Background: Reduced range of motion in the shoulder can be a source of functional limitation. The use of inertial sensors to quantify movement in addition to more common clinical assessments of the shoulder may allow clinicians to understand that they are potentially unnoticed by visual identification. The aim of this study was to generate an explanatory model for shoulder abduction based on data from inertial sensors.
Method: A cross-sectional study was carried out to generate an explanatory model of shoulder abduction based on data from inertial sensors. Shoulder abduction of thirteen older adults suffering from shoulder dysfunction was recorded with two inertial sensors placed on the humerus and scapula. Movement variables (maximum angular mobility, angular peak of velocity, peak of acceleration) were used to explain the functionality of the upper limb assessed using the Upper Limb Functional Index (ULFI). The abduction movement of the shoulder was explained by six variables related to the mobility of the shoulder joint complex. A multivariate analysis of variance (MANOVA) was used to explain the results obtained on the functionality of the upper limb.
Results: The MANOVA model based on angular mobility explained 69% of the variance of the ULFI value (r-squared = 0.69). The most relevant variables were the abduction-adduction of the humerus and the medial/lateral rotation of the scapula.
Conclusions: The method used in the present study reveals the potential importance of the analysis of the scapular and humeral movements for comprehensive evaluation of the upper limb. Further research should include a wider sample and may seek to use this assessment technique in a range of potential clinical applications.
