Contributions of lower extremity kinematics to trunk accelerations during moderate treadmill running

Background: trunk accelerations during running provide useful information about movement economy and injury risk. however,there is a lack of data regarding the key biomechanical contributors to these accelerations. the purpose was to establish the biomechanical variables associated with root mean square (rms) accelerations of the trunk. methods: eighteen healthy males (24.0 ± 4.2 yr; 1.78 ± 0.07 m; 79.7 ± 14.8 kg) performed treadmill running with high resolution accelerometer measurement at the lumbar spine and full-body optical motion capture. we collected 60 sec of data at three speeds (2.22,2.78,3.33 m·s-1). rms was calculated for medio-lateral (ml),anterio-posterior (ap),vertical (vt),and the resultant euclidean scalar (res) acceleration. from motion capture,we calculated 14 kinematic variables,including mean sagittal plane joint angles at foot contact,mid-stance,and toe-off. principal components analysis (pca) was used to form independent components comprised of combinations of the original variables. stepwise regressions were performed on the original variables and the components to determine contributions to rms acceleration in each axis. results: significant speed effects were found for rms-accelerations in all axes (p < 0.05). regressions of the original variables indicated from 4 to 5 variables associated with accelerations in each axis (r2 = 0.71 to 0.82,p < 0.001). the most prominent contributing variables were associated with the late flight and early stance phase. pca reduced the data into four components. component 1 included all hip angles before mid-stance and component 2 was primarily associated with propulsion. regressions indicated key contributions from components 1 and 2 to ml,vt,and res acceleration (p < 0.05). conclusions: the variables with highest contribution were prior to mid-stance and mechanically relate to shock absorption and attenuation of peak forces. trunk acceleration magnitude is associated with global running variables,ranging from energy expenditure to forces lending to the mechanics of injury. these data begin to delineate running gait events and offer relationships of running mechanics to those structures more proximal in the kinetic chain. these relationships may provide insight for technique modification to maximize running economy or prevent injury. © 2014 lindsay et al.