Electromyography Normalization Research Articles

Evacuation safety effects of a lightweight elevator-type evacuation device using carbon material: Focus on plantar pressure and muscle strength.

Elevator-type evacuation devices have proven to be feasible in high-rise buildings through studies on safety performance and evacuation time. However, there is a lack of research on safety using biosignal analysis in the elderly population. A carbon material is used in this study to reduce the weight of an evacuation elevator. The impact on the human body is evaluated by conducting a satisfaction survey involving elderly and youth groups and quantitatively analyzing biological signals, including electromyography (EMG) and plantar pressure, during five repeated uses of the proposed device. The study involves 12 healthy adults in their 20s and 20 elderly individuals with no experience in using an evacuation elevator. The EMG and left and right plantar pressures are analyzed to evaluate the physical factors affected by repeated use. The experiment results showed that the normalization of EMG to maximum voluntary contraction showed a significant decrease with repeated use, especially in the right tibialis anterior muscle. Moreover, plantar pressure shows a significant difference, which decreased with repetition, and the left and right balance gradually tilted to the left. This suggests that with more repeated use, muscle tension decreases owing to adaptation, resulting in lower muscle activity and plantar pressure. Particularly, the tibialis anterior muscle experiences significant muscle activity, indicating increased load, but without any apparent danger. In the future, it will be necessary to evaluate elevators for disabled individuals.

A Comparison of Bioelectric and Biomechanical EMG Normalization Techniques in Healthy Older and Young Adults during Walking Gait.

This study compares biomechanical and bioelectric electromyography (EMG) normalization techniques across disparate age cohorts during walking to assess the impact of normalization methods on the functional interpretation of EMG data. The biomechanical method involved scaling EMG to a target absolute torque (EMGTS) from a joint-specific task and the chosen bioelectric methods were peak and mean normalization taken from the EMG signal during gait, referred to as dynamic mean and dynamic peak normalization (EMGMean and EMGPeak). The effects of normalization on EMG amplitude, activation pattern, and inter-subject variability were compared between disparate cohorts, including OLD (76.6 yrs N = 12) and YOUNG (26.6 yrs N = 12), in five lower-limb muscles. EMGPeak normalization resulted in differences between YOUNG and OLD cohorts in Biceps Femoris (BF) and Medial Gastrocnemius (MG) that were not observed with EMGMean or EMGTS normalization. EMGPeak and EMGMean normalization also demonstrated interactions between age and the phase of gait in BF that were not seen with EMGTS. Correlations showed that activation patterns across the gait cycle were similar between all methods for both age groups and the coefficient of variation comparisons found that EMGTS produced the greatest inter-subject variability. We have shown that the normalization technique can influence the interpretation of findings when comparing disparate populations, highlighting the need to carefully interpret functional differences in EMG between disparate cohorts.

An alternative EMG normalization method: Heterogeneous recurrence quantification analysis of isometric maximum voluntary contraction movements

This study presents an alternative method of normalizing Surface Electromyography (EMG) signals, which provide valuable insights into the musculoskeletal properties of the human body. Traditional normalization through the peak maximum voluntary contraction (MVC) method may result in variable outcomes due to its dependence on pre-processing steps such as smoothing and window length. To address this issue, the study standardizes the EMG pre-processing steps by using non-linear techniques, namely recurrence quantification analysis (RQA) and heterogeneous RQA (HRQA). RQA, specifically HRQA, functions as EMG feature extractors to explore the nonlinear dynamical system and state space trajectories of chaotic EMG signals. Principal component analysis (PCA) and kernel PCA (KPCA) were further applied to the RQA and HRQA results to obtain data with more information. The results show that the first principal components (PC1 and KPC1) of HRQA have a very strong relationship with peak MVC (ρ > |0.90|, p < 0.001), indicating their potential compared to the traditional EMG normalization technique for lower limb muscle groups. Additionally, the study investigated the dynamic differences among isometric MVC movements in lower limb muscle groups and found that the RQA and HRQA methods indicated a greater separation for detecting these differences compared to peak MVC. This study offers a valuable method for assessing the musculoskeletal characteristics of individuals who may have difficulty with activities like walking or providing maximum force during EMG data collection, such as those suffering from Parkinson's disease or walking disabilities. This enhances our understanding of their musculoskeletal properties.

Standard isometric contraction has higher reliability than maximum voluntary isometric contraction for normalizing electromyography during level walking among older adults with knee osteoarthritis.

