Projects

Naturalistic Stimuli for Memory Networks

Naturalistic stimuli such as listening to music and stories activate brain regions in a more natural manner compared to standard task-based paradagim. We are using open-access naturalistic stimuli datasets to explore how the functional connectivity in the memory specific regions of the brain changes with time. We plan to explore these changes on various time (and space) scales and find the similarities/differences on the level of individual subjects. The main objective of the study is to find individualized similaries/differences between network changes in response to naturalistic stimuli and better understand the brain functions during neurological disorders such as Alzeihmer’s Desease.

Alzeihmer’s Desease Progression 

We are working to explore the progression of Alzeihmer’s disease during its different stages starting from MCI. Our focus is on structural and functional changes taking palce at individual level by extracting the connectivity maps. We are using ADNI lognitudinal dataset for this project.

Brain and Behavior

Our brain functionality changes with our behavior under different tasks/conditions. For example, music influences our moods but the influence of same music on different people may be different. Study of the relationship between brain and behavior is challenging but the results may be useful in understanding the role of behavior changes to improve brain functionality. We are investigating the relationship between the underlying structures in EEG and behavior data using topological data analysis and manifold estimation.

Integrated AI Framework for Brain Tumor Detection, Survival Prediction, and Computational Modeling

Brain tumors remain one of the most challenging neurological conditions, requiring accurate detection, characterization, and prognosis to guide clinical decision-making. My research aims to develop an integrated, AI-driven framework that combines automated tumor classification, precise segmentation, and survival prediction using multimodal MRI and clinical data. We are validating theis framework on data from hospitals to deploy it in hospitals.

Low-cost, Portable, Easy-to-use Rehab Solutions

Our lab develops low-cost, portable, and user-friendly wearable systems for patient rehabilitation and monitoring. Some of our key projects include:

• Drop Foot Assistive Device [Video]: A prototype FES-based device that allows drop-foot patients to adjust stimulation on their own and walk more confidently, including on uneven terrain. The system has been tested on a patient at Fauji Foundation Hospital.

• Brain-Controlled Wheelchair [Video]: A wheelchair upgraded from manual to electronic control. After enabling joystick-based movement for individuals with lower-body paralysis, we are now progressing toward eye-blink control using a single-channel EEG device.

• Muscle-Controlled Prosthetic Arm [Video]: We have demonstrated real-time control of a 3D-printed single finger using EMG signals. The next phases include full-hand control and deployment with amputee patients at Fauji Foundation Hospital.

• Muscle-Controlled Emergency Trigger [Video]: A low-cost EMG-based device that sends an alert to a caregiver’s phone when the user clenches their fist—allowing discreet emergency communication.

• Visible-Light Patient Monitoring System [Video]: A wireless monitoring solution that measures vital signs (temperature, heart rate) and transmits data through visible light communication instead of Wi-Fi. This reduces cost, eliminates cable clutter, and avoids electromagnetic interference—beneficial for patients with devices like pacemakers.