A digital tool for monitoring speech decline in ALS

NIH RePORTER · NIH · R42 · $976,474 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease resulting in the progressive loss of limb, trunk, and head and neck (bulbar) motor function and is the most common adult-onset motor neuron disease. The disease is characterized by significant across-patient heterogeneity in the onset region and in pattern and progression rate, making early and accurate diagnosis difficult. Most individuals with ALS will eventually acquire bulbar symptoms, including a loss of speech and swallowing. The social and psychological impact of communication loss on the quality of life of patients with ALS is significant and a diagnostic tool to detect these changes early, accurately, and easily remains unmet. Moreover, improved speech testing tools are critically needed in ALS to (1) improve diagnostic testing and monitoring, and (2) expediting clinical trials of behavioral and pharmacologic interventions. Although speech testing is a core component of many neurological assessment batteries, few commercial digital speech monitoring tools have been developed or scientifically validated, especially for ALS. This project aims to develop and scientifically validate a digital speech assessment tool – the Modality Digital Speech Monitoring Tool (M- DSMT) - for monitoring speech decline due to ALS. The M-DSMT is fully automated, online, objective, scalable, accessible, and is used in real-time. The tool is operating-system and device-agnostic, running on commercially available laptops, tablets, or smartphones. Therefore, if demonstrated to be effective, the proposed tool can be rapidly commercialized and deployed into standard care and clinical trials for ALS. Our specific aims are to (1) optimize the quality and yield of remote audio and video recordings for automated measurement, (2) determine the analytical validity of the M-DSMT, (3) determine the clinical validity of the M-DSMT, and (4) determine the usability of the M-DSMT. This project's objectives are to improve diagnosis for patients with ALS, decrease costs of speech assessment, and allow patients who have difficulty traveling to continue to have access to regular speech assessments. Ultimately, we aim to improve the quality of care in persons with ALS and facilitate ongoing efforts to discover a cure for this fatal disease through the development of this innovative technology.

Key facts

NIH application ID
10875504
Project number
5R42DC019877-03
Recipient
MODALITY.AI , INC
Principal Investigator
JORDAN R GREEN
Activity code
R42
Funding institute
NIH
Fiscal year
2024
Award amount
$976,474
Award type
5
Project period
2022-06-01 → 2026-05-31