Statistical analyses of electromyographic activity in spasmodic dysphonic and normal control subjects

Statistical analyses of electromyographic activity in spasmodic dysphonic and normal control subjects

Journal of Voice Vol. 9, No. I, pp. 3-15 © 1995 Raven Press, Ltd., New York Statistical Analyses of Electromyographic Activity in Spasmodic Dysphonic...

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Journal of Voice Vol. 9, No. I, pp. 3-15 © 1995 Raven Press, Ltd., New York

Statistical Analyses of Electromyographic Activity in Spasmodic Dysphonic and Normal Control Subjects Ben C. Watson, *Donald Mclntire, Rick M. Roark, and Steven D. Schaefer New York Medical College, Valhalla, New York, and *University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.

Summary: Heterogeneity in the quality and task sensitivity of vocal symptoms in the spasmodic dysphonia (SD) population contributes to controversy as to whether this is a single disorder or two disorders with different etiologies (neurogenic versus psychogenic). Perceptual and acoustic assessments of vocal symptoms are inadequate to resolve this controversy. However, myoelectric events are intimately proximal to the source of vocal disruption and may be informative. The present report employs statistical modeling of quantitative amplitude measures of electromyographic activity recorded from thyroarytenoid to examine neuromotor bases of vocal symptoms in SD. Consideration of perceptual ratings of the quality and task sensitivity of vocal symptoms in the context of statistical models provides support for the conclusion that the range of vocal symptoms identified as SD represents a single, neurogenic disorder. Key Words: Spasmodic dysphonia--Quantitative electromyography--Statistical modeling.

Heterogeneity of perceived vocal symptoms is a characteristic feature of the spasmodic dysphonia (SD) population. Heterogeneity is observed in the severity, quality (i.e., strain-strangle identified as adductor SD versus breathy identified as abductor SD), and task sensitivity of vocal symptoms. One controversy fueled by heterogeneity along at least two of these dimensions (quality and task sensitivity of symptoms) is whether SD is a single disorder or two disorders with different etiologies. Twenty years ago, Aronson and colleagues (1,2) argued that the strain-strangle quality of adductor SD and the breathy quality of abductor SD were symptomatic of different underlying pathologies. Adductor SD was described as neurogenic, whereas abductor SD was described as psychogenic. Dedo and colleagues (3,4) also concluded that adductor SD was neurogenic, whereas abductor SD was a Accepted June 25, 1993. Address correspondence and reprint requests to Dr. B . C . Watson at Munger Pavilion, Rm. 170, New York Medical College, Valhalla NY 10595, U.S.A.

different disorder, possibly psychogenic. Shipp et al. (5) advocated separate labels for patients who showed qualitatively different symptoms: adductor SD for those who demonstrated primarily strainstrangle symptoms and "intermittent abductory dysphonia" for those who demonstrated primarily breathy symptoms. The enduring nature of this debate is reflected in opinions expressed recently by Karnell (6) and by Watterson and McFarlane (7). Karnell argued that abductor and adductor SD should be considered " r e l a t e d disorders until proven otherwise" (6, p. 17). Watterson and McFarlane stated that abductor and adductor SD are "different disorders" (7, p. 19). Application of acoustic analysis techniques to identify differences between SD patients grouped on the basis of the perceived quality of vocal symptoms has yielded inconclusive findings. Cannito and Johnson (8) used spectrographic analysis to document coexistence of irregularly spaced vertical striations associated with strain-strangle symptoms and prolonged aspiration associated with breathy

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B.C. WATSON ET AL.

symptoms within a single syllable produced by an SD subject. Freeman et al. (9) documented "intermittent breathy dysphonia" in their adductor SD patients and "intermittent strain-strangle dysphonia" in their abductor SD patients using both spectrographic and perceptual analyses. Failure of these studies to unambiguously distinguish subgroups may be due, at least in part, to relatively high intrasubject variability in acoustic measures and perceived vocal characteristics across tasks (1012). Observations that certain SD patients produce relatively normal voice during simple vocal tasks (vegetative vocalization and sustained phonation) and impaired voice during propositional speech tasks fueled the opinion that SD was a psychiatric disorder in these patients. Subsequent studies failed to identify significant psychopathology in SD patients (13-15) and found neurologic deficits in both adductor and abductor SD subjects (16,17). Finally, evidence of cortical abnormality in recent neurologic and brain imaging studies (16-19) suggests that task sensitivity of vocal symptoms across speech tasks of increasing complexity may reflect activation of hierarchically organized centers for vocal motor control in the CNS instead of an affectsensitive process. Acoustic and perceptual measures of voice quality, while the clinical standard, are relatively distant from the neuromuscular source of vocal symptoms in SD. Physiologic investigations of symptom heterogeneity in SD may be conducted at the level of neuromuscular control by characterizing intrinsic laryngeal muscle activity (electromyographically) and examining neuromotor findings in the context of clinical/perceptual ratings. Such investigations may reveal distinguishing neuromotor features underlying heterogeneity in the quality of vocal symptoms. If qualitatively different symptoms represent different underlying pathology, then patients with primarily adductor spasms and corresponding strain-strangle voice quality should show relatively high levels of activity in adductor muscles, whereas patients with primarily abductor spasms and corresponding breathy voice quality should show lower levels of activity in these muscles. Task sensitivity of vocal symptoms can be examined by documenting the magnitude of neuromotor abnormality as a function of task complexity. If the presence or absence of task sensitivity of vocal symptoms distinguishes different underlying pathology, then only a subgroup of presumably psychogenic SD subjects Journal of Voice, Vol. 9, No. I. 1995

