보행 과정에서 여러 근육이 동시에 수축하는 운동 모듈 또는 근육 시너지는 매우 중요한 중추신경계 운동조절 메커니즘이다. 본 연구는 걷는 동안 근육 간 양성 및 음성 공변 패턴을 이해하는 것을 목표로 한다. 본 연구에서는 트레드밀 보행 시 발생하는 다리 근육 활성을 근전도 검사를 통해 측정하였다. 동시 수축근육 그룹, 즉 운동 모듈을 확인하기 위해 우리는 양쪽 4 개의 다리 근육(전경골근, 내측 비복근, 대퇴직근, 내측 슬괵근)에서 근전도 데이터를 수집하였고, 이를 바탕으로 비음수행렬분해 및 주성분 분석을 수행하였다. 이후 근육 또는 운동 모듈 간의 다양한 조합으로부터 공변이 값을 계산하였고, 이원배치분산분석을 이용하여 각 조합들에서 발생하는 공변이 패턴을 비교하였다. 그 결과, 다양한 조합 사이에 유의미한 공변이 값의 차이가 발견되었다(p < 0.05). 같은 운동 모듈로 정의된 특정 근육 사이에서 발생하는 근 활성은 양성공변이를 보여주었으나 운동 모듈 사이에서는 음성 공변이를 보여주었다. 모든 근육 조합들 사이에서는 음성 공변이가 발생하였다. 운동 모듈 사이에서 안정적으로 발생하는 음성 공변이는 운동 모듈이 복잡한 운동 조정의 제어 단위(control unit) 일 수 있음을 암시하고 있다.
보행 과정에서 여러 근육이 동시에 수축하는 운동 모듈 또는 근육 시너지는 매우 중요한 중추신경계 운동조절 메커니즘이다. 본 연구는 걷는 동안 근육 간 양성 및 음성 공변 패턴을 이해하는 것을 목표로 한다. 본 연구에서는 트레드밀 보행 시 발생하는 다리 근육 활성을 근전도 검사를 통해 측정하였다. 동시 수축근육 그룹, 즉 운동 모듈을 확인하기 위해 우리는 양쪽 4 개의 다리 근육(전경골근, 내측 비복근, 대퇴직근, 내측 슬괵근)에서 근전도 데이터를 수집하였고, 이를 바탕으로 비음수행렬분해 및 주성분 분석을 수행하였다. 이후 근육 또는 운동 모듈 간의 다양한 조합으로부터 공변이 값을 계산하였고, 이원배치분산분석을 이용하여 각 조합들에서 발생하는 공변이 패턴을 비교하였다. 그 결과, 다양한 조합 사이에 유의미한 공변이 값의 차이가 발견되었다(p < 0.05). 같은 운동 모듈로 정의된 특정 근육 사이에서 발생하는 근 활성은 양성공변이를 보여주었으나 운동 모듈 사이에서는 음성 공변이를 보여주었다. 모든 근육 조합들 사이에서는 음성 공변이가 발생하였다. 운동 모듈 사이에서 안정적으로 발생하는 음성 공변이는 운동 모듈이 복잡한 운동 조정의 제어 단위(control unit) 일 수 있음을 암시하고 있다.
In human walking, muscle co-contraction which produces simultaneous activities of multiple muscles is important in motor control mechanism of the central nervous system. This study aims to understand positive and negative covariation mechanism of inter-muscle activities during walking. In this study...
In human walking, muscle co-contraction which produces simultaneous activities of multiple muscles is important in motor control mechanism of the central nervous system. This study aims to understand positive and negative covariation mechanism of inter-muscle activities during walking. In this study, we measured electromyography (EMG) in leg muscles. To identify motor modules, we recored EMG from 4 leg muscles bilaterally (the tibialis anterior, medial gastrocnemius, rectus femoris and medial hamstring muscles) and performed non-negative matrix factorization (NMF) and principa component analysis (PCA). Then, we computed covariation values from various combinations between muscles or motor modules and used two-way repeated measures analysis of variance to identify significantly different covariation patterns between muscle combinations. As the results, we found significant differences between covariation values of muscle combinations (p < 0.05). muscle groups within the same motor modules produced the positive covariations. However, there were strong negative covariation between motor modules. There was negative covariation in all muscle combination. Stable inter-module negative covariation suggests that motor modules may be the control unit in the complex motor coordination.
