Characterizing vocal tremor in progressive neurological diseases via automated acoustic analyses
Abstract
Voice tremor represents a common but frequently overlooked clinical feature of neurological disease. Therefore, we aimed to quantitatively and objectively assess the characteristics of voice tremor in a large sample of patients with various progressive neurological diseases. Voice samples were acquired from 240 patients with neurological disease and 40 healthy controls. The robust automated method was designed, allowing precise tracking of multiple tremor frequencies and distinguish pathological from the physiological tremor. Abnormal tremor was revealed in Huntington's disease (65%), essential tremor (50%), multiple system atrophy (40%), cerebellar ataxia (40%), amyotrophic lateral sclerosis (40%), progressive supranuclear palsy (25%), Parkinson's disease (20%), cervical dystonia (10%), and multiple sclerosis (8%) but not in controls. Low-frequency voice tremor (<4 Hz) was common in all investigated diseases, whereas medium tremor frequencies (4-7 Hz) were specific for movement disorders of Parkinson's disease, multiple system atrophy, essential tremor, and cervical dystonia. Careful estimation of vocal tremor may help with accurate diagnosis and tailored treatment. This study provides (i) more insights into the pathophysiolog...Continue Reading
References
Citations
Voice Analysis with Machine Learning: One Step Closer to an Objective Diagnosis of Essential Tremor.
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