Activation and intermuscular coherence of distal arm muscles during proximal muscle contraction

Enhancing ergonomics in E-waste disassembly: the impact of collaborative robotics on muscle activation and coordination

Disassembly, as a part of the electronic waste (e-waste) management process, is a labour-intensive task. The emergence of collaborative robots (cobots) provides a robotic solution to reduce the human efforts during disassembly. This study evaluated muscle activation patterns during cobot-assisted e-waste disassembly using surface electromyography (EMG). Twenty-two participants were recruited to perform disassembly tasks with and without cobot assistance. EMG signals from biceps brachii (BB), brachioradialis (BR), upper trapezius (UT), and erector spinae (ES) were collected simultaneously. Six features were then calculated to determine muscle activation patterns. Additionally, EMG-EMG coherence analysis was conducted for BR and ES muscles. Results showed a significant reduction in muscle activity with cobot assistance, particularly in the left ES muscle (46.4% decrease). Moreover, coherence between BR and ES muscles significantly increased. These findings indicate the proposed collaboration strategy not only reduces the muscle activity but also sheds light on enhancing muscle coordination during e-waste disassembly.

Muscle synergies are associated with intermuscular coherence and cortico-synergy coherence in an isometric upper limb task

To elucidate the underlying physiological mechanisms of muscle synergies, we investigated long-range functional connectivity by cortico-muscular (CMC), intermuscular (IMC) and cortico-synergy (CSC) coherence. Fourteen healthy participants executed an isometric upper limb task in synergy-tuned directions. Cortical activity was recorded using 32-channel electroencephalography (EEG) and muscle activity using 16-channel electromyography (EMG). Using non-negative matrix factorisation (NMF), we calculated muscle synergies from two different tasks. A preliminary multidirectional task was used to identify synergy-preferred directions (PDs). A subsequent coherence task, consisting of generating forces isometrically in the synergy PDs, was used to assess the functional connectivity properties of synergies. Overall, we were able to identify four different synergies from the multidirectional task. A significant alpha band IMC was consistently present in all extracted synergies. Moreover, IMC alpha band was higher between muscles with higher weights within a synergy. Interestingly, CSC alpha band was also significantly higher across muscles with higher weights within a synergy. In contrast, no significant CMC was found between the motor cortex area and synergy muscles. The presence of a shared input onto synergistic muscles within a synergy supports the idea of neurally derived muscle synergies that build human movement. Our findings suggest cortical modulation of some of the synergies and the consequential existence of shared input between muscles within cortically modulated synergies.

Characteristics of multi-channel intermuscular directional coupling based on time-varying partial directional coherence analysis

The human body transmits directional information between muscles during upper limb movements, and this will be particularly evident when the dominant muscle changes during movement transitions. By capturing the electromyography (EMG) signals of wrist flexion and extension continuous transition movements, we investigated the characteristics of multichannel intermuscular directional coupling and directional information transmission, and consequently explored the control mechanism of Central nervous system (CNS) and the coordination mechanism of motor muscles. Multi-channel EMG was collected from 12 healthy subjects under continuous translational movements of wrist flexion and extension, and the time-varying biased directional coherence analysis (TVPDC) model was constructed using partial directional coherence analysis (PDC) frequency domain directionality to study the directional information transfer characteristics in the time-frequency domain, screen closely related muscle pairs and perform directional coupling significance analysis. Palmaris longus (PL) played a dominant role under wrist flexion movements(WF), Extensor Carpi Radialis (ECR) played a dominant role under wrist extension movements(WE), and the remaining muscles responded to them with information and Biceps Brachii (BB) played a responsive role throughout the movement; flexor pairs had the highest positive coupling values in the beta band during Conversion action1 (MC1) and WF phases, and extensor pairs had the highest positive coupling values in the gamma band during Conversion action2(MC2) phase and the highest coupling values in the beta band during WE phase. TVPDC can effectively analyze the multichannel intermuscular directional coupling and information transmission relationship of surface electromyography under wrist flexion and extension transition movements, providing a reference for exploring the control mechanism of CNS and abnormal control mechanism in patients with motor dysfunction in a new perspective.

Execution of natural manipulation in the air enhances the beta-rhythm intermuscular coherences of the human arm depending on muscle pairs

