ScreenFM: Infant Movement Analysis for Neurological Assessment

Active

Role: Principal Investigator

Duration: 2021 - Present

Funding: DFG (German Research Foundation) - €450,000

Partners: Universität zu Lübeck, Charité Berlin

Developing an automated system for detecting Fidgety Movements (FMs) in infants using RGBD cameras and IMU sensors. The absence of FMs can indicate neurological disorders. The project aims to create a machine learning platform for early intervention in pediatric healthcare.

Key Outcomes:

  • Development of novel movement detection algorithms
  • Dataset of 500+ infant movement recordings
  • Clinical validation with 85% accuracy
  • 3 journal publications, 1 patent pending

AI-Powered Elderly Care Monitoring System

Active

Role: Co-Investigator

Duration: 2022 - 2025

Funding: HEC Pakistan - PKR 15 Million

Partners: PUCIT, Mayo Hospital Lahore

Developing a comprehensive monitoring system for elderly individuals using wearable sensors and environmental monitoring. The system detects falls, monitors daily activities, and provides alerts for unusual behavior patterns.

Expected Outcomes:

  • Real-time activity monitoring system
  • Fall detection with 95% accuracy
  • Mobile application for caregivers
  • Deployment in 5 care facilities

Multimodal HAR for Rehabilitation Assessment

Active

Role: Principal Investigator

Duration: 2023 - 2026

Funding: PSF (Pakistan Science Foundation) - PKR 8 Million

Partners: Shaukat Khanum Hospital

Creating an intelligent system for assessing rehabilitation progress in stroke patients using computer vision and wearable sensors. The system provides quantitative metrics for physical therapy effectiveness.

Progress to Date:

  • Prototype system developed
  • Clinical trials with 50 patients initiated
  • 2 conference papers published
  • Collaboration with 3 rehabilitation centers