should demonstrate task sensitivity of neuromotor abnormality. Early reports of electromyographic (EMG) activity in SD were limited with respect to addressing the issue of heterogeneity in the SD population. Investigators did not record EMG signals from relevant muscles (20) or did not classify SD subjects by perceived symptom quality (21-25). None of these studies reported EMG activity for tasks from a hierarchy of increasing complexity. Early reports were also limited to qualitative analyses of EMG activity. Findings ranged from no abnormality (22) to observations of asymmetric spasms (21) and bursts of activity in association with vocalization (23). Recently, Blitzer et al. (25) described polyphasic potentials, right/left amplitude asymmetry, and "abnormally increased amplitude" during swallow and/or sustained phonation. Ludlow (26) advocated the use of quantitative measures of EMG amplitude characteristics. For several years, we have undertaken the quantification of the nature, extent, and severity of neuromotor abnormality in SD. Our initial efforts were descriptive. Schaefer et al. (12) reported quantitative differences in normalized average EMG amplitude between normal control and SD subjects during production of relatively simple, sustained tasks (/i/, /s/, and/m/) and evidence of extralaryngeal neuromotor abnormality in SD subjects (i.e., levator palatini). Watson et al. (27) reported similarities in normalized average EMG among subgroups of SD subjects identified perceptually as demonstrating primarily adductor or abductor spasms. Again, analyses were based on EMG signals recorded during production of only sustained tasks (/i/ and /s/). In light of the reported task sensitivity of vocal symptoms, differences between perceptually defined subgroups may emerge as tasks increase in complexity. In sum, our early studies demonstrated the potential sensitivity of quantitative analyses of the EMG signal to describe neuromotor abnormality in SD. One advantage of extracting quantitative measures of the EMG signal is that these measures can be used in statistical comparisons between normal control and SD subjects as well as among subgroups of SD subjects. Between-group comparisons of multiple myoelectric measures across a variety of tasks can be used to develop quantitative scales of the severity of laryngeal neuromotor abnormality and provide a normal reference for examining the task sensitivity of EMG amplitude measures.

STATISTICAL A N A L Y S E S OF EMG A M P L I T U D E I N SD

Within-group comparisons among SD subjects can examine relations among perceived quality of vocal symptoms, task sensitivity of symptoms, and neuromotor abnormality. In sum, between- and withingroup statistical analyses of neuromotor activity in SD may contribute to the development of classification strategies that can be used to address the heterogeneity of this population. The nature of neuromotor abnormality(ies) demonstrated by subgroups identified by such classification strategies might have implications for development of appropriate treatment approaches (for example, psychotherapy or behavioral speech therapy with or without Botulinum injection). Schaefer et al. (28) submitted quantitative measures of thyroarytenoid (TA) activity amplitude obtained from normal control and SD subjects to an analysis of variance (ANOVA). Dependent variables entered into the ANOVA were normalized peak amplitudes for two relatively dynamic tasks (five repetitions of the word " b e e p " and the sentence "Beep, beep went the heap") and normalized median amplitudes for two relatively steady-state tasks (quiet breathing and sustained/i/). A significant group-by-task interaction effect was obtained. Post hoc analyses revealed significant betweengroup differences for repetitions of " b e e p " and the sentence, but not for quiet breathing or sustained /i/. This pattern of between-group differences could reflect differential effects of task complexity on neuromotor abnormality in SD subjects or the use of different quantitative measures for the dynamic versus steady-state tasks. Use of the same amplitude measure across tasks is essential to examine the task sensitivity of EMG activity. Selection of a statistical model for analysis of quantitative EMG data requires consideration of several issues. First, the ability to characterize EMG amplitude using multiple quantitative measures (for example, raw and normalized peak, mean, and median values) and the need to assess neuromotor function across a variety of tasks result in an increase in the number of potential dependent measures and, consequently, degrees of freedom in an analysis. One consequence of a large number of degrees of freedom is the need for a relatively large sample population. Unfortunately, the invasive nature of laryngeal EMG recordings makes it difficult to recruit large numbers of subjects. Second, when investigating heterogeneity in the quality and task sensitivity of vocal symptoms in SD, it is informative to evaluate associations across a set of EMG

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measures to examine their underlying structure in the context of perceived symptoms. This goal is achieved by use of interdependence methods rather than dependence methods (29). One statistical model that addressed the issues raised above is principal components analysis (PCA). PCA is well suited to analyses in which there are many dependent variables, but small sample sizes. PCA combines the information of many variables into fewer variables as linear combinations of the original variables. This process reduces the overall dimensionality of the system. That is, reduction in the degrees of freedom is accomplished in PCA by an orthogonal linear transformation of the data (i.e., rotation of the axes of the original data) to explain as much of the variability in the data set in as few dimensions, or weighted combinations of dependent variables, as possible. Since all dependent variables are included in the analysis simultaneously, the structure of components (eigenvectors) can be analyzed to evaluate the relative contributions of constituent dependent variables. Finally, individual subjects can be represented in n-dimensional space (where n represents the number of components in the analysis) to evaluate the discriminate power of the PCA. In the present report, we examine neuromotor bases of the heterogeneity of vocal symptoms in SD by comparing clinical/perceptual ratings of vocal symptoms with the results of PCAs of quantitative measures of EMG amplitude. The first series of PCA includes both normal control and SD subjects. We expect that the largest effect in these analyses will be increased TA amplitude across all levels of task complexity in SD subjects as compared with normal controls. Thus, the first component should provide an index of the overall severity of neuromotor abnormality in SD and should relate to clinical/perceptual ratings of the severity of vocal symptoms. We expect that the next effect to emerge from these analyses will be task sensitivity of TA amplitude. We further expect that this effect will be observed for only SD subjects. That is, the second component should provide an index of the task sensitivity of EMG amplitude with reference to normal controls. Normal control subjects should cluster in a small range of values that reflect approximately equal weights for the three tasks on the second component, whereas SD subjects should be dispersed over a wider range of values. The second series of PCA includes only SD subjects. These analyses permit examination of the Journal of Voice, Vol. 9, No. 1, 1995

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B . C . W A T S O N ET AL.