Introduction: Electromyography (EMG) normalization often relies on maximum voluntary isometric contraction (MVIC), which may not be suitable for knee osteoarthritis (KOA) patients due to difficulties in generating maximum joint torques caused by pain. This study aims to assess the reliability of standard isometric contraction (SIC) for EMG normalization in older adults with KOA, comparing it with MVIC. Methods: We recruited thirty-five older adults with KOA and collected root mean square EMG amplitudes from seven muscles in the affected limb during level walking, SIC, and MVIC tests. EMG data during level walking were normalized using both SIC and MVIC methods. This process was repeated after at least 1week. We calculated intra-class correlation coefficients (ICCs) with 95% confidence intervals to evaluate between- and within-day reliabilities. Results: SIC tests showed higher between- (ICC: 0.75-0.86) and within-day (ICC: 0.84-0.95) ICCs across all seven muscles compared to MVIC tests. When normalized with SIC, all seven muscles exhibited higher between- (ICC: 0.67-0.85) and within-day (ICC: 0.88-0.99) ICCs compared to MVIC normalization. Conclusion: This study suggests that SIC may offer superior movement consistency and reliability compared to MVIC for EMG normalization during level walking in older adults with KOA.

Muscle coactivation during gait in children with and without cerebral palsy

BackgroundChildren with Cerebral Palsy (CP) walk with an uncoordinated gait compared to Typically Developing (TD) children. This behavior may reflect greater muscle co-activation in the lower limb; however, findings are inconsistent, and the determinants of this construct are unclear. Research objectives(i) Compare lower-limb muscle co-activation during gait in children with, and without CP, and (ii) determine the extent to which muscle co-activation is influenced by electromyography normalization procedures and Gross Motor Function Classification System (GMFCS) class. MethodsAn electromyography system measured muscle activity in the rectus femoris, semitendinosus, gastrocnemius, and tibialis anterior muscles during walking in 46 children (19 CP, 27 TD). Muscle co-activation was calculated for the tibialis anterior-gastrocnemius (TA-G), rectus femoris-gastrocnemius (RF-G), and rectus femoris-semitendinosus (RF-S) pairings, both using root mean squared (RMS)-averaged and dynamically normalized data, during stance and swing. Mann-Whitney U and independent t-tests examined differences in muscle co-activation by group (CP vs. TD) and GMFCS class (CP only), while mean difference 95% bootstrapped confidence intervals compared electromyography normalization procedures. ResultsUsing dynamically normalized data, the CP group had greater muscle co-activation for the TA-G and RF-G pairs during stance (p < 0.01). Using RMS-averaged data, the CP group had greater muscle co-activation for TA-G (stance and swing, p < 0.01), RF-G (stance, p < 0.05), and RF-S (swing, p < 0.01) pairings. Muscle co-activation calculated with dynamically normalized, compared to RMS-averaged data, were larger in the RF-S and RF-G (stance) pairs, but smaller during swing (RF-G). Children with CP classified as GMFCS II had greater muscle co-activation during stance in the TA-G pair (p < 0.05). SignificanceGreater muscle co-activation observed in children with CP during stance may reflect a less robust gait strategy. Although data normalization procedures influence muscle co-activation ratios, this behavior was observed independent of normalization technique.

Neuromuscular Control During Stair Descent and Artificial Tibial Translation After Acute ACL Rupture.

Background:Anterior cruciate ligament (ACL) rupture has direct effect on passive and active knee stability and, specifically, stretch-reflex excitability.Purpose/Hypothesis:The purpose of this study was to investigate neuromuscular activity in patients with an acute ACL deficit (ACL-D group) compared with a matched control group with an intact ACL (ACL-I group) during stair descent and artificially induced anterior tibial translation. It was hypothesized that neuromuscular control would be impaired in the ACL-D group.Study Design:Cross-sectional study; Level of evidence, 3.Methods:Surface electromyographic (EMG) activity of the vastus medialis (VM), vastus lateralis (VL), biceps femoris (BF), and semitendinosus (ST) muscles was recorded bilaterally in 15 patients with ACL-D (mean, 13.8 days [range, 7-21 days] since injury) and 15 controls with ACL-I during stair descent and artificially induced anterior tibial translation. The movements of stair descent were divided into preactivity, weight acceptance, and push-off phases. Reflex activity during anterior tibial translation was split into preactivity and short, medium, and late latency responses. Walking on a treadmill was used for submaximal EMG normalization. Kruskal-Wallis test and post hoc analyses with Dunn-Bonferroni correction were used to compare normalized root mean square values for each muscle, limb, movement, and reflex phase between the ACL-D and ACL-I groups.Results:During the preactivity phase of stair descent, the hamstrings of the involved leg of the ACL-D group showed 33% to 51% less activity compared with the matched leg and contralateral leg of the ACL-I group (P < .05). During the weight acceptance and push-off phases, the VL revealed a significant reduction (approximately 40%) in the involved leg of the ACL-D group compared with the ACL-I group. At short latency, the BF and ST of the involved leg of the ACL-D group showed a significant increase in EMG activity compared with the uninvolved leg of the ACL-I group, by a factor of 2.2 to 4.6.Conclusion:In the acute phase after an ACL rupture, neuromuscular alterations were found mainly in the hamstrings of both limbs during stair descent and reflex activity. The potential role of prehabilitation needs to be further studied.

