Quantifying deficits in the 3D force capabilities of a digit caused by selective paralysis: application to the thumb with simulated low ulnar nerve palsy

Kuxhaus, Laurel; Roach, S.; Valero-Cuevas, Francisco J.

doi:10.1016/j.jbiomech.2004.05.010

Cited by 12 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If dimensionality reduction in muscle activation space were observed, it could then be unambiguously interpreted as muscle synergies of neural origin. While the feasible force set has been estimated in human subjects [35], such experiments may prove prohibitively long or fatiguing while maintaining intramuscular electrodes in position to reliably record from all muscles of the limb or finger.…”

Section: Discussionmentioning

confidence: 99%

Challenges and New Approaches to Proving the Existence of Muscle Synergies of Neural Origin

2012

View full text Add to dashboard Cite

Muscle coordination studies repeatedly show low-dimensionality of muscle activations for a wide variety of motor tasks. The basis vectors of this low-dimensional subspace, termed muscle synergies, are hypothesized to reflect neurally-established functional muscle groupings that simplify body control. However, the muscle synergy hypothesis has been notoriously difficult to prove or falsify. We use cadaveric experiments and computational models to perform a crucial thought experiment and develop an alternative explanation of how muscle synergies could be observed without the nervous system having controlled muscles in groups. We first show that the biomechanics of the limb constrains musculotendon length changes to a low-dimensional subspace across all possible movement directions. We then show that a modest assumption—that each muscle is independently instructed to resist length change—leads to the result that electromyographic (EMG) synergies will arise without the need to conclude that they are a product of neural coupling among muscles. Finally, we show that there are dimensionality-reducing constraints in the isometric production of force in a variety of directions, but that these constraints are more easily controlled for, suggesting new experimental directions. These counter-examples to current thinking clearly show how experimenters could adequately control for the constraints described here when designing experiments to test for muscle synergies—but, to the best of our knowledge, this has not yet been done.

show abstract

Section: Discussionmentioning

confidence: 99%

Challenges and New Approaches to Proving the Existence of Muscle Synergies of Neural Origin

2012

View full text Add to dashboard Cite

show abstract

“…The distinct advantage of the feasible wrench set is that it shows the actual biomechanical capabilities of the musculoskeletal system in the coordinates of actual limb endpoint force and torques (Kuxhaus et al, 2005). An important computational distinction needs to be made between the calculation of the feasible wrench set and the manipulability/manipulating force ellipsoids mentioned above.…”

Section: Muscle Space Formulationmentioning

confidence: 99%

“…Adding or removing a basis vector will necessarily change the size and shape of the feasible force and wrench sets (Valero-Cuevas and Hentz, 2002; Kuxhaus et al, 2005; Valero-Cuevas, 2005). A similar effect will be obtained if, say, the basis vectors from two muscles are replaced by a single vector that represents their coupling.…”

Section: Muscle Space Formulationmentioning

confidence: 99%

“…7). We have recorded the basis vectors for the thumb and index finger (Valero-Cuevas et al, 2000; Valero-Cuevas and Hentz, 2002; Pearlman et al, 2004) and used these changes in the feasible wrench sets to detect the functional consequences of peripheral neuropathies, both in simulation and live humans (Valero-Cuevas et al, 2000; Valero-Cuevas and Hentz, 2002; Kuxhaus et al, 2005). Thus, while the simplification of control through synergies may be advantageous in limbs used for locomotion that have more stereotypical function, there is also likely a strong evolutionary advantage to neural independence of muscle control so that the nervous system can achieve the full biomechanically feasible output of the limbs to grant them greater versatility and usefulness.…”

