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Computers in Biology and Medicine|August 5, 2016
Beat-to-beat T-wave alternans detection using the Ensemble Empirical Mode Decomposition methodMuhammad A Hasan, Vijay S Chauhan, Sridhar Krishnan
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|February 1, 2013
Characterization of fractionated electrograms using a novel time-frequency based algorithmBehnaz Ghoraani, Sridhar Krishnan, Vijay S Chauhan
Medical Engineering & Physics|February 22, 2011
T wave alternans evaluation using adaptive time-frequency signal analysis and non-negative matrix factorizationBehnaz Ghoraani, Sridhar Krishnan, Raja J Selvaraj, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 8, 2009
Adaptive time-frequency matrix features for T wave alternans analysisBehnaz Ghoraani, Sridhar Krishnan, Raja J Selvaraj, et al.
Biomedizinische Technik. Biomedical Engineering|December 22, 2016
Increased beat-to-beat T-wave variability in myocardial infarction patientsMuhammad A Hasan, Derek Abbott, Mathias Baumert, et al.
Circulation. Arrhythmia and Electrophysiology|July 15, 2017
Automated Quantification of Low-Amplitude Abnormal QRS Peaks From High-Resolution ECG Recordings Predicts Arrhythmic Events in Patients With CardiomyopathyMoloy Das, Adrian M Suszko, Sachin Nayyar, et al.
Pacing and Clinical Electrophysiology : PACE|September 24, 2005
Pacemaker-like syndrome complicating slow pathway ablation for AV nodal reentrant tachycardiaSatish Toal, Vijay S Chauhan
Medical & Biological Engineering & Computing|August 27, 2009
Computer-aided analysis of gait rhythm fluctuations in amyotrophic lateral sclerosisYunfeng Wu, Sridhar Krishnan
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 25, 2017
Feature analysis of dysphonia speech for monitoring Parkinson's diseaseAlice Rueda, Sridhar Krishnan
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