Fig. 1 (Individual Panel) A1-3, c, D, F show facial, movement, and acoustinc DBM measurements. Fig1. G shows correlations between DBMs over time. Fig2 (Cohort Panel) B shows the distribution of the individuals based on the DBMs selected from panel A. E shows correlations between DBMs, D shows the distribution of DBM values across the cohort.
Abstract: Digital biomarkers (DBMs) are a growing field and increasingly tested in the therapeutic areas of psychiatric and neurodegenerative disorders. Meanwhile, isolated silos of knowledge of audiovisual DBMs use in industry, academia, and clinics hinder their widespread adoption in clinical research. How can we help these non-technical domain experts to explore audiovisual digital biomarkers? The use of open source software in biomedical research to extract patient behavior changes is growing and inspiring a shift toward accessibility to address this problem. OpenDBM integrates several popular audio and visual open source behavior extraction toolkits. We present a visual analysis tool as an extension of the growing open source software, OpenDBM, to promote the adoption of audiovisual DBMs in basic and applied research. Our tool illustrates patterns in behavioral data while supporting interactive visual analysis of any subset of derived or raw DBM variables extracted through OpenDBM.
Digital biomarkers (DBMs) are a growing field and increasingly tested in the therapeutic areas of psychiatric and neurodegenerative disorders. Meanwhile, isolated silos of knowledge of audiovisual DBMs use in industry, academia, and clinics hinder their widespread adoption in clinical research. How can we help these non-technical domain experts to explore audiovisual digital biomarkers? The use of open source software in biomedical research to extract patient behavior changes is growing and inspiring a shift toward accessibility to address this problem. OpenDBM integrates several popular audio and visual open source behavior extraction toolkits. We present a visual analysis tool as an extension of the growing open source software, OpenDBM, to promote the adoption of audiovisual DBMs in basic and applied research. Our tool illustrates patterns in behavioral data while supporting interactive visual analysis of any subset of derived or raw DBM variables extracted through OpenDBM.
@article{floricel2022opening,title={Opening Access to Visual Exploration of Audiovisual Digital Biomarkers: an OpenDBM Analytics Tool},author={Floricel, Carla and Epifano, Jacob and Caamano, Stephanie and Kark, Sarah and Christie, Rich and Masino, Aaron and Paredes, Andre D},journal={IEEE Visualization in Biomedical AI Workshop},year={2022},}
