The Influence Of Normalization Technique On Between-muscle Activation During A Back-squat: Methodological Considerations

Korak, Adam; Bruininks, Brett D.; Paquette, Max R.

doi:10.1249/01.mss.0000682500.56692.37

Cited by 5 publications

(4 citation statements)

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“…First, we used the fourth-order Butterworth high-pass filter (cutoff frequency of 40 Hz) to filter the signal and then removed the means and rectification ( Myers et al, 2003 ). Then, we used the fourth-order Butterworth low-pass filter (cutoff frequency of 4 Hz) to extract the signal envelope and introduced the maximum normalization method ( Esmaeili and Maleki, 2019 ; Korak et al, 2020 ) to normalize each channel EMG data for every trial according to the maximum amplitude value in each channel. We preprocessed all signals for each movement according to the above methods and built a data matrix of L × K ( L was the number of muscles, K was the number of data points), which was set as the muscle activation matrix M .…”

Section: Methodsmentioning

confidence: 99%

Muscle activation patterns and muscle synergies reflect different modes of coordination during upper extremity movement

Chen

Dong

Feng

et al. 2023

Front. Hum. Neurosci.

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A core issue in motor control is how the central nervous system generates and selects the muscle activation patterns necessary to achieve a variety of behaviors and movements. Extensive studies have verified that it is the foundation to induce a complex movement by the modular combinations of several muscles with a synergetic relationship. However, a few studies focus on the synergetic similarity and dissimilarity among different types of movements, especially for the upper extremity movements. In this study, we introduced the non-negative matrix factorization (NMF) method to explore the muscle activation patterns and synergy structure under 6 types of movements, involving the hand open (HO), hand close (HC), wrist flexion (WF), wrist extension (WE), supination (SU), and pronation (PR). For this, we enrolled 10 healthy subjects to record the electromyography signal for NMF calculation. The results showed a highly modular similarity of the muscle synergy among subjects under the same movement. Furthermore, Spearman’s correlation analysis indicated significant similarities among HO-WE, HO-SU, and WE-SU (p < 0.001). Additionally, we also found shared synergy and special synergy in activation patterns among different movements. This study confirmed the theory of modular structure in the central nervous system, which yields a stable synergetic pattern under the same movement. Our findings on muscle synergy will be of great significance to motor control and even to clinical assessment techniques.

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Section: Methodsmentioning

confidence: 99%

Muscle activation patterns and muscle synergies reflect different modes of coordination during upper extremity movement

Chen

Dong

Feng

et al. 2023

Front. Hum. Neurosci.

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“…A pilot session was conducted to assess the acceleration signals during the exercise, leading to the identification of an initial peak corresponding to the initiation of the exercise repetition and another peak observed at the conclusion of the exercise repetition. The RMS sEMG data were expressed as a percentage of the maximum voluntary contraction (MVC) [ 12 ] utilizing the highest sEMG recorded during the resisted plyometric without jumping trials at 5 cm/s [ 13 ].…”

Section: Methodsmentioning

confidence: 99%

Impact of Starting Knee Flexion Angle on Muscle Activity and Performance during Plyometrics without Jumping

