Feasibility Analysis of Phenotype Quantification from Unstructured Clinical Interactions. Issue 1 (11th January 2022)

• Record Type: Journal Article
• Authors: Barron, Daniel S.; Heisig, Stephen; Agurto, Carla; Norel, Raquel; Quagan, Brittany; Powers, Albert; Birnbaum, Michael L.; Constable, Todd; Cecchi, Guillermo; Krystal, John H.
• Is Part Of: Computational psychiatry. Volume 6:Issue 1(2022)
• Page Start: 1
• Page End: 7
• Publication Date: 2022-01-11
• Subjects: digital phenotype -- conversation -- voice -- facial feature -- acoustic; Psychiatry -- Mathematical models -- Periodicals; Psychiatry -- Data processing -- Periodicals; Computational neuroscience -- Periodicals; 616.89140285
• DOI: 10.5334/cpsy.78
• Languages: English
• ISSNs: 2379-6227

Abstract

We conducted a feasibility analysis to determine the quality of data that could be collected ambiently during routine clinical conversations. We used inexpensive, consumer-grade hardware to record unstructured dialogue and open-source software tools to quantify and model face, voice (acoustic and language) and movement features. We used an external validation set to perform proof-of-concept predictive analyses and show that clinically relevant measures can be produced without a restrictive protocol.