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Analytical Validation of a Webcam-Based Assessment of Speech Kinematics: Digital Biomarker Evaluation following the V3 Framework

Authors :
Leif Simmatis
Saeid Alavi Naeini
Deniz Jafari
Michael (Kai Yue) Xie
Chelsea Tanchip
Niyousha Taati
Scotia McKinlay
Rupinder Sran
Justin Truong
Diego L Guarin
Babak Taati
Yana Yunusova
Source :
Digital Biomarkers, Vol 7, Iss 1, Pp 7-17 (2023)
Publication Year :
2023
Publisher :
Karger Publishers, 2023.

Abstract

Introduction: Kinematic analyses have recently revealed a strong potential to contribute to the assessment of neurological diseases. However, the validation of home-based kinematic assessments using consumer-grade video technology has yet to be performed. In line with best practices for digital biomarker development, we sought to validate webcam-based kinematic assessment against established, laboratory-based recording gold standards. We hypothesized that webcam-based kinematics would possess psychometric properties comparable to those obtained using the laboratory-based gold standards. Methods: We collected data from 21 healthy participants who repeated the phrase “buy Bobby a puppy” (BBP) at four different combinations of speaking rate and volume: Slow, Normal, Loud, and Fast. We recorded these samples twice back-to-back, simultaneously using (1) an electromagnetic articulography (“EMA”; NDI Wave) system, (2) a 3D camera (Intel RealSense), and (3) a 2D webcam for video recording via an in-house developed app. We focused on the extraction of kinematic features in this study, given their demonstrated value in detecting neurological impairments. We specifically extracted measures of speed/acceleration, range of motion (ROM), variability, and symmetry using the movements of the center of the lower lip during these tasks. Using these kinematic features, we derived measures of (1) agreement between recording methods, (2) test-retest reliability of each method, and (3) the validity of webcam recordings to capture expected changes in kinematics as a result of different speech conditions. Results: Kinematics measured using the webcam demonstrated good agreement with both the RealSense and EMA (ICC-A values often ≥0.70). Test-retest reliability, measured using the absolute agreement (2,1) formulation of the intraclass correlation coefficient (i.e., ICC-A), was often “moderate” to “strong” (i.e., ≥0.70) and similar between the webcam and EMA-based kinematic features. Finally, the webcam kinematics were typically as sensitive to differences in speech tasks as EMA and the 3D camera gold standards. Discussion and Conclusions: Our results suggested that webcam recordings display good psychometric properties, comparable to laboratory-based gold standards. This work paves the way for a large-scale clinical validation to continue the development of these promising technologies for the assessment of neurological diseases via home-based methods.

Details

Language :
English
ISSN :
2504110X
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Digital Biomarkers
Publication Type :
Academic Journal
Accession number :
edsdoj.7e1d643ac6604a0c8ac7a6555005c003
Document Type :
article
Full Text :
https://doi.org/10.1159/000529685