Effect of motor-unit firing time statistics on e.m.g. spectra

Boys-men mean-power-frequency differences in progressive exercise to exhaustion, confounded by variability and adiposity

BACKGROUND

Only scant research has compared children's mean power frequency (MPF) to adults', with a clear overview still lacking. A significant obstacle has been MPF's high variability, which this study aimed to overcome by elucidating the MPF characteristics distinguishing boys from men in progressive exhaustive exercise.

METHODS

Electromyographic (EMG) data of 20 men (23.5 ± 2.5yrs) and 17 boys (10.2 ± 1.0 yrs), who performed progressively exhausting, intermittent isometric knee extensions, were subjected to secondary MPF analysis. Participants' vastus lateralis MPF data series were transformed to third-order polynomial regressions and expressed as percentages of the peak polynomial MPF values (%MPFpeak). The resulting curves were compared at 5-% time-to-exhaustion (TTE) intervals, using repeated-measures ANOVA. Raw MPFpeak values were adiposity corrected to 0% fat and used to convert the %MPFpeak data back to absolute MPF values (Hz) for estimating muscle-level MPF.

RESULTS

No overall interaction or group effects could be shown between the %MPFpeak plots, but pairwise comparisons revealed significantly higher men's values at 50-70%TTE and lower at 100%TTE, i.e. boys' shallower MPF rise and decline. The adiposity-corrected boys' and men's composite MPF values peaked at 125.7 ± 2.5 and 166.0 ± 2.4 Hz, respectively (110.7 ± 1.7 and 122.5 ± 2.1 Hz, uncorrected), with a significant group effect (p < 0.05) and pairwise differences at all %TTE points.

CONCLUSIONS

The boys were lower than the men in both the observed and, more so, in the adiposity-corrected MPF values that presumably estimate muscle-level MPF. The boys' shallower MPF rise and decline conform to children's claimed type-II motor-unit activation and/or compositional deficits and their related known advantage in muscular endurance.

Estimation of Motor Unit Global Firing Rate by Maximum Power Amplitude

Motor unit (MU) global firing rate is widely applied in physiological and clinical investigation. Currently it still remains difficult to measure the MU global firing rate from sEMG. In this study, we propose a new feature of maximum power amplitude (MPA) from sEMG power spectrum. Based on an analysis of mathematical model and simulated signals, MPA was demonstrated to be highly correlated with the MU global firing rate. The performance of MPA was comparable with features based on sEMG amplitude in the time domain. Moreover, the simulation results showed that the square of MPA changed accordingly with the output force, indicating potential application estimating force using MPA².

EMG-Torque Relation in Chronic Stroke: A Novel EMG Complexity Representation With a Linear Electrode Array

This study examines the electromyogram (EMG)-torque relation for chronic stroke survivors using a novel EMG complexity representation. Ten stroke subjects performed a series of submaximal isometric elbow flexion tasks using their affected and contralateral arms, respectively, while a 20-channel linear electrode array was used to record surface EMG from the biceps brachii muscles. The sample entropy (SampEn) of surface EMG signals was calculated with both global and local tolerance schemes. A regression analysis was performed between SampEn of each channel's surface EMG and elbow flexion torque. It was found that a linear regression can be used to well describe the relation between surface EMG SampEn and the torque. Each channel's root mean square (RMS) amplitude of surface EMG signal in the different torque level was computed to determine the channel with the highest EMG amplitude. The slope of the regression (observed from the channel with the highest EMG amplitude) was smaller on the impaired side than on the nonimpaired side in 8 of the 10 subjects, regardless of the tolerance scheme (global or local) and the range of torques (full or matched range) used for comparison. The surface EMG signals from the channels above the estimated muscle innervation zones demonstrated significantly lower levels of complexity compared with other channels between innervation zones and muscle tendons. The study provides a novel point of view of the EMG-torque relation in the complexity domain, and reveals its alterations post stroke, which are associated with complex neural and muscular changes post stroke. The slope difference between channels with regard to innervation zones also confirms the relevance of electrode position in surface EMG analysis.

Task-Dependent Intermuscular Motor Unit Synchronization between Medial and Lateral Vastii Muscles during Dynamic and Isometric Squats

PURPOSE

Motor unit activity is coordinated between many synergistic muscle pairs but the functional role of this coordination for the motor output is unclear. The purpose of this study was to investigate the short-term modality of coordinated motor unit activity-the synchronized discharge of individual motor units across muscles within time intervals of 5ms-for the Vastus Medialis (VM) and Lateralis (VL). Furthermore, we studied the task-dependency of intermuscular motor unit synchronization between VM and VL during static and dynamic squatting tasks to provide insight into its functional role.

METHODS

Sixteen healthy male and female participants completed four tasks: Bipedal squats, single-leg squats, an isometric squat, and single-leg balance. Monopolar surface electromyography (EMG) was used to record motor unit activity of VM and VL. For each task, intermuscular motor unit synchronization was determined using a coherence analysis between the raw EMG signals of VM and VL and compared to a reference coherence calculated from two desynchronized EMG signals. The time shift between VM and VL EMG signals was estimated according to the slope of the coherence phase angle spectrum.

RESULTS

For all tasks, except for singe-leg balance, coherence between 15-80Hz significantly exceeded the reference. The corresponding time shift between VM and VL was estimated as 4ms. Coherence between 30-60Hz was highest for the bipedal squat, followed by the single-leg squat and the isometric squat.

CONCLUSION

There is substantial short-term motor unit synchronization between VM and VL. Intermuscular motor unit synchronization is enhanced for contractions during dynamic activities, possibly to facilitate a more accurate control of the joint torque, and reduced during single-leg tasks that require balance control and thus, a more independent muscle function. It is proposed that the central nervous system scales the degree of intermuscular motor unit synchronization according to the requirements of the movement task at hand.

