This report reviews the clinical uses of surface electromyography(SEMG) as a diagnostic tool for neurologic disorders. SEMG isassessed with regard to the evaluation of patients with neuromusculardiseases, low back pain, and disorders of motor control. Thisbroadens the scope of a previous assessment of SEMG in neurologicpractice by the American Association of Electrodiagnostic Medicine1in which its utility was examined with regard to neuromusculardiseases only.
Needle electromyographic evaluation (NEMG), in combination withnerve conduction studies, is the gold standard methodology forassessing the neurophysiologic characteristics of neuromusculardiseases. Moreover, fine-wire EMG (FWEMG) often has been usedin the evaluation of gait disorders, kinesiologic studies, andresearch and is also considered a standard. Nevertheless, NEMGand FWEMG are both invasive and painful, and this limits theiruse when activity from several muscles needs to be monitoredsimultaneously.
SEMG is a technique to measure muscle activity noninvasivelyusing surface electrodes placed on the skin overlying the muscle.SEMG differs from NEMG and FWEMG with respect to technical requirementsand electrical properties. Unlike NEMG, SEMG electrodes recordfrom a wide area of muscle territory, have a relatively narrowfrequency band (range, 20 to 500 Hz), have low-signal resolution,and are highly susceptible to movement artifact. SEMG electrodestypically are approximately 10 mm in diameter and usually arepassive (i.e., they are simple conductive surfaces requiringlow skin resistance). They can, however, be active, incorporating
preamplifier electronics that lessen the need for low skin resistanceand improve the signal-to-noise ratio. SEMG can record bothvoluntary and involuntary muscle activity in addition to externallystimulated muscle action potentials such as motor evoked potentialsafter central or peripheral nerve stimulation.2 SEMG has alsobeen used in several non-neurologic settings such as obstetricmonitoring and animal research, but these potential applicationsare beyond the scope of this review.
More than 2500 original articles, reviews, and books were examinedto determine the scope of SEMG utility, its benefits and risks,and the extent to which SEMG techniques vary, and to assessSEMGs strengths and weaknesses for specific clinicalapplications. Manual and computerized literature searches fromthe National Library of Medicine were used to obtain the articles.Key words used included SEMG, spontaneous activity, fasciculation,myopathy, muscle fiber conduction, motor unit estimation, fatigue,low-back pain, tremor, movement disorders, reaction time, andpsychophysics. Representative articles are cited and listedat the end of this article. Other key words relating to neuromusculardiseases (other than when cross-referenced with SEMG) were notsearched for specifically because this topic was the focus ofthe earlier AAEM assessment1 and was not the main focus of thecurrent paper.
No original article or review article has suggested that SEMGis better or even equivalent to NEMG in providing evidence ofdenervation at rest. This is because of the limited spatialresolution of SEMG that results in poor fidelity recordingsof high-frequency signals such as polyphasic potentials, fibrillationpotentials, and positive sharp waves.3 In addition, becauseof electrical cross-talk, SEMG cannot identify the origin ofthe electrical signal when two or more muscles, which lie inclose proximity to each other, are active simultaneously. Furthermore,the electrical signals in SEMG recordings are often attenuatedby intervening soft tissue, particularly when the active muscleis 10 mm or more below the skin surface.4 Insertional activity,another important measure in the evaluation of neuromusculardisease,2,5 cannot be evaluated by SEMG for the self-evidentreason that SEMG is noninvasive.
Some studies have proposed that SEMG may be a useful adjunctin the evaluation of fasciculation, particularly in the assessmentof patients with neuromuscular disease. In a review of 116 patientswith a variety of neuromuscular conditions, including, amongothers, motor neuron disease (n = 43), neuropathy (n = 14),myelopathy or radiculopathy (n = 9), spinal muscular atrophy(n = 6), benign cramps and fasciculation (n = 7), and postpoliosyndrome (n = 5), SEMG was compared to NEMG and clinical observationin detecting fasciculation.6 Pairs of plate electrodes wereplaced in a total of eight sites per patient. SEMG was reportedto detect fasciculation in 284 (82%) of the 344 sites studiedcompared with clinical observation (38.4%) and NEMG (73.6%).This study, however, lacks a gold standard and does not assessthe specificity of the SEMG findings. Further, the study wasretrospective, so there was no standard for the method for eitherclinical observation or conventional NEMG recording. Similarly,patients with motor neuron disease were studied using SEMG,and fasciculations were detected in 107 (95.5%) of 112 sites,whereas clinical examination alone revealed fasciculations in69 (61.1%) of these sites.7 Again, a gold standard is lackingand specificity is not assessed. As a result, these studiesrepresent Class III evidence for a clinical role of SEMG inthe evaluation.
