*Presented at the NEALS Conference 2026

Introduction:

Problem: ALS progressively impairs both speech and respiratory function, but episodic clinic visits often fail to capture rapid functional decline.

Opportunity: Longitudinal, at-home digital monitoring can bridge this gap by tracking acoustic and respiratory biomarkers remotely.

Objectives: Evaluate the relationship between remote speech metrics and remote spirometry, and validate both against clinical disease severity.

Methods:

Speech and respiratory data taken from the Target ALS Global Natural History Study were analyzed [1]. 

 Superior sensitivity: Acoustic metrics differentiate ALS onset phenotypes that standard spirometry cannot distinguish.

Subclinical detection: Articulation rate identifies subclinical bulbar impairment in spinal-onset ALS prior to overt clinical decline.

Clinical trial utility: ki:elements' automated speech pipeline provides an objective, scalable framework for decentralized monitoring.