Within-day Reliability Of Electromyography Normalization With Standard Isometric Contraction In Patients With Knee Osteoarthritis

Within-day Reliability Of Electromyography Normalization With Standard Isometric Contraction In Patients With Knee Osteoarthritis

Design of an Isometric End-Point Force Control Task for Electromyography Normalization and Muscle Synergy Extraction From the Upper Limb Without Maximum Voluntary Contraction.

Muscle synergy analysis via surface electromyography (EMG) is useful to study muscle coordination in motor learning, clinical diagnosis, and neurorehabilitation. However, current methods to extract muscle synergies in the upper limb suffer from two major issues. First, the necessary normalization of EMG signals is performed via maximum voluntary contraction (MVC), which requires maximal isometric force production in each muscle. However, some individuals with motor impairments have difficulties producing maximal effort in the MVC task. In addition, the MVC is known to be highly unreliable, with widely different forces produced in repeated measures. Second, synergy extraction in the upper limb is typically performed with a multidirection reaching task. However, some participants with motor impairments cannot perform this task because it requires precise motor control. In this study, we proposed a new isometric rotating task that does not require precise motor control or large forces. In this task, participants maintain a cursor controlled by the arm end-point force on a target that rotates at a constant angular velocity at a designated force level. To relax constraints on motor control precision, the target is widened and blurred. To obtain a reference EMG value for normalization without requiring maximal effort, we estimated a linear relationship between joint torques and muscle activations. We assessed the reliability of joint torque normalization and synergy extraction in the rotating task in young neurotypical individuals. Compared with normalization with MVC, joint torque normalization allowed reliable EMG normalization at low force levels. In addition, the extraction of synergies was as reliable and more stable than with the multidirection reaching task. The proposed rotating task can, therefore, be used in future motor learning, clinical diagnosis, and neurorehabilitation studies.

Clarify Sit-to-Stand Muscle Synergy and Tension Changes in Subacute Stroke Rehabilitation by Musculoskeletal Modeling.

Post-stroke patients exhibit distinct muscle activation electromyography (EMG) features in sit-to-stand (STS) due to motor deficiency. Muscle activation amplitude, related to muscle tension and muscle synergy activation levels, is one of the defining EMG features that reflects post-stroke motor functioning and motor impairment. Although some qualitative findings are available, it is not clear if and how muscle activation amplitude-related biomechanical attributes may quantitatively reflect during subacute stroke rehabilitation. To better enable a longitudinal investigation into a patient's muscle activation changes during rehabilitation or an inter-subject comparison, EMG normalization is usually applied. However, current normalization methods using maximum voluntary contraction (MVC) or within-task peak/mean EMG may not be feasible when MVC cannot be obtained from stroke survivors due to motor paralysis and the subject of comparison is EMG amplitude. Here, focusing on the paretic side, we first propose a novel, joint torque-based normalization method that incorporates musculoskeletal modeling, forward dynamics simulation, and mathematical optimization. Next, upon method validation, we apply it to quantify changes in muscle tension and muscle synergy activation levels in STS motor control units for patients in subacute stroke rehabilitation. The novel method was validated against MVC-normalized EMG data from eight healthy participants, and it retained muscle activation amplitude differences for inter- and intra-subject comparisons. The proposed joint torque-based method was also compared with the common static optimization based on squared muscle activation and showed higher simulation accuracy overall. Serial STS measurements were conducted with four post-stroke patients during their subacute rehabilitation stay (137 ± 22 days) in the hospital. Quantitative results of patients suggest that maximum muscle tension and activation level of muscle synergy temporal patterns may reflect the effectiveness of subacute stroke rehabilitation. A quality comparison between muscle synergies computed with the conventional within-task peak/mean EMG normalization and our proposed method showed that the conventional was prone to activation amplitude overestimation and underestimation. The contributed method and findings help recapitulate and understand the post-stroke motor recovery process, which may facilitate developing more effective rehabilitation strategies for future stroke survivors.