Local muscle endurance is associated with fatigue-based changes in electromyographic spectral properties, but not with conduction velocity

The purpose of this study was to examine the associations amongst muscle fiber action potential conduction velocity (CV), spectral characteristics of the surface electromyographic (EMG) signal, and endurance time during a sustained submaximal isometric muscle action. Eleven men (mean±SD age=23±4yrs) performed a sustained, submaximal isometric muscle action of the dominant forearm flexors at 60% of the maximum voluntary contraction (MVC) until the designated force level could no longer be maintained. Sixteen separate bipolar surface EMG signals were detected from the biceps brachii with a linear electrode array during this contraction. Two channels from this array were used to measure CV, and one of these two channels was used for further EMG signal processing. The channels that provided the highest signal quality were used for the CV measurements and further data analysis. A wavelet analysis was then used to analyze the bipolar EMG signal, and the resulting wavelet spectrum was decomposed with a nonparametric spectral decomposition procedure. The results showed that the time to exhaustion during the sustained contraction was not correlated with the rate of decrease in CV, but it was highly correlated with both the decrease in high-frequency spectral power (r=0.947) and the increase in low-frequency spectral power (r=0.960). These findings are particularly interesting, considering that the decrease in traditional EMG spectral variables (e.g., mean frequency or median frequency) with fatigue is generally attributed to reductions in CV. While this may indeed be true, the present results suggested that other factors (i.e., other than CV) that can affect the shape of the EMG frequency spectrum during fatigue are more important in determining the endurance capabilities of the muscle than is CV.

Monopolar electromyographic signals recorded by a current amplifier in air and under water without insulation

It was recently proposed that one could use signal current instead of voltage to collect surface electromyography (EMG). With EMG-current, the electrodes remain at the ground potential, thereby eliminating lateral currents. The purpose of this study was to determine whether EMG-currents can be recorded in Tap and Salt water, as well as in air, without electrically shielding the electrodes. It was hypothesized that signals would display consistent information between experimental conditions regarding muscle responses to changes in contraction effort. EMG-currents were recorded from the flexor digitorum muscles as participant's squeezed a pre-inflated blood pressure cuff bladder in each experimental condition at standardized efforts. EMG-current measurements performed underwater showed no loss of signal amplitude when compared to measurements made in air, although some differences in amplitude and spectral components were observed between conditions. However, signal amplitudes and frequencies displayed consistent behavior across contraction effort levels, irrespective of the experimental condition. This new method demonstrates that information regarding muscle activity is comparable between wet and dry conditions when using EMG-current. Considering the difficulties imposed by the need to waterproof traditional bipolar EMG electrodes when underwater, this new methodology is tremendously promising for assessments of muscular function in aquatic environments.

Comparison of the power spectral changes of the voluntary surface electromyogram and M wave during intermittent maximal voluntary contractions

INTRODUCTION

To compare the power spectral changes of the voluntary surface electromyogram (sEMG) and of the compound action potential (M wave) in the vastus medialis and vastus lateralis muscles during fatiguing contractions.

METHODS

Interference sEMG and force were recorded during 48 intermittent 3-s isometric maximal voluntary contractions (MVC) from 13 young, healthy subjects. M waves and twitches were evoked using supramaximal femoral nerve stimulation between the successive MVCs. Mean frequency (F mean), and median frequency were calculated from the sEMG and M waves. Muscle fiber conduction velocity (MFCV) was computed by cross-correlation.

RESULTS

The power spectral shift to lower frequencies was significantly greater for the voluntary sEMG than for the M waves (P < 0.05). Over the fatiguing protocol, the overall average decrease in MFCV (~25%) was comparable to that of sEMG F mean (~22%), but significantly greater than that of M-wave F mean (~9%) (P < 0.001). The mean decline in MFCV was highly correlated with the mean decreases in both sEMG and M-wave F mean.

CONCLUSIONS

The present findings indicated that, as fatigue progressed, central mechanisms could enhance the relative weight of the low-frequency components of the voluntary sEMG power spectrum, and/or the end-of-fiber (non-propagating) components could reduce the sensitivity of the M-wave spectrum to changes in conduction velocity.

The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges

Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.

Multi-scale surface electromyography modeling to identify changes in neuromuscular activation with myofascial pain

To solve the limitations in using the conventional parametric measures to define myofascial pain, a 3-D multi-scale wavelet energy variation graph is proposed as a way to inspect the pattern of surface electromyography (SEMG) variation between the dominant and nondominant sides at different frequency scales during a muscle contraction cycle and the associated changes with the upper-back myofascial pain. The model was developed based on the property of the wavelet energy of the SEMG signal revealing the degree of correspondence between the shape of the motor unit action potential and the wavelet waveform at a certain scale in terms of the frequency band. The characteristic pattern of the graph for each group (30 normal and 26 patient subjects) was first derived and revealed the dominant-hand effect and the changes with myofascial pain. Through comparison of individual graphs across subjects, we found that the graph pattern reveals a sensitivity of 53.85% at a specificity of 83.33% in the identification of myofascial pain. The changes in these patterns provide insight into the transformation between different fiber recruitment, which cannot be explored using conventional SEMG features. Therefore, this multi-scale analysis model could provide a reliable SEMG features to identify myofascial pain.

Thinking about muscles: the neuromuscular effects of attentional focus on accuracy and fatigue

Although the effects of attention on movement execution are well documented behaviorally, much less research has been done on the neurophysiological changes that underlie attentional focus effects. This study presents two experiments exploring effects of attention during an isometric plantar-flexion task using surface electromyography (sEMG). Participants' attention was directed either externally (towards the force plate they were pushing against) or internally (towards their own leg, specifically the agonist muscle). Experiment 1 tested the effects of attention on accuracy and efficiency of force produced at three target forces (30, 60, and 100% of the maximum voluntary contraction; MVC). An internal focus of attention reduced the accuracy of force being produced and increased cocontraction of the antagonist muscle. Error on a given trial was positively correlated with the magnitude of cocontraction on that trial. Experiment 2 tested the effects of attention on muscular fatigue at 30, 60 and 100%MVC. An internal focus of attention led to less efficient intermuscular coordination, especially early in the contraction. These results suggest that an internal focus of attention disrupts efficient motor control in force production resulting in increased cocontraction, which potentially explains other neuromechanical findings (e.g. reduced functional variability with an internal focus).

Motor unit recruitment strategies and muscle properties determine the influence of synaptic noise on force steadiness

Motoneurons receive synaptic inputs from tens of thousands of connections that cause membrane potential to fluctuate continuously (synaptic noise), which introduces variability in discharge times of action potentials. We hypothesized that the influence of synaptic noise on force steadiness during voluntary contractions is limited to low muscle forces. The hypothesis was examined with an analytical description of transduction of motor unit spike trains into muscle force, a computational model of motor unit recruitment and rate coding, and experimental analysis of interspike interval variability during steady contractions with the abductor digiti minimi muscle. Simulations varied contraction force, level of synaptic noise, size of motor unit population, recruitment range, twitch contraction times, and level of motor unit short-term synchronization. Consistent with the analytical derivations, simulations and experimental data showed that force variability at target forces above a threshold was primarily due to low-frequency oscillations in neural drive, whereas the influence of synaptic noise was almost completely attenuated by two low-pass filters, one related to convolution of motoneuron spike trains with motor unit twitches (temporal summation) and the other attributable to summation of single motor unit forces (spatial summation). The threshold force above which synaptic noise ceased to influence force steadiness depended on recruitment range, size of motor unit population, and muscle contractile properties. This threshold was low (<10% of maximal force) for typical values of these parameters. Results indicate that motor unit recruitment and muscle properties of a typical muscle are tuned to limit the influence of synaptic noise on force steadiness to low forces and that the inability to produce a constant force during stronger contractions is mainly attributable to the common low-frequency oscillations in motoneuron discharge rates.