neuromotor bases of the quality and task sensitivity of vocal symptoms among SD subjects. We expect that the largest effect in these analyses will reflect the amplitude of TA activity across all levels of task complexity. Thus, the first component in the within-group model should provide an index of the degree of neuromotor abnormality in TA and should discriminate SD subjects who show primarily strain-strangle spasms from those who show primarily breathy spasms. The second component in the within-group model may provide an index of the task sensitivity of TA activity among SD subjects. If the within-group model achieves good discrimination of SD subjects with primarily breathy symptoms from those with primarily strain-strangle symptoms, then the hypothesis that heterogeneity of vocal symptoms in SD reflects two different disorders is supported. Conversely, if SD subjects with qualitatively different vocal symptoms are not discriminated on either component in the model, then the hypothesis that the complete range of vocal symptoms in SD reflects a single disorder that affects all laryngeal muscles (for example, focal laryngeal dystonia) is supported. METHOD Eleven SD and eight normal control subjects underwent simultaneous acoustic and EMG recordings. SD subjects included four men and seven women (average age 48.6 years, range 28--69 years). Characteristics of SD subjects are summarized in Table 1. Diagnosis of SD was made by a minimum of two otolaryngologists and two speech/language pathologists using both perceptual and fiberoptic laryngoscopic evaluation. No subject had structural or other laryngeal abnormalities that might con-

found measures employed in this study. Duration of dysphonia varied from 1.5 to 20 years (average 8.6 years). Perceptual ratings of vocal tremor were moderate to severe in two subjects, moderate in three subjects, mild to moderate in two subjects, and mild in three subjects. One subject showed no perceptual evidence of vocal tremor. None of the SD subjects had received recurrent laryngeal nerve (RLN) section or Botox therapy. Symbols shown for each subject are used in subsequent graphic presentations of results to facilitate evaluation of statistical models in the context of clinical/perceptual ratings. Five speech/language pathologists, experienced in evaluating voice characteristics of SD, performed clinical/perceptual analyses of all tokens for which EMG data were analyzed. Tokens were evaluated for presence and severity of strain-strangle and breathy qualities on 7-point scales. A rating of 0 is considered normal, ratings of 1-2 reflect a mild abnormality, ratings of 3-4 reflect a moderate abnormality, and ratings of 5-6 reflect a severe abnormality. Global clinical/perceptual ratings were obtained by collapsing ratings across raters, tokens, and tasks and then identifying the most frequent ratings for strain-strangle and breathy qualities for each subject. Figure 1 shows the results of global perceptual analyses. Each symbol represents the most frequent rating on the strain-strangle and breathy dimensions for a subject. Dashed lines indicate median values for both dimensions. The distribution of SD subjects' ratings demonstrates the heterogeneity of this group. Three subjects (O, X, A) showed mild to moderate ratings for both strain-strangle and breathy qualities. Two subjects (5', II) showed mild ratings for strain-strangle quality and moderate to

T A B L E 1. Characteristics o f spasmodic dysphonia subjects ID

Age (yrs)

Gender

Type

Severity

Duration (yrs)

Tremor

Medications

• O X • • (> • V A * •

35 53 36 46 67 48 60 40 69 52 28

Female Female Female Female Male Male Female Female Female Male Male

AB AD MX MX MX AD AB AD AD AD AD

Mod-severe Severe Mild-mod Mild Mild Severe Severe Severe Severe Severe Moderate

2 13 12 I 7 2 12 5.5 20 3 1.5

Mild Severe Mild Moderate Mild-mod Moderate None Moderate Mod-severe Mild Mild-mod

Limbitrol Primarine, calcium Librium, Doxepin, Procardia Estrogen Cardizem, dipyridamole None None None None None Elavil

AB, abductor; AD, adductor; MX, mixed; Mod, moderate.

Journal of Voice, Vol. 9, No. I, 1995

STATISTICAL A N A L Y S E S OF EMG A M P L I T U D E I N SD

7

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severe ratings for breathy quality. Five subjects (*, <>, O, A, V) showed normal to mild ratings for breathy quality and severe ratings for strainstrangle quality. Finally, one subject ( • ) showed a normal rating for breathy quality and a moderate rating for strain-strangle quality. Based on clinical/ perceptual evaluations, this group consists of six (*, O, O, A, V, • ) primarily adductor SD and two (V, II) primarily abductor SD and three (~, X, A) mixed SD. Task sensitivity of clinical/perceptual ratings was documented by collapsing ratings across raters and tokens for each task and then identifying the most frequent ratings for strain-strangle and breathy

, {\',

..~

.... "' '~

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FIG. I. Global perceptual ratings collapsed across all experimental tasks. Each spasmodic dysphonia subject is represented as the m a x i m u m rating received for strain-strangle and breathy voice qualities. For details see the text.

6

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Subject ID FIG. 2. P e r c e p t u a l r a t i n g s of b r e a t h y v o i c e q u a l i t y as a f u n c t i o n of e x p e r i m e n t a l t a s k . F o r d e t a i l s see the t e x t .



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Subject ID FIG. 3. Perceptual ratings of strain-strangle voice quality as a function of experimental task. For details sec the text.

qualities for each task and subject. Figures 2 and 3 showed results of clinical/perceptual analyses of breathy and strain-strangle vocal qualities, respectively, for each SD subject for the sustained vowel, word repetition, and sentence tasks. Examination of changes in each subject's ratings across the three panels reveals within-subject patterns of the task sensitivity of perceived vocal symptoms. One of the two SD subjects rated as abductor (11) on global analyses showed increased severity of breathy ratings as a function of increasing task complexity. The other abductor SD subject showed decreasing severity of breathy ratings across the tasks. Two of the adductor SD subjects (<>, A) showed consistently severe ratings for strain-strangle quality across the three tasks, two (X, • ) showed increasing severity of strain-strangle quality across the tasks, and two (V, O) showed complex changes in severity of strain-strangle quality. For these subjects, severity either increased and then decreased or decreased and then increased as tasks became more complex. The mixed SD subjects also showed inconsistent patterns of vocal symptoms across tasks. In sum, clinical/perceptual ratings of vocal symptoms for these subjects as a function of task do not differentiate the subgroups of SD subjects. This finding is consistent with the report by Freeman et al. (9) that both adductor and abductor SD subjects show task sensitivity in perceived vocal symptoms. Eight normal control subjects, consisting of two men and six women (average age 42 years, range 25-51 years), were recruited from volunteers. None Journal of Voice, Vol. 9, No. 1, 1995

