Roos, TobiasPurps, Christian FelixKunze, ChristopheWoelfel, Matthias2023-08-242023-08-242023https://dl.gi.de/handle/20.500.12116/42087In addition to the health risks posed by advancing age, the elderly population faces additional challenges in global events such as the COVID-19 pandemic, affecting both themselves and their caregivers. This case study addresses the co-creation process for an AI-based care assistant—a hybrid multimodal interaction system—to assist in low-contact on-site care scenarios. The system will consist of three separate units: an AI-supported sensor system that combines the automatic analysis of optical (3D) and acoustic sensor data for activity and situation analysis in the home environment, a control unit (business logic) and a multi-modal interaction system with enhanced video, voice, and freehand gesture interaction. The interaction system uses the information from the sensor system to support care recipients autonomously (e.g. through motivational interaction) or in combination with caregivers in everyday activities. Bringing together different perspectives of stakeholders in both the research team and care providers together as early as possible, a variety of qualitative research methods has been and will be utilized (e.g. semi-standardized interviews, participatory observations, contextual interviews and co-creation workshops). Workshop topics include an activation model for care recipients, interface design and appropriate caregiving scenarios illustrating opportunities to support outpatient care. To date, several interviews and workshops with participants from the professional and informal outpatient care setting have been conducted, discussing predesigned use cases and scenarios, potential benefits and challenges for the outlined care support system and possible approaches for interaction between the system and participants in outpatient care.Text/Workshop Paper10.18420/muc2023-mci-ws06-368