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Articulation and Empirical Mode Decomposition Features in Diadochokinetic Exercises for the Speech Assessment of Parkinson’s Disease Patients

ميزات تحلل النطق والوضع التجريبي في تمارين Diadochokinetic لتقييم النطق لمرضى مرض باركنسون
Authors: Juan Camilo Vásquez-Correa; Cristian D. Ríos-Urrego; Alice Rueda; Juan Rafael Orozco-Arroyave; Sri Krishnan; Elmar Nöth;

Articulation and Empirical Mode Decomposition Features in Diadochokinetic Exercises for the Speech Assessment of Parkinson’s Disease Patients

Abstract

Les troubles de la parole sont l'une des premières manifestations chez les patients atteints de la maladie de Parkinson. En particulier, des déficiences articulaires liées à la capacité du locuteur à déplacer les membres et les muscles du tractus vocal ont été observées chez les patients. Les déficits articulaires ont été évalués chez les patients principalement à l'aide d'exercices diadococinétiques, qui consistent en la répétition rapide de syllabes comme /pa-ta-ka/. Cette étude a pris en compte différentes caractéristiques pour modéliser plusieurs aspects des exercices diadochocinétiques, notamment la capacité de démarrer/arrêter la vibration du pli vocal, le taux de parole et la régularité de la tâche diadochocinétique. Les caractéristiques d'articulation sont combinées à d'autres qui résultent d'une procédure de décomposition en mode empirique, qui ont récemment été utilisées pour modéliser la dysphonie chez les patients atteints de la maladie de Parkinson. Les caractéristiques sont utilisées pour classer les patients atteints de la maladie de Parkinson et les locuteurs en bonne santé, et pour prédire la gravité de la dysarthrie des participants selon une échelle clinique. Selon les résultats, les caractéristiques d'articulation sont capables de classer la présence de la maladie avec une précision allant jusqu'à 76 % et de prédire le niveau de dysarthrie des locuteurs avec une corrélation de Spearman allant jusqu'à 0,68.

Las alteraciones del habla son una de las manifestaciones más tempranas en pacientes con enfermedad de Parkinson. En particular, se han observado en los pacientes alteraciones de la articulación relacionadas con la capacidad del hablante para mover las extremidades y los músculos del tracto vocal. Los déficits de articulación se han evaluado en los pacientes principalmente mediante ejercicios diadococinéticos, que consisten en la repetición rápida de sílabas como /pa-ta-ka/. Este estudio consideró diferentes características para modelar varios aspectos de los ejercicios diadococinéticos, incluida la capacidad de iniciar/detener la vibración de las cuerdas vocales, la velocidad del habla y la regularidad de la tarea diadococinética. Las características de articulación se combinan con otras que resultan de un procedimiento de descomposición en modo empírico, que se han utilizado recientemente para modelar la disfonía en pacientes con Parkinson. Las características se utilizan para clasificar a los pacientes con Parkinson y a los hablantes sanos, y para predecir la gravedad de la disartria de los participantes de acuerdo con una escala clínica. De acuerdo con los resultados, las características de articulación son capaces de clasificar la presencia de la enfermedad con una precisión de hasta el 76%, y de predecir el nivel de disartria de los hablantes con una correlación de Spearman de hasta 0,68.

Speech impairments are one of the earliest manifestations in patients with Parkinson's disease. Particularly, articulation impairments related to the capability of the speaker to move the limbs and muscles of the vocal tract have been observed in the patients. Articulation deficits have been evaluated in the patients mainly using diadochokinetic exercises, which consist in the rapid repetition of syllables like /pa-ta-ka/. This study considered different features to model several aspects of the diadochokinetic exercises, including the capacity to start/stop the vocal fold vibration, the speech rate, and the regularity of the diadochokinetic task. Articulation features are combined with others that result from an empirical mode decomposition procedure, which have been recently used to model dysphonia in Parkinson's patients. The features are used to classify Parkinson's patients and healthy speakers, and to predict the dysarthria severity of the participants according to a clinical scale. According to the results, articulation features are able to classify the presence of the disease with an accuracy up to 76%, and to predict the dysarthria level of the speakers with a Spearman's correlation of up to 0.68.

إعاقات النطق هي واحدة من أقدم المظاهر في المرضى الذين يعانون من مرض باركنسون. على وجه الخصوص، لوحظت إعاقات في النطق تتعلق بقدرة المتحدث على تحريك أطراف وعضلات المجرى الصوتي لدى المرضى. تم تقييم العجز في النطق لدى المرضى بشكل أساسي باستخدام تمارين ثنائية الحركة، والتي تتكون من التكرار السريع للمقاطع مثل /pa - ta - ka/. نظرت هذه الدراسة في ميزات مختلفة لنمذجة العديد من جوانب تمارين الحركية التبادلية، بما في ذلك القدرة على بدء/إيقاف اهتزاز الطية الصوتية، ومعدل الكلام، وانتظام المهمة الحركية التبادلية. يتم دمج ميزات النطق مع الميزات الأخرى الناتجة عن إجراء تحلل الوضع التجريبي، والتي تم استخدامها مؤخرًا لنمذجة خلل النطق لدى مرضى باركنسون. تُستخدم الميزات لتصنيف مرضى باركنسون والمتحدثين الأصحاء، والتنبؤ بشدة عسر الكلام لدى المشاركين وفقًا لمقياس سريري. وفقًا للنتائج، فإن ميزات النطق قادرة على تصنيف وجود المرض بدقة تصل إلى 76 ٪، والتنبؤ بمستوى عسر الكلام للمتحدثين بارتباط Spearman يصل إلى 0.68.

Keywords

Diadochokinetic exercises, Physiology, Parkinson's disease, FOS: Political science, Health Professions, Articulation, Diagnosis and Treatment of Voice Disorders, Filter (signal processing), Pathology, Psychology, Disease, Empirical mode decomposition, Political science, Speaker Diarization, Acoustic Modeling, Politics, Audiology, Speaker Verification, Manner of articulation, Correlation, FOS: Philosophy, ethics and religion, FOS: Psychology, Speech Recognition Technology, Articulation (sociology), Physical Sciences, Medicine, Geometry, FOS: Law, Dysphagia and Swallowing Disorders, Speech recognition, Hilbert–Huang transform, Speech and Hearing, Acoustic Analysis, Artificial Intelligence, Health Sciences, FOS: Mathematics, Vocal tract, Dysarthria, Linguistics, Computer science, Philosophy, Voice Training, Physical medicine and rehabilitation, FOS: Biological sciences, Computer Science, FOS: Languages and literature, Computer vision, Repetition (rhetorical device), Law, Mathematics

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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