A Continuous Wavelet Transform Based Method for Detecting Heart Valve Disorders Using Phonocardiograph Signals. - Shivnarayan Patidar; Ram Bilas Pachori (ICHIT (2), 2012)

Segmentation of cardiac sound signals by removing murmurs using constrained tunable-Q wavelet transform. - Shivnarayan Patidar; Ram Bilas Pachori (Biomed. Signal Process. Control., 2013)

Detection of septal defects from cardiac sound signals using tunable-Q wavelet transform. - Shivnarayan Patidar; Ram Bilas Pachori; Niranjan Garg (DSP, 2014)

Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions. - Ram Bilas Pachori; Shivnarayan Patidar (Comput. Methods Programs Biomed., 2014)

Classification of cardiac sound signals using constrained tunable-Q wavelet transform. - Shivnarayan Patidar; Ram Bilas Pachori (Expert Syst. Appl., 2014)

Automatic diagnosis of septal defects based on tunable-Q wavelet transform of cardiac sound signals. - Shivnarayan Patidar; Ram Bilas Pachori; Niranjan Garg (Expert Syst. Appl., 2015)

Automated diagnosis of coronary artery disease using tunable-Q wavelet transform applied on heart rate signals. - Shivnarayan Patidar; Ram Bilas Pachori; U. Rajendra Acharya (Knowl. Based Syst., 2015)

Classification of Heart Disorders Based on Tunable-Q Wavelet Transform of Cardiac Sound Signals. - Shivnarayan Patidar; Ram Bilas Pachori (Chaos Modeling and Control Systems Design, 2015)

Classification of Normal and Epileptic Seizure EEG Signals Based on Empirical Mode Decomposition. - Ram Bilas Pachori; Rajeev Sharma; Shivnarayan Patidar (Complex System Modelling and Control Through Intelligent Soft Computations, 2015)

Design and Implementation of Tunable Bandpass Filter for Biomedical Applications. - Saurabh B. Kaurati; Nithin Y. B. Kumar; Shivnarayan Patidar; M. H. Vasantha (iNIS, 2016)

Atrial Fibrillation Detection Using Convolutional Neural Networks. - Sandeep Chandra Bollepalli; Challa S. Sastry; Soumya Jana; Shivnarayan Patidar (CinC, 2017)

Automated Detection of Atrial Fbrillation using Fourier-Bessel expansion and Teager Energy Operator from Electrocardiogram Signals. - Shivnarayan Patidar; Ashish Sharma 007; Niranjan Garg (CinC, 2017)

An integrated alcoholic index using tunable-Q wavelet transform based features extracted from EEG signals for diagnosis of alcoholism. - Shivnarayan Patidar; Ram Bilas Pachori; Abhay Upadhyay; U. Rajendra Acharya (Appl. Soft Comput., 2017)

Detection of epileptic seizure using Kraskov entropy applied on tunable-Q wavelet transform of EEG signals. - Shivnarayan Patidar; Trilochan Panigrahi (Biomed. Signal Process. Control., 2017)

Application of Recurrent Neural Network for the Prediction of Target Non-Apneic Arousal Regions in Physiological Signals. - Naimahmed Nesaragi; Shubha Majumder; Ashish Sharma 007; Kouhyar Tavakolian; Shivnarayan Patidar (CinC, 2018)

Design of Area-Power-Delay Efficient Square Root Carry Select Adder. - Chetan Kamble; Siddharth R. K.; Shivnarayan Patidar; M. H. Vasantha; Nithin Y. B. Kumar (iSES, 2018)

Diagnosis of Sepsis Using Ratio Based Features. - Shivnarayan Patidar (CinC, 2019)

Accurate tunable-Q wavelet transform based method for QRS complex detection. - Ashish Sharma 007; Shivnarayan Patidar; Abhay Upadhyay; U. Rajendra Acharya (Comput. Electr. Eng., 2019)

Automated pre-screening of arrhythmia using hybrid combination of Fourier-Bessel expansion and LSTM. - Ashish Sharma 007; Niranjan Garg; Shivnarayan Patidar; Ru-San Tan; U. Rajendra Acharya (Comput. Biol. Medicine, 2020)

Diagnosis of Cardiac Abnormalities Applying Scattering Transform and Fourier-Bessel Expansion on ECG Signals. - Nidhi Kalidas Sawant; Shivnarayan Patidar (CinC, 2021)

Tensor learning of pointwise mutual information from EHR data for early prediction of sepsis. - Naimahmed Nesaragi; Shivnarayan Patidar; Vaneet Aggarwal (Comput. Biol. Medicine, 2021)

A Tensor Decomposition-Based Feature Extraction Method to Predict Neurological Recovery from Coma After Cardiac Arrest Using EEG Signals. - Shivnarayan Patidar; Nidhi Kalidas Sawant (CinC, 2023)