Abstract
Introduction/Aims: There is a substantial need to establish reliable approaches for low-burden at-home monitoring of respiratory function for people with amyotrophic lateral sclerosis (PALS). This preliminary study assessed the potential of acoustic features extracted from a smartphone passage reading task to serve as clinically meaningful outcome measures reflecting instrumental and self-reported respiratory function measures. Methods: Thirty-six PALS completed an in-clinic slow vital capacity (SVC) task, followed by at-home completion of surveys and audio recording of a reading passage using a smartphone application. Speaking rate and pause features were extracted offline. Correlation analysis evaluated the relationship between the acoustic features and both instrumental (SVC) and self-reported (respiratory subscale of the self-entry version of the ALS Functional Rating Scale-Revised; ALSFRS-RSE) measures of respiratory function. Receiver operator characteristic (ROC) with area under the curve (AUC) analysis evaluated the utility of acoustic features for classifying participants with and without respiratory involvement. Results: SVC and respiratory self-ratings were significantly correlated with pause, but not rate, measures. Percent pause time was the most strongly correlated acoustic feature with both SVC (r = −0.62) and ALSFRS-RSE respiratory subscale ratings (r = −0.43). ROC analysis revealed that percent pause time classified participants presenting with respiratory involvement based on instrumentation (SVC < 70% predicted [AUC = 0.70]; SVC < 50% predicted [AUC = 0.88]) and self-ratings when using the respiratory ALSFRS-RSE score cut-off of < 11 (AUC = 0.78), but not < 12 (AUC = 0.61). Discussion: Percent pause time, extracted from a smartphone-recorded passage reading, offers a promising index for remote assessment and monitoring of respiratory function in PALS.
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Connaghan, K. P., Eshghi, M., Haenssler, A. E., Green, J. R., Wang, J., Scheier, Z., … Berry, J. D. (2025). A Preliminary Investigation of Acoustic Features for Remote Monitoring of Respiration in ALS. Muscle and Nerve, 72(2), 321–326. https://doi.org/10.1002/mus.28435
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