Shoulder movement complexity in the aging shoulder: A cross‐sectional analysis and reliability assessment - Overbeek, Celeste L.; Geurkink, Timon H.; Groot, Fleur A.; Klop, Ilse; Nagels, Jochem; Nelissen, Rob G. H. H.; Groot, Jurriaan H. (Journal of orthopaedic research, 2021)
Healthy individuals perform a task such as hitting the head of a nail with an infinite coordination spectrum. This motor redundancy is healthy and allows for learning through exploration and uniform load distribution across muscles. Assessing movement complexity within repetitive movement trajectories may provide insight into the available motor redundancy during aging. We quantified complexity of repetitive arm elevation trajectories in the aging shoulder and assessed test–retest reliability of this quantification. In a cross‐sectional study using 3D‐electromagnetic tracking, 120 asymptomatic subjects, aged between 18 and 70 years performed repetitive abduction and forward/anteflexion movements. Movement complexity was calculated using the Approximate Entropy (ApEn‐value): [0,2], where lower values indicate reduced complexity. Thirty‐three participants performed the protocol twice, to determine reliability (intraclass correlation coefficient [ICC]). The association between age and ApEn was corrected for task characteristics (e.g., sample length) with multiple linear regression analysis. Reproducibility was determined using scatter plots and ICC's. Higher age was associated with lower ApEn‐values during abduction (unstandardized estimate: −0.003/year; 95% confidence interval: [−0.005; −0.002]; p < .001). ICC's revealed poor to good reliability depending on differences in sample length between repeated measurements. The results may imply more stereotype movement during abduction in the ageing shoulder, making this movement prone to the development of shoulder complaints. Future studies may investigate the pathophysiology and clinical course of shoulder complaints by assessment of movement complexity. To this end, the ApEn‐value calculated over repetitive movement trajectories may be used, although biasing factors such as sample length should be taken into account.