Calibration of EMG to force for knee muscles is applicable with submaximal voluntary contractions.

PURPOSE: In this study, the influence of using submaximal isokinetic contractions about the knee compared to maximal voluntary contractions as input to obtain the calibration of an EMG-force model for knee muscles is investigated. METHODS: Isokinetic knee flexion and extension contractions were performed by healthy subjects at five different velocities and at three contraction levels (100%, 75% and 50% of MVC). Joint angle, angular velocity, joint moment and surface EMG of five knee muscles were recorded. Individual calibration values were calculated according to [C.A.M. Doorenbosch, J. Harlaar, A clinically applicable EMG-force model to quantify active stabilization of the knee after a lesion of the anterior cruciate ligament, Clinical Biomechanics 18 (2003) 142-149] for each contraction level. RESULTS: First, the output of the model, calibrated with the 100% MVC was compared to the actually exerted net knee moment at the dynamometer. Normalized root mean square errors were calculated [A.L. Hof, C.A.N. Pronk, J.A. van Best, Comparison between EMG to force processing and kinetic analysis for the calf muscle moment in walking and stepping, Journal of Biomechanics 20 (1987) 167-187] to compare the estimated moments with the actually exerted moments. Mean RMSD errors ranged from 0.06 to 0.21 for extension and from 0.12 to 0.29 for flexion at the 100% trials. Subsequently, the calibration results of the 50% and 75% MVC calibration procedures were used. A standard signal, representing a random EMG level was used as input in the EMG force model, to compare the three models. Paired samples t-tests between the 100% MVC and the 75% MVC and 50% MVC, respectively, showed no significant differences (p>0.05). CONCLUSION: The application of submaximal contractions of larger than 50% MVC is suitable to calibrate a simple EMG to force model for knee extension and flexion. This means that in clinical practice, the EMG to force model can be applied by patients who cannot exert maximal force.     

Towards reducing the impacts of unwanted movements on identification of motion intentions

Surface electromyogram (sEMG) has been extensively used as a control signal in prosthesis devices. However, it is still a great challenge to make multifunctional myoelectric prostheses clinically available due to a number of critical issues associated with existing EMG based control strategy. One such issue would be the effect of unwanted movements (UMs) that are inadvertently done by users on the performance of movement classification in EMG pattern recognition based algorithms. Since UMs are not considered in training a classifier, they would decay the performance of a trained classifier in identifying the target movements (TMs), which would cause some undesired actions in control of multifunctional prostheses. In this study, the impact of UMs was systemically investigated in both able-bodied subjects and transradial amputees. Our results showed that the UMs would be unevenly classified into all classes of the TMs. To reduce the impact of the UMs on the performance of a classifier, a new training strategy that would categorize all possible UMs into a new movement class was proposed and a metric called Reject Ratio that is a measure of how many UMs is rejected by a trained classifier was adopted. The results showed that the average Reject Ratio across all the participants was greater than 91%, meanwhile the average classification accuracy of TMs was above 99% when UMs occurred. This suggests that the proposed training strategy could greatly reduce the impact of UMs on the performance of the trained classifier in identifying the TMs and may enhance the robustness of myoelectric control in clinical applications.     

Feasibility of using combined EMG and kinematic signals for prosthesis control: A simulation study using a virtual reality environment

Transhumeral amputation has a significant effect on a person’s independence and quality of life. Myoelectric prostheses have the potential to restore upper limb function, however their use is currently limited due to lack of intuitive and natural control of multiple degrees of freedom. The goal of this study was to evaluate a novel transhumeral prosthesis controller that uses a combination of kinematic and electromyographic (EMG) signals recorded from the person’s proximal humerus. Specifically, we trained a time-delayed artificial neural network to predict elbow flexion/extension and forearm pronation/supination from six proximal EMG signals, and humeral angular velocity and linear acceleration. We evaluated this scheme with ten able-bodied subjects offline, as well as in a target-reaching task presented in an immersive virtual reality environment. The offline training had a target of 4° for flexion/extension and 8° for pronation/supination, which it easily exceeded (2.7° and 5.5° respectively). During online testing, all subjects completed the target-reaching task with path efficiency of 78% and minimal overshoot (1.5%). Thus, combining kinematic and muscle activity signals from the proximal humerus can provide adequate prosthesis control, and testing in a virtual reality environment can provide meaningful data on controller performance.     