Torres-Banduc,

Chirosa-Ríos,

Chirosa-Ríos

et al. 2023

Sensors

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Most of the existing research has focused on jump plyometrics, where landing reaction forces must be dissipated among lower limb articulations. In contrast, the investigation of resisted plyometrics without jumping, devoid of such landing forces, remains relatively limited. This study aimed to (i) investigate the impact of resisted plyometrics without jumping at two knee flexion angles (60 and 90 degrees) on vastus muscle activity relative to limb dominance and (ii) assess strength, power, and work during the concentric–eccentric phases of these exercises. Thirty-one healthy participants underwent quantification of lower limb muscle amplitude, strength, power, and work during resisted plyometrics without jumping from both 60° and 90° knee flexion positions. After anthropometric evaluations, participants used a dynamometer with a load equal to 80% of body weight while wireless surface electromyography electrodes recorded data. Statistical analyses utilized paired t-tests or nonparametric equivalents and set significance at p ≤ 0.05. Results showed significantly higher muscle activity in the vastus medialis (VM) (dominant: 47.4%, p = 0.0008, rs = 0.90; nondominant: 54.8%, p = 0.047, rs = 0.88) and vastus lateralis (VL) (dominant: 46.9%, p = 0.0004, rs = 0.86; nondominant: 48.1%, p = 0.021, rs = 0.67) muscles when exercises started at 90° knee flexion, regardless of limb dominance. Substantial intermuscle differences occurred at both 60° (50.4%, p = 0.003, rs = 0.56) and 90° (54.8%, p = 0.005, rs = 0.62) knee flexion, favoring VM in the nondominant leg. Concentric and eccentric strength, power, and work metrics significantly increased when initiating exercises from a 90° position. In conclusion, commencing resisted plyometrics without jumping at a 90° knee flexion position increases VM and VL muscle activity, regardless of limb dominance. Furthermore, it enhances strength, power, and work, emphasizing the importance of knee flexion position customization for optimizing muscle engagement and functional performance.

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Section: Introductionmentioning

confidence: 99%

“…One such method is to compare the sEMG signal magnitude during a functional activity to that of a maximal voluntary isometric contraction (MVIC) [7]. While this is a well-known normalization method, true subject effort has been shown to impact the validity of the results [8,9]. Mechanomyography (MMG), a methodology for assessing the mechanical activity of muscle during contraction, has recently gained attention as a counterpart or alternative to EMG [10].…”

Section: Introductionmentioning

confidence: 99%

Assessing Quadriceps Muscle Contraction Using a Novel Surface Mechanomyography Sensor during Two Neuromuscular Control Screening Tasks

Linderman

Scarborough

Aspenleiter³

et al. 2023

Sensors

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Electromyography (EMG) is the clinical standard for capturing muscle activation data to gain insight into neuromuscular control, yet challenges surrounding data analysis limit its use during dynamic tasks. Surface mechanomyography (sMMG) sensors are novel wearable devices that measure the physical output of muscle excursion during contraction, which may offer potential easy application to assess neuromuscular control. This study aimed to investigate sMMG detection of the timing patterns of muscle contraction compared to EMG. Fifteen healthy participants (mean age = 31.7 ± 9.1 y; eight males and seven females) were donned with EMG and sMMG sensors on their right quadriceps for simultaneous data capture during bilateral deep squats, and a subset performed three sets of repeated unilateral partial squats. No significant difference in the total duration of contraction was detected by EMG and sMMG during bilateral (p = 0.822) and partial (p = 0.246) squats. sMMG and EMG timing did not differ significantly for eccentric (p = 0.414) and concentric (p = 0.462) phases of muscle contraction during bilateral squats. The sMMG magnitude of quadriceps excursion demonstrated excellent intra-session retest reliability for bilateral (ICC3,1 = 0.962 mm) and partial (ICC3,1 = 0.936 mm, n = 10) squats. The sMMG sensors accurately and consistently provided key quadriceps muscle performance metrics during two physical activities commonly used to assess neuromuscular control for injury prevention, rehabilitation, and exercise training.

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The Influence Of Normalization Technique On Between-muscle Activation During A Back-squat: Methodological Considerations

Cited by 5 publications

References 0 publications

Muscle activation patterns and muscle synergies reflect different modes of coordination during upper extremity movement

Muscle activation patterns and muscle synergies reflect different modes of coordination during upper extremity movement

Impact of Starting Knee Flexion Angle on Muscle Activity and Performance during Plyometrics without Jumping

Assessing Quadriceps Muscle Contraction Using a Novel Surface Mechanomyography Sensor during Two Neuromuscular Control Screening Tasks

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