4 citations · 4 across the 4 of their papers we have counts for
7 papers
RPnet: A Deep Learning approach for robust R Peak detection in noisy ECG
Sricharan Vijayarangan, Vignesh R, Balamurali Murugesan +3
Automatic detection of R-peaks in an Electrocardiogram signal is crucial in a multitude of applications including Heart Rate Variability (HRV) analysis and Cardio Vascular Disease(…
Robust Modelling of Reflectance Pulse Oximetry for SpO Estimation
Sricharan Vijayarangan, Prithvi Suresh, Preejith SP +2
Continuous monitoring of blood oxygen saturation levels is vital for patients with pulmonary disorders. Traditionally, SpO monitoring has been carried out using transmittance p…
Interpreting Deep Neural Networks for Single-Lead ECG Arrhythmia Classification
Sricharan Vijayarangan, Balamurali Murugesan, Vignesh R +3
Cardiac arrhythmia is a prevalent and significant cause of morbidity and mortality among cardiac ailments. Early diagnosis is crucial in providing intervention for patients sufferi…
Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation
Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana +3
For the task of medical image segmentation, fully convolutional network (FCN) based architectures have been extensively used with various modifications. A rising trend in these arc…
Deep Network for Capacitive ECG Denoising
Vignesh Ravichandran, Balamurali Murugesan, Sharath M Shankaranarayana +4
Continuous monitoring of cardiac health under free living condition is crucial to provide effective care for patients undergoing post operative recovery and individuals with high c…
PPGnet: Deep Network for Device Independent Heart Rate Estimation from Photoplethysmogram
Shyam A, Vignesh Ravichandran, Preejith S. P +2
Photoplethysmogram (PPG) is increasingly used to provide monitoring of the cardiovascular system under ambulatory conditions. Wearable devices like smartwatches use PPG to allow lo…