Neuromuscular effects of shifting the focus of attention in a simple force production task

Research on the focus of attention has begun exploring the physiological changes that underlie the difference between internal and external foci of attention. However, previous electromyography studies have used dynamic tasks, making it difficult to interpret electrophysiological data. The authors analyzed how the focus of attention affects a subject's ability to perform an isometric force production task (focus was directed either at the force platform or the muscles responsible for force production). Subjects received practice without attentional focus instructions and then completed blocks of trials with an external and internal attentional focus separately. An external focus led to significantly less error overall and reduced surface electromyography activity with lower median power frequencies in the antagonist muscle, but attentional focus had no effects on the agonist muscle. Thus, an external focus of attention led to more efficient motor unit recruitment patterns (reduced cocontraction) and improved performance. Posttest surveys revealed subjects were aware of their improved performance with an external focus.

Decreased motor unit discharge rate in the potentiated human tibialis anterior muscle

AIM

The purpose of this study was to examine the influence of post-activation potentiation (PAP), the transient increase in low-frequency isometric force observed after muscle activity, on motor unit discharge rates measured during submaximal contractions.

METHODS

A quadrifilar needle electrode was inserted into the tibialis anterior muscle to determine discharge rate of individual motor units while monopolar electrodes were used to monitor the root-mean-square (RMS) and mean power frequency (MPF) of the surface EMG signal. Control (unpotentiated) and experimental (potentiated) measures were obtained during a 5 s voluntary contraction at 50% of maximal. In between these measures, subjects performed a 10 s maximal voluntary contraction (MVC) to induce PAP.

RESULTS

All subjects data are reported as means ± SEM (n = 10). Compared to baseline values measured prior to the MVC, isometric twitch force measured immediately after the MVC was increased by 260 ± 16% (day 3). Motor unit discharge rate in the potentiated tibialis anterior muscle decreased by approx. 10%, from 20.3 ± 0.8 (before) to 18.3 ± 0.99 pps (P = 0.01) (after). Moreover, the MPF was decreased by approx. 9% (from 58.1 ± 2.84 to 53.6 ± 2.85 Hz; P = 0.01) in the potentiated tibialis anterior. On the other hand, consistent with the absence of fatigue during the MVC, the RMS signal was not altered in the potentiated tibialis anterior (0.29 ± 0.03 vs. 0.33 ± 0.04 mV; P = 0.07).

CONCLUSION

Motor unit discharge rates determined during a brief, submaximal contraction were decreased in the potentiated human tibialis anterior muscle.

EMG analysis of lumbar paraspinal muscles as a predictor of the risk of low-back pain

Studies of EMG power spectra have established associations between low-back pain (LBP) and median frequency (MF). This 2-year prospective study investigates the association of LBP with EMG variables over time. 120 health care workers underwent paraspinal EMG measurements and assessment of back pain disability. The EMG recordings were performed under isometric trunk extension at 2/3 maximum voluntary contraction and acquired from erector spinae muscles at the level of L4/L5. 108 (90%) subjects were reviewed at a minimum 2-year follow up. 16 out of 93 subjects with no history of chronic low-back pain became worse as measured by time off work, disability, reported pain and self-assessment rating. The value of the EMG variable half-width at inception demonstrated significant association with changes in subject's outcome measure and their own assessment of their LBP at follow up (p < 0.05). Based on self-assessment data, subjects with no history of chronic LBP with half-width of greater than 56 Hz were at threefold greater risk of developing back pain compared with the remainder of the population (p = 0.045). The value of the initial median frequency (IMF) and MF slope at inception were also associated with the subjects' own assessment of LBP at follow up. Subjects with an IMF greater than 49 Hz were at 5.8-fold greater risk of developing back pain compared with the remainder of the population (p = 0.014). EMG variables recorded from lumbar paraspinal muscles can identify a sub group of subjects at increased risk of developing low-back pain in the future.

Physical fitness and performance. Fatigue responses during repeated sprints matched for initial mechanical output

PURPOSE

To compare muscle fatigability during two sets of repeated cycling sprints matched for initial mechanical output in a nonfatigued and fatigued state.

METHODS

Eight young men performed 10, 6-s all-out sprints on a cycle ergometer interspersed with 30 s of recovery, followed, after 6 min of passive recovery, by five 6-s sprints, again interspersed by 30 s of recovery.

RESULTS

On the basis of total work (TW), performance in sprint 11 (79.8 +/- 4.8 J.kg) was not significantly different to performance in sprint 4 (80.3 +/- 5.3 J.kg; P = 0.81). The decrease in TW for the five sprints after sprint 4 (i.e., sprints 4 to 8) averaged 14.5% (P < 0.001), which was significantly less than the decrement in TW from sprints 11 to 15 (20.3%; P < 0.05). Despite no significant differences in TW values achieved in sprints 4 and 11, the amplitude of the electromyogram (EMG) signal (i.e., root mean square (RMS)) recorded during sprint 11 (0.398 +/- 0.03 V) was 12.0% lower (P < 0.05) than in sprint 4 (0.452 +/- 0.02 V). In contrast, values of EMG median frequency (MF) recorded during sprint 4 (85.5 +/- 5.5 Hz) and 11 (89.3 +/- 7.2 Hz) were not significantly different (P = 0.33). However, the rate of decrease in EMG activity (i.e., RMS and MF) was similar for the two set of sprints.

CONCLUSIONS

These findings suggest that previous fatiguing repeated-sprint exercise, followed by a rest period, induces greater fatigability during subsequent repeated-sprint exercise, regardless of the initial mechanical output, and that these changes are associated with acute neuromuscular adjustments.