Submaximal contractions can serve as a reliable technique for shoulder electromyography normalization

There are a number of ways to normalize electromyographical data, the most common of which is using a maximal contraction as a reference. However, this technique is not always practical. The purpose of the present study was to assess the reliability of an electromyographical data normalization technique using standardized submaximal contractions. Twenty healthy subjects (ten male, ten female) were used for testing, which was performed using both surface and fine-wire electromyography over two sessions at 15, 30, 45, and 60 percent of the day 1 maximum force. There was a mean of 5.3 days between test days. Data were compared between days, and the resulting ICC and standard error of the measurement values indicate varying levels of reliability at each submaximal percent. All heads of the deltoid, the upper trapezius and the serratus anterior demonstrated good reliability for at least one submaximal condition. The latissimus dorsi and supraspinatus demonstrated moderate reliability for at least one submaximal condition. Finally, the infraspinatus demonstrated poor reliability under all conditions. For situations in which MVC is impractical or anticipated to change, EMG amplitude normalization to one of these submaximal percentages appears to be a viable technique, at least for most muscles.

Effects of Concurrent and Terminal Visual Feedback on Ankle Co-Contraction in Older Adults during Standing Balance.

This preliminary investigation studied the effects of concurrent and terminal visual feedback during a standing balance task on ankle co-contraction, which was accomplished via surface electromyography of an agonist–antagonist muscle pair (medial gastrocnemius and tibialis anterior muscles). Two complementary mathematical definitions of co-contraction indices captured changes in ankle muscle recruitment and modulation strategies. Nineteen healthy older adults received both feedback types in a randomized order. Following an analysis of co-contraction index reliability as a function of surface electromyography normalization technique, linear mixed-effects regression analyses revealed participants learned or utilized different ankle co-contraction recruitment (i.e., relative muscle pair activity magnitudes) and modulation (i.e., absolute muscle pair activity magnitudes) strategies depending on feedback type and following the cessation of feedback use. Ankle co-contraction modulation increased when concurrent feedback was used and significantly decreased when concurrent feedback was removed. Ankle co-contraction recruitment and modulation did not significantly change when terminal feedback was used or when it was removed. Neither ankle co-contraction recruitment nor modulation was significantly different when concurrent feedback was used compared to when terminal feedback was used. The changes in ankle co-contraction recruitment and modulation were significantly different when concurrent feedback was removed as compared to when terminal feedback was removed. Finally, this study found a significant interaction between feedback type, removal of feedback, and order of use of feedback type. These results have implications for the design of balance training technologies using visual feedback.

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.

EMG Signal Feature Extraction, Normalization and Classification for Pain and Normal Muscles Using Genetic Algorithm and Support Vector Machine

Electromyography (EMG) is the process of measuring neuromuscular activities generated during the contraction and expansion period of muscles throughout the body. The potential is recorded by inserting needle or by placing electrodes on the surface of body. In this research, an automatic EMG signal classification system is developed using machine learning oriented Support Vector Machine (SVM). The collected data is selected using Genetic Algorithm (GA). The purpose of GA is to select those rows from the dataset, which contains potential or electrical activities recorded while the patient is in motion. Furthermore, the selected features are neutralized using critic method. To improve the row selection cosine similarity is being used to determine an average value hence also helps for data reduction. Based on the average similarity values, SVM is trained and used for classification during the testing phase. The experiment has been performed in MATLAB tool and the classification accuracy for normal and pain EMG signal of 91.3% and 92.4% respectively is achieved.

