Emotion Recognition in Dementia
Advancing technology for multimodal analysis of emotion expression in everyday life
Mental illnesses, like depression and anxiety, are among the leading causes of the global burden of disease. E-mental health (EMH) interventions, such as web-based psychotherapy treatments, are increasingly used to improve access to psychotherapy for a wider audience. Whereas different EMH interventions tend to be equally effective, the responsiveness to a specific treatment shows large individual differences. The personalization of treatments is seen as the major road for improvement.
eScience methods and tools
Because most EMH interventions use language for communication between counselors and clients, assessing language use provides an important avenue for opening the black box of what happens within therapy. EMH also makes data of the linguistic interactions between client and counselor available on an unprecedented large scale.
The objective of this interdisciplinary project is to use eScience methods and tools, in particular natural language processing, visualization and multivariate analysis methods, to analyze patterns in therapy-related textual features in e-mail correspondence between counselor and client.
Improving the effectiveness of EMH
By connecting patterns of known change indicators to therapy outcome, the question What Works When for Whom? can be answered, which will greatly improve the effectiveness of EMH. The core of the project concerns the development of integrated, modular software for the Dutch language, using data from six EMH-interventions with a total of 10.000 e-mails. These data are sufficiently large and varied to allow for computer-based modelling, and testing of use cases with varying complexity. At the end of the project, the step toward English language software will be made to increase the impact of the project.