Exploration of different classes of metrics to characterize motor variability during repetitive symmetric and asymmetric lifting tasks

Abstract

The substantial kinematic degrees-of-freedom available in human movement lead to inherent variations in a repetitive movement, or motor variability (MV). Growing evidence suggests that characterizing MV permits a better understanding of potential injury mechanisms. Several diverse methods, though, have been used to quantify MV, but limited evidence exists regarding the merits of these methods in the occupational context. In this work, we explored different classes of methods for characterizing MV during symmetric and asymmetric box lifting tasks. Kinematic MV of both the whole-body center-of-mass (COM) and the box were quantified, using metrics derived from a linear method (Standard Deviation), a non-linear method (Sample Entropy; an index of movement regularity), and a novel application of an equifinality method (Goal Equivalent Manifold; an index related to the set of effective motor solutions). Our results suggest that individuals manipulate regularity and the set of effective motor solutions to overcome unwanted motor noises related to the COM. These results, together with earlier evidence, imply that individuals may prioritize stability over variability with increasing task difficulty. Task performance also appeared to deteriorate with decreasing variability and regularity of the COM. We conclude that diverse metrics of MV may be complimentary to reveal differences in MV.

Sample Entropy as a Tool to Assess Lumbo-Pelvic Movements in a Clinical Test for Low-Back-Pain Patients

“…The reason for these lower SampEn values is that both GyrX and AccZ time series contain kinematic information about the b and r rotations performed, i.e., the target to touch on the box or stool. This tends to confirm the hypothesis already put forward, according to which an individual develops a movement strategy aimed at reducing the complexity to increase the precision of a targeted movement during a task [42]. Along these lines, it can be concluded that the large Sampen50 value for AccX stands for the fact that no planned linear movement occurs along the X-axis.…”

“…The stage of flexion-extension influences the level of synchronisation between the pelvis and the spine during b and r with greater involvement of the pelvis during the final and initial phases of forward flexion and backward extension, respectively [39]. Speed is also an important factor that can alter movement strategies to adapt functionally to reduce stress on structures and avoid pain when LBP patients change to optimal complexity and adopt a stereotyped lumbopelvic rhythm [40][41][42].…”

Load Magnitude and Locomotion Pattern Alter Locomotor System Function in Healthy Young Adult Women

“…The multitude of joints and muscles in the lower extremity lead to a large number of degrees of freedom that lends itself to equifinality; infinite number of movement solutions to accomplish the same task (Bernstein, 1967;Gelfand and Latash, 1998;Latash et al, 2010). A goal equivalent manifold (GEM; equifinality technique) approach seeks to quantify the "good" (plotted tangential to the GEM [δ T ]) versus "bad" (plotted perpendicular to the GEM [δ P ]) motor variability to further discriminate optimal performance (known as relative variability [the ratio of "good" motor variability to "bad" motor variability]) (Dingwell et al, 2010;Cusumano and Dingwell, 2013;Sedighi and Nussbaum, 2019). Recent theories have demonstrated that motor variability not only leverages equifinality, making the system more adaptable and stable to perturbation (i.e., overcoming varying terrain or recovering from a slip/trip) (Cusumano and Dingwell, 2013;Dingwell et al, 2017), it also has other cost function benefits (Gates and Dingwell, 2008).…”

Recruit-aged adults may preferentially weight task goals over deleterious cost functions during short duration loaded and imposed gait tasks

“…Movements tangential to a goal manifold are null space variability (δ T ) and those perpendicular are task space variability (δ P ) 17 , 36 , 37 . Therefore, the ratio of tangential to perpendicular variability (relative variability) 16 , 17 , 36 – 38 contextualizes motor variability with ratios greater than 1 indicating an individual leveraging their motor solution capacity in the null space effectively executing the task goal 39 . Indeed, healthy populations can have large spatiotemporal parameter variability (e.g., standard deviation), but will still exhibit more null space variability compared to task space variability 5 .…”