Population aging represents a critical social and economic challenge, particularly in regions such as Cantabria, where the proportion of older adults far exceeds that of younger people. This demographic trend demands more sustainable care models to avoid overloading healthcare systems. The urgency of managing this reality efficiently drives the need to innovate in how the elderly population is monitored and supported, shifting the focus from clinical reactivity to prevention and prolonged autonomy. The MIES project emerges as a strategic technological response that integrates gamification and sensors to assess executive functions in a non-invasive manner. By eliminating traditional clinical bias, it yields objective data on cognitive and physical capacity, enabling early detection of deficits. This approach not only improves quality of life by reducing risks such as falls but also optimizes resources by decreasing the need for in-person assessments, offering more efficient and scalable management through cloud-based architectures. The relevance of this article to the field of open data lies in its focus on interoperability and the ethical use of health information. By establishing standards for early detection and creating interfaces that facilitate the integration of heterogeneous data, MIES promotes the creation of structured and shareable datasets. This could lay the foundation for more transparent health ecosystems, where anonymized and validated data serve to enhance global research and public policies on active aging.
Source: elfaradio.comPublished on 2024-03-07
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