Body
Children with cerebral palsy (CP) often undergo clinical gait analysis to identify, understand, and support gait management. Traditional clinical gait analysis relies on laboratory-based technologies such as optical motion capture systems (which use reflective markers placed on the body and special cameras to track them) and force plates. While highly accurate, these systems are expensive and require extensive infrastructure, calibration, and time, along with skilled technicians to operate and interpret the data. These constraints can limit the accessibility and frequency of gait assessments, especially in community or low-resource clinical settings.
Markerless motion capture (MMC) offers a promising alternative by using video cameras to record a person’s movements and algorithms to automatically analyze them. MMC systems are increasingly capable of capturing clinically relevant motion data for many therapeutic applications and can be used in a variety of clinical environments to support real-time decision-making.
In this project, we will train our MMC system for children with CP. This system will capture high-resolution movements using a simple camera setup. We will first refine the system then test if it can identify gait changes following spasticity treatment. The goal is to develop a more accessible measurement tool that clinics can use to quantify CP-related gait impairments, measure changes over time, and design intervention strategies. Precisely quantifying the impact of CP care strategies, such as botulinum toxin injections for spasticity management, could improve dose optimization and provide earlier, more objective identification of response to treatment. Optimizing spasticity management and improving walking could provide substantial quality-of-life improvements for children with CP.
Project Leads
Body
This project is led by James Cotton, MD, PhD and Tasos Karakostas, MPT, PhD.
Associated Lab
Body
This project is associated with the Regenstein Foundation Center for Bionic Medicine, Computerized Motion Analysis Lab and Building Advanced Cerebral Palsy Assistive Care Solutions (BACPACS).