Two studies reported a relationship between electromechanicalcoupling and myopathies. Using the ratio of SEMG electricalamplitude to acoustic amplitude, children with Duchenne, Becker,and myotonic dystrophy had significantly higher ratios thannormal control subjects.8 Similarly, using the ratio of theroot mean square SEMG amplitude to the mechanomyogram amplitude,the electromechanical coupling efficiency of some muscles wasstatistically different in patients with myotonic dystrophy(all with CTG expansion) compared with that of age-matched controlsubjects.9 In a brief report,10 SEMG activity in one patientwith myotonia congenita and transient weakness showed a declinein mean root SEMG voltage compared with that of a patient withouttransient weakness and a single control. Based on this observation,the authors suggested that SEMG could be a reliable and painlessmethod to investigate and quantify transient weakness in myotoniacongenita. Using a principal component analysis of SEMG activity,patients with Duchenne could be separated from control subjectswhen recording from the biceps but not the brachioradialis musclein severely affected patients.11 These studies, however, usednonstandard and dissimilar methods, did not replicate the findingsof other authors, and generally used small sample sizes. Thus,these reports do not allow an assessment of the sensitivityand specificity of the procedures and constitute, at best, onlyweak and inconsistent Class III evidence in favor of a clinicalrole for SEMG in the evaluation of myopathies.
Using turns frequency, zero crossing frequency, and median powerfrequency analyses, SEMG was compared to NEMG in the study ofinterference patterns of maximal voluntary contraction fromvarious muscles.12 In the tibialis anterior, but not in therectus femoris, there was similarity between SEMG and NEMG parameters.However, data from these two techniques correlated only whenthe needle was within 0.5 mm of the muscle surface. To evaluatethe sensitivity, specificity, and positive predictive valueof SEMG as a diagnostic test, 61 control subjects and 72 patientswere studied using "high-spatial resolution" SEMG. The resultswere compared with those of available recognition rates by NEMGand incorporated into a computerized evaluation procedure thatcombined and weighted different parameters to optimize the recognitionrate of diagnosis.13 Again, NEMG was superior to SEMG by thesemeasures.
A few studies directly compared SEMG to NEMG to examine musclefiber conduction velocity (MFCV), but in none were attemptsmade to ascertain the best methodology using unbiased approachesor double-blind crossover techniques. Thus, patients with ALSshowed significantly reduced mean NEMG MFCV compared with thatof control subjects.14 SEMG, by contrast, showed significantlyhigher mean MFCV compared with that of control subjects. ComparingNEMG to SEMG determination of MFCV in carriers of hypokalemicperiodic paralysis, asymptomatic first-degree relatives, andcontrol subjects, the mean SEMG MFCV in carriers was significantlylower than in control subjects.15 However, in 7 of 22 carrierswith attacks and in 3 of 11 carriers without attacks, SEMG MFCVvalues were in the low normal range. The NEMG method showedMFCV disturbance in all proved carriers, implying a greatersensitivity than SEMG.
Thus, these studies, in general, provide clear Class II evidencein favor of NEMG in preference to SEMG in the evaluation ofpatients with specific disturbances of neuromuscular function.
We conclude that SEMG is substantially inferior to NEMG forthe evaluation of patients with neuromuscular disorders. Someof the most important diagnostic NEMG measurements such as insertionalactivity, spontaneous activity, motor unit size and shape, andinterference pattern have not been or cannot be reliably measuredwith SEMG. Furthermore, SEMG has limited spatial resolution,is more susceptible to mechanical artifact, and is more likelyto show cross-talk between adjacent muscles than NEMG. Therefore,based on Class II data, SEMG is considered unacceptable as aclinical tool in the diagnosis of neuromuscular disease at thistime (Type E recommendation).
The presumed association between low back pain and muscle fatigueprovides the rationale for studying pain with SEMG. Nevertheless,the actual association between pain and fatigue has been difficultto establish. Moreover, the mechanisms of low back pain arenot clearly understood, although excessive fatigue due to muscledeconditioning, inhibition of muscle activation secondary topain, and pain-related action have been suggested as possiblecauses that might be addressed using SEMG.16
During sustained muscle contraction, SEMG signals undergo aspectral shift to lower frequencies. This spectral shift hasbeen suggested, but not convincingly established, to providean index of muscle fatigue.17-24 It is not known whether thereare other causes of similar spectral shifts.25,26 Some spectralparameters such as the mean, mode, and median frequency areknown to decrease continuously after the onset of muscle contraction.It may, therefore, be possible to monitor the fatiguing processearly in contraction before the point of mechanical failurehas been reached.
