Aritra Chaudhuri

Video & EOG based investigation of pure saccades in human subjects

Human Computer Interaction (HCI) is the methodology through which computing systems understand actions of human beings. Some important applications of HCI as reported in literature are eye gaze estimation, eye tracking, alertness and health monitoring etc. Of them major applications are based upon eye movements. However, accurate estimation of these measurements is still a challenge in research community. A particular type of eye movement i.e. saccadic eye movement has potential applications in HCI such as alertness assessment, disease diagnosis etc. Electrooculography (EOG) based measurement of saccadic movements has been reported to be an accurate method. However being a contact based method, alternative method as suggested by literature is image based approach. This paper aims to investigate the correlation between video and EOG based observation of pure horizontal directional saccades to establish a relationship between image and EOG signals.

Effect of sleep deprivation on estimated distributed sources for Scalp EEG signals: A case study on human drivers

The Scalp EEG is a large-scale & robust information source about neocortical dynamic functions. In this paper, we analyze a scalp Electro-Encephalogram (EEG) database of 12 human subjects driving on a simulated condition in laboratory, in 11 different stages of fatigue for characterizing the source natures on the cortex surface. In this paper, the Linear Distributed Current Dipole Approach is used. We have used standardized Low Resolution Brain Electromagnetic Tomography (sLORETA) algorithm, which upon construction of a Lead-field Matrix or a Head model consisting of a grid of 10014 voxels, spatially maps the surface data to corresponding corticular dipole sources at each voxel. The information measures such as Renyi, Shannon & Tsallis entropies of the scouts or voxels nearest to specific electrodes are calculated for various subjects & for varying fatigue levels.

Evaluation of denoising techniques for EOG signals based on SNR estimation

This paper evaluates four algorithms for denoising raw Electrooculography (EOG) data based on the Signal to Noise Ratio (SNR). The SNR is computed using the eigenvalue method. The filtering algorithms are a) Finite Impulse Response (FIR) bandpass filters, b) Stationary Wavelet Transform, c) Empirical Mode Decomposition (EMD) d) FIR Median Hybrid Filters. An EOG dataset has been prepared where the subject is asked to perform letter cancelation test on 20 subjects.

A Multimodal System for Assessing Alertness Levels Due to Cognitive Loading

This paper proposes a scheme for assessing the alertness levels of an individual using simultaneous acquisition of multimodal physiological signals and fusing the information into a single metric for quantification of alertness. The system takes electroencephalogram, high-speed image sequence, and speech data as inputs. Certain parameters are computed from each of these measures as indicators of alertness and a metric is proposed using a fusion of the parameters for indicating alertness level of an individual at an instant. The scheme has been validated experimentally using standard neuropsychological tests, such as the Visual Response Test (VRT), Auditory Response Test (ART), a Letter Counting (LC) task, and the Stroop Test. The tests are used both as cognitive tasks to induce mental fatigue as well as tools to gauge the present degree of alertness of the subject. Correlation between the measures has been studied and the experimental variables have been statistically analyzed using measures such as multivariate linear regression and analysis of variance. Correspondence of trends obtained from biomarkers and neuropsychological measures validate the usability of the proposed metric.

Determining ocular gaze point fixation captured during triggered full saccades using EOG

This paper describes an methodology to detect the end of a triggered horizontal saccade and beginning of gaze fixation in a database of Electrooculography (EOG) data; captured during a target tracking task, designed to generate full horizontal saccades followed by a random interval fixation. This methodology results in generation of accurate assessment of the Saccadic duration, and as such, helps in analysis of the saccadic parameters, which are important in cognitive studies. The saccadic parameters as calculated by this methodology has also been validated by video-oculography (VOG).

Correlation of Estimated Sources in Human Brain Obtained by Source Localization Method with Waves Obtained by Telegrapher's Equation

Information transmission in a neuronal axon is based on electrical processes, which may be compared with the flow of a potential in a dielectric medium inside a cable. Commonly, this wave transition is described by a telegraphers equation & used extensively in structural analysis & modeling of a neuron. In this paper, a three pronged approach was adopted to investigate the relation between these propagating waves and Scalp EEG. Firstly, a unique continuous domain solution for the Current Wave propagation was obtained, and simulated in the frequency band 0-30 Hz. Then, Cortical Source natures were obtained from Scalp EEG by standard Low Resolution Brain Electromagnetic Tomography (sLORETA). Subsequently, the correlation between the spatial average of the current dipole sources obtained from sLORETA and the propagating neuronal current waves were explored.

A low-cost, wearable, portable EOG recording system

This paper describes a new low-cost, wearable and portable system to acquire Electro-oculogram (EOG) signals. The system comprises of three electrodes for recording EOG, an instrumentation amplifier and signal conditioning unit, and a general purpose computer with a custom made EOG analysis software. A special type of signal acquisition arrangement has been made where the electrodes are embedded in a frame of a spectacle that provides adjustable settings for different head sizes. The electrodes comprise of dry Ag-AgCl sensors for acquiring the data. The software consists of preprocessing options such as sensor noise removal, power line noise removal, blink detection, saccade detection, etc. The system has been tested against a standard commercial Polysomnography system.

Source imaging of simple finger movements captured during auditory response tasks using space-time-frequency based sparsity constraints

Neural Information Flow during simple cognitive or motor actions is a significant research topic; one of which is a simple finger movement. In this paper, Electro-encephalograph (EEG) Source Imaging has been used to model the Neural Information flow, during performance of a simple Auditory Response Task (ART), specifically by employment of a space-time-frequency sparsity constrained based algorithm, namely, Spatio-temporal Unifying Tomography (STOUT). The estimated sources are then studied according to location defined based on Destrieux atlas. Then, relative power carried in each scout at each instant has been used to create a neural information flow map, which is then compared with sources computed with standardized low resolution brain electromagnetic tomography (sLORETA).

Source imaging of simple finger movements captured during auditory response tasks: Estimation of variation in neural information flow under varying vigilance levels

Neural Information Flow during simple cognitive or motor actions is very recent research topic. One of the simple movements to be studied is a simple finger movement. In this paper, Electro-encephalograph (EEG) Source Imaging has been used to model the Neural Information flow, during performance of a simple Auditory Response Task (ART). The estimated sources are firstly divided into separate scouts according to the Destrieux Atlas. Then, relative power carried in each scout at each instant has been used to create a neural information flow map. Another key feature of this paper lies in the fact that the database corresponded of subjects performing a group of tasks repetitively until significant drop in vigilance. This provides a unique point of view, as to how drop in vigilance levels affect the Neural Information flow. The results show a correlation between trends reflected in EEG parameters and performance scores of neuropsychological tests.