In human walking, muscle co-contraction which produces simultaneous activities of multiple muscles is important in motor control mechanism of the central nervous system. This study aims to understand positive and negative covariation mechanism of inter-muscle activities during walking. In this study, we measured electromyography (EMG) in leg muscles. To identify motor modules, we recored EMG from 4 leg muscles bilaterally (the tibialis anterior, medial gastrocnemius, rectus femoris and medial hamstring muscles) and performed non-negative matrix factorization (NMF) and principa component analysis (PCA). Then, we computed covariation values from various combinations between muscles or motor modules and used two-way repeated measures analysis of variance to identify significantly different covariation patterns between muscle combinations. As the results, we found significant differences between covariation values of muscle combinations (p < 0.05). muscle groups within the same motor modules produced the positive covariations. However, there were strong negative covariation between motor modules. There was negative covariation in all muscle combination. Stable inter-module negative covariation suggests that motor modules may be the control unit in the complex motor coordination.
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문제 정의
The purpose of the study was to understand covariation mechanism of inter-muscle activities during walking. To identify the mechanism, first, the positive or negative covariation values were demonstrated from inter-muscle activities using electromyography (EMG) during consecutive walking.
This study aimed to identify whether a muscle group composing motor module generate positive covariation during walking. As the results, EMG elements showed that the within-module combinations produced the positive covariation, but inter-module combination had negative covariation.
This divergent properties were also demonstrated by intra-axonal staining, serial-section, and threedimensional reconstruction of their axonal trajectories[23]. This study provides evidence that single cortical motor neurons innervate a functional set of multiple muscles. The multi-connection in neural system implicates the neural implementation of the motor module to reduce redundant control system.
가설 설정
To identify the mechanism, first, the positive or negative covariation values were demonstrated from inter-muscle activities using electromyography (EMG) during consecutive walking. According to the motor module concept, we hypothesized that the muscle activities would show the positive covariation within each module, but not in between-module combinations. In case of agonist antagonist pairs, we expected that the positive covariation would be blocked by reciprocal inhibition.
제안 방법
EMG data were extracted for consecutive 99 gait cycles. Since the aim of this study was to identify relationship between the elements, for spatial normalization across participants, all data were subtracted by each minimum value and then divided by maximum value. After the spatial normalization, all of the EMG data were ranged from 0 to 1.
Sampling rate of EMG was 1000 Hz. To confirm EMG activities, visual inspection was conducted during voluntary submaximal movements for each muscle in standing position. To avoid EMG noise generated by motion artifacts, all EMG signals were pre-amplified and the hardware low pass filter was fixed at 450 Hz.
The combinations of elements to compute inter-covariation were listed in [Table 1]. To identify covariation in the actual space, the analysis was modified from previous study[21]. First, time profiles of individual elements [Ei(t)] and of the sum of the individual elements [Etot(t) = Ei(t)] were arranged per each gait cycle.
To identify the motor modules, we conducted two decomposition techniques, NMF and PCA. The decomposition technique has great advance to simplify large and complicate EMG data measured in various muscles under high sampling rate.
대상 데이터
Participants in this study included sixteen healthy adults (8 females and 8 males; age, 25.3 ± 5.4 yr; body mass, 76.1 ± 14.1 kg; height, 170.2 ± 11.5 cm; dominant side, right).
데이터처리
After the analysis of EMG decomposition, to select the agonist muscles of each muscle weighting, one-way analysis of variance (ANOVA) and Dunncan’s post hoc analysis was conducted.
To identify significant differences in the covariation and mean variance values between the combination indexes, two-way repeated measures ANOVA (10 combination indexes × 99 cycles) and Dunncan’s post hoc were conducted. Specifically, to identify changes of measured values between the gait cycles per each combination, one-way repeated measures ANOVA was performed additionally. Shapiro-Wilk test examined normal distribution of participants’ anthropocentric characteristics such as age, weight, and height.
To identify significant differences in the covariation and mean variance values between the combination indexes, two-way repeated measures ANOVA (10 combination indexes × 99 cycles) and Dunncan’s post hoc were conducted.
성능/효과
This study aimed to identify whether a muscle group composing motor module generate positive covariation during walking. As the results, EMG elements showed that the within-module combinations produced the positive covariation, but inter-module combination had negative covariation. The agonist-antagonist muscle pair did not belong to the within-module combination and showed weak positive or negative covariation compared to other combinations.
후속연구
The decomposition technique has great advance to simplify large and complicate EMG data measured in various muscles under high sampling rate. In addition, since the results of simplified EMG data are quantitated based on the muscle weighing and the module activation profile, these results would be more utilizable to understand human movement mechanism than an intuitive interpretation of individual EMG data.
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