In this study, we aimed to determine if electromyography (EMG) normalization to maximal voluntary isometric contractions (MVIC) was influenced by subacromial pain in patients with subacromial impingement syndrome. Patients performed MVICs in unique testing positions for each shoulder muscle tested before and after subacromial injection of local anesthetic. In addition to collection of MVIC data, EMG data during an arm elevation task were recorded before and after injection. From a visual analog pain scale, patients had a 64% decrease in pain following the injection. Significant increases in MVICs were noted in 4 of the 7 shoulder muscles tested: anterior, middle and posterior deltoid, and lower trapezius. No significant differences were noticed for the upper trapezius, latissimus dorsi, or serratus anterior. MVIC condition (pre and post injection) had a significant influence on EMG normalization for the anterior deltoid and lower trapezius muscle. Results indicate that subacromial pain can influence shoulder muscle activity, especially for the deltoid muscles and lower trapezius. In addition, normalization to MVIC in the presence of pain can have unpredictable results. Caution should be taken when normalizing EMG data to MVIC in the presence of pain.
Lucas Ettinger, Jason Weiss, Matthew Shapiro and Andrew Karduna
Remco J. Baggen, Jaap H. van Dieën, Sabine M. Verschueren, Evelien Van Roie and Christophe Delecluse
placement, skin preparation, and impedance of the skin interface and tissue layer between electrodes and muscle. 1 , 3 To allow for comparisons of muscle activation between participants and within participants between different measurement sessions, EMG signals need to be normalized. 4 Normalization is
David R. Mullineaux, Clare E. Milner, Irene S. Davis and Joseph Hamill
The appropriateness of normalizing data, as one method to reduce the effects of a covariate on a dependent variable, should be evaluated. Using ratio, 0.67-nonlinear, and fitted normalizations, the aim of this study was to investigate the relationship between ground reaction force variables and body mass (BM). Ground reaction forces were recorded for 40 female subjects running at 3.7 ± 0.18 m·s–1 (mass = 58 ± 6 kg). The explained variance for mass to forces (peak-impact-vertical = 70%; propulsive-vertical = 27%; braking = 40%) was reduced to < 0.1% for mass to ratio normalized forces (i.e., forces/BM1) with statistically significantly different power exponents (p < 0.05). The smaller covariate effect of mass on loading rate variables of 2–16% was better removed through fitted normalization (e.g., vertical-instantaneous-loading-rate/BM0.69±0.93; ±95% CI) with nonlinear power exponents ranging from 0.51 to 1.13. Generally, these were similar to 0.67 as predicted through dimensionality theory, but, owing to the large confidence intervals, these power exponents were not statistically significantly different from absolute or ratio normalized data (p > 0.05). Further work is warranted to identify the appropriate method to normalize loading rates either to mass or to another covariate. Ratio normalization of forces to mass, as predicted through Newtonian mechanics, is recommended for comparing subjects of different masses.
Stephen M. Suydam, Kurt Manal and Thomas S. Buchanan
tool for analyzing muscle activation across muscles, tasks, subjects, and testing sessions requires EMG signals to be normalized to a reference value. 8 The need for normalization becomes even greater between days if electrodes are removed and replaced without guide markings to ensure precise
Ferdous Wahid, Rezaul Begg, Noel Lythgo, Chris J. Hass, Saman Halgamuge and David C. Ackland
Normalization of gait data is performed to reduce the effects of intersubject variations due to physical characteristics. This study reports a multiple regression normalization approach for spatiotemporal gait data that takes into account intersubject variations in self-selected walking speed and physical properties including age, height, body mass, and sex. Spatiotemporal gait data including stride length, cadence, stance time, double support time, and stride time were obtained from healthy subjects including 782 children, 71 adults, 29 elderly subjects, and 28 elderly Parkinson’s disease (PD) patients. Data were normalized using standard dimensionless equations, a detrending method, and a multiple regression approach. After normalization using dimensionless equations and the detrending method, weak to moderate correlations between walking speed, physical properties, and spatiotemporal gait features were observed (0.01 < |r| < 0.88), whereas normalization using the multiple regression method reduced these correlations to weak values (|r| < 0.29). Data normalization using dimensionless equations and detrending resulted in significant differences in stride length and double support time of PD patients; however the multiple regression approach revealed significant differences in these features as well as in cadence, stance time, and stride time. The proposed multiple regression normalization may be useful in machine learning, gait classification, and clinical evaluation of pathological gait patterns.
Nick Ball and Joanna Scurr
Electromyograms used to assess neuromuscular demand during high-velocity tasks require normalization to aid interpretation. This paper posits that, to date, methodological approaches to normalization have been ineffective and have limited the application of electromyography (EMG). There is minimal investigation seeking alternative normalization methods, which must be corrected to improve EMG application in sports. It is recognized that differing normalization methods will prevent cross-study comparisons. Users of EMG should aim to identify normalization methods that provide good reliability and a representative measure of muscle activation. The shortcomings of current normalization methods in high-velocity muscle actions assessment are evident. Advances in assessing alternate normalization methods have been done in cycling and sprinting. It is advised that when normalizing high-intensity muscle actions, isometric methods are used with caution and a dynamic alternative, where the muscle action is similar to that of the task is preferred. It is recognized that optimal normalization methods may be muscle and task dependent.