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B. C. W A T S O N ET AL.

of the normal control subjects had a history of speech or neurologic disorders. History and physical findings were unremarkable and these control subjects were regarded as healthy examples of their respective age groups. Subjects were seated in a standard ORL examination chair in an electrically shielded room. An electric condenser microphone ATM33R; Audiotechnica) was mounted on the examination chair and maintained at a distance of 20 cm from the subject's head. Bipolar hooked-wire electrodes were constructed using 0.05-mm coated platinum wire (Semiconductor Packaging Materials; effective recording area 1 mm) and were inserted transcutaneously. The TA was entered by inserting the needle through the midline cricothyroid (CT) membrane, immediately superior to the cricoid cartilage. Upon entering the laryngeal lumen, the needle was maximally directed superolaterally into the TA during phonation of/i/. Care was taken to place the electrode as anteriorly as possible, and within the infraglottal region, to avoid insertion into the lateral cricoarytenoid (LCA) or CT muscles, respectively. The needle was withdrawn upon entering the TA, leaving the hooked-wire electrodes within the muscle. Anesthesia was limited to I% Xylocaine intradermally. Subjects were awake, unsedated, and withdrawn for a minimum of 2 weeks from any medication that might confound findings. Output from each electrode pair was routed to separate EEG amplifiers (Grass Instrument 7P511) through shielded cable. Amplifiers were calibrated and maintained to ensure accuracy of signals and to minimize extraneous noise. The impedance at each input terminal of the preamplifiers was t>20 MfL Each channel was band-pass-filtered with halfamplitude points at 30 and 3,000 Hz. A notch filter was used to minimize 60-Hz interference. All EMG signals were evaluated prior to and during recordings for extraneous artifacts using a Tektronic (model 11401) digital oscilloscope. Signals from the amplifiers were recorded on analog tape using a 14channel (12 FM, 2 direct) data recorder (TEAC-XR510). Nominal full-scale signal amplitudes were +-2 V peak. Recording bandwidths were 2.5 kHz for the FM-coded EMG channel and 18 kHz for the acoustic channel. Verification of insertions was based on appropriateness of electrical activity during specific maneuvers. Insertion was judged to be within the TA when activation was seen on phonation, Valsalva, and swallow, but not on inspiration. Insertion was judged to be within the LCA when activation Journal of Voice, Vol. 9, No. 1, 1995

was seen primarily for sphincteric tasks and minimally for phonation. Insertion was judged to be within the CT when increasing activation was seen during pitch raising (30-32). All experimental sessions were cued by a visual pacing light controlled by a desktop computer (Compaq 386/25) operating under the in-housedeveloped software program ACQUIRE. The computer presented experimental tasks in random order. Three to five repetitions of each task were performed. Tasks reported herein (sustained /i/; five repetitions of " b e e p " ; and "Beep, beep went the heap") represent a subset of experimental tasks administered during the experimental session. EMG signals were low-pass-filtered prior to digitization using constant-delay, sixth-order analog filters ( - 3 dB cutoff frequency of 2,500 Hz). EMG data were sampled at a 5 kHz rate, with 12-bit resolution. Acoustic data were low-pass-filtered at 5,000 Hz and digitized at a 10-kHz rate. Quantization error due to digitization was 0.0122%. Data files were computer coded during the acquisition and digitization sessions according to subject, session, task, token, and signal channel. Calibration signals recorded during the acquisition session were digitized and analyzed to obtain baseline and multiplication parameters for each signal channel. These parameters were used to convert all EMG data to absolute microvolt units, within a 5% margin of precision. Once calibrated, data were stored to write-once, read-many optical media, from which they could be accessed by computeraided analysis programs. Raw EMG files were first screened visually for quality. Tokens that contained artifact or that were saturated were eliminated from the data corpus. A file representing the envelope of the signal was computed for each of the remaining acoustic and EMG files. Generation of envelope files required several steps. These steps are described in detail in Schaefer et al. (28). Briefly, residual DC offset was removed and the signal was rectified and digitally low-pass-filtered (fc = 10 Hz). Data were then software down-sampled at an effective rate of 30 Hz for inclusion in the envelope files. Custom software was developed to automatically process envelope files to extract selected measures. The acoustic envelope was displayed first, start and end times were selected, and these were applied to select segments from the TA EMG signal associated with that token. EMG measures computed and saved for the present analysis were: (a) peak ampli-

STATISTICAL A N A L YSES OF EMG A M P L I T U D E I N SD

tude (I~V) during the selected segment, (b) mean amplitude (~V), (c) median amplitude (ixV), and (d) ratio of average to peak amplitude. Average-topeak amplitude ratio was used to capture information regarding the gross shape of envelope signals independent of absolute amplitude. After parameter files were computed for each envelope file, means and standard deviations of selected measures were computed for each task and subject. Normalized peak and average amplitude measures were added to the parameter record for each token by dividing peak and mean amplitude values by the peak activity level associated with swallow Iphysiologic maximum activity). Thus, normalized measures represent characteristics of TA activity as a percentage of presumed physiologic maximum activation. Using swallow as the maximum activation task presents advantages and disadvantages. Ludlow (26) suggests that ballistic movements are eftective for eliciting maximum activation of TA, but that swallow introduces the risk of motion artifact. Our data-screening procedures convince us that there was no significant TA artifact during the swallows. A large-magnitude artifact would have been identified during visual screening of the EMG waveform. A small magnitude artifact would not affect the peak value. EMG data were submitted to several PCAs. Since we had no way of knowing, a priori, which of our amplitude measures would be most informative, separate PCAs were performed for all tasks and all measures, each task and all measures, and all tasks and a single measure. This series of PCAs was completed for data sets that included all subjects (control and SD) and for a data set that included only SD subjects. The robustness of each PCA was examined using a jackknife procedure. The jackknife (or "leaveone-out") procedure is a sequential approach that may be used, as here, to determine the robustness of the analysis by examining the influence of single observations. First, a subject is removed from the PCA calculations. Next, the PCA linear combinations are applied to that subject and the coordinates of the PCA system are noted. This two-step process is repeated for all subjects. Differences in the locations of the subjects plotted in this manner are compared to the PCA of the full data set. If an individual is "different," then the jackknifed plot will differ from the full PCA plot. Eigenvectors for each of the jackknifed sets are also compared to identify differences. These comparisons also provide an estimate

