A Fine-Grained Temporal Analysis of Multimodal Oral Diadochokinetic Performance to Assess Speech Impairment in...

This study used a semiautomated fine-grained temporal analysis to extract features of temporal oral diadochokinetic (DDK) performance across multiple modalities and tasks, from neurologically healthy and impaired individuals secondary to amyotrophic lateral sclerosis (ALS). The aims were to (a) delineate temporal oral DDK deficits relating to the neuromotor pathology of ALS and (b) identify the optimal task-feature combinations to detect speech impairment in ALS.

Mandibular myoelectric, kinematic, and acoustic data were acquired from 13 individuals with ALS and 10 healthy controls producing three alternating motion rate tasks and one sequential motion rate task. Twenty-seven features were extracted from the multimodal data, characterizing three temporal constructs: duration/rate, variability, and coordination. The disease impacts on these features were assessed across tasks, and the task eliciting the greatest disease-related change was identified for each feature. Such "optimal" task-feature combinations were fed into logistic regression to differentiate individuals with ALS from healthy controls.

Temporal deficits in ALS were characterized by (a) increased duration and variability and reduced coordination of jaw muscle activities, (b) increased duration and variability and altered temporal symmetry of jaw velocity profile, (c) increased muscle-burst-to-peak-velocity duration, and (d) increased motion-to-voice onset duration. These temporal features were differentially affected across tasks. The optimal task-feature combinations, which were further clustered into three composite factors reflecting temporal variability, coarser-grained duration, and finer-grained duration, differentiated ALS from controls with an F1 score of 0.86 (precision = 1.00, recall = 0.75).

Temporal oral DDK deficits are likely attributed to a hierarchy of interrelated neurophysiological and biomechanical factors associated with the neuromotor pathology of ALS. These deficits, as assessed crossmodally, provide previously unavailable insights into the multifaceted timing impairment of oromotor performance in ALS. The optimal task-feature combinations targeting these deficits show promise as quantitative markers for (early) detection of speech impairment in ALS.