Atrial Fibrillation detection on electrocardiogram

Mabrouki, Rebeh; Khaddoumi, Balkine; Sayadi, Mounir

doi:10.1109/atsip.2016.7523112

Cited by 11 publications

(8 citation statements)

References 8 publications

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“…The Pan-Tompkins algorithm [23] is then used to complete the R Peak detection. The Pan-Tompkins algorithm consists of four stages: the ECG signal must pass through a low pass filter [24] and a high pass filter (bandpass filter [25] to filter out the noise such as 50Hz power line noise), a differentiator is applied to the signal to provide QRS slope information, a squaring function is applied to make the points positive and amplify the higher frequency output, and a moving window integrator is introduced to detect the QRS complex by averaging the samples [23]. The R peaks are clearly being noticed after the QRS complex have formed.…”

Section: R Peak Detectionmentioning

confidence: 99%

The Sensitivity of The Heart Rate Detection for Atrial Electrograms Signal

Kong¹,

Ahmad²,

Hassan³

et al. 2021

Elektrika

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Atrial Fibrillation (AF) is the most familiar example of arrhythmia that will occur health problems such as stroke, heart failure and other complications. Globally, the number of AF patients will more than triple by 2050 worldwide. Current methods involve performing large-area ablation without knowing the exact location of key parts. The reliability of the technology can be used as a target for atrial fibrillation’s catheter ablation. The factors that leading to the onset of atrial fibrillation include the triggering factors that induce arrhythmia and the substrate that maintains the arrhythmia. The project’s aim is to create a method for identifying AF that can be used as screening tool in medical practice. The primary goals for the detection method’s design are to develop a MATLAB software program that can compare the complexity of a normal ECG signal and an AF ECG signal. Currently, this can be achieved by the ECG Signal’s R peaks and RR Interval. For AF detection, there are more R peaks and RR Intervals and it is irregular. In this research, the detection of AF is based on the heart rate (RR Intervals). For the ECG preprocessing, Pan-Tompkins Algorithm and Discrete Wavelet Transform is used to detect the sensitivity on the R peaks and RR Intervals. As a result, Discrete Wavelet Transform algorithm gives 100% sensitivity for the dataset obtained from MIT-BIH Atrial Fibrillation and MIT-BIH Arrhythmia Database.

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Section: R Peak Detectionmentioning

confidence: 99%

The Sensitivity of The Heart Rate Detection for Atrial Electrograms Signal

Kong¹,

Ahmad²,

Hassan³

et al. 2021

Elektrika

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show abstract

“…Furthermore, P, QRS and T points of the AFR signals have been detected with a 100% success rate at this stage. R. Mabrouki et al (2016) performed AF detection via RRI through nonlinear statistical analysis. Here, they obtained 97.91% success rate from the MIT-BIH AF Database and 99.65% from the MIT-BIH Arrhythmia Database.…”

Section: Scientific Literature Scanningmentioning

confidence: 99%

Atri̇yal Fi̇bri̇lasyonun Rr Araliği İle Otomati̇k Tespi̇ti̇

Güzeler

Bilgin

2019

Mühendislik Bilimleri Ve Tasarım Dergisi

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Heart diseases are rapidly increasing worldwide and in our country. This increase causes difficulties in the diagnosis processes of heart diseases. Considering these problems, the studies of engineering applications related to medical science give effective results in terms of solutions. By means of engineering devices and algorithms, positive contributions are made to medical applications. These contributions assist physicians especially in the diagnosis stages and speed up these processes. In this study, a new algorithm is developped so that Atrial Fibrillation (AF), which is the most common type of arrhythmia encountered, can be automatically detected at a high success rate. Electrocardiogram (ECG) data used in this study were obtained from physiobank ATM database. 31 samples of Atrial Fibrillation Rhythm (AFR) and 31 samples of Normal Sinus Rhythm (NSR) were obtained from this database. RR Interval (RRI) sequences being 12 hours long are used in the study. The change of the RRI sequences is an important parameter for AF. The RRI sequences are re-sampled using signal pre-processing techniques. The Discrete Wavelet Transform (DWT) was then applied to the resampled signals. In this way, feature extraction process is performed and the wavelet energies of these signals are visually examined with boxplot. The wavelet energies of the RRI sequences are classified by the Support Vector Machine (SVM). Finally, AFR and NSR are successfully separated as 99.60% achievement.

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“…• aos intervalos entre picos R consecutivos, denominados intervalos RR (Kalsi;Prakash, 2016;Moody et al, 1983;Logan;Healey, 2005;Mohebbi;Ghassemian, 2012;Ladavich;Ghoraani, 2014;Pürerfellner et al, 2014;Maji;Mitra;Pal, 2014;Hargittai, 2014;Kennedy et al, 2016;Linker et al, 2016;Islam et al, 2016;Mabrouki;Khaddoumi;Sayadi, 2016;Yoon et al, 2015;Andersson et al, 2015;Nemati et al, 2016);…”

Section: Sinais Para a Detecção De Fibrilação Atrialmentioning

confidence: 99%

“…• gráficos de Poincaré, dos intervalos RR atuais versus os intervalos anteriores (Mohebbi;Ghassemian, 2012;Mabrouki;Khaddoumi;Sayadi, 2016;Chong et al, 2015);…”

Section: Parâmetros Para a Detecção De Fibrilação Atrialunclassified

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Classificação de segmentos de eletrocardiograma normais e com fibrilação atrial: estudo metodológico.

Jeong¹

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Primeiramente, gostaria de agradecer aos meus pais, que me incentivaram e apoiaram durante a minha formação. Principalmente a minha mãe que infelizmente acabou partindo, durante o decorrer do mestrado.Aos meus irmãos que tem me dado suporte. Seus incentivos foram fundamentais para que eu não perdesse os prazos de submissão e de apresentação do artigo no congresso.À Profa. Dra. Cinthia Itiki, por toda a sua paciência e excelente orientação. Apesar de todas as dificuldades e situações durante o período do mestrado, esteve constantemente me orientando e ajudando.

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Atrial Fibrillation detection on electrocardiogram

Cited by 11 publications

References 8 publications

The Sensitivity of The Heart Rate Detection for Atrial Electrograms Signal

The Sensitivity of The Heart Rate Detection for Atrial Electrograms Signal

Atri̇yal Fi̇bri̇lasyonun Rr Araliği İle Otomati̇k Tespi̇ti̇

Classificação de segmentos de eletrocardiograma normais e com fibrilação atrial: estudo metodológico.

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