9

of the sensitivity of the PCA to individual observations. RESULTS Task sensitivity of vocal symptoms was first examined by conducting PCA on combined data for normal control and SD subjects. These analyses examined task sensitivity of vocal symptoms in SD subjects relative to normal controls. Observation of a task sensitivity effect on TA activity in our normal controls would render uninformative observation of such an effect in the SD subjects. Table 2 summarizes PCA for all permutations of tasks and amplitude measures. Shown for each PCA are variables in the analysis, variance explained by the first and second principal components, and cumulative explained variance. All analyses were robust to jackknifing. Highest cumulative R 2 values were obtained for analyses that included all tasks and a single measure. Table 3 summarizes eigenvectors for the first and second components for the three analyses that provided the highest proportion of cumulative explained variance. All three tasks had similar eigenvectors for the first component across the three measures. The first component may reflect overall EMG amplitude across the three tasks. Eigenvectots for the second component differed as a function of measure. The greatest contrast was between the sustained/i/and word repetition tasks for average and median measures. The greatest contrast was between the word repetition and sentence tasks for the normalized average measure. The second component may reflect between-task differences in EMG amplitude. PCA of the normalized average measure yielded 100% discrimination of SD and control subjects. This finding is illustrated in Fig. 4. Subjects are plotted as a function of their weights on the first and second components. Normal controls are shown as open squares. SD subjects are represented by the symbols referenced in Table 1. Values for the first component are shown on the y-axis. High positive values for this component reflect large EMG amplitudes across all three tasks, whereas negative values for this component reflect relatively low EMG amplitudes across the three tasks. Values for the second component are shown on the x-axis. High positive values for the second component reflect the dominance of large EMG amplitude for the word repetition task. High negative values for this Journal of Voice, Vol. 9, No. 1, 1995

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B. C. W A T S O N E T A L .

6

O

T A B L E 3. Eigenvectors for principal components analyses with highest proportion of variance explained

5

Eigenvectors Measure in equation

4

3

Average

2

Median

©

1

Normalized average"

O~ -1

Task

Principal component 1

Principal component 2

Vowel Word Sentence Vowel Word Sentence Vowel Word Sentence

0.573477 0.575135 0.583390 0.571965 0.576579 0.583448 0.579489 0.575659 0.576897

0.736838 - 0.673358 - 0.060488 0.776436 - 0.609974 - 0.158361 - 0.128621 0.7635944 - 0.632757

" Provided 100% discrimination of control and spasmodic dysphonia subjects.

-2

-0.000

-0.400

-0.200 Principal

0.000

0.200

Component

0.400

2

FIG. 4. B e t w e e n - g r o u p model of normalized average thyroarytenoid activity. Subjects are represented as their weights on the two components. Regression line was computed without two outlying spasmodic dysphonia subjects ( 0 , II). For details see the text.

component reflect the dominance of large EMG amplitude for the sentence task. Values near zero for this component reflect the dominance of large EMG amplitude for sustained /i/ or equal amplitudes across the three tasks. The vertical dashed line represents zero on the x-axis. The two outlying SD subjects were excluded from computation of the regression line separating normal control and SD subjects. T A B L E 2.

Between-group principal components analyses (PCAs) Proportion of variance explained

Variables in equation All tasks and measures Selected manually~ Vowel all measures Word repetitions all measures Sentence all measures Peak all tasks Average all tasks Median all tasks Peak/average all tasks Normalized average all tasks Normalized peak all tasks

Principal component I

Principal component 2

Cumulative

0.460

0.304

0.765

0.577

0.323

0.900

0.513

0.333

0.847

0.439

0.316

0.756

0.484 0.873 0.973 0.971

0.300 0.106 0.023 0.025

0.784 0.980 0.996 0.997

0.630

0.326

0.956

0.984

0.011

0.996

0.929

0.047

0.976

° Based on weightings on principal component 1 and principal component 2 for PCA on all tasks and measures.

Journal of Voice, Vol. 9, No. 1, 1995

Normal control subjects (I--1) are tightly clustered in Fig. 4. Uniformly low values on the first component suggest that our normal subjects showed relatively low levels of EMG activity across the three tasks. Clustering of the normal control subjects near zero on the second component can be interpreted in two ways. Either these subjects showed highest EMG amplitude for the sustained/i/task, or they showed equal amplitudes across the three tasks. Table 4 summarizes group mean normalized average EMG amplitudes as a function of task for normal control and SD subjects. Normal controls showed equal EMG amplitudes across the three tasks. Thus, our normal controls do not show a task sensitivity effect on TA amplitude. Finally, note that the PCA successfully minimized variance in the normal population while preserving the distinction between the normal and SD populations. Relatively wide dispersion of the SD subjects in Fig. 4 is due to two outlying subjects. These subjects were rated as a severe abductor SD with no tremor (11) and a moderate mixed SD with moderate tremor (O). Thus, only one outlier received extreme clinical/perceptual ratings of vocal symptoms. The majority of SD subjects, regardless of symptom quality, are clustered within a relatively narrow range along the first component. Values for these subjects suggest that TA EMG amplitude was Average (standard deviation) normalized EMG amplitudes for normal control and spasmodic dysphonia (SD) subjects as a function of task

T A B L E 4.

