Muscle Synergy Plasticity in Motor Function Recovery After Stroke

In certain neurological disorders such as stroke, the impairment of upper limb function significantly impacts daily life quality and necessitates enhanced neurological control. This poses a formidable challenge in the realm of rehabilitation due to its intricate nature. Moreover, the plasticity of muscle synergy proves advantageous in assessing the enhancement of motor function among stroke patients pre and post rehabilitation training intervention, owing to the modular control strategy of central nervous system. It also facilitates the investigation of long-term alterations in remodeling of muscle functional performance among patients undergoing clinical rehabilitation, aiming to establish correlations between changes in muscle synergies and stroke characteristics such as type, stage, and sites. In this study, a three-week rehabilitation monitoring experiment was conducted to assess the motor function of stroke patients at different stages of rehabilitation based on muscle synergy performance. Additionally, we aimed to investigate the correlation between clinical scale scores, rehabilitation stages, and synergy performance in order to provide a more comprehensive understanding of stroke patient recovery. The results of 7 healthy controls and 16 stroke patients showed that high-functioning patients were superior to low-functioning patients in terms of motor function plasticity towards healthy individuals. Moreover, there was a high positive correlation between muscle synergies and clinical scale scores in high-functioning patients, and the significance gradually emerged with treatment, highlighting the potential of muscle synergy plasticity as a valuable tool for monitoring rehabilitation progress. The potential of this study was also demonstrated for elucidating the physiological mechanisms underlying motor function reconstruction within the central nervous system, which is expected to promote the further application of muscle synergy in clinical assessment.

Analysis of muscle synergy and gait kinematics during regain of gait function through rehabilitation in a monoplegic patient

Purpose

We conducted muscle synergy and gait analyses in a monoplegic patient whose gait function improved through training, to explore the possibility of using these parameters as indicators of training.

Case presentation

A 49-year-old male had monoplegia of the right lower limb caused by infarction of the left paracentral lobule. After 2 months of training, he was able to walk and returned to work.

Methods

Consecutive analyses were done after admission. Muscle synergy analysis: during walking, surface electromyograms of gluteus maximus, quadriceps femoris, adductor femoris, hamstrings, tibialis anterior, medial/lateral gastrocnemius, and soleus on both sides were recorded and processed for non-negative matrix factorization (NNMF) analysis. Gait analysis: markers were placed at foot, and walking movements were video recorded as changes in position of the markers.

Results

Compared with three muscle synergies detected on the non-paretic side, two muscle synergies were extracted on the paretic side at admission, and the number increased to three and then four with progress in rehabilitation training. Changes in weighting and activity of the muscle synergies were greater on the non-paretic side than on the paretic side. With training, the knee joint flexor and the ankle dorsiflexor activities on the paretic side and the gluteus maximus activity on the non-paretic side increased during swing phase as shown by weight changes of muscle synergies, and gait analysis showed increased knee joint flexion and ankle joint dorsiflexion during swing phase in the paretic limb. On the non-paretic side, however, variability of muscle activity was observed, and three or four muscle synergies were extracted depending on the number of strides analyzed.

Conclusion

The number of muscle synergies is considered to contribute to motor control. Rehabilitation training improves gait by increasing the number of muscle synergies on the paretic side and changing the weights of the muscles constituting the muscle synergies. From the changes on the non-paretic side, we propose the existence of compensatory mechanisms also on the non-paretic side. In muscle synergy analysis, in addition to the filters, the number of strides used in each analysis set has to be examined. This report highlights the issues of NNMF as analytical methods in gait training for stroke patients.

Applying muscle synergy analysis to forearm high-density electromyography of healthy people

Introduction

Muscle synergy is regarded as a motor control strategy deployed by the central nervous system (CNS). Clarifying the modulation of muscle synergies under different strength training modes is important for the rehabilitation of motor-impaired patients.

Methods

To represent the subtle variation of neuromuscular activities from the smaller forearm muscles during wrist motion, we proposed to apply muscle synergy analysis to preprocessed high-density electromyographic data (HDEMG). Here, modulation of muscle synergies within and across the isometric and isotonic training modes for strengthening muscles across the wrist were investigated. Surface HDEMGs were recorded from healthy subjects (N = 10). Three different HDEMG electrode configurations were used for comparison and validation of the extracted muscle synergies. The cosine of principal angles (CPA) and the Euclidian distance (ED) between synergy vectors were used to evaluate the intra- and inter-mode similarity of muscle synergies. Then, how the activation coefficients modulate the excitation of specific synergy under each mode was examined by pattern recognition. Next, for a closer look at the mode-specific synergies and the synergies shared by the two training modes, k-means clustering was applied.

