ORCID Profile
0000-0002-2926-8014
Current Organisations
Western Sydney University
,
University of Sydney
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Publisher: ACM
Date: 08-07-2009
Publisher: Elsevier BV
Date: 06-2011
Publisher: IEEE
Date: 2009
DOI: 10.1109/AMS.2009.125
Publisher: IEEE
Date: 12-2011
DOI: 10.1109/ICI.2011.13
Publisher: ACM
Date: 08-07-2009
Publisher: Springer Science and Business Media LLC
Date: 12-2018
Publisher: Elsevier BV
Date: 12-2023
Publisher: ACM
Date: 08-07-2009
Publisher: Routledge
Date: 17-06-2016
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: IEEE
Date: 11-2019
Publisher: MDPI AG
Date: 21-11-2019
DOI: 10.3390/S19235079
Abstract: Abnormal heart rhythms are one of the significant health concerns worldwide. The current state-of-the-art to recognize and classify abnormal heartbeats is manually performed by visual inspection by an expert practitioner. This is not just a tedious task it is also error prone and, because it is performed, post-recordings may add unnecessary delay to the care. The real key to the fight to cardiac diseases is real-time detection that triggers prompt action. The biggest hurdle to real-time detection is represented by the rare occurrences of abnormal heartbeats and even more are some rare typologies that are not fully represented in signal datasets the latter is what makes it difficult for doctors and algorithms to recognize them. This work presents an automated heartbeat classification based on nonlinear morphological features and a voting scheme suitable for rare heartbeat morphologies. Although the algorithm is designed and tested on a computer, it is intended ultimately to run on a portable i.e., field-programmable gate array (FPGA) devices. Our algorithm tested on Massachusetts Institute of Technology- Beth Israel Hospital(MIT-BIH) database as per Association for the Advancement of Medical Instrumentation(AAMI) recommendations. The simulation results show the superiority of the proposed method, especially in predicting minority groups: the fusion and unknown classes with 90.4% and 100%.
Publisher: MDPI AG
Date: 08-06-2020
DOI: 10.3390/S20113275
Abstract: With this paper we communicated the existence of a surface electrocardiography (ECG) recordings dataset, named WCTECGdb, that aside from the standard 12-lead signals includes the raw electrode biopotential for each of the nine exploring electrodes refereed directly to the right leg. This dataset, comprises of 540 ten second segments recorded from 92 patients at C belltown Hospital, NSW Australia, and is now available for download from the Physionet platform. The data included in the dataset confirm that the Wilson’s Central Terminal (WCT) has a relatively large litude (up to 247% of lead II) with standard ECG characteristics such as a p-wave and a t-wave, and is highly variable during the cardiac cycle. As further ex les of application for our data, we assess: (1) the presence of a conductive pathway between the legs and the heart concluding that in some cases is electrically significant and (2) the initial assumption about the limbs potential stating the dominance of the left arm concluding that this is not always the case and that might requires case to case assessment.
Publisher: PhysioNet
Date: 2020
DOI: 10.13026/F73Z-AN96
Publisher: MDPI AG
Date: 20-07-2018
DOI: 10.3390/S18072353
Abstract: Since its inception, electrocardiography has been based on the simplifying hypothesis that cardinal limb leads form an equilateral triangle of which, at the center/centroid, the electrical equivalent of the cardiac activity rotates during the cardiac cycle. Therefore, it is thought that the three limbs (right arm, left arm, and left leg) which enclose the heart into a circuit, where each branch directly implies current circulation through the heart, can be averaged together to form a stationary reference (central terminal) for precordials/chest-leads. Our hypothesis is that cardinal limbs do not form a triangle for the majority of the duration of the cardiac cycle. As a corollary, the central point may not lie in the plane identified by the limb leads. Using a simple and efficient algorithm, we demonstrate that the portion of the cardiac cycle where the three limb leads form a triangle is, on average less, than 50%.
Publisher: Elsevier BV
Date: 04-2012
Publisher: MDPI AG
Date: 15-10-2016
No related grants have been discovered for Hossein Moeinzadeh.