Group

/i/

Word

Sentence

Normal control SD

0.02 (0.03) 0.465 (0.47)

0.02 (0.03) 0.5 (0.4)

0.02 (0.03) 0.527 (0.416)

STA TI STI C A L A N A L Y S E S OF EMG A M P L I T U D E I N SD

Within-group principal components analyses (PCAs) for spasmodic dysphonia subjects

T A B L E 5.

Proportion of variance explained Variables in equation

Principal component l

All tasks and measures Selected manually" Vowel all measures Word all measures Sentence all measures Peak all tasks Average all tasks Median all tasks Peak/average all tasks Normalized average all tasks Normalized peak all tasks

Principal component 2 Cumulative

0.516

0.286

0.803

0.540

0.284

0.825

0.522

0.344

0.867

0.463

0.268

0.732

0.595 0.760 0.982 0.991

0.279 0.218 0.015 0.006

0.874 0.978 0.998 0.997

0.661

0.315

0.976

0.978

0.019

0.997

0.926

0.049

0.973

Based on weightings on principal component I and principal component 2 for PCA on all tasks and measures.

uniformly higher than for the normal controls across the three tasks. Not withstanding the two outliers, the SD subjects show wider dispersion along the second component than the normal controls. Thus, PCA of combined normal control and SD subject data reveals a task sensitivity effect for only the SD subjects. Detailed examination of symptom quality and task sensitivity within the SD group was conducted through a second series of PCA. Table 5 summarizes variables in the equation, variance explained by the first and second principal components, and cumulative explained variance for analyses of TA EMG data for only the SD subjects. All analyses T A B L E 6. Eigenvectors for principal components analyses with highest proportion of variance e x p l a i n e d

Eigenvectors Measure in equation Average Median Normalized average

Task

Principal component 1

Principal component 2

Vowel Word Sentence Vowel Word Sentence Vowel Word Sentence

0.575748 0.575049 0.581234 0.576163 0.577754 0.578 ! 31 0.581854 0.573683 0.576484

- 0.685239 0.727 ! 84 - 0.812719 0.813911 - 0.470248 - 0.341199 -0.134524 0.7669514 -0.627447

11

were robust to jackknifing. Highest cumulative R 2 values were obtained for analyses that included all tasks and single measures. Table 6 summarizes eigenvectors for the first and second components for the three analyses that provided the highest cumulative explained variance. All three tasks have similar eigenvectors for the first component across the three measures. Thus, the first component may reflect overall TA EMG amplitude across the three tasks. Eigenvectors for the second component differed as a function of measure. The greatest contrast is between the sustained/i/and word repetition tasks for average and median measures and between the word repetition and sentence tasks for the normalized average measure. Thus, the second component may reflect between-task differences in TA EMG amplitude. The highest cumulative variance is explained by analysis of average TA activity across all tasks. Figure 5 shows individual SD subjects plotted as a function of their weights on the first and second components. SD subjects are represented by the symbols referenced in Table 1. Values for the first component are shown on the x-axis. Values for the second component are shown on the y-axis. Use of the same symbols permits examination of the relation between clinical/perceptual rating and the model. SD subjects are widely distributed along both components in Fig. 5. Distinct subgroup clusters are not present in either dimension considered separately. However, visual examination of the figure suggests that the SD subjects can be subgrouped in 0.6

0.4

*

A

0.2 o

© /

0.0

\

,' x

v~', J

-0.2

-0.4 -3

~ -2

' -I

~7

' 0

~ I

Principal

' 2

Component

' 3

' 4

5

!

FIG. 5. Within-group model of average thyroarytenoid activity

for spasmodic dysphonia subjects. Subjects are represented as their weights on the two components. For details see the text.

Journalof Voice, Vol.

9, No. I, 1995

12

B. C. W A T S O N E T AL.

the two-dimensional space. This grouping is illustrated by the dashed line. SD subjects enclosed within the line have relatively low weights on both components, whereas SD subjects outside the line have relatively high weights on at least one component. Two of six SD subjects enclosed by the line were rated as severe (one abductor, one adductor). The remaining subjects received ratings ranging from mild to moderate-to-severe. Five of six SD subjects (83%) enclosed by the line presented primarily abductor or mixed spasms. Four of five SD subjects (80%) outside the line were rated as severe; the fifth subject was rated as moderate. Five of five SD subjects outside the line presented primarily adductor spasms. The two SD subjects who received the highest weightings on both components were rated as showing severe vocal spasms as well as moderate to severe (a) or severe (O) vocal tremor. Eigenvalues for the second component differed as a function of task. Eight of 11 SD subjects clustered between 0.07 and -0.20 on the second component. Values within this range are dominated by the eigenvalue for the sentence task. Thus, most SD subjects, regardless of symptom type or severity, showed greater EMG amplitude for the sentence task than for the sustained vowel or word repetition tasks. DISCUSSION Heterogeneity in the quality and task sensitivity of vocal symptoms in SD has raised the question of whether diverse symptoms in this population represent one disorder or two. The present study used quantitative measures of EMG amplitude to document the neuromotor foundation of vocal symptoms and thereby test the single- and dual-disorder hypotheses. Quantitative measures were used to develop statistical models. The first model examined the amplitude of EMG activity in SD subjects relative to normal controls. The second model examined the amplitude of EMG activity among SD subjects. Analysis of any single amplitude measure across multiple tasks explained more between-group variance than did analysis of multiple measures and tasks or of multiple measures for any one task. This finding is consistent with previous reports that abnormalities in SD are task dependent (10,12,19). However, the PCA of all measures and tasks revealed the smallest cumulative explained variance Journal of Voice, Vol. 9, No. 1, 1995

