Evaluation of Speech-Based Digital Biomarkers: Review and Recommendations

Speech represents a promising novel biomarker by providing a window into brain health, as shown by its disruption in various neurological and psychiatric diseases. As with many novel digital biomarkers, however, rigorous evaluation is currently lacking and is required for these measures to be used e...

Full description

Saved in:
Bibliographic Details
Published in:Digital biomarkers 2020-09, Vol.4 (3), p.99-108
Main Authors: Robin, Jessica, Harrison, John E., Kaufman, Liam D., Rudzicz, Frank, Simpson, William, Yancheva, Maria
Format: Article
Language:English
Subjects:
Accuracy
Acoustics
Algorithms
Automation
Biomarkers
Cognition & reasoning
Data processing
Dementia
digital biomarkers
digital health
Disease
Language
Natural language
Noise
Smartphones
Speech
validation
Validation – Review Article
Validation − Review
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Speech represents a promising novel biomarker by providing a window into brain health, as shown by its disruption in various neurological and psychiatric diseases. As with many novel digital biomarkers, however, rigorous evaluation is currently lacking and is required for these measures to be used effectively and safely. This paper outlines and provides examples from the literature of evaluation steps for speech-based digital biomarkers, based on the recent V3 framework (Goldsack et al., 2020). The V3 framework describes 3 components of evaluation for digital biomarkers: verification, analytical validation, and clinical validation. Verification includes assessing the quality of speech recordings and comparing the effects of hardware and recording conditions on the integrity of the recordings. Analytical validation includes checking the accuracy and reliability of data processing and computed measures, including understanding test-retest reliability, demographic variability, and comparing measures to reference standards. Clinical validity involves verifying the correspondence of a measure to clinical outcomes which can include diagnosis, disease progression, or response to treatment. For each of these sections, we provide recommendations for the types of evaluation necessary for speech-based biomarkers and review published examples. The examples in this paper focus on speech-based biomarkers, but they can be used as a template for digital biomarker development more generally.
ISSN:2504-110X
2504-110X
DOI:10.1159/000510820