Optimality versus variability: effect of fatigue in multi-finger redundant tasks

Abstract

We used two methods to address two aspects of multi-finger synergies and their changes after fatigue of the index finger. Analytical inverse optimization (ANIO) was used to identify cost functions and corresponding spaces of optimal solutions over a broad range of task parameters. Analysis within the uncontrolled manifold (UCM) hypothesis was used to quantify co-variation of finger forces across repetitive trials that helped reduce variability of (stabilized) performance variables produced by all the fingers together. Subjects produced steady-state levels of total force and moment of force simultaneously as accurately as possible by pressing with the four fingers of the right hand. Both before- and during-fatigue, the subjects performed single trials for many force-moment combinations covering a broad range; the data were used for the ANIO analysis. Multiple trials were performed at two force-moment combinations; these data were used for analysis within the UCM hypothesis. Fatigue was induced by 1-min maximal voluntary contraction (MVC) exercise by the index finger. Principal component (PC) analysis showed that the first two PCs explained over 90% of the total variance both before and during fatigue. Hence, it was concluded that experimental observations formed a plane in the four-dimensional finger force space both before and during fatigue conditions. Based on this conclusion, quadratic cost functions with linear terms were assumed. The dihedral angle between the plane of optimal solutions and the plane of experimental observations was very small (a few degrees); it increased during fatigue. There was an increase with fatigue of the coefficient at the quadratic term for the index finger force balanced by a drop in the coefficients for the ring and middle fingers. Within each finger pair (index-middle and ring-little), the contribution of the “central” fingers to moment production increased during fatigue. An index of antagonist moment production dropped with fatigue. Fatigue led to higher co-variation indices during pronation tasks (index finger is an agonist) but opposite effects during supination tasks. The results suggest that adaptive changes in co-variation indices that help stabilize performance may depend on the role of the fatigued element, agonist or antagonist.

Prehension Synergies During Fatigue of a Single Digit: Adaptations in Control With Referent Configurations

“…We expected the adaptations to fatigue to be consistent with our previous studies where both V UCM and V ORT increased in accurate force production tasks during fatigue with V UCM showing a larger increase (Park et al, 2012; Singh, SKM, Zatsiorsky, & Latash, 2010a; Singh et al, 2010b; Singh et al, 2012). Therefore, our second hypothesis was that indices of force stabilizing synergies would increase at both levels of the hierarchy.…”

“…Some studies have shown that in motor tasks that involve a redundant set of elements, the goal-relevant features of performance are relatively preserved during fatigue (Gates & Dingwell, 2008; Huffenus, Amarantini, & Forestier, 2006). We have also shown this to be true in accurate force production tasks (Park, Singh, Zatsiorsky, & Latash, 2012; Singh et al, 2010b; Singh, Zatsiorsky, & Latash, 2012). In the current study, we investigated the effects of exercise-induced fatigue of a single digit on motor variability and digit coordination in a static prehension task.…”

“…In contrast, fatigue of only one finger may have little effect on the variability of the total output of the VF (Singh et al, 2010b). In fact, our previous studies have shown a fatigue-induced increase in force stabilizing synergies during accurate force production tasks when the index finger was fatigued (Park et al, 2012; Singh et al, 2010b). Based on these results, we expected that synergies stabilizing task-related performance variables in prehension tasks would become stronger during fatigue and lead to a larger increase in V UCM compared to V ORT (the second hypothesis).…”

Intrinsic movement variability at work. How long is the path from motor control to design engineering?

“…Indeed, redundancy makes it possible to adapt movements to the main constraints, i.e., the objective of the task, and to the secondary environmental constraints, which include perturbations or parallel tasks cropping up as the movement is performed (Latash, 2012). This approach differentiates state variables characterising the system, such as joint angle or muscle activation, and performance variables that describe performance of the task, such as an exerted force or a trajectory of the final effector (Park et al, 2010(Park et al, , 2012. Some of the state variables significantly affect task performance and should be controlled, while others have little effect and can be more loosely constrained.…”

Age-related Changes in Multi-finger Synergy during Constant Force Production with and without Additional Mechanical Constraint

“…For example, in a task that requires the use of the index and middle fingers to produce a sum force of 10 N, the interaction between the two fingers to maintain 10 N in real time is measured via within-trial analysis, while the various combinations of the two fingers during repeat performance of this task is measured via between-trial analysis. Precedent studies mostly studied synergy mechanisms through between-trial analysis (Shim et al, 2004;Park, Singh, Zatsiorsky, & Latash, 2012). However, according to Scholz & Schoner (1999), between-trial and within-trial motor analyses are analyzing other controlling capabilities of the CNS (Scholz & Schöner, 1999).…”