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

BACKGROUND/OBJECTIVE: Currently, no gold standard electromyography (EMG) normalizing technique exists when conducting between-muscle comparisons of muscle activity during isotonic resistance training exercises. The aim of this study was to assess if between-muscle activation during the back-squat differed among electromyography (EMG) normalization techniques when normalizing to: (1) 1 repetition maximum (1RM), (2) maximal voluntary isometric contraction (MVIC), and (3) the first of a set of three repetitions (Rep1%) in trained female lifters. METHODS: Thirteen participants completed a back-squat 1RM, MVIC of the rectus-femoris (RF) and gluteus-maximus (GM), and three repetitions of the back-squat at 80% 1RM. For the 1RM and MVIC normalization techniques, the average of the peak RMS signal of both muscles during the three submaximal reps were normalized to the peak 1RM and MVIC signals. The Rep1% averaged the peak RMS signals of both muscles during the 2nd and 3rd submaximal repetitions normalized to the peak signal during the 1st repetition. RESULTS: The RF-GM between-muscle EMG (ΔEMG) differed among normalization techniques (p < 0.001, ηp2 = 0.48). Post-hoc pairwise comparisons indicated MVIC normalization elicited different ΔEMG with large effects compared to both 1RM (p = 0.037; d = 1.2) and Rep1% (p = 0.004; d = 1.9) techniques, but the 1RM and Rep1% did not produce different ΔEMG (p = 0.27; d = 0.8). CONCLUSION: Our findings suggest EMG normalization technique influences the magnitude and direction of between-muscle activation during common lifting exercises, and we recommend normalizing isotonic movements to dynamic normalization methods such as a 1RM or Rep1%. Key Words: Electromyography; Methodology; Signal processing; Lower extremity; Training; Exercise

Surface Electromyography Normalization Affects the Interpretation of Muscle Activity and Coactivation in Children With Cerebral Palsy During Walking.

Investigating muscle activity and coactivation with surface electromyography (sEMG) gives insight into pathological muscle function during activities like walking in people with neuromuscular impairments, such as children with cerebral palsy (CP). There is large variation in the amount of coactivation reported during walking in children with CP, possibly due to the inconsistent handling of sEMG and in calculating the coactivation index. The aim of this study was to evaluate how different approaches of handling sEMG may affect the interpretation of muscle activity and coactivation, by looking at both absolute and normalized sEMG. Twenty-three ambulatory children with CP and 11 typically developing (TD) children participated. We conducted a three-dimensional gait analysis (3DGA) with concurrent sEMG measurements of tibialis anterior, soleus, gastrocnemius medialis, rectus femoris, and hamstring medialis. They walked barefoot at a self-selected, comfortable speed back and forth a 7-m walkway. The gait cycle extracted from the 3DGA was divided into six phases, and for each phase, root mean square sEMG amplitude was calculated (sEMG-RMS-abs), and also normalized to peak amplitude of the linear envelope (50-ms running RMS window) during the gait cycle (sEMG-RMS-norm). The coactivation index was calculated using sEMG-RMS-abs and sEMG-RMS-norm values and by using two different indices. Differences between TD children's legs and the affected legs of children with CP were tested with a mixed model. The between-subject muscle activity variability was more evenly distributed using sEMG-RMS-norm; however, potential physiological variability was eliminated as a result of normalization. Differences between groups in one gait phase using sEMG-RMS-abs showed opposite differences in another phase using sEMG-RMS-norm for three of the five muscles investigated. The CP group showed an increased coactivation index in two out of three muscle pairs using sEMG-RMS-abs and in all three muscle pairs using sEMG-RMS-norm. These results were independent of index calculation method. Moreover, the increased coactivation indices could be explained by either reduced agonist activity or increased antagonist activity. Thus, differences in muscle activity and coactivation index between the groups change after normalization. However, because we do not know the truth, we cannot conclude whether to normalize and recommend incorporating both.

Reliability of different electromyographic normalization methods for pelvic floor muscles assessment.

To evaluate the reliability of different methods to normalize pelvic floor muscles (PFM) electromyography (EMG). Thirty nulliparous women (23.9 ± 3.2 years), free from PFM dysfunction, completed two test sessions 7 days apart. For EMG normalization, signals were acquired during four different tasks using a vaginal probe in situ: PFM maximal voluntary contraction (MVC) and three daily activities with increased intra-abdominal pressure (coughing, Valsalva maneuver, and abdominal contraction). The intraclass correlation coefficients (ICC), standard error of measurement (SEM), relative standard error of measurement (%SEM), and minimal detectable change (MDC) were calculated for each variable. ICC values for test-retest reliability of normalization methods ranged from 0.61 to 0.95. The highest values were obtained for mean root mean square (RMS) of the abdominal contraction and peak RMS of PFM-MVC. Normalization using RMS of PFM-MVC showed the lowest values of SEM and MDC. The normalization of EMG data is considered a fundamental part of EMG investigations. These findings suggest that the normalization of PFM-EMG by either peak RMS of PFM-MVC or mean and peak RMS of abdominal contraction has excellent reliability and it can be applied in studies involving the evaluation of young women.