Mandibular physiological tremor is reduced by increasing-force ramp contractions and periodontal anaesthesia

We have previously shown that the application of anaesthesia to periodontal mechanoreceptors (PMRs) dramatically reduces the 6-12 Hz physiological tremor (PT) in the human mandible during constant isometric contractions where visual feedback is provided. This current study shows that during a ramp contraction where force is slowly increased, the amplitude of mandibular PT is almost five times smaller on average than when the same force ramp is performed in reverse, i.e. force is slowly decreased. This smaller tremor is associated with a higher mean firing rate of motor units (MUs) as measured by the sub-30 Hz peak in the multi-unit power spectrum. The decrease in the amplitude of PT following PMR anaesthetisation is associated in some instances with a similar increase in the overall firing rate; however this change does not match the diminution of tremor. The authors postulate that the decrease in mandibular PT during increasing force ramps may be due to a change in the mean firing rate of the MUs. The change in tremor seen during PMR anaesthetisation may in part be due to a similar mechanism; however other factors must also contribute to this.

Comparison of lumbar muscle sEMG between health and LBP patients during dynamic back extensions

Nonlinear sEMG signal complexity and recurrence quantification analysis (RQA) methods together with the traditional linear spectrum analysis were used to compare the differences between non-specific chronic low back pain patients and healthy subjects, and to evaluate the active physical therapy effects on LBP patients during dynamic isoinertial extension test.

The mechanomyography of persons after stroke during isometric voluntary contractions

This study was to investigate the properties of mechanomyography (MMG), or muscle sound, of the paretic muscle in the affected side of hemiplegic subjects after stroke during isometric voluntary contractions, in comparison with those from the muscle in the unaffected side of the hemiplegic subjects and from the healthy muscle of unimpaired subjects. MMG and electromyography (EMG) signals were recorded simultaneously from the biceps brachii muscles of the dominant arm of unimpaired subjects (n=5) and the unaffected and affected arms of subjects after stroke (n=8), when performing a fatiguing maximal voluntary contraction (MVC) associated with the decrease in elbow flexion torque, and then submaximal elbow flexions at 20%, 40%, 60% and 80% MVCs. The root mean squared (RMS) values, the mean power frequencies (MPF, in the power density spectrum, PDS) of the EMG and MMG, and the high frequency rate (HF-rate, the ratio of the power above 15Hz in the MMG PDS) were used for the analysis. The MMG RMS decreased more slowly during the MVC in the affected muscle compared to the healthy and unaffected muscles. A transient increase could be observed in the MMG MPFs from the unaffected and healthy muscles during the MVC, associated with the decrease in their simultaneous EMG MPFs due to the muscular fatigue. No significant variation could be seen in the EMG and MMG MPFs in the affected muscles during the MVC. The values in the MPF and HF-rate of MMG from the affected muscles were significantly lower than those from the healthy and unaffected muscles (P<0.05) at the high contraction level (80% MVC). Both the MMG and EMG RMS values in the healthy and unaffected groups were found to be significantly higher than the affected group (P<0.05) at 60% and 80% MVCs. These observations were related to an atrophy of the fast-twitch fibers and a reduction of the neural input in the affected muscles of the hemiplegic subjects. The results in this study suggested MMG could be used as a complementary to EMG for the analysis on muscular characteristics in subjects after stroke.

Adaptive certainty-based classification for decomposition of EMG signals

An adaptive certainty-based supervised classification approach for electromyographic (EMG) signal decomposition is presented and evaluated. Similarity criterion used for grouping motor unit potentials (MUPs) is based on a combination of MUP shapes and two modes of use of motor unit (MU) firing pattern information: passive and active. Performance of the developed classifier was evaluated using synthetic signals of known properties and real signals and compared with the performance of the certainty classifier (CC). Across the sets of simulated and real EMG signals used for comparison, the adaptive certainty classifier (ACC) had both better average performance and lower performance variability. For simulated signals of varying intensity, the ACC had an average correct classification rate (CCr ) of 83.7% with a mean absolute deviation (MAD) of 5.8% compared to 78.3 and 8.7%, respectively, for the CC. For simulated signals with varying amounts of shape and/or firing pattern variability, the ACC had a CCr of 79.7% with a MAD of 4.7% compared to 76.6 and 6.9%, respectively, for the CC. For real signals, the ACC had a CCr of 70.0% with a MAD of 6.3% compared to 64.9 and 6.4%, respectively, for the CC. The test results demonstrate that the ACC can manage both MUP shape variability as well as MU firing pattern variability. The ACC adapts to EMG signal characteristics to create dynamic data driven classification criteria so that the number of MUP assignments made reflects the signal complexity and the number of erroneous assignments is kept sufficiently low. The ability of the ACC to adjust to specific signal characteristics suggests that it can be successfully applied to a wide variety of EMG signals.

Physiologically based simulation of clinical EMG signals

An algorithm that generates electromyographic (EMG) signals consistent with those acquired in a clinical setting is described. Signals are generated using a model constructed to closely resemble the physiology and morphology of skeletal muscle, combined with line source models of commonly used needle electrodes positioned in a way consistent with clinical studies. The validity of the simulation routines is demonstrated by comparing values of statistics calculated from simulated signals with those from clinical EMG studies of normal subjects. The simulated EMG signals may be used to explore the relationships between muscle structure and activation and clinically acquired EMG signals. The effects of motor unit (MU) morphology, activation, and neuromuscular junction activity on acquired signals can be analyzed at the fiber, MU and muscle level. Relationships between quantitative features of EMG signals and muscle structure and activation are discussed.

Time–frequency analysis and estimation of muscle fiber conduction velocity from surface EMG signals during explosive dynamic contractions

Time-frequency analysis of the surface electromyographic (EMG) signal is used to assess muscle fiber membrane properties during dynamic contractions. The aim of this study was to compare the direct estimation of average muscle fiber conduction velocity (CV) with instantaneous mean frequency (iMNF) of surface EMG signals in isometric and explosive dynamic contractions. The muscles investigated were the vastus lateralis and medialis of both thighs in 12 male subjects. The isometric contractions were at linearly increasing force (0-100% of the maximal voluntary contraction in 10s). The explosive contractions were performed on a multipurpose ergometer-dynamometer (MED). The subject, sitting on the MED, performed six explosive contractions, separated by 2 min rest, by pushing against two force platforms and thrusting himself backwards with the maximum possible speed, while completely extending his legs. The estimated CV significantly increased with force in both the isometric (mean+/-S.D., from 3.24+/-0.34 to 5.12+/-0.31 m/s for vastus lateralis and from 3.17+/-0.26 to 5.11+/-0.34 m/s for vastus medialis, with force in the range 10-100% of the maximal voluntary contraction level) and explosive contractions (from 4.36+/-0.49 to 5.00+/-0.47 m/s for vastus lateralis, and from 4.32+/-0.46 to 4.94+/-0.44 m/s for vastus medialis, with force in the range 17.5-100% of maximal thrusting force). Moreover, estimated CV was not significantly different at the maximal force in the two exercises. On the contrary, iMNF, computed from the Choi-Williams time-frequency transform, was significantly lower in the explosive (57.7+/-8.2 and 66.5+/-10.3 Hz for vastus laterialis and medialis, respectively) than in the isometric exercises (73.7+/-9.2 and 75.0+/-8.5 Hz for vastus laterialis and medialis, respectively) and did not change with force in any of the conditions. It was concluded that EMG spectral features provide different information with respect to average muscle fiber CV in dynamic contractions. Thus, in general, they cannot be used to infer CV changes during the exertion of a dynamic task. A joint analysis of CV and EMG spectral features is necessary in this type of contractions.

