Differences in muscle synergies between healthy subjects and transfemoral amputees during normal transient-state walking speed

Muscle synergy and kinematic synergy analyses during sit-to-stand motions in hallux valgus patients before and after treatment with Kinesio taping

OBJECTIVES

To explore the impact of hallux valgus (HV) on lower limb neuromuscular control strategies during the sit-to-stand (STS) movement, and to evaluate the effects of Kinesio taping (KT) intervention on these control strategies in HV patients.

METHODS

We included 14 young healthy controls (HY), 13 patients in the HV group (HV), and 11 patients in the HV group (HVI) who underwent a Kinesio taping (KT) intervention during sit-to-stand (STS) motions. We extracted muscle and kinematic synergies from EMG and motion capture data using non-negative matrix factorization (NNMF). In addition, we calculated the center of pressure (COP) and ground reaction forces (GRF) to assess balance performance.

RESULTS

There were no significant differences in the numbers of muscle and kinematic synergies between groups. In the HV group, knee flexors and ankle plantar flexors were abnormally activated, and muscle synergy D was differentiated. Muscle synergy D was not differentiated in the HVI group.

CONCLUSION

Abnormal activation of knee flexors and plantar flexors led to the differentiation of module D in HV patients, which can be used as an indicator of the progress of HV rehabilitation. KT intervention improved motor control mechanisms in HV patients.

Few sex-specific effects of fatigue on muscle synergies in a repetitive pointing task

Previous studies have identified some sex differences in how individual muscles change their activation during repetitive multi-joint arm motion-induced fatigue. However, little is known about how indicators of multi-muscle coordination change with fatigue in males and females. Fifty-six (29 females) asymptomatic young adults performed a repetitive, forward-backward pointing task until scoring 8/10 on a Borg CR10 scale while surface electromyographic activity of upper trapezius, anterior deltoid, biceps brachii, and triceps brachii was recorded. Activation coefficient, synergy structure, and relative weight of each muscle within synergies were calculated using the non-negative matrix factorization method. Two muscle synergies were extracted from the fatiguing task. The synergy structures were mostly preserved after fatigue, while the activation coefficients were altered. A significant Sex × Fatigue interaction effect showed more use of the anterior deltoid in males especially before fatigue in synergy 1 during shoulder stabilization (p = 0.04). As for synergy 2, it was characterized by variations in the relative weight of biceps, which was higher by 16 % in females compared to males (p = 0.04), and increased with fatigue (p = 0.03) during the elbow flexion acceleration phase and the deceleration phase of the backward pointing movement. Findings suggest that both sexes adapted to fatigue similarly, using fixed synergy structures, with alterations in synergy activation patterns and relative weights of individual muscles. Results support previous findings of an important role for the biceps and anterior deltoid in explaining sex differences in patterns of repetitive motion-induced upper limb fatigue.

Muscular activity comparison between non-amputees and transfemoral amputees during normal transient-state walking speed

RESEARCH QUESTION

Would there be differences in muscle activation between healthy subjects' (HS) dominant leg and transfemoral amputees' (TFA) intact-leg/contralateral-limb (IL) during normal transient-state walking speed?

METHODS

The muscle activation patterns are obtained by calculating the linear envelope of the EMG signals for each group. The activation patterns/temporal changes are compared between-population using statistical parametric mapping (SPM).

RESULTS

Individual muscle activity showed significant differences in all muscles except vastus lateralis (VL), semitendinosus (SEM) and tensor fascia latae (TFL) activities.

SIGNIFICANCE

The information could be used by the therapists to prevent secondary physical conditions and prosthetic companies to improve the mobility of the amputees.

Modular reorganization of gait in chronic but not in artificial knee joint constraint