Twelve patients with a history of chronic low back pain (averageduration, 15.2 years) were compared to 12 control subjects ina two-group, stepwise discriminant analysis using the medianspectral frequency of muscle contraction.27 Spectral frequencywas determined at three contraction force levels: 40%, 60%,and 80% of maximal voluntary contraction (MVC). At 40% MVC,the discriminant analysis correctly classified 92% of the lowback pain group and 82% of the control group. At 80% MVC, analysiscorrectly classified 84% of the low back pain group and 91%of control subjects. At 60% MVC, however, classification waspoor (67% in the control group, 75% in the low back pain group).In addition, this particular discriminant function was not verifiedon an independent sample of patients and controls. Such inconclusiveor incomplete findings are characteristic of most studies inthis area, possibly related to external factors such as motivationbias, body movement, and electrode placement, each of whichcan adversely affect these measurements.
In an attempt to address some of these issues, 27 patients withchronic low back pain of more than 6 months were divided into"avoiders" (i.e., those who reduced physical and social activitiesto cope with the pain) and "confronters" (i.e., those who remainedactive despite their back pain) and compared to 22 control subjects.28Discriminant analysis correctly classified 88.9% of the avoidersbut did less well with confronters. The relevance of these findingsto clinical issues, however, is unclear and, again, the findingswere not replicated in an independent sample.
Among rowers with and without low back pain, discriminant analysiswas able to correctly classify all 6 patients and 14 (93%) of15 without low back pain.29 Similarly, when the same methodologyis applied, 25 rowers were examined: 8 with and 17 without lowback pain.30 The percentage of recovery in the median spectralfrequency at 1 minute and at 2 minutes after a 30-second contraction(80% MVC) was applied to a discriminant analysis, which correctlyclassified from 88% to 100% of both groups. More important,however, is that the similarity of the discriminant functionsused in these two studies is not known, so these two studiescannot be considered replications of each other.
In an attempt to correlate pain with changes in SEMG spectralfrequency, 403 nurses without any serious low back pain historywere prospectively evaluated.31 At baseline, spectral parameterswere measured during a 28-second muscle contraction at 80% MVC.A decline in the median SEMG spectral frequency was associatedwith a greater probability of subjects having low back paindevelop in the future. In a related study,32 mixed results werefound regarding the reliability of SEMG spectral parameters.In this study, muscle function of the multifidus and iliocostaliswas evaluated in the prone position (trunk holding test) in12 normal subjects. Two trials were performed in two testingsessions over 3 days. Pearsons product moment correlationcoefficients, t-tests for paired data, analysis of varianceof intrasubject coefficient of variation, and intraclass coefficientcorrelation were used as reliability measures of the initialmedian frequency and median frequency slope. Within-day reliabilityand between-days reliability of the initial median frequencyrecorded in the multifidus and iliocostalis were good (Pearsonsr = 0.74 to 0.94), but median frequency slope reliability measurementswere less stable compared with the initial median frequency(Pearsons r = 0.39 to 0.55). These findings imply thatthe basis for SEMG determination of low back pain may not bereliable.
In addition, several considerations make the reported SEMG findingsin low back pain of doubtful clinical value. First, althoughmuscle fatigue is thought to be related to the development oflow back pain and is associated with changes in SEMG spectralfrequency, the relationship between the two is uncertain. Second,it is unclear what other factors may influence spectral frequency,making the specificity of the SEMG findings in this clinicalsetting unclear. Third, many of the reports use discriminantfunctions based on case-control studies, which have not beenverified on independent samples of patients and control subjects.Fourth, the actual discriminant functions used have differedbetween reports. Fifth and finally, even if the reports areaccepted at face value, the findings suggest only that SEMGcan identify patients who have low back pain. Presumably, thegold standard is the clinical history and, in this circumstance,it would be easier and cheaper simply to ask the patient whetherhis or her back hurts (unless the patients are malingering andone wishes to determine whether the patient truly has low backpain). A more useful clinical application of this techniquewould be to distinguish patients with nerve root compressionsyndromes from those with back pain due to other causes, butthis question has not been addressed by the studies to date.
