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Published on: June 5, 2019
An ANN-based HRV classifier for cardiac health prognosis
Ramesh Kumar Sunkaria1, Vinod Kumar1, Suresh Chandra Saxena1
1Electrical Engineering Department, Indian Institute of Technology Roorkee, Roorkee (Uttaranchal), 247667, India.
Abstract:
A multi-layer artificial neural network (ANN)-based heart rate variability (HRV) classifier has been proposed, which gives the cardiac health status as the output based on HRV of the patients independently of the cardiologists' view. The electrocardiogram (ECG) data of 46 patients were recorded in the out-patient department (OPD) of a hospital and HRV was evaluated using self-designed autoregressive-model-based technique. These patients suspected to be suffering from cardiac abnormalities were thoroughly examined by experienced cardiologists. On the basis of symptoms and other investigations, the attending cardiologists advised them to be classified into four categories as per the severity of cardiac health. Out of 46, the HRV data of 28 patients were used for training and data of 18 patients were used for testing of the proposed classifier. The cardiac health classification of each tested patient with the proposed classifier matches with the medical opinion of the cardiologists.
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Assessment of apical radial pulse
The A-R pulse assessment involves simultaneous evaluation of the apical and radial pulses. When the apical and radial pulse rates vary, this assessment helps identify a pulse deficit.
Pre-Procedural Preparation