It is currently unknown if modular reorganization does occur if not the central nervous system, but the musculoskeletal system is affected. The aims of this study were to investigate 1) the effects of an artificial knee joint constraint on the modular organization of gait in healthy subjects; and 2) the differences in modular organization between healthy subjects with an artificial knee joint constraint and people with a similar but chronic knee joint constraint. Eleven healthy subjects and eight people with a chronic knee joint constraint walked overground at 1 m/s. The healthy subjects also walked with a constraint limiting knee joint movement to 20°. The total variance accounted (tVAF) for one to four synergies and modular organization were assessed using surface electromyography from 11 leg muscles. The distribution of number of synergies were not significantly different between groups. The tVAF and the motor modules were not significantly affected by the artificial knee constraint. A higher tVAF for one and two synergies, as well as merging of motor modules were observed in the chronic knee constraint group. We conclude that in the short-term a knee constraint does not affect the modular organization of gait, but in the long-term a knee constraint results in modular reorganization. These results indicate that merging of motor modules may also occur when changes in the mechanics of the musculoskeletal system is the primary cause of the motor impairment.NEW & NOTEWORTHY It is currently unknown if modular reorganization does occur if not the central nervous system, but the musculoskeletal system is affected. This study showed that in the short-term a knee constraint does not affect the modular organization of gait, but in the long-term a knee constraint results in modular reorganization. These results indicate that modular reorganization may also occur when changes in the mechanics of the musculoskeletal system is the primary cause of the motor impairment.

Functional muscle synergies to support the knee against moment specific loads while weight bearing

OBJECTIVE

Externally applied abduction and rotational loads are major contributors to the knee joint injury mechanism; yet, how muscles work together to stabilize the knee against these loads remains unclear. Our study sought to evaluate lower limb functional muscle synergies in healthy young adults such that muscle activation can be directly related to internal knee joint moments.

METHODS

Concatenated non-negative matrix factorization extracted muscle and moment synergies of 22 participants from electromyographic signals and joint moments elicited during a weight-bearing force matching protocol.

RESULTS

Two synergy sets were extracted: Set 1 included four synergies, each corresponding to a general anterior, posterior, medial, or lateral force direction. Frontal and transverse moments were coupled during medial and lateral force directions. Set 2 included six synergies, each corresponding to a moment type (extension/flexion, ab/adduction, internal/external rotation). Hamstrings and quadriceps dominated synergies associated with respective flexion and extension moments while quadriceps-hamstring co-activation was associated with knee abduction. Rotation moments were associated with notable contributions from hamstrings, quadriceps, gastrocnemius, and hip ab/adductors, corresponding to a general co-activation muscle synergy.

CONCLUSION

Our results highlight the importance of muscular co-activation of all muscles crossing the knee to support it during injury-inducing loading conditions such as externally applied knee abduction and rotation. Functional muscle synergies can provide new insight into the relationship between neuromuscular control and knee joint stability by directly associating biomechanical variables to muscle activation.

Evaluation of Synergy Extrapolation for Predicting Unmeasured Muscle Excitations from Measured Muscle Synergies

Electromyography (EMG)-driven musculoskeletal modeling relies on high-quality measurements of muscle electrical activity to estimate muscle forces. However, a critical challenge for practical deployment of this approach is missing EMG data from muscles that contribute substantially to joint moments. This situation may arise due to either the inability to measure deep muscles with surface electrodes or the lack of a sufficient number of EMG channels. Muscle synergy analysis (MSA) is a dimensionality reduction approach that decomposes a large number of muscle excitations into a small number of time-varying synergy excitations along with time-invariant synergy weights that define the contribution of each synergy excitation to all muscle excitations. This study evaluates how well missing muscle excitations can be predicted using synergy excitations extracted from muscles with available EMG data (henceforth called "synergy extrapolation" or SynX). The method was evaluated using a gait data set collected from a stroke survivor walking on an instrumented treadmill at self-selected and fastest-comfortable speeds. The evaluation process started with full calibration of a lower-body EMG-driven model using 16 measured EMG channels (collected using surface and fine wire electrodes) per leg. One fine wire EMG channel (either iliopsoas or adductor longus) was then treated as unmeasured. The synergy weights associated with the unmeasured muscle excitation were predicted by solving a nonlinear optimization problem where the errors between inverse dynamics and EMG-driven joint moments were minimized. The prediction process was performed for different synergy analysis algorithms (principal component analysis and non-negative matrix factorization), EMG normalization methods, and numbers of synergies. SynX performance was most influenced by the choice of synergy analysis algorithm and number of synergies. Principal component analysis with five or six synergies consistently predicted unmeasured muscle excitations the most accurately and with the greatest robustness to EMG normalization method. Furthermore, the associated joint moment matching accuracy was comparable to that produced by initial EMG-driven model calibration using all 16 EMG channels per leg. SynX may facilitate the assessment of human neuromuscular control and biomechanics when important EMG signals are missing.