Impact of the EMG normalization method on muscle activation and the antagonist-agonist co-contraction index during active elbow extension: Practical implications for post-stroke subjects

Electromyographic (EMG) raw signals are sensitive to intrinsic and extrinsic factors. Consequently, EMG normalization is required to draw proper interpretations of standardized data. Specific recommendations are needed regarding a relevant EMG normalization method for participants who show atypical EMG patterns, such as post-stroke subjects. This study compared three EMG normalization methods (“isometric MVC”, “isokinetic MVC”, “isokinetic MVC kinematic-related”) on muscle activations and the antagonist-agonist co-contraction index. Fifteen post-stroke subjects and fifteen healthy controls performed active elbow extensions, followed by isometric and isokinetic maximum voluntary contractions (MVC). Muscle activations were obtained by normalizing EMG envelopes during active movement using a reference value determined for each EMG normalization method. The results showed no significant difference between the three EMG normalization methods in post-stroke subjects on muscle activation and the antagonist-agonist co-contraction index. We highlighted that the antagonist-agonist co-contraction index could underestimate the antagonist co-contraction in the presence of atypical EMG patterns. Based on its practicality and feasibility, we recommend the use of isometric MVC as a relevant procedure for EMG normalization in post-stroke subjects. We suggest combined analysis of the antagonist-agonist co-contraction index and agonist and antagonist activations to properly investigate antagonist co-contraction in the presence of atypical EMG patterns during movement.

Evaluating gluteus maximus maximal voluntary isometric contractions for EMG normalization in male rugby players.

[Purpose] The aim of this study was to determine the highest electromyography (EMG) amplitude of the gluteus maximus from closed and open kinetic gluteal maximal voluntary isometric contractions (MVICs). [Participants and Methods] Ten healthy male rugby players performed three MVIC techniques that included, in random order: single leg squat, prone hip extension and standing gluteal squeeze. EMG signals were recorded from the inferior and superior regions of gluteus maximus of the dominant leg, and were normalized to the prone hip extension. [Results] For statistical analysis the EMG of both gluteus maximus regions were pooled together. The standing gluteal squeeze revealed a significantly lower EMG compared to single leg squat and prone hip extension. However, there was no significant difference in gluteal EMG activity between single leg squat and prone hip extension. [Conclusion] There is no distinct advantage for either single leg squat or prone hip extension in eliciting maximum EMG activity. Future research should compare the present positions with other MVICs that are commonly prescribed or have been demonstrated to produce high EMG amplitudes.

The Lack of Electromyography Normalization May Limit the Conclusions in: Traditional vs. Suspended Push-up Muscle Activation in Athletes and Sedentary Women.

The Lack of Electromyography Normalization May Limit the Conclusions in: Traditional vs. Suspended Push-up Muscle Activation in Athletes and Sedentary Women.

Reflex activity of pelvic floor muscles during drop landings and mini-trampolining-exploratory study.

Complex functional movements such as jumping typically provoke stress urinary incontinence (SUI) in women. The aim of this study was to investigate pelvic floor muscle (PFM) activity in young, healthy women during jumps to explore their activity characteristics. Surface electromyography (EMG) from PFMs was measured in 16 healthy women with a tripolar vaginal probe during drop landings from heights of 15, 30 and 45cm (DL 15, 30, 45) as well as during mini-trampolining with a pace of 90 and 75 jumps per minute (MT 90, 75). Time of foot strike and body weight force (BWF) in % (= ground reaction force, normalised to body weight) was determined by force plates. Root mean square values of the EMG signals were analyzed from 30ms before to 150ms after foot strike. Peak activity during maximum voluntary contraction (MVC) was set as 100% for EMG normalization. The PFM onset threshold was determined as the mean of rest activity plus 2 standard deviations. Data were analysed with non-parametric statistical methods. EMG activity during all jumps was above the PFM onset threshold. Mean pre- and reflex activity increased significantly with jumping height (p < 0.05) as well as with increasing BWF. The PFM activation pattern of DL was with peak activity of 115-182 %MVC between 34 and 44ms after foot strike, which was different from MT with peak PFM activity of 85-115 %MVC reached at 133ms. Jumping and mini-trampolining provoked significant PFM activity in healthy volunteers. The next research step will be to examine the PFM activity of women suffering from SUI during jumps.