Intersegmental kinetics significantly impact mapping from finger musculotendon forces to fingertip forces

Estimation of the effects of hand growth on muscle activation patterns: A musculoskeletal modeling study

Throughout childhood growth and development, both the nervous and the musculoskeletal systems undergo rapid change. The goal of this study was to examine the impact of growth-related changes in skeletal size and muscle strength on the neural control of finger force generation. By modifying an existing OpenSim hand model in accordance with pediatric anthropometric data, we created 10 distinct models representing males and females at each year of development from 6 to 10 years old. We then used the static optimization tool to estimate the requisite muscle activations to create a maximal palmar force with the index finger in two different postures (metacarpophalangeal, proximal interphalangeal, distal interphalangeal) - Posture 1: (0°, 30°, 0°) and Posture 2: (0°, 60°, 30°). For Posture 1, multiple regression analysis revealed a significant effect of both age and sex on activation for all muscles (p < 0.035) with exception of the flexor digitorum profundus. For Posture 2, only the extensor digitorum communis activation had a significant relationship with age (p = 0.010), while no other muscles showed a significant relationship with age, sex, or the age-sex interaction activation (p > 0.054). Exchanging the activation patterns between the youngest and oldest models altered both the predicted index finger force and direction. Therefore, our simulations suggest that the changes in hand size and morphology associated with growth may necessitate changes in muscle activation patterns to be able to continue to perform a given hand function. Children may need to substantially adjust or even relearn motor control strategies throughout childhood.

Neuromuscular control: from a biomechanist's perspective

Understanding neural control of movement necessitates a collaborative approach between many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics grounds us to the laws of physics that our musculoskeletal system must obey. Neuroscience reveals the inner workings of our nervous system that functions to control our body. Motor control investigates the coordinated motor behaviours we display when interacting with our environment. The combined efforts across the many disciplines aimed at understanding human movement has resulted in a rich and rapidly growing body of literature overflowing with theories, models, and experimental paradigms. As a result, gathering knowledge and drawing connections between the overlapping but seemingly disparate fields can be an overwhelming endeavour. This review paper evolved as a need for us to learn of the diverse perspectives underlying current understanding of neuromuscular control. The purpose of our review paper is to integrate ideas from biomechanics, neuroscience, and motor control to better understand how we voluntarily control our muscles. As biomechanists, we approach this paper starting from a biomechanical modelling framework. We first define the theoretical solutions (i.e., muscle activity patterns) that an individual could feasibly use to complete a motor task. The theoretical solutions will be compared to experimental findings and reveal that individuals display structured muscle activity patterns that do not span the entire theoretical solution space. Prevalent neuromuscular control theories will be discussed in length, highlighting optimality, probabilistic principles, and neuromechanical constraints, that may guide individuals to families of muscle activity solutions within what is theoretically possible. Our intention is for this paper to serve as a primer for the neuromuscular control scientific community by introducing and integrating many of the ideas common across disciplines today, as well as inspire future work to improve the representation of neural control in biomechanical models.

Modulation of finger muscle activation patterns across postures is coordinated across all muscle groups

Successful grasp requires that grip forces be properly directed between the fingertips and the held object. Changes in digit posture significantly affect the mapping between muscle force and fingertip force. Joint torques must subsequently be altered to maintain the desired force direction at the fingertips. Our current understanding of the roles of hand muscles in force production remains incomplete, as past studies focused on a limited set of postures or force directions. To thoroughly examine how hand muscles adapt to changing external (force direction) and internal (posture) conditions, activation patterns of six index finger muscles were examined with intramuscular electrodes in 10 healthy subjects. Participants produced submaximal isometric forces in each of six orthogonal directions at nine different finger postures. Across force directions, participants significantly altered activation patterns to accommodate postural changes in the interphalangeal joint angles but not changes in the metacarpophalangeal joint angles. Modulation of activation levels of the extrinsic hand muscles, particularly the extensors, were as great as those of intrinsic muscles, suggesting that both extrinsic and intrinsic muscles were involved in creating the desired forces. Despite considerable between-subject variation in the absolute activation patterns, principal component analysis revealed that participants used similar strategies to accommodate the postural changes. The changes in muscle coordination also helped increase joint impedance in order to stabilize the end-point force direction. This effect counteracts the increased signal-dependent motor noise that arises with greater magnitude of muscle activation as interphalangeal joint flexion is increased. These results highlight the role of the extrinsic muscles in controlling fingertip force direction across finger postures.NEW & NOTEWORTHY We examined how hand muscles adapt to changing external (force direction) and internal (posture) conditions. Muscle activations, particularly of the extrinsic extensors, were significantly affected by postural changes of the interphalangeal, but not metacarpophalangeal, joints. Joint impedance was modulated so that the effects of the signal-dependent motor noise on the force output were reduced. Comparisons with theoretical solutions showed that the chosen activation patterns occupied a small portion of the possible solution space, minimizing the maximum activation of any one muscle.

A Platform for Rehabilitation of Finger Individuation in Children with Hemiplegic Cerebral Palsy

The brain injury that results in cerebral palsy CP may adversely affect fine motor control of the hand. The degradation of manual dexterity in the fingers profoundly impacts overall functionality of the upper limb, yet research efforts to facilitate rehabilitation of finger individuation in children with CP have been limited. This study describes the development of an integrated hardware and software platform for training and evaluating finger individuation. A pneumatically actuated glove provides extension assistance or flexion resistance independently to each digit in concert with playing a virtual reality keyboard. This setup enables intensive and efficient practice of fine motor control of either or both hands. Bimanual training options range from mirror movements to fully independent motions and rhythms in each hand, thereby enabling maintenance of the proper level of challenge. Additionally, an instrument was created to provide assessment of individuated fingertip force generation in order to evaluate effectiveness of the training. Preliminary data were obtained from children both with and without CP using this tool.

Development of a dynamic index finger and thumb model to study impairment

Modeling of the human hand provides insight for explaining deficits and planning treatment following injury. Creation of a dynamic model, however, is complicated by the actions of multi-articular tendons and their complex interactions with other soft tissues in the hand. This study explores the creation of a musculoskeletal model, including the thumb and index finger, to explore the effects of muscle activation deficits. The OpenSim model utilizes physiological axes of rotation at all joints, passive joint torques, and appropriate moment arms. The model was validated through comparison with kinematic and kinetic experimental data. Simulated fingertip forces resulting from modeled musculotendon loading largely fell within one standard deviation of experimental ranges for most index finger and thumb muscles, although agreement in the sagittal plane was generally better than for the coronal plane. Input of experimentally obtained electromyography data produced the expected simulated finger and thumb motion. Use of the model to predict the effects of activation deficits on pinch force production revealed that the intrinsic muscles, especially first dorsal interosseous (FDI) and adductor pollicis (ADP), had a substantial impact on the resulting fingertip force. Reducing FDI activation, such as might occur following stroke, altered fingertip force direction by up to 83° for production of a dorsal fingertip force; reducing ADP activation reduced force production in the thumb by up to 62%. This validated model can provide a means for evaluating clinical interventions.