The minimum number of contractions required to examine the EMG amplitude versus isometric force relationship for the vastus lateralis and vastus medialis

Studies have demonstrated that the electromyographic (EMG) amplitude versus submaximal isometric force relationship is relatively linear. The purpose of this investigation was to determine the minimum number of contractions required to study this relationship. Eighteen men (mean age = 23 years) performed isometric contractions of the leg extensors at 10–90% of the maximum voluntary contraction (MVC) in 10% increments while surface EMG signals were detected from the vastus lateralis and vastus medialis. Linear regression was used to determine the coefficient of determination, slope coefficient, and y-intercept for each muscle and force combination with successively higher levels included in the model (i.e., 10–30%, … 10–90% MVC). For the slope coefficients, there was a main effect for force combination (P < .001). The pairwise comparisons showed there was no difference from 10–60% through 10–90% MVC. For the y-intercepts, there were main effects for both muscle (vastus lateralis [4.3 μV RMS] > vastus medialis [−3.7 μV RMS]; P = .034) and force combination (P < .001), with similar values shown from 10–50% through 10–90% MVC. The linearity of the absolute EMG amplitude versus isometric force relationship for the vastus lateralis and vastus medialis suggests that investigators may exclude high force contractions from their testing protocol.     

A comparison of a maximum exertion method and a model-based, sub-maximum exertion method for normalizing trunk EMG

The problem with normalizing EMG data from patients with painful symptoms (e.g., low back pain) is that such patients may be unwilling or unable to perform maximum exertions. Furthermore, the normalization to a reference signal, obtained from a maximal or sub-maximal task, tends to mask differences that might exist as a result of pathology. Therefore, we presented a novel method (GAIN method) for normalizing trunk EMG data that overcomes both problems. The GAIN method does not require maximal exertions (MVC) and tends to preserve distinct features in the muscle recruitment patterns for various tasks. Ten healthy subjects performed various isometric trunk exertions, while EMG data from 10 muscles were recorded and later normalized using the GAIN and MVC methods. The MVC method resulted in smaller variation between subjects when tasks were executed at the three relative force levels (10%, 20%, and 30% MVC), while the GAIN method resulted in smaller variation between subjects when the tasks were executed at the three absolute force levels (50 N, 100 N, and 145 N). This outcome implies that the MVC method provides a relative measure of muscle effort, while the GAIN-normalized data gives an estimate of the absolute muscle force. Therefore, the GAIN-normalized data tends to preserve the differences between subjects in the way they recruit their muscles to execute various tasks, while the MVC-normalized data will tend to suppress such differences. The appropriate choice of the EMG normalization method will depend on the specific question that an experimenter is attempting to answer.     

Non-uniform electromyographic activity during fatigue and recovery of the vastus medialis and lateralis muscles

The aim of the study was to investigate EMG signal features during fatigue and recovery at three locations of the vastus medialis and lateralis muscles. Surface EMG signals were detected from 10 healthy male subjects with six 8-electrode arrays located at 10%, 20%, and 30% of the distance from the medial (for vastus medialis) and lateral (vastus lateralis) border of the patella to the anterior superior spine of the pelvic. Subjects performed contractions at 40% and 80% of the maximal force (MVC) until failure to maintain the target force, followed by 20 2-s contractions at the same force levels every minute for 20 min (recovery). Average rectified value, mean power spectral frequency, and muscle fiber conduction velocity were estimated from the EMG signals in 10 epochs from the beginning of the contraction to task failure (time to task failure, mean ± SD, 70.7 ± 25.8 s for 40% MVC; 27.4 ± 16.8 s for 80% MVC) and from the 20 2 s time intervals during recovery. During the fatiguing contraction, the trend over time of EMG average rectified value depended on location for both muscles (P < 0.05). After 20-min recovery, mean frequency and conduction velocity of both muscles were larger than in the beginning of the fatigue task (P < 0.05) (supernormal values). Moreover, the trend over time of mean frequency during recovery was affected by location and conduction velocity values depended on location for both muscles (P < 0.05). The results indicate spatial dependency of EMG variables during fatigue and recovery and thus the necessity of EMG spatial sampling for global muscle assessment.     

