Individual Responses to Different Vibration Frequencies Identified by Electromyography and Dynamometry in Different Types of Vibration Application.

ABSTRACT: Oliveira, MP, Menzel, H-JK, Cochrane, DJ, Drummond, MD, Demicheli, C, Lage, G, and Couto, BP. Individual responses to different vibration frequencies identified by electromyography and dynamometry in different types of vibration application. J Strength Cond Res 35(6): 1748-1759, 2021-The application of mechanical vibration is a common neuromuscular training technique used in sports training programs to generate acute increases in muscle strength. The principal aim of the study was to compare the individual optimal vibration frequency (IOVF) identified by electromyography (EMG) activity and force production in strength training. Twenty well-trained male volunteers (age: 23.8 ± 3.3 years) performed a familiarization and 2 interventions sessions, which included 5 maximal voluntary contractions (MVCs) of the elbow flexors with a duration of 10 seconds and 5-minute intervals between each MVC. The first MVC was performed without vibration followed by 4 randomized MVCs with application of vibration in the direction of the resultant muscle forces' vector (VDF) or whole-body vibration (WBV) at frequencies of 10, 20, 30, or 40 Hz. The mechanical vibration stimulus was superimposed during the MVC. Individual optimal vibration frequency, as identified by EMG, did not coincide with IOVF identified by force production; low agreement was observed between the vibration frequencies in generating the higher EMG activity, maximal force, and root mean square of force. These findings suggest that the magnitude of the vibratory stimulus response is individualized. Therefore, if the aim is to use acute vibration in conjunction with strength training, a preliminary vibration exposure should be conducted to determine the individualized vibratory stimulus of the subject, so that training effects can be optimized.

Exploratory factor analysis for differentiating sensory and mechanical variables related to muscle-tendon unit elongation.

BACKGROUND: Stretching exercises are able to promote adaptations in the muscle-tendon unit (MTU), which can be tested through physiological and biomechanical variables. Identifying the key variables in MTU adaptations is crucial to improvements in training. OBJECTIVE: To perform an exploratory factor analysis (EFA) involving the variables often used to evaluate the response of the MTU to stretching exercises. METHOD: Maximum joint range of motion (ROMMAX), ROM at first sensation of stretching (FSTROM), peak torque (torqueMAX), passive stiffness, normalized stiffness, passive energy, and normalized energy were investigated in 36 participants during passive knee extension on an isokinetic dynamometer. Stiffness and energy values were normalized by the muscle cross-sectional area and their passive mode assured by monitoring the EMG activity. RESULTS: EFA revealed two major factors that explained 89.68% of the total variance: 53.13% was explained by the variables torqueMAX, passive stiffness, normalized stiffness, passive energy, and normalized energy, whereas the remaining 36.55% was explained by the variables ROMMAX and FSTROM. CONCLUSION: This result supports the literature wherein two main hypotheses (mechanical and sensory theories) have been suggested to describe the adaptations of the MTU to stretching exercises. Contrary to some studies, in the present investigation torqueMAX was significantly correlated with the variables of the mechanical theory rather than those of the sensory theory. Therefore, a new approach was proposed to explain the behavior of the torqueMAX during stretching exercises.

Exploratory factor analysis for differentiating sensory and mechanical variables related to muscle-tendon unit elongation

ABSTRACT Background Stretching exercises are able to promote adaptations in the muscle-tendon unit (MTU), which can be tested through physiological and biomechanical variables. Identifying the key variables in MTU adaptations is crucial to improvements in training. Objective To perform an exploratory factor analysis (EFA) involving the variables often used to evaluate the response of the MTU to stretching exercises. Method Maximum joint range of motion (ROMMAX), ROM at first sensation of stretching (FSTROM), peak torque (torqueMAX), passive stiffness, normalized stiffness, passive energy, and normalized energy were investigated in 36 participants during passive knee extension on an isokinetic dynamometer. Stiffness and energy values were normalized by the muscle cross-sectional area and their passive mode assured by monitoring the EMG activity. Results EFA revealed two major factors that explained 89.68% of the total variance: 53.13% was explained by the variables torqueMAX, passive stiffness, normalized stiffness, passive energy, and normalized energy, whereas the remaining 36.55% was explained by the variables ROMMAX and FSTROM. Conclusion This result supports the literature wherein two main hypotheses (mechanical and sensory theories) have been suggested to describe the adaptations of the MTU to stretching exercises. Contrary to some studies, in the present investigation torqueMAX was significantly correlated with the variables of the mechanical theory rather than those of the sensory theory. Therefore, a new approach was proposed to explain the behavior of the torqueMAX during stretching exercises.

Functional data analyses for the assessment of joint power profiles during gait of stroke subjects.

Lower extremity kinetic data during walking of 12 people with chronic poststroke were reanalyzed, using functional analysis of variance (FANOVA). To perform the FANOVA, the whole curve is represented by a mathematical function, which spans the whole gait cycle and avoids the need to identify isolated points, as required for traditional parametric analyses of variance (ANOVA). The power variables at the ankle, knee, and hip joints, in the sagittal plane, were compared between two conditions: With and without walking sticks at comfortable and fast speeds. For the ankle joint, FANOVA demonstrated increases in plantar flexion power generation during 60-80% of the gait cycle between fast and comfortable speeds with the use of walking sticks. For the knee joint, the use of walking sticks resulted in increases in the knee extension power generation during 10-30% of the gait cycle. During both speeds, the use of walking sticks resulted in increased power generation by the hip extensors and flexors during 10-30% and 40-70% of the gait cycle, respectively. These findings demonstrated the benefits of applying the FANOVA approach to improve the knowledge regarding the effects of walking sticks on gait biomechanics and encourage its use within other clinical contexts.