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Imagine a smartphone application that acts as your health companion, understanding your unique needs and offering guidance throughout your golden years. This mHealth app aims to improve an elderly person's health management by analyzing simple physical tasks to assess key health indicators such as ADL, mood, cognitive function, mobility, and potential fall risks. It monitors daily activities to gain insights into overall well-being, identify potential health risks, and proactively suggest preventive measures or connect with appropriate healthcare services. Healthcare services are being offered on the LINE platform through a feature called "Long-term Care". This feature provides personalized health advice and recommendations that are tailored to Thai cultural health beliefs and practices. It also includes interactive communication to ensure better understanding. To analyze this feature, a healthcare dataset consisting of 913 samples has been collected from both Ubon Ratcha Thani and Sisaket provinces. This dataset will be used with machine learning algorithms. It analyzes and presents the principal component analysis (PCA) approach of activities of daily living (ADL), highlighting important features for AI models. It also allows users to share their health data and progress with family members or caregivers, enabling informed decision-making and collaborative care. This can help develop intervention services for the community. Finally, the team has successfully developed a mobile health (mHealth) application using Principal Component Analysis (PCA) to gain data-driven insights. In the future, they plan to use the identified features to create personalized intervention protocols for caregivers, which will improve support for elderly individuals in their Activities of Daily Living (ADLs). The app integrates with the LINE platform to encourage community engagement and empower both caregivers and healthcare providers to provide comprehensive care.
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