi:10.1088/2057-1976/ab6995

Cited by 24 publications

(12 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The MNDA parameter, approximate entropy, can recognize drug-induced arrhythmias but fails to distinguish arrhythmias induced by different drug treatments. This limitation on arrhythmia distinguishing also existed in a previously reported method using automated template matching to recognize arrhythmias 28 , 40 . To overcome this limitation, our work employed two-dimensional phase space reconstruction in MNDA analysis for drug-induced arrhythmia classification based on cardiomyocyte beating recording.…”

Section: Discussionmentioning

confidence: 99%

A biosensing system using a multiparameter nonlinear dynamic analysis of cardiomyocyte beating for drug-induced arrhythmia recognition

Wang

Zou

et al. 2022

Microsyst Nanoeng

View full text Add to dashboard Cite

Cardiovascular disease is the number one cause of death in humans. Therefore, cardiotoxicity is one of the most important adverse effects assessed by arrhythmia recognition in drug development. Recently, cell-based techniques developed for arrhythmia recognition primarily employ linear methods such as time-domain analysis that detect and compare individual waveforms and thus fall short in some applications that require automated and efficient arrhythmia recognition from large datasets. We carried out the first report to develop a biosensing system that integrated impedance measurement and multiparameter nonlinear dynamic algorithm (MNDA) analysis for drug-induced arrhythmia recognition and classification. The biosensing system cultured cardiomyocytes as physiologically relevant models, used interdigitated electrodes to detect the mechanical beating of the cardiomyocytes, and employed MNDA analysis to recognize drug-induced arrhythmia from the cardiomyocyte beating recording. The best performing MNDA parameter, approximate entropy, enabled the system to recognize the appearance of sertindole- and norepinephrine-induced arrhythmia in the recording. The MNDA reconstruction in phase space enabled the system to classify the different arrhythmias and quantify the severity of arrhythmia. This new biosensing system utilizing MNDA provides a promising and alternative method for drug-induced arrhythmia recognition and classification in cardiological and pharmaceutical applications.

show abstract

Section: Discussionmentioning

confidence: 99%

A biosensing system using a multiparameter nonlinear dynamic analysis of cardiomyocyte beating for drug-induced arrhythmia recognition

Wang

Zou

et al. 2022

Microsyst Nanoeng

View full text Add to dashboard Cite

show abstract

“…In our previous work, 20 the proposed ECG processing, feature extraction, and PVC detection were simulated and evaluated before implementation in the hardware devices, using actual ECG records obtained from five Baseline noise is the time variation of the baseline from a straight line caused by respiration, variations in electrode impedance, and excessive body movements. Normally, baseline interference is a low-frequency noise over the range of 0-0.8 Hz.…”

Section: Signal Preprocessing Feature Extraction and Pvc Detectionmentioning

confidence: 99%

From fabric to smart T-shirt: fine tuning an improved robust system to detect arrhythmia

Malek¹,

Elnahrawy

Anwar

et al. 2021

Textile Research Journal

Self Cite

View full text Add to dashboard Cite

Wearable electrocardiogram (ECG) systems should be comfortable, non-stigmatizing, and capable of producing high-quality data. Many different designs of wearable textile ECG systems have recently emerged. Some of them are not considered to be smart garments, whereas most of the others present only the electronic side of the system. Our research work introduces a comprehensive study for an improved single-lead ECG smart shirt to identify automatically premature ventricular contraction as a common form of arrhythmia. For artifact-free results, Marvelous Designer is implemented to design our optimized relaxed slim fit shirt. In addition, a weft-knitted fabric of 80% nylon–20% spandex is used to manufacture the outer part of the shirt. Moreover, lightweight and small size electronic components are integrated to the outer part via low-resistance dry textile electrodes and 100% cotton fabric as an inner layer for easy transmission of weak ECG signals.

show abstract

“…Consumer engagement is often far very restricted. The volume of its CPU, information memory, & energy endurance is typically used to make an efficient market [1]. Signals analysis was emphasized for this product at the level which was rarely seen in overall worn computer technologies.…”

Section: Introductionmentioning

confidence: 99%

Implementation of QT Interval Measurement to Remove Errors in ECG

Chitra¹,

Jayalakshmi²

2022

IJACSA

View full text Add to dashboard Cite

Wireless Body Sensor Network (WBSNs) are devices that can be ported with different detection, storage, computer, but also communication capabilities. Interfacing was beneficial whenever information was collected by many sources, which may lead to erroneous sensory information. During this paper, an information nuclear fission Ensembles technique for working raw healthcare information through WBSNs during ambient cloud computer settings as described. Monitoring data were collected through various instruments and combined to provide statistics on high movements. The simulation was conducted using the low-cost Internet of Things (IoT) surveillance system on chronic kidney disease (CKD). Biosensors have been used in healthcare surveillance systems to record health problems. Patients with CKD would benefit from the developed surveillance system, which will facilitate the early diagnosis of the predominant diseases. This merged information was then sent into using the Aggregation algorithm can forecast premature cardiac illness and CKD. These groups were housed within a Cloud processing context; therefore these forecasting calculations were distributed. Another lengthy practical investigation backs that system provides application, while those findings were encouraging, with 98 percent efficiency whenever the height of that tree was equivalent with 15, total amount if estimation methods are 40, while the overall predicting job was based upon 8 attributes. We compute a mean square ECG waveform from all available leads and use a new technique to measure the QT interval. We tested this algorithm using standard and unique ECG databases. Our real-time QT interval measurement algorithm was found to be stable, accurate, and capable of tracking changing QT values.

show abstract

Automated detection of premature ventricular contraction in ECG signals using enhanced template matching algorithm

Cited by 24 publications

References 23 publications

A biosensing system using a multiparameter nonlinear dynamic analysis of cardiomyocyte beating for drug-induced arrhythmia recognition

A biosensing system using a multiparameter nonlinear dynamic analysis of cardiomyocyte beating for drug-induced arrhythmia recognition

From fabric to smart T-shirt: fine tuning an improved robust system to detect arrhythmia

Implementation of QT Interval Measurement to Remove Errors in ECG

Contact Info

Product

Resources

About