Section: Muscle Space Formulationmentioning

confidence: 99%

See 1 more Smart Citation

A Mathematical Approach to the Mechanical Capabilities of Limbs and Fingers

Valero-Cuevas

2009

Advances in Experimental Medicine and Biology

View full text Add to dashboard Cite

Neuromuscular function is the interaction between the nervous system and the physical world. Limbs and fingers are, therefore, the ultimate mechanical filters between the motor commands that the nervous system issues and the physical actions that result. In this chapter we present a mathematical approach to understanding how their anatomy (i.e., physical structure) defines their mechanical capabilities. We call them "mechanical filters" because they attenuate, amplify, and transform neural signals into mechanical output. We explicitly distinguish between limbs and fingers because their subtle anatomical differences have profound effects on their mechanical properties. Our main message is that many aspects of neuromuscular function such as co-contraction, posture selection, muscle redundancy, optimality of motor command, are fundamentally affected (if not defined) by the physical structure of limbs and fingers. We attempt to present the fundamental filtering properties of limbs and fingers in a unified manner to allow for a direct and useful application of powerful mathematical concepts to the study of neuromuscular function. Every researcher of motor control is well advised to consider these filtering properties to properly understand the co-evolution and synergistic interactions between brain and body. At the end of the day, every inquiry in neuromuscular function can be reduced to the fundamental question whether and how the nervous system can perform the necessary sensorimotor functions to exploit and reach the mechanical capabilities of limbs and fingers. Limbs and Fingers Transform the Output of the Nervous System into Mechanical ActionsThe anatomical structure of limbs and fingers takes as inputs muscular actions and produces as outputs motions and forces. We will use the generic term "limb" for both limbs and fingers, and will distinguish between them where necessary. We begin by applying the mathematical tools of robotics where the limb is a serial kinematic chain of rigid links articulated by rotational joints, and muscles are idealized as linear actuators that produce joint torques (for a more detailed discussion see (Yoshikawa, 1990;Valero-Cuevas et al., 1998)). The propagation of information and/or energy through the system can be described as a forward model or, alternatively, as a serial cascade of filters ( Fig. 1). In this chapter we call the neuromuscular system a series of "mechanical filters" because they attenuate, amplify, and transform neural signals into mechanical output.To analyze the idealized 3-joint limb shown in Fig. 2, the first step in defining the mapping from muscular actions to mechanical outputs is to establish the mapping from joint angles (the vector of three generalized rotational coordinates q⃗ = {q 1 , q 2 , q 3 } T ) to limb endpoint position and orientation (the vector of three endpoint coordinates x⃗ = {x, y, α} T ) for a given set of link lengths: NIH Public Access( 1) where G(q⃗ ) is the geometric model defined by the trigonometric equations for the end point...

show abstract

“…Heavy overlap, we believe, is a desirable quality that benefits surgical reconstruction of grasp, for example, involving very few muscles. In general, however, careful coordination of a larger group of muscles offers versatility in accomplishing grasping tasks and control over fewer muscles (simulated [4,11] and actual neurologic deficits [12]) reduces grasping ability. Future studies will examine the robustness of study findings to 3D endpoint force distributions and to other functionally relevant postures of the index finger.…”

Section: Discussionmentioning

confidence: 99%

Capacity of small groups of muscles to accomplish precision grasping tasks

Towles

Valero-Cuevas

Hentz

2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

View full text Add to dashboard Cite

An understanding of the capacity or ability of various muscle groups to generate endpoint forces that enable grasping tasks could provide a stronger biomechanical basis for the design of reconstructive surgery or rehabilitation for the treatment of the paralyzed or paretic hand. We quantified two-dimensional endpoint force distributions for every combination of the muscles of the index finger, in cadaveric specimens, to understand the capability of muscle groups to produce endpoint forces that accomplish three common types of grasps-tripod, tip and lateral pinch-characterized by a representative level of Coulomb friction. We found that muscle groups of 4 or fewer muscles were capable of generating endpoint forces that enabled performance of each of the grasping tasks examined. We also found that flexor muscles were crucial to accomplish tripod pinch; intrinsic muscles, tip pinch; and the dorsal interosseus muscle, lateral pinch. The results of this study provide a basis for decision making in the design of reconstructive surgeries and rehabilitation approaches that attempt to restore the ability to perform grasping tasks with small groups of muscles.

show abstract

Quantifying deficits in the 3D force capabilities of a digit caused by selective paralysis: application to the thumb with simulated low ulnar nerve palsy

Cited by 12 publications

References 15 publications

Challenges and New Approaches to Proving the Existence of Muscle Synergies of Neural Origin

Challenges and New Approaches to Proving the Existence of Muscle Synergies of Neural Origin

A Mathematical Approach to the Mechanical Capabilities of Limbs and Fingers

Capacity of small groups of muscles to accomplish precision grasping tasks

Contact Info

Product

Resources

About