S. Sabut

发表

De-noising of ECG Signal and QRS Detection Using Hilbert Transform and Adaptive Thresholding

Santanu Sahoo, P. Biswal, Tejaswini Das, 2016 .

CLINICAL GAIT ANALYSIS OF SUBJECTS WITH TRANS-FEMORAL AMPUTATION USING POLYCENTRIC FOUR-BAR LINKAGE PROSTHETIC KNEE JOINT

R. K. Mohanty, S. Das, S. Sabut, 2020 .

VENTRICULAR TACHYCARDIA AND FIBRILLATION DETECTION USING DWT AND DECISION TREE CLASSIFIER

S. Sabut, M. Mohanty, P. Biswal, 2019, Journal of Mechanics in Medicine and Biology.

Multiresolution wavelet transform based feature extraction and ECG classification to detect cardiac abnormalities

Santanu Sahoo, Sukanta Sabut, Suresh Behera, 2017 .

Effect of functional electrical stimulation on the effort and walking speed, surface electromyography activity, and metabolic responses in stroke subjects.

Manjunatha Mahadevappa, Prasanna K Lenka, M. Mahadevappa, 2010, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

Detection of Liver Cancer Using Modified Fuzzy Clustering and Decision Tree Classifier in CT Images

Sukanta Sabut, Amita Das, S. Sabut, 2019, Pattern Recognition and Image Analysis.

Efficient Detection and Classification of Diabetic Foot Ulcer Tissue using PSO Technique

S. Sabut, Babu K S, Nithya D K, 2018, International Journal of Engineering & Technology.

Machine learning approach for epileptic seizure detection using the tunable-Q wavelet transform based time–frequency features

S. Sabut, N. Rout, Sasweta Pattnaik, 2022, International Journal of Information Technology.

Functional electrical stimulation on improving foot drop gait in poststroke rehabilitation: a review of its technology and clinical efficacy.

M Manjunatha, M. Manjunatha, S. Sabut, 2013, Critical reviews in biomedical engineering.

Computational Intelligence Approach for Predicting Ischemic Stroke using Brain MRI

S. Sabut, A. Subudhi, M. Mohanty, 2018, 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT).

Deep learning-based system to predict cardiac arrhythmia using hybrid features of transform techniques

P. Dash, Santanu Sahoo, S. Sabut, 2022, Intell. Syst. Appl..

Application of Machine Learning Techniques for Characterization of Ischemic Stroke with MRI Images: A Review

Ruyan Tan, Usha R. Acharya, S. Sabut, 2022, Diagnostics.

Machine learning approach to recognize ventricular arrhythmias using VMD based features

S. Sabut, M. Mohanty, P. Biswal, 2019, Multidimensional Systems and Signal Processing.

Automated Detection of Brain Stroke in MRI with Hybrid Fuzzy C-Means Clustering and Random Forest Classifier

Sukanta Sabut, Asit Subudhi, Subhransu S. Jena, 2019, Int. J. Comput. Intell. Appl..

Detection of ventricular arrhythmia using hybrid time–frequency-based features and deep neural network

S. Sabut, M. Mohanty, B. P. Mishra, 2021, Physical and Engineering Sciences in Medicine.

Novel and accurate non-linear index for the automated detection of haemorrhagic brain stroke using CT images

Joel Koh En Wei, U. Acharya, U. Raghavendra, 2021, Complex & Intelligent Systems.

Classification of ventricular arrhythmias using empirical mode decomposition and machine learning algorithms

Pradyut Kumar Biswal, Sukanta Sabut, Manasa Dash, 2021, Progress in Artificial Intelligence.

A systematic review on design technology and application of polycentric prosthetic knee in amputee rehabilitation

Rajesh Kumar Mohanty, R C Mohanty, Sukanta Kumar Sabut, 2020, Physical and Engineering Sciences in Medicine.

Automated segmentation and classification of brain stroke using expectation-maximization and random forest classifier

Sukanta Sabut, Asit Subudhi, Manasa Dash, 2020, Biocybernetics and Biomedical Engineering.

Restoration of gait and motor recovery by functional electrical stimulation therapy in persons with stroke

Manjunatha Mahadevappa, Chanda Sikdar, Ramkrishna Mondal, 2010, Disability and rehabilitation.

Deep learning based liver cancer detection using watershed transform and Gaussian mixture model techniques

U. Rajendra Acharya, Sukanta Sabut, Amita Das, 2019, Cognitive Systems Research.

Kernelized Fuzzy C-means Clustering with Adaptive Thresholding for Segmenting Liver Tumors

Sukanta Sabut, Amita Das, S. Sabut, 2016 .

Automatic detection of ischemic stroke using higher order spectra features in brain MRI images

U. Rajendra Acharya, Oliver Faust, Kristen M. Meiburger, 2019, Cognitive Systems Research.

Automated ECG beat classification using DWT and Hilbert transform-based PCA-SVM classifier

Santanu Sahoo, S. Sabut, M. Mohanty, 2020, International Journal of Biomedical Engineering and Technology.

Detection of Epileptic Seizure Using Wavelet Transform and Neural Network Classifier

S. L. Nalbalwar, S. M. Wani, S. Sabut, 2018, Advances in Intelligent Systems and Computing.

Functional electrical stimulation of dorsiflexor muscle: effects on dorsiflexor strength, plantarflexor spasticity, and motor recovery in stroke patients.

Manjunatha Mahadevappa, M. Mahadevappa, S. Sabut, 2011, NeuroRehabilitation.