On the usability of intramuscular EMG for prosthetic control: A Fitts’ Law approach

Previous studies on intramuscular EMG based control used offline data analysis. The current study investigates the usability of intramuscular EMG in two degree-of-freedom using a Fitts’ Law approach by combining classification and proportional control to perform a task, with real time feedback of user performance. Nine able-bodied subjects participated in the study. Intramuscular and surface EMG signals were recorded concurrently from the right forearm. Five performance metrics (Throughput, Path efficiency, Average Speed, Overshoot and Completion Rate) were used for quantification of usability. Intramuscular EMG based control performed significantly better than surface EMG for Path Efficiency (80.5 ± 2.4% vs. 71.5 ± 3.8%, P = 0.004) and Overshoot (22.0 ± 3.0% vs. 45.1 ± 6.6%, P = 0.01). No difference was found between Throughput and Completion Rate. However the Average Speed was significantly higher for surface (51.8 ± 5.5%) than for intramuscular EMG (35.7 ± 2.7%). The results obtained in this study imply that intramuscular EMG has great potential as control source for advanced myoelectric prosthetic devices.     

Effect of innervation zones in estimating biceps brachii force-EMG relationship during isometric contraction

Measuring muscle forces in vivo is invasive and consequently indirect methods e.g., electromyography (EMG) are used in estimating muscular force production. The aim of the present paper was to examine what kind of effect the disruption of the physiological signal caused by the innervation zone has in predicting the force/torque output from surface EMG. Twelve men (age 26 (SD ±3) years; height 179 (±6) cm; body mass 73 (±6) kg) volunteered as subjects. They were asked to perform maximal voluntary isometric contraction (MVC) in elbow flexion, and submaximal contractions at 10%, 20%, 30%, 40%, 50% and 75% of the recorded MVC. EMG was measured from biceps brachii muscle with an electrode grid of 5 columns × 13 rows. Force-EMG relationships were determined from individual channels and as the global mean value. The relationship was deemed inconsistent if EMG value did not increase in successive force levels. Root mean squared errors were calculated for 3rd order polynomial fits. All subjects had at least one (4-52) inconsistent channel. Two subjects had inconsistent relationship calculated from the global mean. The mean root mean squared error calculated using leave one out method for the fits of the individual channels (0.33 ± 0.17) was higher (P < 0.001) than the error for the global mean fit (0.16 ± 0.08). It seems that the disruption of the physiological signal caused by the innervation zone affects the consistency of the force-EMG relationship on single bipolar channel level. Multichannel EMG recordings used for predicting force overcame this disruption.     

Comparison between muscle activation measured by electromyography and muscle thickness measured using ultrasonography for effective muscle assessment

In this study, we aimed to compare the intrarater reliability and validity of muscle thickness measured using ultrasonography (US) and muscle activity via electromyography (EMG) during manual muscle testing (MMT) of the external oblique (EO) and lumbar multifidus (MF) muscles. The study subjects were 30 healthy individuals who underwent MMT at different grades. EMG was used to measure the muscle activity in terms of ratio to maximum voluntary contraction (MVC) and root mean square (RMS) metrics. US was used to measure the raw muscle thickness, the ratio of muscle thickness at MVC, and the ratio of muscle thickness at rest. One examiner performed measurements on each subject in 3 trials. The intrarater reliabilities of the % MVC RMS and raw RMS metrics for EMG and the % MVC thickness metrics for US were excellent (ICC = 0.81–0.98). There was a significant difference between all the grades measured using the % MVC thickness metric (p < 0.01). Further, this % MVC thickness metric of US showed a significantly higher correlation with the EMG measurement methods than with the others (r = 0.51–0.61). Our findings suggest that the % MVC thickness determined by US was the most sensitive of all methods for assessing the MMT grade.     

History dependence of the electromyogram: Implications for isometric steady-state EMG parameters following a lengthening or shortening contraction

Residual force enhancement (RFE) and force depression (FD) refer to an increased or decreased force following an active lengthening or shortening contraction, respectively, relative to the isometric force produced at the same activation level and muscle length. Our intent was to determine if EMG characteristics differed in the RFE or FD states compared with a purely isometric reference contraction for maximal and submaximal voluntary activation of the adductor pollicis muscle. Quantifying these alterations to EMG in history-dependent states allows for more accurate modeling approaches for movement control in the future. For maximal voluntary contractions (MVC), RFE was 6–15% (P < 0.001) and FD was 12–19% (P < 0.001). The median frequency of the EMG was not different between RFE, FD and isometric reference contractions for the 100% and 40% MVC intensities (P > 0.05). However, root mean square EMG (EMG_RMS) amplitude for the submaximal contractions was higher in the FD and lower in the RFE state, respectively (P < 0.05). For maximal contractions, EMG_RMS was lower for the FD state but was the same for the RFE state compared to the isometric reference contractions (P > 0.05). Neuromuscular efficiency (NME; force/EMG) was lower in the force depressed state and higher in the force enhanced state (P < 0.05) compared to the isometric reference contractions. EMG spectral properties were not altered between the force-enhanced and depressed states relative to the isometric reference contractions, while EMG amplitude measures were.     