Results

We observed high similarity of muscle synergies across different tasks within each training mode, but decreased similarity of muscle synergies across different training modes. Both intra- and intermode similarity of muscle synergies were consistently robust to electrode configurations regardless of the similarity metric used.

Discussion

Overall, our findings suggest that applying muscle synergy analysis to HDEMG is feasible, and that the traditional muscle synergies defined by whole-muscle components may be broadened to include sub-muscle components represented by the HDEMG channels. This work may lead to an appropriate neuromuscular analysis method for motor function evaluation in clinical settings and provide valuable insights for the prescription of rehabilitation training therapies.

Clarify Sit-to-Stand Muscle Synergy and Tension Changes in Subacute Stroke Rehabilitation by Musculoskeletal Modeling

Post-stroke patients exhibit distinct muscle activation electromyography (EMG) features in sit-to-stand (STS) due to motor deficiency. Muscle activation amplitude, related to muscle tension and muscle synergy activation levels, is one of the defining EMG features that reflects post-stroke motor functioning and motor impairment. Although some qualitative findings are available, it is not clear if and how muscle activation amplitude-related biomechanical attributes may quantitatively reflect during subacute stroke rehabilitation. To better enable a longitudinal investigation into a patient's muscle activation changes during rehabilitation or an inter-subject comparison, EMG normalization is usually applied. However, current normalization methods using maximum voluntary contraction (MVC) or within-task peak/mean EMG may not be feasible when MVC cannot be obtained from stroke survivors due to motor paralysis and the subject of comparison is EMG amplitude. Here, focusing on the paretic side, we first propose a novel, joint torque-based normalization method that incorporates musculoskeletal modeling, forward dynamics simulation, and mathematical optimization. Next, upon method validation, we apply it to quantify changes in muscle tension and muscle synergy activation levels in STS motor control units for patients in subacute stroke rehabilitation. The novel method was validated against MVC-normalized EMG data from eight healthy participants, and it retained muscle activation amplitude differences for inter- and intra-subject comparisons. The proposed joint torque-based method was also compared with the common static optimization based on squared muscle activation and showed higher simulation accuracy overall. Serial STS measurements were conducted with four post-stroke patients during their subacute rehabilitation stay (137 ± 22 days) in the hospital. Quantitative results of patients suggest that maximum muscle tension and activation level of muscle synergy temporal patterns may reflect the effectiveness of subacute stroke rehabilitation. A quality comparison between muscle synergies computed with the conventional within-task peak/mean EMG normalization and our proposed method showed that the conventional was prone to activation amplitude overestimation and underestimation. The contributed method and findings help recapitulate and understand the post-stroke motor recovery process, which may facilitate developing more effective rehabilitation strategies for future stroke survivors.

Characterizing Strategic Contributions of Physical Therapy to Natural Standing Motion in the Muscle Synergy Space

Understanding the contributions of therapist skill during intervention is essential for improving existing rehabilitation methodologies. This study aims to characterize therapist intervention on an important activity of daily living, the sit-to-stand motion. Using the concept of muscle synergy, we quantify and compare naturally-occurring standing strategies with those induced by a physical therapist. In this paper, we show that natural standing strategies are not shared among healthy subjects. However, each subject retains their own set of strategies. Moreover, the results suggest that a therapist does not introduce new strategies during therapy, but rather modulates the existing strategies of the individuals. Using such a low-dimensional representation of standing behavior allows for development of low-cost tools for wider distribution.

Temporal Features of Muscle Synergies in Sit-to-Stand Motion Reflect the Motor Impairment of Post-Stroke Patients

Sit-to-stand (STS) motion is an important daily activity, and many post-stroke patients have difficulty performing STS motion. Previous studies found that there are four muscle synergies (synchronized muscle activations) in the STS motion of healthy adults. However, for post-stroke patients, it is unclear whether muscle synergies change and which features primarily reflect motor impairment. Here, we use a machine learning method to demonstrate that temporal features in two muscle synergies that contribute to hip rising and balance maintenance motion reflect the motor impairment of post-stroke patients. Analyzing the muscle synergies of age-matched healthy elderly people ( n = 12 ) and post-stroke patients ( n = 33 ), we found that the same four muscle synergies could account for the muscle activity of post-stroke patients. Also, we were able to distinguish post-stroke patients from healthy people on the basis of the temporal features of these muscle synergies. Furthermore, these temporal features were found to correlate with motor impairment of post-stroke patients. We conclude that post-stroke patients can still utilize the same number of muscle synergies as healthy people, but the temporal structure of muscle synergies changes as a result of motor impairment. This could lead to a new rehabilitation strategy for post-stroke patients that focuses on activation timing of muscle synergies.

