Synergies in Grasping. In: Laczko J, Latash ML, editors. Progress in Motor Control. Cham: Springer International Publishing; 2016. pp. 21-34. [DOI: 10.1007/978-3-319-47313-0_2]

A Systematic Review of EMG Applications for the Characterization of Forearm and Hand Muscle Activity during Activities of Daily Living: Results, Challenges, and Open Issues

The role of the hand is crucial for the performance of activities of daily living, thereby ensuring a full and autonomous life. Its motion is controlled by a complex musculoskeletal system of approximately 38 muscles. Therefore, measuring and interpreting the muscle activation signals that drive hand motion is of great importance in many scientific domains, such as neuroscience, rehabilitation, physiotherapy, robotics, prosthetics, and biomechanics. Electromyography (EMG) can be used to carry out the neuromuscular characterization, but it is cumbersome because of the complexity of the musculoskeletal system of the forearm and hand. This paper reviews the main studies in which EMG has been applied to characterize the muscle activity of the forearm and hand during activities of daily living, with special attention to muscle synergies, which are thought to be used by the nervous system to simplify the control of the numerous muscles by actuating them in task-relevant subgroups. The state of the art of the current results are presented, which may help to guide and foster progress in many scientific domains. Furthermore, the most important challenges and open issues are identified in order to achieve a better understanding of human hand behavior, improve rehabilitation protocols, more intuitive control of prostheses, and more realistic biomechanical models.

High intensity aerobic exercise improves bimanual coordination of grasping forces in Parkinson's disease

INTRODUCTION

Parkinson's disease (PD) disrupts the control and coordination of grasping forces, likely due to a disruption in basal ganglia circuitry and diminished activity within the supplementary motor area (SMA). High intensity aerobic exercise has been shown to enhance connectivity between basal ganglia nuclei and cortical areas, including the SMA. The aim of this project was to determine the effects of high intensity lower extremity exercise on motor control patterns underlying a manual dexterity task.

METHODS

PD participants completed eight weeks of high intensity aerobic exercise under forced or voluntary exercise (FE or VE) modalities. Grasping forces for each limb were quantified during a functional bimanual dexterity task. Data were collected while OFF antiparkinsonian medication at baseline, end of treatment (EOT), and eight weeks after exercise cessation (EOT+8).

RESULTS

Eight weeks of high intensity exercise improved MDS-UPDRS Motor III clinical ratings by more than 4 points (~15%) for the FE and VE groups. Time to complete the task decreased nearly 30% across both groups as well. The control and coordination of grasping forces, simultaneity of force initiation, and rate of grip and load force exhibited significant improvements following exercise. In general, improvements in biomechanical outcomes were sustained following exercise cessation.

CONCLUSION

High intensity aerobic exercise, achieved via a forced or voluntary mode, improved PD symptoms and bimanual dexterity. Sustained improvement of upper extremity motor control following exercise cessation indicates high intensity exercise enhances CNS functioning and suggests exercise may be a candidate for altering PD progression.

Synergy-Based Sensor Reduction for Recording the Whole Hand Kinematics

Simultaneous measurement of the kinematics of all hand segments is cumbersome due to sensor placement constraints, occlusions, and environmental disturbances. The aim of this study is to reduce the number of sensors required by using kinematic synergies, which are considered the basic building blocks underlying hand motions. Synergies were identified from the public KIN-MUS UJI database (22 subjects, 26 representative daily activities). Ten synergies per subject were extracted as the principal components explaining at least 95% of the total variance of the angles recorded across all tasks. The 220 resulting synergies were clustered, and candidate angles for estimating the remaining angles were obtained from these groups. Different combinations of candidates were tested and the one providing the lowest error was selected, its goodness being evaluated against kinematic data from another dataset (KINE-ADL BE-UJI). Consequently, the original 16 joint angles were reduced to eight: carpometacarpal flexion and abduction of thumb, metacarpophalangeal and interphalangeal flexion of thumb, proximal interphalangeal flexion of index and ring fingers, metacarpophalangeal flexion of ring finger, and palmar arch. Average estimation errors across joints were below 10% of the range of motion of each joint angle for all the activities. Across activities, errors ranged between 3.1% and 16.8%.

Hand Kinematics Characterization While Performing Activities of Daily Living Through Kinematics Reduction

Improving the understanding of hand kinematics during the performance of activities of daily living may help improve the control of hand prostheses and hand function assessment. This work identifies sparse synergies (each degree of freedom is present mainly in only one synergy), representative of the global population, with emphasis in unveiling the coordination of joints with small range of motion (palmar arching and fingers abduction). The study is the most complete study described in the literature till now, involving 22 healthy subjects and 26 representative day-to-day life activities. Principal component analysis was used to reduce the original 16 angles recorded with an instrumented glove. Five synergies explained 75% of total variance: closeness (coordinated flexion and abduction of metacarpophalangeal finger joints), digit arching (flexion of proximal interphalangeal joints), palmar-thumb coordination (coordination of palmar arching and thumb carpometacarpal flexion), thumb opposition, and thumb arch. The temporal evolution of these synergies is provided during reaching per intended grasp and during manipulation per specific task, which could be used as normative patterns for the global population. Reaching has been observed to require the modulation of closeness, digit arch and thumb opposition synergies, with different control patterns per grasp. All the synergies are very important during manipulation and need to be modulated for all the tasks. Finally, groups of tasks with similar kinematic requirements in terms of synergies have been identified, which could benefit the selection of tasks for rehabilitation and hand function assessments.

A review of grasping as the movements of digits in space

It is tempting to describe human reach-to-grasp movements in terms of two, more or less independent visuomotor channels, one relating hand transport to the object’s location and the other relating grip aperture to the object’s size. Our review of experimental work questions this framework for reasons that go beyond noting the dependence between the two channels. Both the lack of effect of size illusions on grip aperture and the finding that the variability in grip aperture does not depend on the object’s size indicate that size information is not used to control grip aperture. An alternative is to describe grip formation as emerging from controlling the movements of the digits in space. Each digit’s trajectory when grasping an object is remarkably similar to its trajectory when moving to tap the same position on its own. The similarity is also evident in the fast responses when the object is displaced. This review develops a new description of the speed-accuracy trade-off for multiple effectors that is applied to grasping. The most direct support for the digit-in-space framework is that prism-induced adaptation of each digit’s tapping movements transfers to that digit’s movements when grasping, leading to changes in grip aperture for adaptation in opposite directions for the two digits. We conclude that although grip aperture and hand transport are convenient variables to describe grasping, treating grasping as movements of the digits in space is a more suitable basis for understanding the neural control of grasping.

Modelling the structure of object-independent human affordances of approaching to grasp for robotic hands

Grasp affordances in robotics represent different ways to grasp an object involving a variety of factors from vision to hand control. A model of grasp affordances that is able to scale across different objects, features and domains is needed to provide robots with advanced manipulation skills. The existing frameworks, however, can be difficult to extend towards a more general and domain independent approach. This work is the first step towards a modular implementation of grasp affordances that can be separated into two stages: approach to grasp and grasp execution. In this study, human experiments of approaching to grasp are analysed, and object-independent patterns of motion are defined and modelled analytically from the data. Human subjects performed a specific action (hammering) using objects of different geometry, size and weight. Motion capture data relating the hand-object approach distance was used for the analysis. The results showed that approach to grasp can be structured in four distinct phases that are best represented by non-linear models, independent from the objects being handled. This suggests that approaching to grasp patterns are following an intentionally planned control strategy, rather than implementing a reactive execution.