Predicting maximum eccentric strength from surface EMG measurements

The origin of the well-documented discrepancy between maximum voluntary and in vitro tetanic eccentric strength has yet to be fully understood. This study aimed to determine whether surface EMG measurements can be used to reproduce the in vitro tetanic force–velocity relationship from maximum voluntary contractions. Five subjects performed maximal knee extensions over a range of eccentric and concentric velocities on an isovelocity dynamometer whilst EMG from the quadriceps were recorded. Maximum voluntary (MVC) force–length–velocity data were estimated from the dynamometer measurements and a muscle model. Normalised amplitude–length–velocity data were obtained from the EMG signals. Dividing the MVC forces by the normalised amplitudes generated EMG corrected force–length–velocity data. The goodness of fit of the in vitro tetanic force–velocity function to the MVC and EMG corrected forces was assessed. Based on a number of comparative scores the in vitro tetanic force–velocity function provided a significantly better fit to the EMG corrected forces compared to the MVC forces (p?0.05), Furthermore, the EMG corrected forces generated realistic in vitro tetanic force–velocity profiles. A 58±19% increase in maximum eccentric strength is theoretically achievable through eliminating neural factors. In conclusion, EMG amplitude can be used to estimate in vitro tetanic forces from maximal in vivo force measurements, supporting neural factors as the major contributor to the difference between in vitro and in vivo maximal force.     

Comparing surface and indwelling electromyographic signals of the supraspinatus and infraspinatus muscles during submaximal axial humeral rotation

This study quantified the relationship between EMG signals recorded by surface and indwelling electrodes for the infraspinatus and supraspinatus during submaximal axial humeral rotation. Muscular activity was measured on 20 participants during 82 submaximal isometric internal or external axial humeral rotations in a range of postures and intensities. Equations to predict indwelling magnitudes from surface data were generated and the effects of humeral angle and intensity on this relationship were also evaluated.Supraspinatus surface data explained 72–76% of the variance in the indwelling data. Surface data overestimated indwelling data by up to 30% of maximal voluntary contraction (MVC). Infraspinatus surface data explained 62–64% of the variance in the indwelling data, but overestimated by 72% and 400% MVC in external and internal axial humeral rotation trials, respectively. Humeral abduction angle and exertion intensity both altered the relationship between electrode types modestly (p < 0.01) for most muscles and exertions. Better variance explanation was achieved for these submaximal exertions than previously reported values for maximal exertions.These results help inform electrode type selection for the recording of supraspinatus and infraspinatus EMG. Caution is recommended when interpreting surface recordings as indicators of indwelling recordings for exertions where the muscle studied is not a primary mover.     

Mean frequency and signal amplitude of the surface EMG of the quadriceps muscles increase with increasing torque--a study using the continuous wavelet transform.

The continuous wavelet transform (CWT), a time-frequency method, was used when calculating mean frequency of the power spectrum (MNF) and signal amplitude (RMS) of the surface EMG to investigate their relationships to force during a gradually increasing knee extension (ramp). Based upon the CWT, MNF was redefined to include time dependence on the EMG signal frequency contents, the short-time MNF (STMNF). Surface EMG was recorded from vastus lateralis, rectus femoris and vastus medialis in 21 clinically healthy subjects during a brief, gradually increasing contraction up to 100% of a maximum voluntary contraction (MVC), with a duration of approximately 10 s. The relationships between the EMG variables and force using linear regression were determined for each subject. For vastus lateralis, we also investigated if certain aspects of the muscle morphology (i.e., proportions and areas of different fibre types) influenced the EMG-force relationship.For the majority of subjects (17-18 out of 21 subjects) there were significant positive correlations between STMNF and force in the three muscles. No sex differences were found in intercepts or regression coefficients of STMNF. The muscle morphology had a significant influence on the STMNF-force intercept and the regression coefficient. Positive and highly significant linear correlations between RMS and force were found for all subjects and all three muscles.In conclusion, time frequency methods can be applied when investigating EMG during brief contractions associated with non-stationarity. In a great majority of the subjects, and in the three muscles, significant linear force dependencies were found for STMNF. Thus, when evaluating muscle fatigue, e.g., in ergonomic situations, it is important to consider the force level as one factor that can influence the results. Morphological variables (fibre proportions and fibre areas) influenced the STMNF-force relationship in vastus lateralis.     