John W. Wannop, Jay T. Worobets and Darren J. Stefanyshyn
Authors who report ground reaction force (GRF), free moment (FM), and resultant joint moments usually normalize these variables by division normalization. Normalization parameters include body weight (BW), body weight x height (BWH), and body weight x leg length (BWL). The purpose of this study was to explore the appropriateness of division normalization, power curve normalization, and offset normalization on peak GRF, FM, and resultant joint moments. Kinematic and kinetic data were collected on 98 subjects who walked at 1.2 and 1.8 m/s and ran at 3.4 and 4.0 m/s. Linear curves were best fit to the data, and regression analyses performed to test the significance of the correlations. It was found that the relationship between peak force and BW, as well as joint moments and BW, BWH, and BWL, were not always linear. After division normalization, significant correlations were still found. Power curve and offset normalization, however, were effective at normalizing all variables; therefore, when attempting to normalize GRF and joint moments, perhaps nonlinear or offset methods should be implemented.
Tishya A. L. Wren and Jack R. Engsberg
The traditional method for normalizing quantitative strength data is to divide force or torque by body mass. We have previously shown that this method is not appropriate for able-bodied children and young adults and that normalization using allometric scaling is more effective. The purpose of the current study was to evaluate the effectiveness of applying existing normalization equations for lower extremity strength to children, adolescents, and young adults with cerebral palsy (CP) and, if appropriate, to develop CP-specific normalization equations using allometric scaling. We measured the maximum torque generated during hip abduction/adduction, knee extension/flexion, and ankle dorsiflexion/plantar flexion in 96 subjects with spastic diplegia CP ages 4–23 years. Traditional mass normalization (Torque/Mass1.0) and allometric scaling equations from children without disability (Torque/Mass1.6 for hip and knee; Torque/Mass1.4 for ankle) were not effective in eliminating the influence of body mass. Normalization using CP-specific allometric scaling equations was effective using both muscle-specific and common (Torque/Mass0.8 for ankle plantar flexors; Torque/Mass1.4 for all others) scaling relationships. For the first time, normalization equations have been presented with demonstrated effectiveness in adjusting strength measures for body size in a group of children, adolescents, and young adults with CP.
David R. Mullineaux, Hilary M. Clayton and Lauren M. Gnagey
This study assessed the effect of offset normalizations on variability in kinematic data. The tarsal angles for 12 elderly horses, with mild lameness of the tarsal joint, were measured at the trot pre and post 2 weeks administration of a dietary supplement intended to promote joint health (Corta-Flx, Nature's Own, Aiken, SC). For five strides, pre- and postsupplement, the tarsal angles measured on the flexor side (full exten. = 180°) were smoothed, normalized to 101 data points, and averaged. Four offset normalizations were applied: minus standing tarsal angle (Tarsal); minus impact angle (Impact); minus mean angle (Average); multiplicative scatter correction (MSC). For 11 angle variables across the stride there were no significant differences pre- and postsupplement, p > 0.05. Normalization had no effect on the timing of variables or magnitude of angles, but generally the variability in the angles was reduced. Least to greatest reduction occurred with the Tarsal, Impact, Average, then MSC normalizations. The Average and MSC techniques resulted in two and three variables, respectively, becoming significantly different. These differences were small, emphasizing that significant findings should be interpreted for meaningfulness. Normalizations based on the data gave the largest reductions in variability, but these may introduce biases into the data. Thus, normalization with respect to measurements external to data capture may be preferable, but their theoretical and statistical relationship to the kinematic variables should be confirmed. MSC altered the shape of the kinematic trace, which may be misleading. Offset normalizations should be used with care, but they can reduce variability in kinematic data to increase statistical power in biomechanical studies.
Martin Švehlík, Kryštof Slabý, Tomáš Trc̆ and Jir̆í Radvanský
The aim of the study is to investigate whether the net nondimensional oxygen utilization scheme is able to detect postoperative improvement in the energy cost of walking in children with cerebral palsy and to compare it with a body mass normalization scheme. We evaluated 10 children with spastic cerebral palsy before and 9 months after equinus deformity surgery. Participants walked at a given speed of 2 km/hr and 3 km/hr on a treadmill. Oxygen utilization was measured, and mass relative VO2 and net nondimensional VO2 were calculated. Coefficient of variation was used for the description of variability among subjects. Postoperatively, gait kinematics normalized and the mass relative VO2 and net nondimensional VO2 showed significant improvement. Net nondimensional VO2 is able to detect postoperative improvement with smaller variability among subjects than body mass related normalization in children with cerebral palsy.