SCIENTIFIC PROJECTS

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• Bimanual motor coordination

The project investigates the behavioral, computational and neural framework of bimanual coordination in humans.

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• Temporal and spatial aspects of adaptive control in hand reaching movement

The project investigates the computational principles behind reaching behavior during mechanical perturbations in a robotic arm

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• Dependency in the dynamics of control and prediction during adaptation in eye-hand coordinated tasks.

The project explores how the update of cognitive prediction of the state might influence the update of movement control, and vice versa, by studying the transfer of learning between two visuomotor tasks both requiring adaptation.

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• Role of Primary Motor Cortex in Eye-Hand Coordination

The goal of the current study is to explore the effect of Transcranial Magnetic Stimulation (TMS) the hand area of the primary motor cortex (M1) on smooth pursuit during eye-hand coordination task.

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• Brain State Dependency in MRI guided Paired Stimulation Paradigm for Stroke Rehabilitation

The work investigates the impact of brain state in inducing plasticity while pairing peripheral and cortical stimulations (FES & TMS) at different pairing time intervals (EEG/EMG analysis). Haptic devices are controlled in a closed loop environment paired with MRI guided brain stimulation.

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• MRI guided Penta Stimulation Technique as a Mapping Protocol for Stroke Rehabilitation

Motor unit recruitment during cortical & nerve stimulation is investigated as a mapping method to formulate therapy sessions for upperlimb stroke.

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• EEG Based Patient Monitoring System for Mental Alertness Using Adaptive Neuro-Fuzzy Approach

The project models EEG based brain computer interface for cognitive responses using adaptive neuro-fuzzy system in matlab. The research exploits mental tasks to control alarm system.

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• Realtime implementation of Matched filtering in Arduino Microcontroller for Brain Computer Interface

Visual Evoked signals (EEG) are amplified and filtered realtime (Embedded C) for controlling micro robots. The work includes realtime VEP-BCI monitoring software design in Matlab.

• EEG Feature Extraction and classification for Brain-computer Interface

This project was focused on signal feature extraction techniques like wavelets, spectral patterns and autoregressive components and machine learning algorithms like Bayesian Discriminators, K Nearest Neighbor, Support Vector machines, Neural Networks, Neuro Fuzzy Classifiers etc, to extract key denominations and device control messages from EEG.

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• 3D Modeling And Volumetric Analysis Of Brain Tumor in MRI