Journal of Movement Disorders

Original Article

Reliability and Validity of the Embouchure Dystonia Severity Rating Scale: Tobias Mantel, André Lee, Shinichi Furuya, Masanori Morise, Eckart Altenmüller, Bernhard Haslinger; J Mov Disord. 2023;16(2):191-195. Published online May 24, 2023; DOI: https://doi.org/10.14802/jmd.22213

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Objective
Embouchure dystonia (ED) is a task-specific movement disorder that leads to loss of fine motor control of the embouchure and tongue muscles in wind musicians. In contrast to musicians’ hand dystonia, no validated severity rating for ED exists, posing a major obstacle for structured assessment in scientific and clinical settings. The aim of this study is to validate an ED severity rating scale (EDSRS) allowing for a standardized estimation of symptom severity in ED.
Methods
The EDSRS was set up as a composite score of six items evaluating audio-visual disease symptoms during the performance of three standardized musical tasks (sustained notes, scales, and fourths) separately for each body side. For validation, 17 musicians with ED underwent standardized audiovisual recordings during performance. Anonymized and randomized recordings were assessed by two experts in ED (raters). Statistical analysis included metrics of consistency, reliability, and construct validity with the fluctuation of the fundamental frequency of the acoustic signal (F0) (extracted in an audio analysis of the sustained notes).
Results
The EDSRS showed high internal consistency (Cronbach’s α = 0.975−0.983, corrected item-total correlations r = 0.90−0.96), interrater reliability (intraclass correlation coefficient [ICC] for agreement/consistency = 0.94/0.96), intrarater reliability over time (ICC per rater = 0.93/0.87) and good precision (standard error of measurement = 2.19/2.65), and correlated significantly with F0 variability (r = 0.55–0.60, p = 0.011–0.023).
Conclusion
The developed EDSRS is a valid and reliable tool for the assessment of ED severity in the hands of trained expert raters. Its easy applicability makes it suitable not only for routine clinical practice but also for scientific studies.

Citations

Citations to this article as recorded by

Preventing Musician’s Focal Dystonia: A guide for music educators
Anna Détári, Eckart Altenmüller
International Journal of Music Education.2025;[Epub] CrossRef

Brief communication

Phonatory Characteristics of Male Patients with Classic Essential Tremor: Preetie Shetty Akkunje, Belur Keshavaprasad Yamini, Ravi Yadav, Nagarajarao Shivashankar, Palash Kumar Malo, Kandavel Thennarasu, Shantala Hegde, Pramod Kumar Pal; J Mov Disord. 2021;14(3):226-230. Published online August 18, 2021; DOI: https://doi.org/10.14802/jmd.21010

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Abstract PDF Supplementary Material

Objective
Voice tremor (VT) is one of the characteristics of essential tremor (ET). This study was designed to describe the group and phonatory characteristics of classic ET patients with VT.
Methods
This retrospective case-control study compared classic ET patients with age and sex-matched controls. The ET population was subgrouped based on auditory perceptual voice analysis. Electroglottography and acoustic voice samples obtained from both groups were analyzed for contact quotient (CQ) and multidimensional voice program parameters, i.e., fundamental frequency (F₀), perturbation, noise, and tremor parameters.
Results
The CQ, F₀, perturbation, noise, and tremor characteristics significantly increased from the moderate VT group to the severe VT group.
Conclusion
The CQ, F₀, and noise characteristics reflected the vocal folds’ functionality. The perturbation and tremor parameters variation were reasoned considering the tremor-related changes occurring in the laryngeal, vocal tract, and expiratory muscles in patients with ET. Thus, phonatory analysis may help in monitoring the progression of ET.

Citations

Citations to this article as recorded by

Voice Analysis in Patients with Essential Tremor
Hakan Silek, Muzeyyen Dogan
Journal of Voice.2025; 39(5): 1414.e9. CrossRef
Central auditory processing deficits in essential tremor
Preetie Shetty Akkunje, Belur Keshavaprasad Yamini, Ravi Yadav, Shantala Hegde, Aravind Kumar Rajasekaran, Pradeep Yuvaraj, Prashasti Prakash Poovaiah, Parthipulli Vasuki Prathyusha, Kandavel Thennarasu, Nagarajarao Shivashankar, Pramod Kumar Pal
Clinical Neurophysiology.2025; 176: 2110764. CrossRef
Exploiting speech tremors: machine learning for early diagnosis of amyotrophic lateral sclerosis
Ritu Chauhan, Urvashi Sharma
Engineering Research Express.2024; 6(4): 045224. CrossRef

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