In summary, based on Class III and inconclusive or inadequateClass II data, SEMG is considered unacceptable as a clinicaltool in the evaluation of patients with low back pain at thistime (Type E recommendation).
There are several applications of SEMG in which this techniqueis considered standard. For example, the use of SEMG recordingsis routinely used to measure nerve conduction velocities afterelectrical stimulation of a peripheral nerve.2 Similarly, SEMGis the standard for recording compound muscle action potentialsafter magnetic stimulation either transcranially or peripherally.SEMG has been used for decades as a technique for studying humanmotion,22,33-43 for recording EMG signals from multiple musclesin other clinical settings, and for monitoring response timesin experimental circumstances.38,44-53 Indeed, because of thenoninvasive and painless nature of the method, this should beconsidered a standard application of SEMG (often superior toeither NEMG or FWEMG), although the precise clinical utilityof such recordings in these latter circumstances remains tobe defined.22,35 Few articles in this area critically compareSEMG with other methods of recording muscle activity and rarelyis a gold standard (e.g., NEMG, imaging studies, or muscle biopsies)identified. The reason for this is twofold. First, there isno adequate gold standard for movement analyses. Second, thetechnique of SEMG is not usually in question but merely usedas a tool within the scope of a larger testing goal.33,35,53-56
The neurophysiologic analysis of movement disorders, particularlytremor, myoclonus, dystonia, and dyskinesia, typically is studiedusing SEMG rather than NEMG or FWEMG. An important reason forthis is that the mean rectified SEMG signal, as opposed to theNEMG or FWEMG signal, varies linearly with the force generatedat constant length57-59 as well as during constant velocitycontractions.60 This linear relationship remains true even infatigued or diseased muscle,61,62 thus facilitating interpretationof SEMG data as they relate to muscle force generation. Anotherimportant advantage to SEMG in this setting is that it allowsprolonged recordings of muscle activity from multiple sitessimultaneously.
Surface electromyography may be used to classify movement disordersthrough measurement of frequency and amplitude of muscle activity,and its relationship to separately recorded limb or truncalmovement or force. This is based on Class III evidence as mostreports are formulated from expert opinion, nonrandomized historicalcontrol subjects, and observations from case series. These ClassIII studies show that many tremor disorders reveal distinctmuscle activity patterns (e.g., orthostatic tremor56,63) suchthat SEMG data can be helpful diagnostically. SEMG can provideinformation about motor unit recruitment and synchronizationwith the tremor activity64,65 and can also determine the relationshipof involved muscles to tremor movements and reveal whether antagonists(such as wrist flexors and extensors) discharge simultaneouslyor alternately to produce the tremor. Differentiating tremorfrom myoclonus,56 spasmodic torticollis from other head tremors,66and primary writing tremor from writers cramp67 and identifyingspeed of spread of muscle activity68 and origin of muscle activityin propriospinal myoclonus68 are other potentially importantclinical applications of SEMG. SEMG is also useful in the analysesof movement disorders in which prolonged recordings must bepain-free and interfere minimally with the clinical phenomenology.69
Rhythmic EMG signals containing bursts of activity, as in chewing,70-72walking,22,73-75 and breathing,76-81 can be analyzed using SEMGand automated burst detection methods. These have an advantagein that large amounts of SEMG data can be processed easily andobjectively.71 Multiple cycles of movement may be recorded andaveraged patterns of muscle activation and joint movements determined.Psychophysical measurements, such as movement and reaction timeanalysis,38,44-48 requiring precise timing of muscle contractiononset benefit from SEMG as a noninvasive tool for this purpose.Without SEMG, painful intramuscular insertion of an NEMG orFWEMG electrode would be required to determine the onset ofmovement, adversely interfering with the psychophysical measurementsunder analysis.
In summary, based on Class III evidence, SEMG is consideredan acceptable tool for kinesiologic analysis of movement disordersbecause it is a method for recording and quantifying clinicallyimportant muscle-related activity with the least interferenceon the clinical picture. SEMG may also be useful in differentiatingthe many types of tremors, myoclonus, and dystonia; for evaluatinggait and posture; and for evaluating psychophysical measurementsof reaction and movement time (Type C recommendation).
1. Based on Class II data, SEMG is considered unacceptable asa clinical tool in the diagnosis of neuromuscular disease atthis time (Type E recommendation).
2. Based on Class III dataand inconclusive or inadequate ClassII data, SEMG is consideredunacceptable as a clinical toolin the diagnosis of low backpain at this time (Type E recommendation).
