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Humeral motion can be challenging to measure and analyze. Typically, Euler/Cardan sequences are used for humeral angle decomposition, but choice of rotation sequence has substantial effects on outcomes. A new method called True axial rotation calculation may be more precise. The objective of this study is to compare humeral axial rotation measured from two systems (optical motion capture and inertial measurement units (IMUs)) and calculated with two methods (Euler angles and True axial). Motion of torso and dominant humerus of thirty participants free from any upper limb impairments was tracked using both systems. Each participant performed a functional tasks protocol. Humeral axial rotation was calculated with Euler decomposition and the True axial method. Waveforms were compared with two-way ANOVA statistical parametric mapping. A consistent pattern emerged: axial rotation was not different between motion capture systems when using the True axial method (p >.05), but motion capture systems showed relatively large magnitude differences (~ 20–30°) when using Euler angle calculation. Between-calculation method differences were large for both motion capture systems. Findings suggest that the True axial rotation method may result in more consistent findings that will allow for precise measurements and comparison between motion capture systems. Two methods for calculating humeral axial rotation measured from optical motion capture and inertial measurement units were compared. [ABSTRACT FROM AUTHOR]

Understanding scapular motion during everyday tasks is essential for adequate return-to-work and intervention programming, yet most scapular assessments involve restricted motion analysis within a laboratory setting. Inertial measurement units (IMUs) have been used to track scapular motion, but their validity compared to "gold standard" optical motion capture is not well defined. Further, it is unclear how different IMU sensor placements could affect scapular kinematic outcomes during a functional task protocol. To assess the reliability of scapular motion measurements with the use of the "gold standard" optical motion capture and IMUs, and to compare scapular IMU placement to assess which location (acromion or spine) was best for reliability of scapular motion, participants completed two testing sessions. During each lab visit, participant torso, humeri, and scapulae motion was tracked during 3 trials of 8 dynamic tasks and two elevation movements. Scapular angles were extracted during each task. To assess intra-session reliability, intra-class correlation coefficients (ICCs), and root mean square errors (RMSEs) were calculated. Results showed ICCs and RMSEs were acceptable. Although there appeared offsets between the two motion capture system scapular kinematics outcomes based on the plotted waveforms, the movement patterns appeared consistent between both motion capture methods. Data also showed that acromion IMU placement produced slightly more reliable outcomes than placement on the spine. Two placements of scapular tracking IMUs were tested with identical procedures. [ABSTRACT FROM AUTHOR]

Most human movement research takes place within controlled laboratories where researchers observe participant movement. Because a majority of daily activity is performed without observation, we hypothesized movement within a laboratory would vary when there was a small, large or absence of research group. We also hypothesized that personality type would influence movement during observation. Participants completed a personality questionnaire, then walked in a laboratory during three different conditions: no research group (no researchers), small research group (2 researchers), and large research group (6–10 researchers). Results revealed spatiotemporal parameters were altered between conditions, however personality type did not influence changes in movement. As the number of researchers increased, gait speed, cadence, and stride length increased, and step duration decreased. Gait speed increased by.03 m/s from the no research group to the small research group, by.06 m/s from the no research group to the large research group, and by.03 m/s from the small to large research group (all p values <.001). Understanding how researcher observation modifies movement is important and affects the replicability of results, as well as the interpretation of laboratory-based movement studies to activities of daily living in real world settings. [ABSTRACT FROM AUTHOR]