Abdullah Ruhi Soylu

Detection of surface electromyography recording time interval without muscle fatigue effect for biceps brachii muscle during maximum voluntary contraction

The effects of fatigue on maximum voluntary contraction (MVC) parameters were examined by using force and surface electromyography (sEMG) signals of the biceps brachii muscles (BBM) of 12 subjects. The purpose of the study was to find the sEMG time interval of the MVC recordings which is not affected by the muscle fatigue. At least 10s of force and sEMG signals of BBM were recorded simultaneously during MVC. The subjects reached the maximum force level within 2s by slightly increasing the force, and then contracted the BBM maximally. The time index of each sEMG and force signal were labeled with respect to the time index of the maximum force (i.e. after the time normalization, each sEMG or force signals 0s time index corresponds to maximum force point). Then, the first 8s of sEMG and force signals were divided into 0.5s intervals. Mean force, median frequency (MF) and integrated EMG (iEMG) values were calculated for each interval. Amplitude normalization was performed by dividing the force signals to their mean values of 0s time intervals (i.e. -0.25 to 0.25s). A similar amplitude normalization procedure was repeated for the iEMG and MF signals. Statistical analysis (Friedman test with Dunns post hoc test) was performed on the time and amplitude normalized signals (MF, iEMG). Although the ANOVA results did not give statistically significant information about the onset of the muscle fatigue, linear regression (mean force vs. time) showed a decreasing slope (Pearson-r=0.9462, p<0.0001) starting from the 0s time interval. Thus, it might be assumed that the muscle fatigue starts after the 0s time interval as the muscles cannot attain their peak force levels. This implies that the most reliable interval for MVC calculation which is not affected by the muscle fatigue is from the onset of the EMG activity to the peak force time. Mean, SD, and range of this interval (excluding 2s gradual increase time) for 12 subjects were 2353, 1258ms and 536-4186ms, respectively. Exceeding this interval introduces estimation errors in the maximum amplitude calculations of MVC-sEMG studies for BBM. It was shown that, simultaneous recording of force and sEMG signals was required to calculate the maximum amplitude of the MVC-sEMG more accurately.

Shear Wave Elastography Is a Reliable and Repeatable Method for Measuring the Elastic Modulus of the Rectus Femoris Muscle and Patellar Tendon

The purpose of this study was to determine intraobserver, interobserver, and inter‐day reliability levels for stiffness measurements of the patellar tendon and rectus femoris muscle using shear wave elastography (SWE).

Patellar tendon mechanical properties change with gender, body mass index and quadriceps femoris muscle strength

Objective The purpose of this study is to assess the effect and correlation of gender, body mass index (BMI) and quadriceps femoris (QF) muscle strength on patellar tendon (PT) thickness and stiffness in healthy sedentary individuals. Methods This study was carried out with 67 (36 female, 31 male) healthy sedentary individuals between the ages of 18–44 (28.0 ± 7.5 years). The individuals included in the study were divided into two groups according to their gender and BMI (18.5 < BMI < 25 and 25 < BMI). The body composition was determined with Tanita Body Composition Analyser. PT thickness and stiffness was measured with ACUSON S3000 Ultrasonography Device using 9L4 ultrasonography probe. QF concentric muscle strength of the individuals was measured with Biodex® System 4 Dynamometer at 60°/sec angular speed. Results It was found that PT stiffness was higher in males compared to females (p < 0.001). It was found that PT stiffness was lower in obese individuals compared to individuals with normal weight (p = 0.017). A negative and weak correlation was found between BMI and PT stiffness (r = −0.26, p = 0.032), whereas a negative and moderate correlation was found between fat percentage and PT stiffness (r = −0.50, p < 0.001). A moderate correlation was found between BMI and PT thickness (r = 0.54, p < 0.001). It was found that peak torque at 60°/sec angular speed had a moderate correlation with PT stiffness (r = 0.44, p < 0.001) and PT thickness (r = 0.45, p < 0.001). Conclusions PT stiffness is correlated and affected by gender, BMI and QF muscle strength whereas PT thickness is correlated and affected only to BMI and QF muscle strength.

The Effect of Kick Type on the Relationship between Kicking Leg Muscle Activation and Ball Velocity

This study aimed to identify the effects of different kick types on the relationship between kicking leg muscle activation and ball velocity. The muscle activation of selected knee extensor and flexor muscles of 10 amateur soccer players were measured using electromyography during the performance of six maximal soccer kick types. The highest ball velocity was achieved by the instep kick (96.2 km/hr-1), followed by the lofted kick, the inside curve kick, the outside kick, the outside curve kick, and finally the inside kick (81.3 km/hr-1). There were significant positive correlations between muscle activation and ball velocity for the vastus lateralis and lofted (0.765), inside curve (0.792) and instep kicks (0.788), and for the gastrocnemious with the outside kick (0.796). Non-significant correlations between muscle activation and ball velocity exhibited a trend such that they were positive for the vastus medialis and vastus lateralis but negative for the biceps femoris and gastrocnemious for inside-foot-dominated kicks, while this trend was reversed for outside-foot-dominated kicks. According to results, the noted trends can be explained by the change in muscle activation patterns required to orientate the foot for each type of kick; this has implications for players’ training activities.

A preliminary study for evaluating immediate post-vibration effects of whole body vibration on postural control

The aim of the preliminary study was to evaluate body sways simultaneously in mediolateral (ML) and anteroposterior (AP) directions of postural control measurements immediately after vibration stimulus. The participants were exposed to vibration stimulus for 60 s time period in static squat position with 1500 knee flexion on force platform that is placed on vibration platform. The vibration stimulus was given by a Compex WINPLATE Galileo 2000 device in up-down direction. Vibration amplitude and frequency were 2 mm and 40 Hz respectively. Each subject’s recording time was 70 s (5 s rest, 60s vibration and 5 s rest) for all sessions. The subjects stayed on the force measuring platform during each 70 s recording session. Soft mat of the vibration platform was placed between the vibration and force measuring platforms for reliable data and to prevent any damage on the force device. ML and AP force values normalized with respect to body weights for each subject. There were no statistically significant differences between the pre-vibration and post-vibration normalized force values. So, we claim that post-vibration effects are not statistically detectable unless a posture disturbance factor (for example moving from vibration device to force measurement device) occurs. The present study can be used as a reference to pave the way for the development an effective and sensitive measurement protocol of postural control.

Fundamentals of Quantitative Gait Analysis

Gait assessment is an important part of neurologic and orthopaedic examination. Visual gait analysis provides significant contribution to diagnosis of neuromuscular disorders, treatment planning and follow-up. However, three-dimensional motion of the segments during walking cannot be detected simultaneously in all planes. In addition to this, the physician does not have any information about the moment and power which are the causes of motion. 3D motion analysis systems have been used to overcome these limitations of visual gait assessment. These systems present motion, moment, power and electromyographic data of a gait cycle in the form of graphs for the use of clinicians. Physicians should have sufficient knowledge about functional anatomy, neural control of locomotion, muscle and motion mechanics and kinesiological electromyography to interpret these data.