Continuous time-series data are frequently distilled into single values and analyzed using discrete statistical methods, underutilizing large datasets. Statistical parametric mapping (SPM) allows hypotheses over the entire spectrum, but consistency with discrete analyses of kinematic data is unclear. We applied SPM to evaluate effect of load and postural demands during reaching on thoracohumeral kinematics in older and young adults, and examined consistency between one-dimensional SPM and discrete analyses of the same dataset. We hypothesized that older adults would choose postures that bring the humerus anterior to the frontal plane (towards flexion) even for low demand tasks, and that SPM would reveal differences persisting over larger temporal portions of the reach. Ten healthy older (72.4±3.1yrs) and 16 young (22.9±2.5yrs) adults reached upward and forward with high and low loads. SPM and discrete t-tests were used to analyze group effects for elevation plane, elevation, and axial rotation joint angles and velocity. Older adults used more positive (anterior) elevation plane and less elevated postures to initiate and terminate reaching (p<0.008), with long duration differences during termination. When reaching upward, differences in elevation persisted over longer temporal periods at midreach for high loads (32–58% of reach) compared to low load (41–45%). SPM and discrete analyses were consistent, but SPM permitted clear identification of temporal periods over which differences persisted, while discrete methods allowed analysis of extracted values, like ROM. This work highlights the utility of SPM to analyze kinematics time series data, and emphasizes importance of task selection when assessing age-related changes in movement.
All Science Journal Classification (ASJC) codes
- Orthopedics and Sports Medicine
- Biomedical Engineering