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

Singh, Tarkeshwar; Zatsiorsky, Vladimir M.; Latash, Mark L.

doi:10.1123/mc.2013-0069

Cited by 6 publications

(5 citation statements)

References 63 publications

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“…It is possible to have strong synergies at both levels as shown in experiments for synergies stabilizing tangential force during one-hand prehensile tasks (Gorniak et al 2009; Sun et al 2011). Nevertheless, the overall tendency for synergy indices computed at the two levels is to compete with each other (e.g., Wu et al 2012; Singh et al 2014). …”

Section: Discussionmentioning

confidence: 99%

Interpersonal synergies: static prehension tasks performed by two actors

Solnik

Reschechtko

et al. 2016

Exp Brain Res

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We investigated multi-digit synergies stabilizing components of the resultant force vector during joint performance of a static prehension task by two persons as compared to similar tasks performed by a single person using both hands. Subjects transferred the instrumented handle from the right hand to the left hand (one-person condition) or passed that handle to another person (two-person condition) while keeping the handle's position and orientation stationary. Only three digits were involved per hand, the thumb, the index finger, and the middle finger; the forces and moments produced by the digits were measured by six-component sensors. We estimated the performance stabilizing synergies within the uncontrolled manifold (UCM) framework by quantifying the inter-trial variance structure of digit forces and moments. The analysis was performed at three levels: between hands, between virtual finger and virtual thumb (imagined digits producing the same mechanical variables as the corresponding actual digits combined) produced by the two hands (in both interpersonal and intrapersonal conditions), and between the thumb and virtual finger for one hand only. Additionally, we performed correlation and phase synchronization analyses of resultant tangential forces and internal normal forces. Overall, the one-person conditions were characterized by higher amount of inter-trial variance that did not affect resultant normal force components, higher internal components of normal forces, and stronger synchronization of the normal forces generated by the hands. Our observations suggest that in two-person tasks, when participants try to achieve a common mechanical outcome, the performance stabilizing synergies depend on non-visual information exchange, possibly via the haptic and proprioceptive systems. Therefore, synergies quantified in tasks using visual feedback only may not be generalizable to more natural tasks.

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Section: Discussionmentioning

confidence: 99%

Interpersonal synergies: static prehension tasks performed by two actors

Solnik

Reschechtko

et al. 2016

Exp Brain Res

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“…The details of the experimental paradigm are provided in previous publications (Singh, et al, 2013; Singh, Zatsiorsky, & Latash, 2014). Briefly, five six-component sensors (model Nano 17-R; ATI, Apex, NC, USA) were used to measure the forces and moments produced by the individual digits.…”

Section: Methodsmentioning

confidence: 99%

“…Vladimir Zatsiorsky and Mark Latash for allowing us to reanalyze data from a previously published study (Singh, et al, 2014). The study was in part supported by NIH grants AG-018751, NS-035032, and AR-048563 awarded to Drs.…”

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confidence: 99%

A soft-contact model for computing safety margins in human prehension

Singh

Ambike

2017

Human Movement Science

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The soft human digit tip forms contact with grasped objects over a finite area and applies a moment about an axis normal to the area. These moments are important for ensuring stability during precision grasping. However, the contribution of these moments to grasp stability is rarely investigated in prehension studies. The more popular hard-contact model assumes that the digits exert a force vector but no free moment on the grasped object. Many sensorimotor studies use this model and show that humans estimate friction coefficients to scale the normal force to grasp objects stably, i.e. the smoother the surface, the tighter the grasp. The difference between the applied normal force and the minimal normal force needed to prevent slipping is called safety margin and this index is widely used as a measure of grasp planning. Here we define and quantify safety margin using a more realistic contact model that allows digits to apply both forces and moments. Specifically, we adapt a soft-contact model from robotics and demonstrate that the safety margin thus computed is a more accurate and robust index of grasp planning than its hard-contact variant. Previously, we have used the soft-contact model to propose two indices of grasp planning that show how humans account for the shape and inertial properties of an object. A soft-contact based safety margin offers complementary insights by quantifying how humans may account for surface properties of the object and skin tissue during grasp planning and execution.

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“…Specifically, in participants with many neurological diseases such as atypical development, cerebellar disorders, basal ganglia disorders, or stroke, it is observed that these patients struggle with maintaining stability during the execution of consecutive movements (for review see, Latash and Huang, 2015 ; Vaz et al, 2019 ). Among the reasons for loss of movement stability, aging with all its negative consequences (Olafsdottir et al, 2007; Christou and Enoka, 2011 ; SKM et al, 2012 ) and fatigue ( Enoka and Stuart, 1992 ; Reisman and Scholz, 2006 ; Singh et al, 2014 ) must be mentioned. Furthermore, all of the above-mentioned individuals cannot perform multiple trials without a loss of concentration ( Green et al, 1989 ; Mirsky, 1995 ).…”

Section: Introductionmentioning

confidence: 99%

“…However, the most often number of repetitions of movement in the later studies has been about 20 to 25 ( Shinohara et al, 2004 ; Zhang et al, 2006 ; Gorniak et al, 2007 ; Shim et al, 2008 ; Martin et al, 2009 ; Park et al, 2012 ; Reschechtko et al, 2014 ). Similarly, in prehension tasks, it has ranged from 15 to 24 ( Zhang et al, 2009 ; Latash et al, 2010a ; Singh et al, 2014 ; Jo et al, 2015 ). The same diversity is observed in the UCM analysis for electromyographic (EMG) variables in different tasks.…”

Section: Introductionmentioning

confidence: 99%

Number of Trials Necessary to Apply Analysis within the Framework of the Uncontrolled Manifold Hypothesis at Different Levels of Hierarchical Synergy Control

Pawłowski¹,

Furmanek²,

Sobota³

et al. 2021

Journal of Human Kinetics

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The uncontrolled manifold hypothesis is a method used to quantify motor synergies, defined as a specific central nervous system organization that maintains the task-specific stability of motor actions. The UCM allows for inter-trial variance analysis between consecutive trials. However, despite the large body of literature within this framework, there is no report on the number of movement repetitions required for reliable results. Based on the hypothetical hierarchical control of motor synergies, this study aims to determine the minimum number of trials necessary to achieve a good to excellent level of reliability. Thirteen young, healthy participants performed fifteen bilateral isometric contractions of elbow flexion when visual feedback was provided. The force and electromyography data were recorded to investigate synergies at different levels of hierarchical control. The intraclass correlation coefficient was used to determine the reliability of the variance indices. Based on the obtained results, at least twelve trials are required to analyze the inter-trial variance in both force and muscle synergies within the UCM framework.

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

Cited by 6 publications

References 63 publications

Interpersonal synergies: static prehension tasks performed by two actors

Interpersonal synergies: static prehension tasks performed by two actors

A soft-contact model for computing safety margins in human prehension

Number of Trials Necessary to Apply Analysis within the Framework of the Uncontrolled Manifold Hypothesis at Different Levels of Hierarchical Synergy Control

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