Influence of high motor unit synchronization levels on non-linear and spectral variables of the surface EMG

The aim of this study was to investigate the influence of high degrees of motor unit synchronization on surface EMG variables extracted by linear and non-linear analysis techniques. For this purpose, spectral and recurrent quantification analysis (RQA) were applied to both simulated and experimental EMG signals. Synthetic surface EMG signals were generated with a model of volume conductor comprising muscle, fat, and skin tissues. The synchronization was quantified by the percent of discharges of each motor unit synchronized with discharges of other motor units. The simulated signals presented degrees of synchronization in the range 0-80% (10% increments) and three mean values of motor unit conduction velocity distribution (3, 4 and 5 m/s). Experimental signals were collected from the first dorsal interosseous muscle of five patients with Parkinson disease during 10s of rest and 10s of isometric voluntary contraction at 50% of the maximal force. Mean power spectral frequency (MNF) and percent of determinism (%DET) of the surface EMG were computed from the simulated and experimental signals. In the simulated signals, %DET was linearly related to the level of synchronization in the entire range considered while MNF was sensitive to changes in synchronization in a smaller range (0-20%), outside which it levelled off. The experimental results indicated that %DET was significantly higher in the resting condition (with presence of tremor; mean +/- S.E., 85.4 +/- 0.8%) than during the voluntary contraction (which partly suppressed tremor; 60.0 +/- 2.3%; P < 0.01). On the contrary, MNF did not depend on the condition (114.3 +/- 1.5 Hz and 118.0 +/- 0.8 Hz for the resting and voluntary contraction, respectively), confirming the simulation results. Overall, these results indicated that linear and non-linear analyses of the surface EMG may have different sensitivities to the underlying physiological mechanisms in specific conditions, thus their joint use provides a more complete view of the muscle status than spectral analysis only.

The extraction of neural strategies from the surface EMG

This brief review examines some of the methods used to infer central control strategies from surface electromyogram (EMG) recordings. Among the many uses of the surface EMG in studying the neural control of movement, the review critically evaluates only some of the applications. The focus is on the relations between global features of the surface EMG and the underlying physiological processes. Because direct measurements of motor unit activation are not available and many factors can influence the signal, these relations are frequently misinterpreted. These errors are compounded by the counterintuitive effects that some system parameters can have on the EMG signal. The phenomenon of crosstalk is used as an example of these problems. The review describes the limitations of techniques used to infer the level of muscle activation, the type of motor unit recruited, the upper limit of motor unit recruitment, the average discharge rate, and the degree of synchronization between motor units. Although the global surface EMG is a useful measure of muscle activation and assessment, there are limits to the information that can be extracted from this signal.

Oscillations in the power spectra of motor unit signals caused by refractoriness variations

The refractory period of a motor unit is an important mechanism that regulates the motor unit firing, and its variation has been found in many physiological cases. In this study, a new observation that an increase in the motor unit refractoriness results in an enhancement of oscillations, or ripple effects, in the motor unit output power density spectra (PDS) has been identified and studied. The effects of the refractoriness variation on the PDS of motor unit firing were investigated on three levels: theoretical modeling, simulation and electromyographic (EMG) experimentation on human subjects. Both theoretical modeling and simulation showed the enhanced oscillations, ripple effects, in MUAPT PDS, given the increase in the refractoriness. It was also found that the extent of the increment in output PDS oscillation could be related to the motor unit size and the mean firing rate of the stimulation. A needle EMG experiment on biceps brachii muscles of five healthy human subjects was carried out during isometric contraction at 20% maximum voluntary contraction (MVC) for 20 s with a fatigue effort proceeded by MVC. The increased oscillations in the PDS of the real MUAPTs were observed with the rising of the motor unit refractoriness due to fatigue. The study gives new information for EMG spectra interpretation, and also provides a potential method for accessing neuromuscular transmission failure (NTF) due to fatigue during voluntary contraction.

Surface electromyogram signal modelling

The paper reviews the fundamental components of stochastic and motor-unit-based models of the surface electromyogram (SEMG). Stochastic models used in ergonomics and kinesiology consider the SEMG to be a stochastic process whose amplitude is related to the level of muscle activation and whose power spectral density reflects muscle conduction velocity. Motor-unit-based models for describing the spatio-temporal distribution of individual motor-unit action potentials throughout the limb are quite robust, making it possible to extract precise information about motor-unit architecture from SEMG signals recorded by multi-electrode arrays. Motor-unit-based models have not yet been proven as successful, however, for extracting information about recruitment and firing rates throughout the full range of contraction. The relationship between SEMG and force during natural dynamic movements is much too complex to model in terms of single motor units.

Effects of supramaximal exercise on the electromyographic signal

AIM

To determine the neuromuscular recruitment characteristics during supramaximal exercise.

METHODS

Ten healthy subjects completed the Wingate anaerobic test (WAT) cycling protocol. Electromyographic (EMG) data and rate of fatigue were recorded throughout the cycling.

RESULTS

The mean (SD) rate of fatigue (decrease in power output) was 44.5 (8.6)%. No significant change was found in EMG amplitude. A significant decrease (p<0.01) in mean power frequency spectrum was found over the 30 second period.

CONCLUSIONS

During WAT, mean power frequency spectrum was attenuated with no decline in EMG amplitude, which may be caused by an accumulation of metabolites in the periphery. However, it is also possible that the feedback loop from intramuscular metabolism to the central nervous system is unable, within the 30 second period of the WAT, to affect neural recruitment strategy.