Central and peripheral contributions to muscle fatigue in humans during sustained maximal effort

The purpose of this study was to estimate the relative contributions of central and peripheral factors to the development of human muscle fatigue. Nine healthy subjects [five male, four female; age = 30 (2) years, mean (SE)] sustained a maximum voluntary isometric contraction (MVC) of the ankle dorsiflexor muscles for 4 min. Fatigue was quantitated as the fall in MVC. Three measures of central activation and one measure of peripheral activation (compound muscle action potential, CMAP) were made using electromyography (EMG) and electrical stimulation. Measures of intramuscular metabolism were made using magnetic resonance spectroscopy. After exercise, MVC and electrically stimulated tetanic contraction (50 Hz, 500 ms) forces were 22.2 (3.7)% and 37.3 (7.1)% of pre-exercise values, respectively. The measures of central activation suggested some central fatigue during exercise: (1) the central activation ratio [MVC/(MVC + superimposed tetanic force)] fell from 0.94 (0.03) to 0.78 (0.09), (2) the MVC/tetanic force ratio fell from 2.3 (0.7) to 1.3 (0.7), and (3) the integral of the EMG (iEMG) signal decreased to 72.6 (9.1)% of the initial value, while the CMAP amplitude was unchanged. Intramuscular pH was associated by regression with the decline in MVC force (and therefore fatigue) and iEMG. The results indicate that central factors, which were not associated with altered peripheral excitability, contributed approximately 20% to the muscle fatigue developed, with the remainder being attributable to intramuscular (i.e., metabolic) factors. The association between pH and iEMG is consistent with proton concentration as a feedback mechanism for central motor drive during maximal effort.     

Estimation of muscle fiber conduction velocity from two-dimensional surface EMG recordings in dynamic tasks

The aims of this study are (1) to demonstrate that multi-channel surface electromyographic (EMG) signals can be detected with negligible artifacts during fast dynamic movements with an adhesive two-dimensional (2D) grid of 64 electrodes and (2) to propose a new method for the estimation of muscle fiber conduction velocity from short epochs of 2D EMG recordings during dynamic tasks. Surface EMG signals were collected from the biceps brachii muscle of four subjects with a grid of 13 × 5 electrodes during horizontal elbow flexion/extension movements (range 120–170°) at the maximum speed, repeated cyclically for 2 min. Action potentials propagating between the innervation zone and tendon regions could be detected during the dynamic task. A maximum likelihood method for conduction velocity estimation from the 2D grid using short time intervals was developed and applied to the experimental signals. The accuracy of conduction velocity estimation, assessed from the standard deviation of the residual of the regression line with respect to time, decreased from (range) 0.20–0.33 m/s using one column to 0.02–0.15 m/s when combining five columns of the electrode grid. This novel method for estimation of muscle fiber conduction velocity from 2D EMG recordings provides an estimate which is global in space and local in time, thus representative of the entire muscle yet able to track fast changes over the execution of a task, as is required for assessing muscle properties during fast movements.     

The contribution of the supraspinatus muscle at sub-maximal contractions

During maximum effort, the supraspinatus muscle contributes approximately 50% of the torque need to elevate the arm, but this has not been examined at sub-maximal levels. The purpose of this study was to determine the contribution of the supraspinatus muscle to shoulder elevation at sub-maximal levels. Seven healthy subjects (four males, three females) performed isometric ramp contractions at the shoulder. Middle deltoid electromyography (EMG) and force applied at the wrist were collected before and after a suprascapular nerve block. For the same level of deltoid EMG, less external force will be measured after the nerve block as the supraspinatus muscle no longer contributes. The difference between the EMG/force curve was the contribution of the supraspinatus muscle. The supraspinatus contributed 40%, 95% CI [32%–48%], to shoulder elevation. The effect of angle (p = .67) and % maximal voluntary contraction (p = .13) on supraspinatus contribution were not significant. The maximum is slightly less than reported in a previous suprascapular nerve block study using maximal contractions. The results from this study can be used to assess supraspinatus contribution in rotator cuff tears, after rehabilitation interventions, and as a restraint in computation modelling.     