Important Movement Concepts: Clinical Versus Neuroscience Perspectives

Human movement is complex, presenting clinical and research challenges regarding how it is described and investigated. This paper discusses the commonalities and differences on how human movement is conceptualized from neuroscientific and clinical perspectives with respect to postural control; the limitations of linear measures; movement efficiency with respect to metabolic energy cost and selectivity; and, how muscle synergy analysis may contribute to our understanding of movement variability. We highlight the role of sensory information on motor performance with respect to the base of support and alignment, illustrating a potential disconnect between the clinical and neuroscientific perspectives. The purpose of this paper is to discuss the commonalities and differences in how movement concepts are defined and operationalized by Bobath clinicians and the neuroscientific community to facilitate a common understanding and open the dialogue on the research practice gap.

Motor Control System for Adaptation of Healthy Individuals and Recovery of Poststroke Patients: A Case Study on Muscle Synergies

Understanding the complex neuromuscular strategies underlying behavioral adaptation in healthy individuals and motor recovery after brain damage is essential for gaining fundamental knowledge on the motor control system. Relying on the concept of muscle synergy, which indicates the number of coordinated muscles needed to accomplish specific movements, we investigated behavioral adaptation in nine healthy participants who were introduced to a familiar environment and unfamiliar environment. We then compared the resulting computed muscle synergies with those observed in 10 moderate-stroke survivors throughout an 11-week motor recovery period. Our results revealed that computed muscle synergy characteristics changed after healthy participants were introduced to the unfamiliar environment, compared with those initially observed in the familiar environment, and exhibited an increased neural response to unpredictable inputs. The altered neural activities dramatically adjusted through behavior training to suit the unfamiliar environment requirements. Interestingly, we observed similar neuromuscular behaviors in patients with moderate stroke during the follow-up period of their motor recovery. This similarity suggests that the underlying neuromuscular strategies for adapting to an unfamiliar environment are comparable to those used for the recovery of motor function after stroke. Both mechanisms can be considered as a recall of neural pathways derived from preexisting muscle synergies, already encoded by the brain's internal model. Our results provide further insight on the fundamental principles of motor control and thus can guide the future development of poststroke therapies.

Alterations of Muscle Synergies During Voluntary Arm Reaching Movement in Subacute Stroke Survivors at Different Levels of Impairment

Motor system uses muscle synergies as a modular organization to simplify the control of movements. Motor cortical impairments, such as stroke and spinal cord injuries, disrupt the orchestration of the muscle synergies and result in abnormal movements. In this paper, the alterations of muscle synergies in subacute stroke survivors were examined during the voluntary reaching movement. We collected electromyographic (EMG) data from 35 stroke survivors, ranging from Brunnstrom Stage III to VI, and 25 age-matched control subjects. Muscle synergies were extracted from the activity of 7 upper-limb muscles via nonnegative matrix factorization under the criterion of 95% variance accounted for. By comparing the structure of muscle synergies and the similarity of activation coefficients across groups, we can validate the increasing activation of pectoralis major muscle and the decreasing activation of elbow extensor of triceps in stroke groups. Furthermore, the similarity of muscle synergies was significantly correlated with the Brunnstrom Stage (R = 0.52, p < 0.01). The synergies of stroke survivors at Brunnstrom Stage IV–III gradually diverged from those of control group, but the activation coefficients remained the same after stroke, irrespective of the recovery level.

Generation of Human-Like Movement from Symbolized Information

An important function missing from current robotic systems is a human-like method for creating behavior from symbolized information. This function could be used to assess the extent to which robotic behavior is human-like because it distinguishes human motion from that of human-made machines created using currently available techniques. The purpose of this research is to clarify the mechanisms that generate automatic motor commands to achieve symbolized behavior. We design a controller with a learning method called tacit learning, which considers system–environment interactions, and a transfer method called mechanical resonance mode, which transfers the control signals into a mechanical resonance mode space (MRM-space). We conduct simulations and experiments that involve standing balance control against disturbances with a two-degree-of-freedom inverted pendulum and bipedal walking control with humanoid robots. In the simulations and experiments on standing balance control, the pendulum can become upright after a disturbance by adjusting a few signals in MRM-space with tacit learning. In the simulations and experiments on bipedal walking control, the robots realize a wide variety of walking by manually adjusting a few signals in MRM-space. The results show that transferring the signals to an appropriate control space is the key process for reducing the complexity of the signals from the environment and achieving diverse behavior.