Rectification and non-linear pre-processing of EMG signals for cortico-muscular analysis

Rectification of the electromyographic (EMG) signal is a commonly used pre-processing procedure that allows detection of significant coherence between EMG and measured cortical signals. However, despite its accepted and wide-spread use, no detailed analysis has been presented to offer insight into the precise function of rectification. We begin this paper with arguments based on single motor unit action potential (AP) trains to demonstrate that rectification effectively enhances the firing rate information of the signal. Enhancement is achieved by shifting the peak of the AP spectrum toward the lower firing rate frequencies, whilst maintaining the firing rate spectra. A similar result is obtained using the analytic envelope of the signal extracted using the Hilbert transform. This argument is extended to simulated EMG signals generated using a published EMG model. Detection of firing rate frequencies is obtained using phase randomised surrogate data, where the original EMG power spectrum exceeds the averaged rectified surrogate spectra at integer multiples of firing rate frequencies. Model simulations demonstrate that this technique accurately determines grouped firing rate frequencies. Extraction of grouped firing rate frequencies prior to coherency analyses may further aid interpretation of significant cortico-muscular coherence findings.

Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization

Amplitude and frequency content of the surface electromyographic (EMG) signal reflect central and peripheral modifications of the neuromuscular system. Classic surface EMG spectral variables applied to assess muscle functions are the centroid and median power spectral frequencies. More recently, nonlinear tools have been introduced to analyze the surface EMG; among them, the recurrence quantification analysis (RQA) was shown to be particularly promising for the detection of muscle status changes. The purpose of this work was to analyze the effect of motor unit short-term synchronization and conduction velocity (CV) on EMG spectral variables and two variables extracted by RQA, the percentage of recurrence (%Rec) and determinism (%Det). The study was performed on the basis of a simulation model, which allowed changing the degree of synchronization and mean CV of a number of motor units, and of an experimental investigation of the surface EMG signal properties detected during high-force-level isometric fatiguing contractions of the biceps brachii muscle. Simulations and experimental results were largely in agreement and show that 1) spectral variables, %Rec, and %Det are influenced by CV and degree of synchronization; 2) spectral variables are highly correlated with %Det (R = -0.95 in the simulations and -0.78 and -0.75 for the initial values and normalized slopes, respectively, in the experimental signals), and thus the information they provide on muscle properties is basically the same; and 3) variations of %Det and %Rec in response to changes in muscle properties are significantly larger than the variations of spectral variables. This study validates RQA as a means for fatigue assessment with potential advantages (such as the higher sensitivity to changes of muscle status) with respect to the classic spectral analysis.

Motor unit recruitment strategies investigated by surface EMG variables

During isometric contractions of increasing strength, motor units (MUs) are recruited by the central nervous system in an orderly manner starting with the smallest, with muscle fibers that usually show the lowest conduction velocity (CV). Theory predicts that the higher the velocity of propagation of the action potential, the higher the power at high frequencies of the detected surface signal. These considerations suggest that the power spectral density of the surface detected electromyogram (EMG) signal may give indications about the MU recruitment process. The purpose of this paper is to investigate the potential and limitations of spectral analysis of the surface EMG signal as a technique for the investigation of muscle force control. The study is based on a simulation approach and on an experimental investigation of the properties of surface EMG signals detected from the biceps brachii during isometric linearly increasing torque contractions. Both simulation and experimental data indicate that volume conductor properties play an important role as confounding factors that may mask any relation between EMG spectral variables and estimated CV as a size principle parameter during ramp contractions. The correlation between spectral variables and CV is thus significantly lower when the MU pool is not stable than during constant-torque isometric contractions. Our results do not support the establishment of a general relationship between spectral EMG variables and torque or recruitment strategy.

Is the VO2 slow component dependent on progressive recruitment of fast-twitch fibers in trained runners?

The goal of this study was to use spectral analysis of EMG data to test the hypothesis that the O2 uptake VO2) slow component is due to a recruitment of fast fibers. Thirteen runners carried out a treadmill test with a constant speed, corresponding to 95% of the velocity associated with maximal VO2. The VO2 response was fit with the classical model including three exponential functions. Electrical activity of six lower limb muscles (vastus lateralis, soleus, and gastrocnemius of both sides) was measured using electromyogram surface electrodes. Mean power frequency (MPF) was used to study the kinetics of the electromyogram discharge frequency. Three main results were observed: 1) a common pattern of the MPF kinetics in the six muscles studied was noted; 2) MPF decreased in the first part of the exercise, followed by an increase for all the muscles studied, but only the vastus lateralis, and gastrocnemius muscles of both sides increased significantly (P < 0.05); and 3) the beginning of the MPF increase of the four muscles mentioned above corresponded with the beginning of the slow component. Our results suggest a progression in the average frequency of the motor unit discharge toward the high frequencies, which coheres with the hypothesis of the progressive recruitment of fast-twitch fibers during the VO2 slow component. However, this interpretation must be taken with caution because MPF is the result of a balance between several phenomena.

Surface EMG models: properties and applications

After a general introduction on the kind of models and the use of models in the natural sciences, the main body of this paper reviews potential properties of structure based surface EMG (sEMG) models. The specific peculiarities of the categories (i) source description, (ii) motor unit structure, (iii) volume conduction, (iv) recording configurations and (v) recruitment and firing behaviour are discussed. For a specific goal, not all aspects conceivable have to be part of a model description. Therefore, finally an attempt is made to integrate the 'question level' and the 'model property level' in a matrix providing direction to the development and application of sEMG models with different characteristics and varying complexity. From this overview it appears that the least complex are models describing how the morphological muscle features are reflected in multi-channel EMG measurements. The most challenging questions in terms of model complexity are related to supporting the diagnosis of neuromuscular disorders.

Spectral compression of the electromyographic signal due to decreasing muscle fiber conduction velocity

Spectral compression of the electromyographic (EMG) signal, due largely to decreasing muscle fiber conduction velocity, is commonly used as an indication of muscle fatigue. Current methods of estimating conduction velocity using characteristic frequencies such as the median frequency of the power spectrum, are based on an assumption of uniform spectral compression. To examine changes in the EMG frequency spectrum during fatigue, muscle fiber conduction velocity was measured during sustained, isometric contractions of the biceps brachii. Compression of the EMG power and amplitude spectra was simultaneously examined using the median frequency and an alternative method-the spectral distribution technique. The spectral distribution technique consistently gave a better estimate of the relative change in muscle fiber conduction velocity than either of the median frequencies. This was further examined using a physiologically based EMG simulation model, which confirmed these findings. The model indicated that firing statistics can significantly influence spectral compression, particularly the behavior of characteristic frequencies in the vicinity of the firing rates. The relative change in the median frequency, whether of the amplitude or frequency spectrum, was consistently greater than the relative change in conduction velocity. The most accurate indication of the relative change in conduction velocity was obtained by calculating the mean shift in the midfrequency region of the EMG amplitude spectrum using the spectral distribution technique.