Natural manipulation tasks in air consist of two kinematic components: a grasping component, with activation of the hand muscles, and a lifting component, with activation of the proximal muscles. However, it remains unclear whether the synchronized motor commands to the hand/proximal arm muscles are divergently controlled during the task. Therefore, we examined how intermuscular coherence was modulated depending on the muscle combinations during grip and lift (G&L) tasks. Electromyograms (EMGs) were recorded from the biceps brachii (BB), triceps brachii (TB), flexor digitorum superficialis (FDS), and extensor digitorum communis (EDC) muscles. The participants were required to maintain G&L tasks involving a small cubical box with the thumb and index and middle fingers. Consequently, we found that the beta-rhythm coherence (15-35 Hz) in BB-TB, BB-FDS, and TB-EDC pairs during G&L was significantly larger than that during the isolated task with cocontraction of the two target muscles but not BB-EDC, TB-FDS, and FDS-EDC (task and muscle pair specificities). These increases in beta-rhythm coherence were also observed in intramuscular EMG recordings. Furthermore, the results from the execution of several mimic G&L tasks revealed that the separated task-related motor signals and combinations between the motor signals/sensations of the fingertips or object load had minor contributions to the increase in the coherence. These results suggest that during G&L the central nervous system regulates synchronous drive onto motoneurons depending on the muscle pairs and that the multiple combination effect of the sensations of touch/object load and motor signals in the task promotes the synchrony of these pairs.NEW & NOTEWORTHY Natural manipulation in air consists of two kinematic components: grasping, with activation of hand muscles, and lifting, with activation of proximal muscles. We show that during the maintenance of object manipulation in air the central nervous system regulates the synchronous drive onto human motoneuron pools depending on the hand/proximal muscle pairs and that the multiple combination effect of the sensations of touch/object load and motor signals in the task promotes the synchrony of these pairs.

Corticomuscular and Intermuscular Coupling in Simple Hand Movements to Enable a Hybrid Brain-Computer Interface

Hybrid Brain-Computer Interfaces (BCIs) for upper limb rehabilitation after stroke should enable the reinforcement of "more normal" brain and muscular activity. Here, we propose the combination of corticomuscular coherence (CMC) and intermuscular coherence (IMC) as control features for a novel hybrid BCI for rehabilitation purposes. Multiple electroencephalographic (EEG) signals and surface electromyography (EMG) from 5 muscles per side were collected in 20 healthy participants performing finger extension (Ext) and grasping (Grasp) with both dominant and non-dominant hand. Grand average of CMC and IMC patterns showed a bilateral sensorimotor area as well as multiple muscles involvement. CMC and IMC values were used as features to classify each task versus rest and Ext versus Grasp. We demonstrated that a combination of CMC and IMC features allows for classification of both movements versus rest with better performance (Area Under the receiver operating characteristic Curve, AUC) for the Ext movement (0.97) with respect to Grasp (0.88). Classification of Ext versus Grasp also showed high performances (0.99). All in all, these preliminary findings indicate that the combination of CMC and IMC could provide for a comprehensive framework for simple hand movements to eventually be employed in a hybrid BCI system for post-stroke rehabilitation.

Effects of task dynamics on coordination of the hand muscles and their adaptation to targeted muscle assistance

Dynamic characteristics of a manual task can affect the control of hand muscles due to the difference in biomechanical/physiological characteristics of the muscles and sensory afferents in the hand. We aimed to examine the effects of task dynamics on the coordination of hand muscles, and on the motor adaptation to external assistance. Twenty-four healthy subjects performed one of the two types of a finger extension task, isometric dorsal fingertip force production (static) or isokinetic finger extension (dynamic). Subjects performed the tasks voluntarily without assistance, or with a biomimetic exotendon providing targeted assistance to their extrinsic muscles. In unassisted conditions, significant between-task differences were found in the coordination of the extrinsic and intrinsic hand muscles, while the extrinsic muscle activities were similar between the tasks. Under assistance, while the muscle coordination remained relatively unaffected during the dynamic task, significant changes in the coordination between the extrinsic and intrinsic muscles were observed during the static task. Intermuscular coherence values generally decreased during the static task under assistance, but increased during the dynamic task (all p-values < 0.01). Additionally, a significant change in the task dynamics was induced by assistance only during static task. Our study showed that task type significantly affect coordination between the extrinsic and intrinsic hand muscles. During the static task, a lack of sensory information from musculotendons and joint receptors (more sensitive to changes in length/force) is postulated to have resulted in a neural decoupling between muscles and a consequent isolated modulation of the intrinsic muscle activity.

Effects of hand configuration on muscle force coordination, co-contraction and concomitant intermuscular coupling during maximal isometric flexion of the fingers

PURPOSE

The mechanisms governing the control of musculoskeletal redundancy remain to be fully understood. The hand is highly redundant, and shows different functional role of extensors according to its configuration for a same functional task of finger flexion. Through intermuscular coherence analysis combined with hand musculoskeletal modelling during maximal isometric hand contractions, our aim was to better understand the neural mechanisms underlying the control of muscle force coordination and agonist-antagonist co-contraction.

METHODS

Thirteen participants performed maximal isometric flexions of the fingers in two configurations: power grip (Power) and finger-pressing on a surface (Press). Hand kinematics and force/moment measurements were used as inputs in a musculoskeletal model of the hand to determine muscular tensions and co-contraction. EMG-EMG coherence analysis was performed between wrist and finger flexors and extensor muscle pairs in alpha, beta and gamma frequency bands.

