Paper ID
2950
Paper Type
full
Description
In the course of digitalisation, healthcare systems are undergoing a major transformation. The generation and processing of health-related data are intended to improve health concerns. However, individual health awareness remains inadequate. To counteract this problem, issues in the fields of health awareness, wearable health monitoring systems, conversational agents, and user interface design were identified. Meta-requirements were derived from these issues and then converted into design principles. We developed the FeelFit conversational agent under consideration of those design principles. FeelFit measures vital parameters with various wearable sensors and presents them, enriched with personalised health information, to the user in the form of a conversation via individually configurable input and output devices. The conversational agent was evaluated by two experiments with 90 participants and a workshop. The results confirm a positive usability and task fulfilment of our conversational agent. Compared to known applications, the participants highlighted the more natural interaction and seamless integration of various sensors as strengths of FeelFit.
Recommended Citation
Meier, Pascal; Beinke, Jan Heinrich; Fitte, Christian; Behne, Alina; and Teuteberg, Frank, "FeelFit – Design and Evaluation of a Conversational Agent to Enhance Health Awareness" (2019). ICIS 2019 Proceedings. 22.
https://aisel.aisnet.org/icis2019/is_health/is_health/22
FeelFit – Design and Evaluation of a Conversational Agent to Enhance Health Awareness
In the course of digitalisation, healthcare systems are undergoing a major transformation. The generation and processing of health-related data are intended to improve health concerns. However, individual health awareness remains inadequate. To counteract this problem, issues in the fields of health awareness, wearable health monitoring systems, conversational agents, and user interface design were identified. Meta-requirements were derived from these issues and then converted into design principles. We developed the FeelFit conversational agent under consideration of those design principles. FeelFit measures vital parameters with various wearable sensors and presents them, enriched with personalised health information, to the user in the form of a conversation via individually configurable input and output devices. The conversational agent was evaluated by two experiments with 90 participants and a workshop. The results confirm a positive usability and task fulfilment of our conversational agent. Compared to known applications, the participants highlighted the more natural interaction and seamless integration of various sensors as strengths of FeelFit.