7 citations · 8 across the 4 of their papers we have counts for
5 papers
EEG aided boosting of single-lead ECG based sleep staging with Deep Knowledge Distillation
Vaibhav Joshi, Sricharan V, Preejith SP +1
An electroencephalogram (EEG) signal is currently accepted as a standard for automatic sleep staging. Lately, Near-human accuracy in automated sleep staging has been achievable by…
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…
KD-MRI: A knowledge distillation framework for image reconstruction and image restoration in MRI workflow
Balamurali Murugesan, Sricharan Vijayarangan, Kaushik Sarveswaran +2
Deep learning networks are being developed in every stage of the MRI workflow and have provided state-of-the-art results. However, this has come at the cost of increased computatio…