Abstract
The availability of new miniaturized technologies for measuring the health status in self and remote conditions is rapidly pushing the development of new digital health solutions. The new AI and Metaverse era is also targeting the health field. This requires the evolution of new integrated models for health data fusion and representation. This paper presents development of a novel Digital Health Twin dedicated to prevention and implementing a cardiovascular risk index. Cardiovascular pathologies are the most diffused and relevant in the society. The model is combined with a Heath Pod solution for a territorial medicine approach even through corporate welfare solutions. This setting was adopted for the validation of the Digital Health Twin model and its User eXperience. A panel of 1314 subjects participated to the pilot test: they carried out a total number of 3755 test, that meant and average of 2,72 test per subject. Very good and promising results were obtained. The DHT model was well appreciated by 90% of subjects with excellent (about 70%) or good (about 20%) positive answers. Also the collective dashboard demonstrated to be a useful representation and tools to identify a status of health of a population, capable to highlight both individual issues and problems in specific category of people (by age, by gender, by occupation or section in the company).
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Galuzzi, G., Nizardo Chailly, A., Andreoni, G. (2023). Digital Health Twin in the Prevention Era for Personal and Corporate Wellbeing. In: Marcus, A., Rosenzweig, E., Soares, M.M. (eds) Design, User Experience, and Usability. HCII 2023. Lecture Notes in Computer Science, vol 14034. Springer, Cham. https://doi.org/10.1007/978-3-031-35705-3_20
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DOI: https://doi.org/10.1007/978-3-031-35705-3_20
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