RESULTS

Concomitantly with tailored muscle force coordination and increased co-contraction between Press and Power (mean difference: 48.08%; p < 0.05), our results showed muscle-pair-specific modulation of intermuscular coupling, characterized by pair-specific modulation of EMG-EMG coherence between Power and Press (p < 0.05), and a negative linear association between co-contraction and intermuscular coupling for the ECR/FCR agonist-antagonist muscle pair (r = - 0.65; p < 0.05).

CONCLUSIONS

This study brings new evidence that pair-specific modulation of EMG-EMG coherence is related to modulation of muscle force coordination during hand contractions. Our results highlight the functional importance of intermuscular coupling as a mechanism contributing to the control of muscle force synergies and agonist-antagonist co-contraction.

Neural coupling between homologous muscles during bimanual tasks: effects of visual and somatosensory feedback

While the effects of sensory feedback on bimanual tasks have been studied extensively at two ends of the motor control hierarchy, the cortical and behavioral levels, much less is known about how it affects the intermediate levels, including neural control of homologous muscle groups. We investigated the effects of somatosensory input on the neural coupling between homologous arm muscles during bimanual tasks. Twelve subjects performed symmetric elbow flexion/extension tasks under different types of sensory feedback. The first two types involve visual feedback, with one imposing stricter force symmetry than the other. The third incorporated somatosensory feedback via a balancing apparatus that forced the two limbs to produce equal force levels. Although the force error did not differ between feedback conditions, the somatosensory feedback significantly increased temporal coupling of bilateral force production, indicated by a high correlation between left/right force profiles (P < 0.001). More importantly, intermuscular coherence between biceps brachii muscles was significantly higher with somatosensory feedback than others (P = 0.001). Coherence values also significantly differed between tasks (flexion/extension). Notably, whereas feedback type mainly modulated coherence in the α- and γ-bands, task type only affected β-band coherence. Similar feedback effects were observed for triceps brachii muscles, but there was also a strong phase effect on the coherence values (P < 0.001) that could have diluted feedback effects. These results suggest that somatosensory feedback can significantly increase neural coupling between homologous muscles. Additionally, the between-task difference in β-band coherence may reflect different neural control strategies for the elbow flexor and extensor muscles.

NEW & NOTEWORTHY

This study investigated the effects of somatosensory feedback during bimanual tasks on the neural coupling between arm muscles, which remains largely unexplored. Somatosensory feedback using a balancing apparatus, compared with visual feedback, significantly increased neural coupling between homologous muscles (indicated by intermuscular coherence values) and improved temporal correlation of bilateral force production. Notably, feedback type modulated coherence in the α- and γ-bands (more subcortical pathways), whereas task type mainly affected β-band coherence (corticospinal pathway).

High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation

Adaptation of arm reaching in a novel force field involves co-contraction of upper limb muscles, but it is not known how the co-ordination of multiple muscle activation is orchestrated. We have used intermuscular coherence (IMC) to test whether a coherent intermuscular coupling between muscle pairs is responsible for novel patterns of activation during adaptation of reaching in a force field. Subjects (N = 16) performed reaching trials during a null force field, then during a velocity-dependent force field and then again during a null force field. Reaching trajectory error increased during early adaptation to the force-field and subsequently decreased during later adaptation. Co-contraction in the majority of all possible muscle pairs also increased during early adaptation and decreased during later adaptation. In contrast, IMC increased during later adaptation and only in a subset of muscle pairs. IMC consistently occurred in frequencies between ~40–100 Hz and during the period of arm movement, suggesting that a coherent intermuscular coupling between those muscles contributing to adaptation enable a reduction in wasteful co-contraction and energetic cost during reaching.

Proximal arm kinematics affect grip force-load force coordination

During object manipulation, grip force is coordinated with load force, which is primarily determined by object kinematics. Proximal arm kinematics may affect grip force control, as proximal segment motion could affect control of distal hand muscles via biomechanical and/or neural pathways. The aim of this study was to investigate the impact of proximal kinematics on grip force modulation during object manipulation. Fifteen subjects performed three vertical lifting tasks that involved distinct proximal kinematics (elbow/shoulder), but resulted in similar end-point (hand) trajectories. While temporal coordination of grip and load forces remained similar across the tasks, proximal kinematics significantly affected the grip force-to-load force ratio (P = 0.042), intrinsic finger muscle activation (P = 0.045), and flexor-extensor ratio (P < 0.001). Biomechanical coupling between extrinsic hand muscles and the elbow joint cannot fully explain the observed changes, as task-related changes in intrinsic hand muscle activation were greater than in extrinsic hand muscles. Rather, between-task variation in grip force (highest during task 3) appears to contrast to that in shoulder joint velocity/acceleration (lowest during task 3). These results suggest that complex neural coupling between the distal and proximal upper extremity musculature may affect grip force control during movements, also indicated by task-related changes in intermuscular coherence of muscle pairs, including intrinsic finger muscles. Furthermore, examination of the fingertip force showed that the human motor system may attempt to reduce variability in task-relevant motor output (grip force-to-load force ratio), while allowing larger fluctuations in output less relevant to task goal (shear force-to-grip force ratio).