(R z = 0.765). Failure to explain a larger amount of the variance in this analysis may reflect the greater amount of variability to be explained given six measures across three tasks. This assumption is supported by observation of higher cumulative explained variance in subsequent analyses that contained fewer variables. While PCA of the median amplitude measure across all tasks yielded the highest cumulative explained variance, this measure did not result in good discrimination of the two groups. Perfect discrimination was obtained for the normalized average measure across all tasks. Indeed, the first component in the PCA for normalized average amplitude across tasks returned an R 2 value of 0.984. That is, the first component alone explained >98% of the variance. This finding supports Ludlow's suggestion that EMG amplitude normalization (i.e., with reference to a task that elicits presumed physiologic maximum activation of a given muscle) may be critical in quantitative analyses of EMG data. The normalization process eliminates the influence of amplifier settings, size of the electrode recording field, and properties of the muscle tissue (33). Eliminating these sources of variability in the EMG signal facilitates identification of differences between normal control and SD subjects. Normalization also facilitates comparison of EMG findings across studies and laboratories. Eigenvectors for the first component in the between-group model were equally weighted across the three tasks. We interpret this component as an index of magnitude of TA activity relative to normal controls irrespective of task. All SD subjects, regardless of perceived symptom quality, showed increased TA activity relative to normal controls. Indeed, the two SD subjects who showed the highest positive weights on this component were rated as abductor and mixed SD by clinical/perceptual criteria. The dual-disorder hypothesis predicts that only subjects who show primarily strain-strangle s y m p t o m s associated with a d d u c t o r y spasms should show elevated levels of TA activity. Thus, the present findings do not support the hypothesis that the vocal spasms identified as abductor and adductor SD are manifestations of different disorders. It is, however, consistent with recent descriptions of SD as a focal laryngeal dystonia that affects all intrinsic laryngeal muscles (25). Individual subject weights along this component provide objective quantification of the magnitude of EMG abnormality. Such quantification is critical for documenting

STA TI STI C A L A N A L YSES OF EMG A M P L I T U D E I N SD

the presence and degree of neuromotor abnormality and the efficacy of treatments whose goal is a reduction in neuromotor activity (for example, RLN section and Botulinum injection). Eigenvectors for the second component in the between-group model showed different weights for the three tasks. We interpret this component as an index of the task sensitivity of vocal symptoms in SD relative to normal controls. Clustering of normal controls near the zero value for this component indicates no task sensitivity of EMG amplitude. Dispersion of SD subjects along this component indicates the task sensitivity of TA activity. Four of I 1 $D subjects showed positive weights indicative of highest TA activity for the word repetition task. ~our of 11 SD subjects showed negative weights indicative of highest TA activity for the sentence task. Thus, eight of 11 SD subjects showed increased TA activity as tasks increased in complexity. Further, these eight subjects differed in clinical/ perceptual ratings of symptom severity and quality. Observation of a task sensitivity effect for the majority of SD subjects supports theories of SD that posit disruption at relatively high levels of the CNS as the source of laryngeal neuromotor abnormality. Observation of a task sensitivity effect across SD subjects who differ in symptom quality supports the single-disorder hypothesis. In sum, the betweengroup model provides quantitative indices of the magnitude and task sensitivity of laryngeal neuromotor abnormality in SD and supports the singledisorder hypothesis. The within-group model sought to identify a neuromotor basis for the heterogeneity of clinical/ perceptual ratings of symptom quality and of the task sensitivity of vocal symptoms. Analysis of any single amplitude measure across multiple tasks explained more within-group variance than did analysis of multiple measures and tasks or of multiple measures for any one task. PCA of the average amplitude measure yielded the highest cumulative explained variance. The first and second components in the within-group model represented overall TA amplitude and task sensitivity of TA amplitude, respectively. If the within-group model had achieved orthogonal separation of our SD subjects along one or both of the components, then the dual-disorder hypothesis would have been supported. However, we failed to achieve good separation of the SD subjects along either component. Instead, SD subjects were distributed continuously along both components.

13

However, we can identify a central core of subjects and a surrounding "orbit" of subjects. The SD subjects who form the "orbit" in this model received clinical/perceptual ratings of moderate to severe strain-strangle quality with moderate to severe vocal tremor. The SD subject at the aphelion of the "orbit" was rated the most severe by clinical/perceptual evaluation of spasms and of vocal tremor. With the exception of one severe adductor SD, the subjects who form the central core received clinical/perceptual ratings ranging from mild mixed strain-strangle/breathy to s e v e r e breathy and from no vocal tremor to moderate vocal tremor. The SD subject at one extreme of this core was rated as a severe abductor SD, with no perceivable vocal tremor. The severe abductor SD subject with no vocal tremor and the severe adductor SD subject with severe vocal tremor can be considered as endpoints of a continuum of symptom quality among SD subjects (8). Observation of a continuum of neuromotor abnormality associated with qualitatively different vocal symptoms is consistent with the single-disorder hypothesis. The distribution of SD subjects along the second component reveals a cluster of subjects (7 of 11 ; 63%) in a region dominated by the contribution of TA amplitude during the sentence task. This cluster includes all subjects from the central core and the severe adductor SD at aphelion. Two subjects in this cluster were rated as severe adductor SD; the remainder was rated as mixed or abductor SD. Two of 11 subjects with the lowest weights on the second component showed consistently high TA amplitude across all three tasks. Finally, 2 of 11 subjects with the highest weights on the second component showed highest TA amplitude for the word repetition task. In sum, task sensitivity of TA abnormality was observed for subjects who showed adductor, abductor, and mixed vocal symptoms. This finding supports the single-disorder hypothesis and implicates higher cortical areas in the motor control deficit underlying SD. Results of this study reveal the potential use of statistical modeling of quantitative EMG data in the study of normal and abnormal vocal function. The PCA technique used here may be particularly informative for data sets that contain multiple EMG measures across multiple laryngeal muscles and tasks. In this case, weights for each component should reflect relative contribution of activity in a given muscle to performance of a given task. Freeman et al. (9) cautioned that clinical/perJournal of Voice, Vol. 9, No. 1, 1995

