Hello, I'm Sundari Elango
I'm a PhD candidate in Computational Neuroscience at IIT Madras, specializing in stroke rehabilitation, motor learning, and developing innovative virtual reality applications for healthcare. I have extensive experience in AI research and computational neuroscience.
About
I'm currently pursuing my PhD in Computational Neuroscience at IIT Madras with a CGPA of 9.3. My research focuses on developing patient-specific computational tools for rehabilitation in hemiparetic stroke of the upper extremity.
I combine computational neuroscience, machine learning, and virtual reality to create innovative solutions for stroke rehabilitation and motor learning. My work bridges the gap between theoretical neuroscience and practical healthcare applications.
I have extensive experience in developing virtual reality gaming systems for stroke patients, automated movement evaluation systems, and hierarchical motor learning networks. My work has been published in prestigious journals and presented at international conferences.
Research Focus
Computational Models for Stroke Rehabilitation
My primary research focus is on developing computational models that can help understand and improve rehabilitation strategies for stroke patients. I work on creating patient-specific models that can predict recovery trajectories and optimize therapy approaches.
Motor Learning and Adaptation
I study the neural mechanisms underlying motor learning and adaptation, with a particular focus on how the brain adapts to perturbations and transfers skills between limbs. This research has implications for understanding recovery after neurological injury.
Virtual Reality Applications in Healthcare
I develop and evaluate virtual reality applications for healthcare, particularly focusing on rehabilitation. My work includes creating engaging VR environments that can motivate patients and provide real-time feedback during therapy.
Stroke Rehabilitation Projects
RL-based Model for Stroke Patient Assistance
Developing an RL-based model to learn how to play a virtual tennis game for stroke rehabilitation. The system anticipates and assists patients in recovery by playing the game along with the patient during rehabilitation.
Virtual Reality Gaming System for Stroke Rehabilitation
A comprehensive virtual reality gaming system for upper extremity rehabilitation in stroke patients. The system has been deployed in several hospitals across India, integrating computer vision techniques to recognize patient gestures.
Automated Movement Evaluation System for Stroke Patients
Using computer vision techniques to develop low-cost, affordable tools for evaluating motor performance in stroke patients. Building systems to evaluate, monitor and track improvements in motor performance.
Mapping Rehabilitation Therapy to Lesion in Stroke
Developed a simple feedforward network to capture basic features of bimanual reaching. Introduced stroke to this network and analyzed impact of increasing complexity of movements used in retraining on recovery.
Publications
Journal Articles
A lateralized motor network in order to understand adaptation to visuomotor rotation
S. Elango, V. S. Chakravarthy, and P. K. Mutha
Journal of Neural Engineering, vol. 21, 2024
View Article →Feasibility and efficacy of virtual reality rehabilitation compared with conventional physiotherapy for upper extremity impairment due to ischaemic stroke
R. Paul, S. Elango, Sylaja, et al.
BMJ Open, vol. 7, 2024
View Article →Interaction of network and rehabilitation therapy parameters in defining recovery after stroke in a bilateral neural network
S. Elango, A. J. A. Francis, and V. S. Chakravarthy
Journal of NeuroEngineering and Rehabilitation, vol. 19, 2022
View Article →A cortico-basal ganglia model for choosing an optimal rehabilitation strategy in hemiparetic stroke
R. Narayanamurthy, S. Jayakumar, S. Elango, V. Muralidharan, and V. S. Chakravarthy
Scientific Reports, vol. 9, 2019
View Article →Recent Conference Proceedings
A computational model to understand hemispheric specialization in motor control
S. Elango, V. S. Chakravarthy, and P. Mutha
32nd Annual Computational Neuroscience Meeting, Germany, 2023
A comprehensive gaming system for rehabilitation of upper extremity post stroke
S. Elango, A. J. A. F, D. Darshini, et al.
11th International Brain Research Organization World Congress of Neuroscience, Spain, 2023
View Details →Feasibility and efficacy of virtual reality rehabilitation for the treatment of impairment of the upper extremity due to ischemic stroke
R. Paul, S. Elango, S. Hafsa, et al.
11th Annual Conference of the Indian Federation of Neurorehabilitation, 2023
Automation of fugl-meyer assessment
A. Sharma, A. J. A. F, S. Elango, and V. S. Chakravarthy
13th World Stroke Congress (WSO 2021), 2021
View Details →Patents
Virtual Reality Gaming System for Stroke Rehabilitation
A comprehensive virtual reality gaming system designed specifically for upper extremity rehabilitation in stroke patients. The system integrates computer vision techniques for gesture recognition and provides real-time feedback for motor performance evaluation.
Automated Movement Evaluation System for Motor Performance Assessment
A low-cost, computer vision-based system for automated evaluation of motor performance in patients. The system uses advanced algorithms to track and analyze movement patterns, providing objective assessments for rehabilitation progress.
Interaction of Network and Rehabilitation Therapy Parameters in Defining Recovery After Stroke
A computational framework that models the interaction between neural network parameters and rehabilitation therapy variables to predict and optimize recovery outcomes in stroke patients. The system provides insights into personalized rehabilitation strategies.
Cortico-Basal Ganglia Model for Optimal Rehabilitation Strategy Selection
A biologically-inspired computational model based on cortico-basal ganglia circuits that determines optimal rehabilitation strategies for hemiparetic stroke patients. The model considers patient-specific factors to recommend personalized therapy approaches.
Get in Touch
I'm always interested in discussing research collaborations, innovative projects in computational neuroscience, and opportunities to apply AI in healthcare and rehabilitation.