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.
翻译:数字生物标志(DBM)是一个日益扩大的领域,在精神和神经退化性失调的治疗领域日益受到测试。与此同时,工业、学术界和诊所使用的视听DBM知识孤立的散落阻碍了临床研究的广泛采用。我们如何帮助这些非技术领域专家探索视听数字生物标志?生物医学研究中使用开放源软件以诱导病人行为变化,并促使人们转向无障碍地解决这一问题。OpenDBM综合了几个受欢迎的视听开放源行为提取工具包。我们提出了一个视觉分析工具,作为不断增长的开放源软件(OpenDBM)的延伸,以促进在基础研究和应用研究中采用视听DBM。我们的工具展示了行为数据模式,同时支持对通过OpenDBM提取的任何一组衍生或原始DBM变量进行互动式视觉分析。