Possible mechanisms of muscle cramp from temporal and spatial surface EMG characteristics

In this study, the initiation and development of muscle cramp are investigated. For this, we used a 64-channel surface electromyogram (EMG) to study the triceps surae muscle during both cramp and maximal voluntary contraction (MVC) in four cramp-prone subjects and during cramp only in another four cramp-prone subjects. The results show that cramp presents itself as a contraction of a slowly moving fraction of muscle fibers, indicating that either the spatial arrangement of the motoneurons and muscle fibers is highly related or that cramp spreads at a level close to the muscle. Spectral analyses of the EMG and peak-triggered average potentials show the presence of extremely short potentials during cramp compared with during MVC. These results can also be interpreted in two ways. Either the motoneurons fire with enlarged synchronization during MVC compared with cramp, or smaller units than motor units are active, indicating that cramp is initiated close to or even at the muscle fiber level. Further research is needed to draw final conclusions.

A model of EMG generation

Simulation models are unavoidable in experimental research when the point is to develop new processing algorithms to be applied on real signals in order to extract specific parameter values. Such algorithms have generally to be optimized by comparing true parameter values to those deduced from the algorithm. Only a simulation model can allow the user to access and control the actual process parameter values. This constraint is especially true when dealing with biomedical signals like surface electromyogram (SEMG). This work is an attempt to produce an efficient SEMG simulation model as a help for assessing algorithms related to SEMG features description. It takes into account the most important parameters which could influence these characteristics. This model includes all transformations from intracellular potential to surface recordings as well as a fast implementation of the extracellular potential computation. In addition, this model allows multiple graphically-programmable electrode-set configurations and SEMG simulation in both voluntary and elicited contractions.

Reliability of spectral EMG parameters of healthy back extensors during submaximum isometric fatiguing contractions and recovery

Spectral EMG parameters are being used as an objective evaluation of low back rehabilitation programs. The reliability of these spectral parameters is important in determining the validity of this evaluation tool. Two groups of eight subjects, with no history of back pain, were measured: the first group every day for one week; the second group one day per week for four weeks. During each session, subjects performed a 30-second isometric fatiguing contraction of the back extensors at 60% MVC followed by a 60-second rest and a 10-second repeat contraction. The intraclass correlation coefficient (ICC) did not demonstrate high reliability (ICC < 0.6) for the rate of median power frequency (MedPF) change (Hz/s), the magnitude of the recovery (Hz) and differences between the dominant and the non-dominant sides within a subject. However, the initial MedPF (Hz) of the fatigue and repeat contractions demonstrated excellent reliability (ICC > 0.8) with five or more repeated measures. The practical implication of this work is that the experimental condition must have sufficiently large changes in MedPF (signal)--at least larger than the variability inherent in the MedPF (noise)--to constitute a valid measure.

Poor correlations between isometric tests and dynamic performance: relationship to muscle activation

The purpose of this research was to perform isometric tests at two joint angles and examine their relationship to dynamic performance. In addition, electromyograph data were collected from the triceps brachii and pectoralis major muscles to compare underlying neural characteristics between the isometric tests and dynamic movement. A group of 24 healthy male subjects performed two isometric tests in a bench press position, at elbow angles of 90 and 120 degrees. From these data, the maximal force and rate of force development were determined. In addition, each subject performed a seated medicine ball throw as a measure of dynamic upper body performance. Correlations showed that isometric measurements of force (r = 0.47-0.55) and rate of force development (r = 0.08-0.31) were poor predictors of dynamic performance. The angle of isometric assessment had little effect on the relationship between the tests and measurements of performance. The myo-electric data was processed in terms of the integrated electromyogram and the Fourier transformed frequency spectrum. These data demonstrated differences in the neural activation patterns of the musculature, between the isometric 90 degrees test and the medicine ball throw. The poor relationship between isometric tests and medicine ball performance was consequently, at least partially, attributed to differing motor unit activation patterns between isometric and dynamic movement. The results of this research strongly suggest that isometric tests have limited value when assessing dynamic upper body performance.

Rate modulation of jaw-elevator motor units as revealed from the low-frequency power spectrum of the surface electromyogram in myogenous CMD patients

The firing pattern of the motor units (MUs) in jaw-elevator muscles was studied within a wide range of isometric contraction levels by means of changes in the frequency and broadness of the primary peak in the low-frequency (5-40 Hz) power spectral density function of the surface EMG. EMG was recorded from both masseter and anterior temporal muscles in 11 myogenous CMD patients as well as in 11 gender- and age-matched controls who clenched in intercuspal occlusion under the control of visual feedback at various levels (0.5-67% MVC for the various muscles studied). The EMG was digitized for 12 periods of 1.6 s per condition; the power spectrum was averaged and smoothed for the various clenching levels. Linear regression analysis showed that the positive slope in the peak frequency (PF)/% MVC relationship, a measure of rate modulation of the MUs, did not differ significantly between patients and controls. At a low clenching level, PF was smaller (p < 0.01) for the anterior temporal muscles of the patients, suggesting lower firing rates for a wide range of clenching levels of the patients because of a similar rate modulation for patients and controls. Furthermore, the variance in the slope values was larger (p < 0.05) for the masseteric muscles of the patients, which may be explained by more heterogeneity of the masseteric rate modulation in the patient group. The broadness of the primary peak was smallest at a low clenching level (p < 0.001) for the anterior temporal muscles of the patients, suggesting a more uniform firing rate or more synchronization between MUs.

Single motor unit myoelectric signal analysis with nonstationary data

The information content of the myoelectric signal (MES) is commonly revealed by statistical measures in the time or frequency domain. Empirical analyses of the MES from a single motor unit have generally assumed that features are invariant with time. Theoretical and experimental work has been done to demonstrate how nonstationary behavior in the discharge statistics of a motor neuron may affect estimates of features extracted from the motor unit's contribution to the MES. Specifically, it has been shown that nonstationary behavior can markedly influence estimates of features describing motor neuron firing behavior and consequently, the low-frequency portion of the MES power spectral density. These results may help to explain the discrepancies in the literature which report empirical models of motor neuron firing statistics.

