Performance and injury risk are strongly affected by an athlete’s ability to consistently execute effective rowing technique. Previous rowing biomechanics studies focused on kinematic descriptions of the lower extremity and lumbar spine. Detailed biomechanical analyses of the upper extremity during rowing are limited, despite repetitive, high intensity loading across the shoulder complex and the prevalence of long-lasting upper extremity overuse injuries.
This thesis aims to examine upper body biomechanics in ergometer rowing (for performance enhancement and injury mitigation), by developing kinematic and kinetic descriptions of technique. Computational modelling examined internal biomechanics, external kinematics, and performance metrics, across athletes of various ages and skill levels. Optical motion capture and bespoke instrumentation were used in whole-body tracking during ergometer rowing. Kinetic and kinematic data drove a multibody inverse dynamics model. Joint and muscle force patterns were analyzed to quantify upper extremity influence and create a biofeedback structure for rowers and coaches.
As stroke rate increases, significant changes to the shape and timing of seat force profiles, shoulder joint angle profiles, and lumbar and thoracic spinal flexion, arose. Muscle force patterns highlight the importance of rotator cuff support for load transfer across the glenohumeral joint, with subscapularis and infraspinatus stabilizing the upper extremity before the finish and catch, respectively. Sex and age-related comparisons indicated differential prioritization of scapula stabilizers and prime movers in muscle force distribution. Masters rowers recruit arm accessory muscles but decrease rotator cuff force. Muscle forces impact external movement, joint forces, contact patterns, and shoulder stability, which over many cycles, have implications on performance and injury risk.
Musculoskeletal modelling enhances spatio-temporal analyses, offering population-wide insight into how muscle and joint forces relate to traditional power metrics. Parameters provided deeper context on technique optimization for individual’s performance by identifying important muscles and the timing of their loading.