The influence of task and angle on torque production and muscle activity at the elbow

This study investigated the effect of changing internal mechanical variables and task demands on muscle activity and torque production during high effort isometric contractions of the elbow flexors. The effect of adding a 50% maximal voluntary contraction (MVC) of supination to an MVC of elbow flexion was studied over a range of angles from 30° to 110° of elbow flexion. Surface EMGs were recorded from the biceps brachii (BIC), brachioradialis (BRAD) and triceps brachii (TRI) of 10 healthy subjects. BIC was the only muscle to show a consistent trend of increasing root mean square (rms) EMG with increasing elbow flexion angle. BIC activity also remained constant or increased with the addition of the supination task at all angles. In contrast, BRAD showed decreased activity when supination was added at several angular positions. Maximal flexion torque was reduced when the second task of submaximal supination was added. This torque reduction was statistically significant at all angles except 70° and appeared related to the decreased contribution from BRAD. In a small subset of subjects, however, BRAD activity did not decrease when the second degrees of freedom (df) task was added. These subjects exhibited higher flexion torques averaged over task than the majority, at all angles except 30°. These data support the view that internal mechanical considerations influence the manner in which the central nervous system (CNS) distributes activity to muscular synergists in response to altered task demands. Further, subject-specific patterns exist which must be recognized if these findings are to be incorporated in training or rehabilitation programmes.     

Muscle pain induces task-dependent changes in cervical agonist/antagonist activity.

This study examined the effect of experimental neck muscle pain on the EMG-force relationship of cervical agonist and antagonist muscles. Surface EMG signals were detected from the sternomastoid, splenius capitis, and upper trapezius muscles bilaterally from 14 healthy subjects during cervical flexion and extension contractions of linearly increasing force from 0 to 60% of the maximum voluntary contraction (MVC). Measurements were performed before and after injection of 0.5 ml hypertonic and isotonic saline into either the sternomastoid or splenius capitis in two experimental sessions. EMG average rectified value (ARV) of the sternomastoid, splenius capitis, and upper trapezius muscles and the muscle fiber conduction velocity (CV) of the sternomastoid muscle were estimated at 5% MVC force increments. During cervical flexion with injection of hypertonic saline in sternomastoid, ARV of sternomastoid was lower on the side of pain in the force range 25-60% MVC (P < 0.05) and was associated with a bilateral reduction of splenius capitis and upper trapezius ARV (P < 0.01). During cervical extension, injection of hypertonic saline in splenius capitis resulted in lower estimates of splenius capitis ARV on the painful side from 45 to 60% MVC (P < 0.05), which was associated with a bilateral increase in upper trapezius ARV estimates from 50 to 60% MVC (P < 0.001). However, no significant change was identified for estimates of sternomastoid ARV. Experimentally induced neck muscle pain resulted in task-dependent changes in cervical agonist/antagonist activity without modifications in muscle fiber CV.     

The influence of the type of contraction on the masseter muscle EMG power spectrum

Different behaviours of the EMG power spectrum across increasing force levels have been reported for the masseter muscle. A factor that could explain these different behaviours may be the type of contraction used, as was recently shown for certain upper limb muscles⁵. The purpose of this study was to compare, between two types of isometric contractions, the behaviour of EMG power spectrum statistics (median frequency (MF) and mean power frequency (MPF)) obtained across increasing force levels. Ten women exerted, while biting in the intercuspal position, three 5 s ramp contractions that increased linearly from 0 to 100% of the maximal voluntary contraction (MVC). They also completed three step contractions (constant EMG amplitude) at each of the following levels: 20, 40, 60 and 80% MVC. EMG signals from the masseter muscle were recorded with miniature surface electrodes. The RMS, as well as the MPF and MF of the power spectrum were calculated at 20, 40, 60 and 80% MVC for each type of contraction. As expected, the RMS values showed similar increases with increasing levels of effort for both types of contractions. Different behaviours for both MPF (contraction^*force interaction, ANOVA, P<0.05) and MF (contraction^*force interaction, ANOVA, P>0.05) across increasing levels of effort were found between the two types of contraction. The use of step contractions gave rise to a decrease of both MPF and MF with increasing force, while the use of ramp contractions gave rise to an increase in both statistics up to at least 40% MVC followed by a decrease at higher force levels. These findings suggest that the type of contraction used does influence the behaviour of the spectral statistics across increasing force levels and that this could explain the differences obtained in previous studies for the masseter muscle.