Surface EMG analysis of tibialis anterior muscle in walking with FES in stroke subjects

M. Mahadevappa, M. Mahadevappa, S. Sabut, 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

Design of a programmable multi-pattern FES system for restoring foot drop in stroke rehabilitation

M Mahadevappa, S K Sabut, R Kumar, 2010, Journal of medical engineering & technology.

Fusion of Higher Order Spectra and Texture Extraction Methods for Automated Stroke Severity Classification with MRI Images

U. Acharya, A. Majid, O. Faust, 2021, International journal of environmental research and public health.

An EMG-control functional electrical stimulation (FES) system for restoration of gait in foot drop patients

M. Manjunatha, S. Sabut, 2013 .

Machine Learning Approach to Detect Cardiac Arrhythmias in ECG Signals: A Survey

Sukanta Sabut, Santanu Sahoo, Suresh Behera, 2020 .

Automated approach for detection of ischemic stroke using Delaunay Triangulation in brain MRI images

U. Rajendra Acharya, Sukanta Sabut, Asit Subudhi, 2018, Comput. Biol. Medicine.

Detection of Liver Cancer using Optimized Techniques in CT Scan Images

Sukanta Sabut, Soumya S. Panda, Amita Das, 2018, 2018 International Conference on Applied Electromagnetics, Signal Processing and Communication (AESPC).

Detection of Liver Cancer Using Modified Fuzzy Clustering and Decision Tree Classifier in CT Images

S. Sabut, Priti Das, S. S. Panda, 2019, Pattern Recognition and Image Analysis.

An Efficient Classifier-Based Approach for Early Arrhythmia Detection with Feature Reduction Using Ranker Search Algorithm

Pradyut Kumar Biswal, Sukanta Sabut, Monalisa Mohanty, 2020 .

Efficient classification of ventricular arrhythmias using feature selection and C4.5 classifier

Pradyut Kumar Biswal, Sukanta Sabut, Santanu Sahoo, 2018, Biomed. Signal Process. Control..

Evaluation of Classifiers for Recognition of Ventricular Arrhythmia using DWT based Features

Pradyut Kumar Biswal, Monalisa Mohanty, Asit Kumar Subudhi, 2018, 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT).

Classification of Ventricular Arrhythmias Using DWT Based VMD Features

Sukanta Sabut, Monalisa Mohanty, Asit Subudhi, 2018, 2018 2nd International Conference on Data Science and Business Analytics (ICDSBA).

Effective ECG Beat Classification and Decision Support System Using Dual-Tree Complex Wavelet Transform

Badrinarayan Sahu, Sukanta Sabut, Santanu Sahoo, 2020 .

Feature extraction of ECG signal based on wavelet transform for arrhythmia detection

Santanu Sahoo, S. Sabut, A. Subudhi, 2015, 2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO).

Deep Transfer Learning for Automatic Prediction of Hemorrhagic Stroke on CT Images

Usha R. Acharya, S. Sabut, K. H. Cheong, 2022, Computational and mathematical methods in medicine.

Conformity assessment with structural strength requirements of mechanical polycentric prosthetic knee used for amputee rehabilitation

S. Sabut, R. Mohanty, Mukundjee Pandey, 2022, Computer Methods in Biomechanics and Biomedical Engineering.

Delineation of the ischemic stroke lesion based on watershed and relative fuzzy connectedness in brain MRI

Sukanta Sabut, Asit Subudhi, Subhransu Jena, 2017, Medical & Biological Engineering & Computing.

Delineation of the ischemic stroke lesion based on watershed and relative fuzzy connectedness in brain MRI

S. Sabut, A. Subudhi, S. Jena, 2017, Medical & Biological Engineering & Computing.

Automatic Classification of Cardiac Arrhythmias Based on Hybrid Features and Decision Tree Algorithm

Sukanta Sabut, Santanu Sahoo, Asit Subudhi, 2020, International Journal of Automation and Computing.

Classification of heart rhythm disorders using instructive features and artificial neural networks

Priti Das, Sukanta Sabut, Santanu Sahoo, 2018, Int. J. Medical Eng. Informatics.

CLINICAL USE OF FUNCTIONAL ELECTRICAL STIMULATION FOR CORRECTION OF FOOT DROP: A COMPARISON BETWEEN SUBACUTE AND CHRONIC STROKE PATIENTS

Manjunatha Mahadevappa, M. Mahadevappa, S. Sabut, 2011 .

Delineation of infarct lesions by Multi-dimensional Fuzzy C-Means of acute ischemic stroke patients

S. Sabut, A. Subudhi, S. Jena, 2015, 2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO).

Machine learning approach to recognize ventricular arrhythmias using VMD based features

Pradyut Kumar Biswal, Monalisa Mohanty, Sukanta Sabut, 2019, Multidimensional Systems and Signal Processing.

Transfer learning based epileptic seizure classification using scalogram images of EEG signals

S. Sabut, N. Rout, Sasweta Pattnaik, 2024, Multimedia Tools and Applications.

DELINEATION AND CLASSIFICATION OF LIVER CANCER USING LEVEL SET METHOD IN CT IMAGES

Sukanta Sabut, Amita Das, S. S. Panda, 2017 .

Application of control strategies and machine learning techniques in prosthetic knee: a systematic review

S. Sabut, R. Mohanty, Dr. Rajesh Kumar Mohanty, 2022, Advances in Computational Intelligence.