Abstract
We need open platforms driven by specialists, in which queries can be created and collected for long periods and the diagnosis made based on a rigorous clinical follow-up. In this work, we developed a multi-language robot interface helping to evaluate the mental health of seniors by interacting through questions. Through the voice interface, the specialist can propose questions, as well as receive users’ answers, in text form. The robot can automatically interact with the user using the appropriate language. It can process the answers and under the guidance of a specialist, questions and answers can be oriented towards the desired therapy direction. The prototype was implemented on an embedded device meant for edge computing, thus it was able to filter environmental noise and can be placed anywhere at home. The proposed platform allows the integration of well-known open source and commercial data flow processing frameworks. The experience is now available for specialists to create queries and answers through a Web-based interface.
Highlights
Mental health care and diagnosis are today migrating towards mobile solutions [1,2]
We need open platforms driven by specialists, in which queries can be created and collected for long periods and the diagnosis made based on a rigorous clinical follow-up
The platform is able to process text form queries from the to mention that the interface is automatically personalized according to the language chosen by the caregiver and collect user answers
Summary
Mobile applications provide more accessible support [3] This becomes interesting, knowing that people dealing with mood, stress or anxiety do not always seek professional help or get care when it is really needed [4]. The authors in [7] present CHADMon, a dedicated mobile application for voice analysis and monitoring of mental state and phase change detection. Their interest and the required techniques were already under study, taking into account multiple aspects, from acceptability to clinical efficacy, including targeted therapies and clinical benefits [2]. We need open platforms driven by specialists, in which queries can be created and collected for long periods and the diagnosis made based on a rigorous clinical follow-up
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