Analysis of synchrony (correlations) in neural populations by means of unit-to-aggregate coherence computations

This paper presents a general outline of the mathematical basis of an approach for analysis of population synchrony by means of coherence computations, a demonstration of the use of this approach, and a discussion of the potential utility and limitations of the approach. The coherence function for the pair single-unit activity and population-aggregate activity is studied in the light of theoretical considerations on the superposition of partially correlated unitary activities. The theoretical analysis, as well as computer simulations, indicate that when a subset of units in a population are correlated around some frequency, the unit-to-aggregate coherence function for members of this subset shows, in a wide range of conditions, a clear peak around that frequency (and possibly harmonic peaks), being very low at other frequencies where there is no synchrony. Specifically, the value of the peak coherence at the frequency of synchrony reflects the strength of the unitary correlations and their extent within the population, the numerical size of the population, and the degree of phase concentration for the units of the correlated subset. This value remains substantial, or at least significant, for wide ranges of values of these parameters. In contrast, the unit-to-aggregate coherence function for the remaining uncorrelated units has very low values at all frequencies, and tends to zero in the case of a large population. On the basis of these properties, an approach is presented for analysis of synchrony (correlations) in a neural population, which is simple and efficient, particularly when the population is large in numerical size. This approach utilizes unit-to-aggregate coherence computations for a sample of recorded unitary activities as a means for detecting population synchrony and estimating the extent of synchrony. In addition, this analysis can provide useful information on other characteristics of synchrony, such as the strengths of the unitary correlations. The use of the approach is demonstrated with an example from a study of fast rhythms in inspiratory activities, and other applications are also briefly described. The main advantage of unit-to-aggregate coherence analysis is that by using readily recorded activities, it efficiently identifies correlated units in a population and provides information on characteristics of synchrony, at every frequency within the range of interest.

Electromyographic turns analysis of sustained contraction in human masseter muscles at various isometric force levels

The jaw-closing muscles differ from peripheral limb muscles in that the maximum attainable force does not decline following a sustained isometric contraction. Also, the averaged electromyographic (EMG)/force ratio in these muscles does not change with sustained contraction, whereas it increases in fatiguing limb muscles. The present study analysed EMG records from masseters in healthy male subjects. No statistically significant difference was seen between average rectified EMG signals at the beginning or the end of a sustained isometric contraction at 25-100% of maximum voluntary contraction (MVC). However, when the number of turns, or reversals of direction, was taken at various percentage MVC levels, a significant decrease was seen after 60s or at the end of the contraction. The turns/force ratio decreased monotonically with percentage MVC, but the ratio was not significantly different at the end of a contraction from that at the beginning. This result confirms an earlier suggestion that neuromuscular fatigue does not accompany sustained contractions of these muscles.

The spatial integration effect of surface electrode detecting myoelectric signal

The spectral properties of surface electrodes used for myoelectric signal detection were investigated using both a theoretical and an experimental approach. On the basis of the theoretical model, the single surface electrode was found to act as a low pass filter depending on the electrode diameter (d) and the fiber conduction velocities (CV). Several dips in the power spectrum were also predicted for varying frequencies depending on d and CV. The mathematical expression of the surface electrode filter was highly consistent with previously demonstrated properties of the single fiber power spectrum. An experimental comparison between myoelectric signals from the vastus lateralis muscle recorded using two electrode pairs with different diameters confirmed this low pass filter effect. However, the dip phenomenon was not observed from experimental data. The practical consequences of the electrode filter effect are discussed with respect to the interpretation of changes in surface myoelectric signal spectrum, particularly when a shift toward the high frequencies is observed.

A comparative study of simultaneous vibromyography and electromyography with active human quadriceps

Vibromyographic (VMG) signals, which are low-frequency vibration signals generated during muscle contraction, were studied in comparison with electromyographic (EMG) signals recorded simultaneously during isometric contraction of the human quadriceps muscles. The comparison was accomplished by evaluating the averaged root mean squared (rms) value, mean frequency (MF), and peak frequency (PF) of the VMG and EMG signals for four muscle contraction levels at joint angles of 30 degrees, 60 degrees, and 90 degrees. The four contraction levels, namely 20, 40, 60, and 80% of maximum voluntary contraction (MVC), were estimated and controlled by the torque readings of a Cybex II dynamometer. It was found that the VMG and EMG under the same conditions on the same muscle group are in general equally sensitive to the levels of muscle contraction. Results show that the rms value of the VMG signal increases linearly, in a manner similar to the EMG rms/%MVC relationship, with increasing muscle contraction levels. Furthermore, the study indicates that the averaged MF (6-24 Hz) and PF (9-19 Hz) of the VMG signals are much lower than the MF (75-109 Hz) and PF (40-80 Hz) of the EMG signals. The slopes of MF/%MVC curves for the VMG and EMG are approximately the same for 60 degrees and 90 degrees joint angles (approximately 3.1 Hz per 20% MVC for VMG and approximately 2.6 Hz per 20% MVC for EMG).(ABSTRACT TRUNCATED AT 250 WORDS)

Mathematical modeling and spectrum analysis of the physiological patello-femoral pulse train produced by slow knee movement

Analysis of vibration signals emitted by the knee joint has the potential for the development of a noninvasive procedure for the diagnosis and monitoring of knee pathology. In order to obtain as much information as possible from the power density spectrum of the knee vibration signal, it is necessary to identify the physiological factors (or physiologically relevant parameters) that shape the spectrum. This paper presents a mathematical model for knee vibration signals, in particular the physiological patello-femoral pulse (PFP) train produced by slow knee movement. It demonstrates through the mathematical model that the repetition rate of the physiological PFP train introduces repeated peaks in the power spectrum, and that it affects the spectrum mainly at low frequencies. The theoretical results also show that the spectral peaks at multiples of the PFP repetition rate become more evident when the variance of the interpulse interval (IPI) is small, and that these spectral peaks shift toward higher frequencies with increasing PFP repetition rates. To evaluate the mathematical model, a simulation algorithm was developed, which generates PFP signals with adjustable repetition rate and IPI variance. Signals generated by simulation were seen to possess representative spectral characteristics typically observed in physiological PFP signals. This simulation procedure allows an interactive examination of several factors which affect the PFP train spectrum. Finally, in vivo measurements of physiological PFP signals of normal volunteers are presented. Results of simulations and analysis of signals recorded from human subjects support the mathematical model's prediction that the IPI statistics play a very significant role in determining the low-end power spectrum of the physiological PFP signal.(ABSTRACT TRUNCATED AT 250 WORDS)