Automated Golf Performance Assessment Using Markerless Motion Capture Derived from a Cell Phone Camera

The spine is an complex system of joints requiring refined motor control strategies to coordinate movement between the lower and upper limbs. Back injuries occur due to poor spine control during sudden/unexpected spine loading. The golf swing is unique to each individual, repetitive, and involves multiple major joints during performance, making the golf swing an excellent surrogate to investigate spine and hip motion and related injuries.

Typically, spine and lumbopelvic motor control research requires high-grade motion capture equipment managed by highly trained personnel. This prohibits the use of conventional objective movement analyses to assess athletes (i.e., golfers) in field-based settings. Recent advancements in computer vision have simplified gathering human movements in 3D using data derived from 2D video cameras (including those within a cellphone). Different functional movement strategies exist in the population which relate to motor performance and/or musculoskeletal injury [2]. Therefore, it is possible that previous approaches taken to evaluate pitching and workplace movements may assist in the objective analysis of golfing to improve/optimize performance and/or reduce the prevalence of injury.

Faculty Supervisor:

Shawn Beaudette

Student:

Partner:

3motionAI Inc.

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Brock University

Program: