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Digital twins, dynamic and real-time simulations of systems or environments, represent a paradigm shift in elderly care. In this perspective, we explore their applications in monitoring self-care capability and mental health among the elderly. By integrating real-time data, wearable technology, and predictive analytics, digital twins hold the promise of enhancing personalized care strategies, advancing precision healthcare, and optimizing resource allocation for aging populations. However, implementing digital twins in elderly care faces challenges such as data accuracy, individual variability, and ethical considerations. This emphasizes the need for actionable frameworks to balance innovation with data governance and public trust.