We present a QRS detection algorithm for wearable ECG applications using a proportional-derivative (PD) control. ECG data of arrhythmia have irregular intervals and magnitudes of QRS waves that impede correct QRS detection. To resolve the problem, PD control is applied to avoid missing a small QRS wave followed from a large QRS wave and to avoid falsely detecting noise as QRS waves when an interval between two adjacent QRS waves is large (e.g. bradycardia, pause, and arioventricular block). ECG data was obtained from 78 patients with various cardiovascular diseases and tested for the performance evaluation of the proposed algorithm. The overall sensitivity and positive predictive value were 99.28% and 99.26%, respectively. The proposed algorithm has low computational complexity, so that it can be suitable to apply mobile ECG monitoring system in real time.
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http://dx.doi.org/10.1109/EMBC.2012.6347273 | DOI Listing |
Biomed Phys Eng Express
January 2025
Electronics and Communication Engineering, Rajiv Gandhi University, Rono Hills, Doimukh, ITANAGAR, Itanagar, Arunachal Pradesh, 791112, INDIA.
Accurate detection of cardiac arrhythmias is crucial for preventing premature deaths. The current study employs a dual-stage Discrete Wavelet Transform (DWT) and a median filter to eliminate noise from ECG signals. Subsequently, ECG signals are segmented, and QRS regions are extracted for further preprocessing.
View Article and Find Full Text PDFPhysiol Res
December 2024
Department of Physiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
Myocardial remodelling involves structural and functional changes in the heart, potentially leading to heart failure. The deoxycorticosterone acetate (DOCA)/salt model is a widely used experimental approach to study hypertension-induced cardiac remodelling. It allows to investigate the mechanisms underlying myocardial fibrosis and hypertrophy, which are key contributors to impaired cardiac function.
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
Electronics and Communication Engineering, Rajiv Gandhi University, Rono Hills, Doimukh, ITANAGAR, Itanagar, Arunachal Pradesh, 791112, INDIA.
Accurate detection of cardiac arrhythmias is crucial for preventing premature deaths. The current study employs a dual-stage Discrete Wavelet Transform (DWT) and a median filter to eliminate noise from ECG signals. Subsequently, ECG signals are segmented, and QRS regions are extracted for further preprocessing.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Cardiac wall motion abnormalities (WMA) are strong predictors of mortality, but current screening methods using Q waves from electrocardiograms (ECGs) have limited accuracy and vary across racial and ethnic groups. This study aimed to identify novel ECG features using deep learning to enhance WMA detection, referencing echocardiography as the gold standard. We collected ECG and echocardiogram data from 35,210 patients in California and labeled WMA using unstructured language parsing of echocardiographic reports.
View Article and Find Full Text PDFCardiol Young
January 2025
Saitama Children's Medical Center, Division of Pediatric Cardiology, Saitama, Japan.
Background: The Wolff-Parkinson-White pattern is a delta wave frequently detected in school-based cardiovascular screening programs in Japan. Although most children with Wolff-Parkinson-White pattern are asymptomatic, initial symptoms may include syncope or sudden death, necessitating accurate diagnosis and management. Delta waves can also indicate a fasciculoventricular pathway, which poses no risk and does not require management.
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