MoCaP–ScoRe: Markerless Motion Capture for Precision Scoliosis Rehabilitation

Adolescent idiopathic scoliosis (AIS) is a common spinal condition that affects posture, movement, and quality of life. Deficiencies in proprioception, the body’s sense of position and movement, may play a role by disrupting balance and postural control, contributing to spinal misalignment.

Scoliosis is typically assessed with static images such as X-rays, which cannot show how the spine moves during daily activities. The most accurate technology for studying movement, marker-based motion capture, is costly, complex not allowing for routine clinical care.

This project will develop a safe, non-invasive, markerless system that uses machine learning (ML) trained on surface scans and X-ray images. The result will be an easy-to-use app that allows clinicians to assess posture, spinal movement, and postural control in real time.

In partnership with Curvy Spine, a specialty scoliosis clinic, the project will deliver a tool to track progress, personalize treatments, and measure the effects of exercises and bracing. This practical and scalable system will reduce reliance on repeated X-rays, improve clinical assessments and personalized intervention. Ultimately, it brings cutting-edge science into everyday practice to improve outcomes for young people with scoliosis.

Faculty Supervisor:

Milad Nazarahari;Lindsey Westover

Student:

Partner:

Curvy Spine Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Alberta

Program: