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Conceptual and Clinical Updates on Vocal Tremor

2010; American Speech–Language–Hearing Association; Volume: 15; Issue: 14 Linguagem: Inglês

10.1044/leader.ftr2.15142010.16

1085-9586

Julie Barkmeier‐Kraemer, Brad H. Story,

Botulinum Toxin and Related Neurological Disorders

You have accessThe ASHA LeaderFeature1 Nov 2010Conceptual and Clinical Updates on Vocal Tremor Julie Barkmeier-Kraemer, andPhD, CCC-SLP Brad StoryPhD Julie Barkmeier-Kraemer Google Scholar , PhD, CCC-SLP and Brad Story Google Scholar , PhD https://doi.org/10.1044/leader.FTR2.15142010.16 SectionsAbout ToolsAdd to favorites ShareFacebookTwitterLinked In Tremor can affect nearly any part of the body that can be moved voluntarily. When tremor affects muscles within the speech mechanism and causes involuntary rhythmic modulation of the voice, it is referred to as vocal tremor. The perceptual threshold findings indicate that the magnitude of tremor necessary before listeners can perceive the presence of a vocal tremor is unequal across each of the sources tested. Laryngeal-based tremors (i.e. F0 and glottal width) were the easiest to detect compared to tremor originating from the respiratory system, or from the pharynx. A second finding was the superior ability of acoustic methods to detect and measure vocal tremor compared to perceptual methods. This finding would suggest that the best clinical evaluation tool for detecting the presence of a vocal tremor is acoustic measurement. Vocal tremor is considered a neurogenic voice disorder and is described as having a nearly rhythmic alteration, or modulation, in pitch and loudness. Individuals most commonly seeking treatment for vocal tremor also tend to have essential tremor, Parkinson's disease, and spasmodic dysphonia. The primary treatment approach for these individuals is medical intervention. Speech-language pathologists with expertise in voice disorders may offer treatment to reduce any increased muscle tension in the speech mechanism associated with compensatory strategies used during speaking. However, the literature offers little instruction or evidence that intervention by SLPs can be helpful to those with vocal tremor. A conceptual model of vocal tremor is being investigated at the University of Arizona. The goal of this research is to characterize the contribution of each component of the speech mechanism to the perceptual and acoustic patterns of vocal tremor and to use this information to improve on current methods for evaluating and treating vocal tremor. Characteristics of Vocal Tremor Perceptual and acoustic characterization of vocal tremor is best achieved during a sustained phonation task (Brown & Simonson, 1963; Barkmeier, Case, & Ludlow, 2001). This result is likely because the typical rate of speech averages five syllables per second and the voice turns off and on for individual phonemes at a rate that is faster than the rate of the tremor. Interestingly, a common strategy used by individuals with vocal tremor is to slow their rate of speech to an average of three syllables per second (Lundy, Roy, Xue, Casiano, & Jassir, 2004). This speaking pattern may offer greater opportunity for listeners to hear the vocal tremor during prolonged voicing of speech sounds. Acoustic measures have been used to describe the rate of modulation of fundamental frequency and intensity and are reported to vary between 3–12 times per second (Hz). In addition, the magnitude of fundamental frequency or intensity modulation can range between 3%–15% and 19%–56% of the mean, respectively (Brown & Simonson, 1963; Ramig & Shipp, 1987; Dromey, Warrick, & Irish, 2002). Modulation rate and magnitude also may change at different levels of pitch and loudness (Dromey et al., 2002). Of particular interest to our research group is the degree of individual variability in vocal tremor patterns reported by several studies. Many factors may contribute to this variability, including etiology, type of tremor (e.g., resting, postural, action), age, duration since onset, and affected musculature. Most clinical and research efforts focus on the contribution of the laryngeal musculature to vocal tremor. However, further investigation of laryngeal contributions to perceptual and acoustic patterns of vocal tremor and of the contributions of the respiratory system and articulators is needed. Previous studies described the presence of tremor in musculature affecting the respiratory and articulatory components of the speech mechanism. However, the focus of prior work did not characterize the contribution of affected musculature to associated acoustic and perceptual patterns of the vocal tremor. Thus, using the ability to isolate and manipulate each component of the speech mechanism and study the resulting output would be a valuable approach for improving understanding of the underlying physiology of vocal tremor and its associated acoustic and perceptual traits. Such an approach is impossible to conduct directly in individuals with vocal tremor. However, computer modeling of the speech mechanism allows us to manipulate each part of the speech mechanism and study the resulting output. Hypotheses developed using this approach can then be tested in those affected by vocal tremor. Acoustic Analysis Using Computer Modeling Speech is produced by an orchestration of muscle activity that generates pressure in the respiratory system, adducts the vocal folds, and sets the configuration of the vocal tract. In a typical operating state, this process results first in generation of a steady pressure from the respiratory system necessary to set the vocal folds into vibration, and then creates a sound wave that travels (propagates) through the airspaces of the trachea, pharynx, and oral cavity. The "speech signal" is the sound pressure that radiates from the open space at the lips. This process is illustrated in Figure 1 [PDF]. The constant "Pressure" shown at the bottom is representative of bronchial pressure developed by respiratory forces. Subsequent vocal fold vibration generates a glottal airflow signal as indicated in the middle left part of the figure, and propagation of this signal through the vocal tract (as labeled by "Pharynx" and "Oral Cavity") produces the speech waveform. This figure is a graphic representation of a computational speech production model that is capable of generating a wide range of speech material (Story, 1995; Story, 2005; Titze, 2006). A problem in studying vocal tremor using only the speech signal, however, is that the source of the tremor [i.e., the anatomical structure(s) with unintended oscillatory movement] is typically unknown, so even an extensive analysis of the signal doesn't necessarily provide specific information about the origin of the tremor. As a step toward understanding how different sources of tremor contribute to the acoustic characteristics of the speech signal, we have begun using our computational model, as shown in Figure 1, to impose tremor-like oscillations on different components of the speech production system. The advantage is that the location and degree of imposed oscillation are controlled entirely by the investigator, so that the origin of any modulation present in the output speech signal is known. For instance, the bronchial pressure could be varied in amplitude to simulate a pure respiratory tremor. The modulations observed in the output signal could then be related directly to the oscillation of the bronchial pressure. The bottom three panels of Figure 2 [PDF] show waveforms produced when the bronchial pressure is modulated three times per second (3 Hz) with a magnitude of 20%; the vocal tract shape was configured to produce a neutral vowel. The variation in pressure is transferred to the amplitude of the glottal airflow (Ug) produced by vocal fold vibration and finally to the output speech signal (Pout). The upper two panels show analyses of fundamental frequency (F0) and intensity performed on the speech signal. Note that the intensity contains a modulation, but the fundamental frequency (F0) is flat over the time course of the vowel because only the bronchial pressure was modulated. Other independent sources of tremor, such as oscillation of vocal fold adduction, fundamental frequency of vibration, or vocal tract shape also can be imposed using this model. Thus, this approach is being used to learn how a wide range of isolated tremor sources contributes to the amplitude and frequency modulations observed through analysis of the speech signal. That is, an acoustic profile will be developed for each type of tremor-like oscillation of the speech production system. A next step is to simulate vowel sounds based on combinations of multiple tremor sources simultaneously imposed on the system. Using the knowledge gained from the independent source analysis, we hope to develop an algorithm that will allow us to identify multiple sources of tremor from the acoustic recording of a patient. Studying Perception by Source In addition to the acoustic analysis of vocal tremor, we addressed how well listeners can detect vocal tremor originating from the respiratory, phonatory, and articulatory sources. A set of preliminary experiments using the speech production model studied the magnitude of tremor simulated across four different sources. The range of tremor magnitude was varied from 0% to 30% of the average value for bronchial pressure (i.e., respiratory tremor), F0 (i.e., vocal fold length change), glottal width (i.e., vocal fold adduction/abduction), and pharyngeal diameter (i.e., vocal tract). In experiments for each of four sources of tremor, naïve and expert listeners were asked to listen to a pair of simulated productions of /a/ and judge them to sound the same or different. One of the paired signals presented without modulation. The other paired signal presented a magnitude of modulation that ranged between 0% and 30%. Threshold was achieved when listeners could detect with accuracy when the two signals differed on three of four trials. In addition, the magnitude at which vocal temor was perceptually detected was compared to the magnitude at which it was acoustically detected and measured. As shown in Figure 3 [PDF], expert and naïve listeners performed similarly using this perceptual testing paradigm with a slightly improved average performance by expert listeners on the respiratory source tremor. The perceptual threshold findings indicate that the magnitude of tremor necessary for listeners to perceive a vocal tremor is unequal across each of the tested sources. Laryngeal-based tremors (i.e., F0 and glottal width) were the easiest to detect compared to tremor originating from the respiratory system or pharynx. In fact, many naïve listeners did not achieve a threshold of detection for the respiratory-based tremor, indicating that this source of vocal tremor may be the most difficult for listeners to hear. A second finding of great interest was the superior ability of acoustic methods to detect and measure vocal tremor compared to perceptual methods. This finding would suggest that the best clinical evaluation tool for detecting the presence of a vocal tremor is acoustic measurement. Research is underway to determine the perceptual and acoustic correlates for each of the tremor sources and their combinations using the speech production model. Findings from these modeling experiments will be compared to physiologic, perceptual, and acoustic findings in individuals presenting with vocal tremor. Investigating Vocal Tremor and Connected Speech Although sustained phonation tasks are used to detect and characterize vocal tremor, little is known about how sustained voicing characteristics reflect connected speech patterns. Given that vocal tremor is perceived best during prolonged voicing, we hypothesized that shortened voicing durations during connected speech would reduce the opportunity to hear the vocal tremor. Two studies investigated this hypothesis in two different ways. The first study presented naïve listeners with several repetitions of five speakers' productions of "Pop took his socks off" and "We were away a year ago." The first sentence is loaded with voiceless speech sounds anticipated to reduce voicing duration. The second sentence contains all-voiced speech sounds requiring constant voicing. Thus, speakers were expected to be judged as having less severe vocal tremor during production of the first sentence compared to the second. All of the speakers were judged to have a moderately severe vocal tremor during sustained phonation. As shown in Figure 4 [PDF], three of the speakers showed the predicted reduction in perception of shakiness by naïve listeners during the voiceless-loaded sentence. Two speakers showed no difference in the perceived amount of shakiness between the two sentences, suggesting they did not adjust voicing duration due to more voiceless speech sounds. These results motivated a second approach to investigate the relation of voicing duration to perceived vocal tremor severity during connected speech. A 2008 undergraduate honors thesis by Twohig and Finnegan at the University of Iowa addressed the association between severity of perceived vocal tremor and the duration of voicing segments. They asked eight female speakers with vocal tremor to produce several sentences using either a legato or staccato manner to manipulate voicing duration. An SLP with expertise in voice disorders and an undergraduate student rated the severity of vocal tremor for each of the recorded utterances using a 100-mm visual analog scale. Speakers producing an average voicing segment duration below 500 ms were rated as having mild or no tremor compared to voicing segments longer than 500 ms that were rated as having moderate to severe vocal tremor. This finding suggests that individuals with vocal tremor who are able to reduce voicing duration during connected speech may reduce listener perception of vocal tremor. Evaluation and Treatment These preliminary research findings help address whether voice and speech production tasks can elucidate the affected speech mechanism musculature. Comparisons will be made between vocal tremor acoustic patterns and associated physiologic patterns to test hypotheses regarding contributions predicted from each component of the speech mechanism to vocal tremor. This information will be used to design a treatment protocol aimed at modifying connected speech patterns to reduce the opportunity for listeners to hear the vocal tremor. Preliminary outcomes suggest that SLPs may be able to offer individuals with vocal tremor a speech treatment option in the near future (Barkmeier-Kraemer, Lato, & Wiley, in press). References Barkmeier J.M., Case J.L., & Ludlow C.L. (2001). Identification of symptoms for spasmodic dysphonia and vocal tremor: a comparison of expert and non-expert judges.Journal of Communication Disorders, 34, 21–37. Google Scholar Bové M., Daamen N., Rosen C., Wang C. C., Sulica L., & Gartner-Schmidt J. (2006). Development and validation of the vocal tremor scoring system.The Laryngoscope, 116, 1662–1667. Google Scholar Brown J.R., & Simonson J.(1963). Organic voice tremor: A tremor of phonation.Neurology, 13, 520–525. Google Scholar Dromey C., Warrick P. & Irish J. (2002). 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(1987). Voice tremor: Dysregulation of voluntary expiratory muscles.Neurology, 37,117–122. CrossrefGoogle Scholar Twohig A. & Finnegan I. (2008). The effect of vowel duration on tremor severity for patients with vocal tremor. Unpublished undergraduate thesis, University of Iowa, Iowa City. Google Scholar Warrick P., Dromey C., Irish J., Durkin L. (2000).The treatment of essential voice tremor with botulinum toxin A: A longitudinal case report.Journal of Voice, 14(3), 410–421. Google Scholar Warrick P., Dromey C., Irish J.C., Durkin L., Pakiam A., & Lang A. (2000). Botulinum toxin for essential tremor of the voice with multiple anatomical sites of tremor: A crossover design study of unilateral versus bilateral injection.The Laryngoscope, 110,1366–1374. Google Scholar Author Notes Julie Barkmeier-Kraemer, PhD, CCC-SLP, is an associate professor at the University of Arizona. Her clinical and research efforts investigate neural controls of the larynx during respiration, deglutition, and voice production with particular focus on neurogenic voice disorders. Contact her at [email protected]. Brad Story, PhD, is associate professor of speech, language, and hearing sciences at the University of Arizona. His research is focused on the acoustics, mechanics, and physiology of human sound production. Contact him at [email protected]. Advertising Disclaimer | Advertise With Us Advertising Disclaimer | Advertise With Us Additional Resources FiguresSourcesRelatedDetailsCited byJournal of Speech, Language, and Hearing Research62:10 (3689-3705)25 Oct 2019Objective Acoustic Quantification of Perceived Voice Tremor SeverityYouri Maryn, Marc Leblans, Andrzej Zarowski and Julie Barkmeier-Kraemer Volume 15Issue 14November 2010 Get Permissions Add to your Mendeley library History Published in print: Nov 1, 2010 Metrics Current downloads: 1,318 Topicsasha-topicsleader_do_tagasha-article-typesCopyright & Permissions© 2010 American Speech-Language-Hearing AssociationLoading ...