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heart-ventricle-extrasystole
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Robust detection of premature ventricular contractions using a wave-based Bayesian framework
, Article IEEE transactions on bio-medical engineering ; Volume 57, Issue 2 , September , 2010 , Pages 353-362 ; 15582531 (ISSN) ; Shamsollahi, M. B ; Clifford, G. D ; Sharif University of Technology
2010
Abstract
Detection and classification of ventricular complexes from the ECG is of considerable importance in Holter and critical care patient monitoring, being essential for the timely diagnosis of dangerous heart conditions. Accurate detection of premature ventricular contractions (PVCs) is particularly important in relation to life-threatening arrhythmias. In this paper, we introduce a model-based dynamic algorithm for tracking the ECG characteristic waveforms using an extended Kalman filter. The algorithm can work on single or multiple leads. A "polargram"--a polar representation of the signal--is introduced, which is constructed using the Bayesian estimations of the state variables. The polargram...
LSTM-Based ecg classification for continuous monitoring on personal wearable devices
, Article IEEE Journal of Biomedical and Health Informatics ; Volume 24, Issue 2 , 2020 , Pages 515-523 ; Oveisi, M ; Hashemi, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
Objective: A novel electrocardiogram (ECG) classification algorithm is proposed for continuous cardiac monitoring on wearable devices with limited processing capacity. Methods: The proposed solution employs a novel architecture consisting of wavelet transform and multiple long short-term memory (LSTM) recurrent neural networks (see Fig. 1). Results: Experimental evaluations show superior ECG classification performance compared to previous works. Measurements on different hardware platforms show the proposed algorithm meets timing requirements for continuous and real-time execution on wearable devices. Conclusion: In contrast to many compute-intensive deep-learning based approaches, the...
Clinical validation of a smartphone-based handheld ECG device: A validation study
, Article Critical Pathways in Cardiology ; Volume 21, Issue 4 , 2022 , Pages 165-171 ; 1535282X (ISSN) ; Gharebaghi, M ; Kamalian, E ; Hajghassem, H ; Ghanbari, A ; Karimi, A ; Mansoury, B ; Dayari, M. S ; Khatmi Nemati, M ; Karimi, A ; Zarghami, M. H ; Vasheghani Farahani, A ; Sharif University of Technology
Lippincott Williams and Wilkins
2022
Abstract
Background: Remote cardiac monitoring and screening have already become an integral telemedicine component. The wide usage of several different wireless electrocardiography (ECG) devices warrants a validation study on their accuracy and reliability. Methods: Totally, 300 inpatients with the Nabz Hooshmand-1 handheld ECG device and the GE MAC 1200 ECG system (as the reference) were studied to check the accuracy of the devices in 1 and 6-limb lead performance. Simultaneous 10-second resting ECGs were assessed for the most common ECG parameters in lead I. Afterward, 6-lead ECGs (limb leads), were performed immediately and studied for their morphologies. Results: Of the 300 patients, 297 had...