14

B. C. W A T S O N E T AL.

ceptual ratings of vocal symptoms in SD include contributions of underlying neuromotor abnormality plus idiosyncratic compensations. We expect that models which include data from additional laryngeal muscles, in particular p o s t e r i o r cricoarytenoid, will further clarify relations between perceptual ratings, neuromotor abnormality, and compensatory strategies. Multimuscle and multitask analyses may also be useful in studies of the control of vocal fundamental frequency and intensity. Finally, statistical modeling techniques may be informative in elucidating relations among levels of measurement of vocal function (i.e., kinematic and EMG). In this case, correlation and regression analyses can be used to identify redundancies among levels of measurement and relations among levels of measurement, respectively. Another future application of statistical modeling techniques is the development of statistical models of normal and abnormal vocal function. Measures taken in multiple domains for a variety of tasks can be reduced through correlation and regression analyses and combined through PCAs to yield a multidimensional space. A confidence sphere can then be described in the axes of the first several principal components (with a sufficient sample size, the specific confidence level of such a sphere can be determined statistically). This sphere provides a profile of a given subject group. Individual subjects can then be compared to the confidence sphere for various diagnostic groups to determine the nature and extent of overlap among patient groups or between normal control and patient groups. Such analyses will facilitate development of objective, quantitative measures of vocal function, will help to advance theories of normal and abnormal vocal function, and may be useful in differential diagnosis and the design of appropriate therapeutic strategies. Acknowledgment: Data analyzed for this study represent a portion of the data reported by Schaefer et al. (28). Research support was provided in part by NIH grant DC00410.

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4. Dedo HH, Townsend JJ, lzdebski K. Current evidence for the organic etiology of spastic dysphonia. Otolaryngol Head Neck Surg 1978;86:875--80. 5. Shipp T, Mueller P, Zwitman D. Intermittent abductory dysphonia. J Speech Hear Res 1980;45:283. 6. Karnell M. Adductor and abductor spasmodic dysphonia: related until proven otherwise. Am J Speech Lang Pathol 1992;1:17--8. 7. Watterson T, McFarlane S. Adductor and abductor spasmodic dysphonia: different disorders. Am J Speech Lang Pathol 1992;1:19-20. 8. Cannito M, Johnson J. Spastic dysphonia: a continuum disorder. J Commun Disord 1981; 14:215-23. 9. Freeman FJ, Cannito M, Finitzo T. Classification of spasmodic dysphonia by visual, perceptual, and acoustic means. In: Gates G, ed. Spastic dysphonia: state of the art. New York: Voice Foundation, 1985:5-18. 10. Bloch CS, Hirano M, Gould WJ. Symptom response of spastic dysphonia in response to phonatory tasks. Ann Otol Rhinol Laryngol 1985;94:51-4. 11. Freeman FJ, Schaefer SD. Theory and research in voice disorders. In: Lawrence V, ed. Proceedings of the eleventh symposium on the care of the professional voice. New York: Voice Foundation, 1982:14--24. 12. Schaefer SD, Watson BC, Freeman FJ, et al. Vocal tract electromyographic abnormalities in spasmodic dysphonia: a preliminary report. Trans Am Laryngol Assoc 1987;108:18796. 13. Aronson A, Brown JR, Litin EM, Pearson JS. Spastic dysphonia. 1. Voice, neurologic, and psychiatric aspects. J Speech Hear Disord 1968;33:203-18. 14. Wolfe V, Bacon M. Spectrographic comparison of two types of spastic dysphonia. J Speech Hear Disord 1976;41:325-32. 15. Zwitman D. Bilateral cord dysfunctions: abductor type spastic dysphonia. J Speech Hear Disord 1979;44:373--8. 16. Freeman FJ, Finitzo T. Spasmodic dysphonia, whether and where: results of seven years of research. J Speech Hear Res 1989;32:541-55. 17. Pool KD, Freeman FJ, Finitzo T, et al. Heterogeneity in spasmodic dysphonia: neurologic and voice findings. Arch Neurol 1991;48:305-9. 18. Devous MD, Pool KD, Finitzo T, et al. Evidence for cortical dysfunction in spasmodic dysphonia: regional cerebral blood flow and quantitative electrophysiology. Brain Lang 1990; 39:331--44. 19. Watson BC, Freeman FJ, Pool KD, et al. Laryngeal reaction time profiles in spasmodic dysphonia: relation to cortical electrophysiologic abnormality. J Speech Hear Res 1991;34: 269--78. 20. Tarasch H. Muscle spasticity in functional aphonia and dysphonia. Med Woman's J 1946;53:25-33. 21. Blair RL, Berry H, Briant TD. Laryngeal electromyography: techniques and application. Otolaryngol Clin North Am 1978; I 1:325-46. 22. Fritzell B, Feuer E, Haglund S, Knutsson E, Schiratzki H. Experience with recurrent laryngeal nerve section for spastic dysphonia. Folia Phoniatr (Basel) 1982;34:160-7. 23. Hirose H. Electromyography of the larynx and other speech organs. In: Sawashima M, Cooper F, eds. Dynamic aspects of speech production Tokyo: University of Tokyo Press, 1981:49--65. 24. Rabuzzi D, McCall G. Spasmodic dysphonia. Trans Am Acad Ophthalmol Otolaryngol 1972;76:724--8. 25. Blitzer A, Lovelace RE, Brin M, Fahn S, Fink ME. Electromyographic findings in focal laryngeal dystonia (spastic dysphonia). Ann Otol Rhinol Laryngol 1985;94:591-4.

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29. Dillon WR, Goldstein M. Multivariate analysis: methods and application. New York: Wiley, 1984. 30. Gay T, Hirose H, Strome M, Sawashima M. Electromyography of the intrinsic laryngeal muscles during phonation. Ann Otol Rhinol Laryngol 1972;81:401-9. 31. Hirano M, Ohala J. Use of hooked-wire electrodes for electromyography of the intrinsic laryngeal muscles. J Speech Hear Res 1969;12:362-73. 32. Freeman FJ, Ushijima T. Laryngeal activity during stuttering. J Speech Hear Res 1978;21:538--62. 33. De Luca CJ. Physiology and mathematics of myoelectric signals. IEEE Trans Biomed Eng 1979;26:313-25.

Journal of Voice. Vol. 9, No. 1, 1995