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Brain Research|March 2, 2020
Complex network analysis of MCI-AD EEG signals under cognitive and resting stateSurya Das, Subha D PuthankattilBrain Connectivity|November 2, 2023
Electroencephalogram-Based Metastability in Mild Cognitive Impairment Alzheimer's DiseaseSurya Das, Subha D PuthankattilComputers in Biology and Medicine|August 25, 2022
MVME-RCMFDE framework for discerning hyper-responsivity in Autism Spectrum DisordersPriyalakshmi Sheela, Subha D PuthankattilFrontiers in Computational Neuroscience|June 23, 2022
Functional Connectivity and Complexity in the Phenomenological Model of Mild Cognitive-Impaired Alzheimer's DiseaseSurya Das, Subha D PuthankattilComputers in Biology and Medicine|June 21, 2021
A noise-robust sparse approach to the time-frequency representation of visual evoked potentialsPriyalakshmi Sheela, Subha D PuthankattilJournal of Neuroscience Methods|February 23, 2020
A hybrid method for artifact removal of visual evoked EEGPriyalakshmi Sheela, Subha D PuthankattilInternational Journal of Developmental Neuroscience : the Official Journal of the International Society for Developmental Neuroscience|May 16, 2018
Event related potential analysis techniques for autism spectrum disorders: A reviewPriyalakshmi Sheela, Subha D PuthankattilCognitive Neurodynamics|March 23, 2018
Analysis of long range dependence in the EEG signals of Alzheimer patientsT Nimmy John, Subha D Puthankattil, Ramshekhar MenonAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
Assessment of emotional states in EEG signals using multi-frequency power spectrum and functional connectivity patternsHimanshu Kumar, Nagarajan Ganapathy, Subha D Puthankattil, et al.Studies in Health Technology and Informatics|May 25, 2022
Classification of Emotional States Using EEG Signals and Wavelet Packet Transform FeaturesHimanshu Kumar, Nagarajan Ganapathy, Subha D Puthankattil, et al.Pageof 2