Use of Beiwe Smartphone App to Identify and Track Speech Decline in Amyotrophic Lateral Sclerosis (ALS)

The capacity for smartphones to remotely capture speech data affords significant clinical and research opportunities for degenerative neurologic diseases such as amyotrophic lateral sclerosis (ALS). Longitudinal data may inform ALS disease prognosis, facilitate timely intervention, and document response to treatment [1]. A recent study established the feasibility of the Beiwe smartphone-based digital phenotyping to track the clinical progression of ALS across multiple domains [2]. The current investigation extends this work to address the utility of Beiwe to identify and track speech decline in ALS. Twelve participants with ALS used the Beiwe app weekly to record reading passages and self-report (ALSFRS-R) ratings of bulbar (speech) function. Speaking rate and pause variables were automatically extracted from recordings offline [3]. Speech function measures at baseline were significantly different for participants with and without bulbar symptoms. In addition, the rate of decline of all measured speech functions was greater for participants with bulbar symptoms. The successful use of Beiwe for speech function analysis suggests that smartphone-based capture of speech has potential for diagnostic screening and disease progress monitoring in ALS. Further large sample investigation across a comprehensive set of speech variables is warranted.