activity
20142018
most citedClassification of Autism Spectrum Disorder Using Supervised Learning of Brain Connectivity Measures Extracted from Synchrostates

93 citations · 525 across the 17 of their papers we have counts for

collaborators
Showing 2014Show all

6 papers · 1 filter

physics.med-ph2014★ 93 cited

Classification of Autism Spectrum Disorder Using Supervised Learning of Brain Connectivity Measures Extracted from Synchrostates

Wasifa Jamal, Saptarshi Das, Ioana-Anastasia Oprescu +3

Objective. The paper investigates the presence of autism using the functional brain connectivity measures derived from electro-encephalogram (EEG) of children during face perceptio…

physics.med-ph2014★ 19 cited

Artifact reduction in multichannel pervasive EEG using hybrid WPT-ICA and WPT-EMD signal decomposition techniques

Valentina Bono, Wasifa Jamal, Saptarshi Das +1

In order to reduce the muscle artifacts in multi-channel pervasive Electroencephalogram (EEG) signals, we here propose and compare two hybrid algorithms by combining the concept of…

physics.med-ph2014★ 9 cited

A novel approach for the diagnosis of ventricular tachycardia based on phase space reconstruction of ECG

George Koulaouzidis, Saptarshi Das, Grazia Cappiello +3

Ventricular arrhythmias comprise a group of disorders which manifest clinically in a variety of ways from ventricular premature beats (VPB) and no sustained ventricular tachycardia…

physics.bio-ph2014★ 47 cited

Forward and Inverse Modelling Approaches for Prediction of Light Stimulus from Electrophysiological Response in Plants

Shre Kumar Chatterjee, Sanmitra Ghosh, Saptarshi Das +6

In this paper, system identification approach has been adopted to develop a novel dynamical model for describing the relationship between light as an environmental stimulus and the…

physics.med-ph2014★ 60 cited

Fractional Dynamical Model for the Generation of ECG like Signals from Filtered Coupled Van-der Pol Oscillators

Saptarshi Das, Koushik Maharatna

In this paper, an incommensurate fractional order (FO) model has been proposed to generate ECG like waveforms. Earlier investigation of ECG like waveform generation is based on two…

q-bio.NC2014★ 9 cited

Prediction of Synchrostate Transitions in EEG Signals Using Markov Chain Models

Wasifa Jamal, Saptarshi Das, Ioana-Anastasia Oprescu +1

This paper proposes a stochastic model using the concept of Markov chains for the inter-state transitions of the millisecond order quasi-stable phase synchronized patterns or synch…