3. Based on ClassIII data, SEMG is considered an acceptabletool for kinesiologicanalysis of movement disorders; for differentiatingtypes oftremors, myoclonus, and dystonia; for evaluating gaitand posturedisturbances; and for evaluating psychophysicalmeasures ofreaction and movement time (Type C recommendation).
Further studies comparing specificity and sensitivity of FWEMGwith SEMG are to be encouraged.
This statement is provided as an educational service of theAmerican Academy of Neurology. It is based on an assessmentof current scientific and clinical information. It is not intendedto include all possible proper methods of care for a particularneurologic problem or all legitimate criteria for choosing touse a specific procedure. Neither is it intended to excludeany reasonable alternative methodologies. The AAN recognizesthat specific patient care decisions are the prerogative ofthe patient and the physician caring for the patient, basedon all of the circumstances involved.
American Academy of Neurology Therapeutics and Technology AssessmentSubcommittee members: Douglas S. Goodin, MD (Chair); ElliotMark Frohman, MD, PhD; Robert Goldman, MD; John Ferguson, MD;Philip B. Gorelick, MD, MPH; Chung Hsu, MD, PhD; Andres Kanner,MD; Anne Marini, MD, PhD; Carmel Armon, MD; David Hammond, MD;David Lefkowitz, MD; and Edward Westbrook, MD.
Class I. Evidence provided by one or more well-designed clinicalstudies of a diverse population using a "gold standard" referencetest in a blinded evaluation appropriate for the proposed diagnosticapplication.
Class II. Evidence provided by one or more clinicalstudiesof a restricted population using a reference test ina blindedevaluation of diagnostic accuracy.
Class III. Evidenceprovided by expert opinion, nonrandomizedhistorical controls,or observation(s) from case series.
Definitions
Safe. A judgment of the acceptability of risk in a specifiedsituation, e.g., for a given medical problem, by a providerwith specified training, at a specified type of facility.
Effective. Producing a desired effect under conditions of actualuse.
Established. Accepted as appropriate by the practicingmedicalcommunity for the given indication in the specifiedpatientpopulation.
Possibly useful. Given current knowledge,this technology appearsto be appropriate for the given indicationin the specifiedpatient population. If more experience andlong-term follow-upare accumulated, this interim rating maychange.
Investigational. Evidence insufficient to determineappropriateness,warrants further study. Use of this technologyfor given indicationin the specified patient population shouldbe confined largelyto research protocols.
Doubtful. Givencurrent knowledge, this technology appearsto be inappropriatefor the given indication in the specifiedpatient population.If more experience and long-term follow-upare accumulated,this interim rating may change.
Unacceptable. Regarded bythe practicing medical communityas inappropriate for the givenindication in the specified patientpopulation.
Suggested strength of recommendations
Type A. Strong positive recommendations, based on Class I evidence,or overwhelming Class II evidence when circumstances precluderandomized clinical trials.
Type B. Positive recommendation,based on Class II evidence.
Type C. Positive recommendation,based on strong consensusof Class III evidence.
Type D.Negative recommendation, based on inconclusive or conflictingClass II evidence.
Type E. Negative recommendation, basedon evidence of ineffectivenessor lack of efficacy, based onClass II or Class I evidence.
Type O. Insufficient data tomake a recommendation.
Acknowledgments
The AAN TTA thanks Seth L. Pullman, MD, FRCPC, for his serviceto the Academys membership as the lead author of thispractice parameter; Anne Marini, MD, PhD, and Douglas S. Goodin,MD, for facilitating this project; and Anthony I. Marquinez,MD, Samer Tabbal, MD, and Michael Rubin, MD, for providing theirexpertise, time, and insight into the development of this document.
The AAN also thanks the numerous individuals, AAN Sections,and organizations that reviewed drafts of this practice parameter,including the American Association of Electrodiagnostic Medicine,Child Neurology Section, Clinical Neurophysiology Section, GeriatricNeurology Section, Government Service Section, NeurogeneticsSection, Neuromuscular Section, Pain Medicine Section, and theSection on Womens Issues.
Footnotes
Approved by the AAN Therapeutics and Technology Assessment SubcommitteeOctober 9, 1999. Approved by the Practice Committee January15, 2000. Approved by the AAN Board of Directors February 26,2000.
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Received November 23, 1999.
Accepted in final form January 11, 2000.
This article has been cited by other articles:
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Neurology,
May 22, 2001;
56(10):
1421 - 1422.
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