Abstract

Bulbar deterioration in amyotrophic lateral sclerosis (ALS) is a devastating characteristic that impairs patients’ ability to communicate, and is linked to shorter survival. The existing clinical instruments for assessing bulbar function lack sensitivity to early changes. In this paper, using a cohort of N = 65 ALS patients who provided regular speech samples for 3–9 months, we demonstrated that it is possible to remotely detect early speech changes and track speech progression in ALS via automated algorithmic assessment of speech collected digitally.

Details

Title
Early detection and tracking of bulbar changes in ALS via frequent and remote speech analysis
Author
Stegmann, Gabriela M 1   VIAFID ORCID Logo  ; Hahn, Shira 1 ; Liss, Julie 1 ; Shefner, Jeremy 2 ; Seward, Rutkove 3 ; Shelton Kerisa 2 ; Duncan Cayla Jessica 2 ; Visar, Berisha 1 

1  Arizona State University, Phoenix, USA (GRID:grid.215654.1) (ISNI:0000 0001 2151 2636); Aural Analytics, Scottsdale, USA (GRID:grid.215654.1) 
2  Barrow Neurological Institute, Phoenix, USA (GRID:grid.427785.b) (ISNI:0000 0001 0664 3531) 
3  Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) 
Publication year
2020
Publication date
Dec 2020
Publisher
Nature Publishing Group
e-ISSN
23986352
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41746-020-00335-x
ProQuest document ID
2528863706
Copyright
© The Author(s) 2020. corrected publication 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.