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The rapidly aging global population presents significant challenges, particularly in managing neurodegenerative diseases such as dementia. This paper discusses the development of a comprehensive wearable device system designed to monitor and care for elderly individuals with dementia. This study focuses on the identification of relevant functional requirements and presents an initial prototype of the envisioned device. By integrating advanced sensor technologies and artificial intelligence, the system aims to ensure accurate and continuous monitoring of health indicators and daily activities. Its design approach emphasizes usability and non-intrusiveness, making it suitable for continuous wear by elderly users. The device incorporates sensors to collect data on heart rate, blood oxygen levels, and daily activities. These data are processed using a variety of machine learning techniques to provide reliable activity recognition and health monitoring, aiming to enhance the quality of life and facilitate timely medical interventions for both patients and caregivers. Preliminary results demonstrate the system’s potential in providing dependable health monitoring and activity detection, which could significantly aid in managing dementia.

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Towards the Development of a Wearable Device Enhancing Inclusivity and Monitoring for Dementia Patients

  • 会议论文

  • 发表日期：

    2025年

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  • Marcelo Arantes,
  • Mariana Carvalho,
  • Inês C. Rocha,
  • José Soares,
  • António Moreira,
  • Marta Pinto,
  • Demétrio Matos,
  • Pedro Morais,
  • Vítor Carvalho

摘要

The rapidly aging global population presents significant challenges, particularly in managing neurodegenerative diseases such as dementia. This paper discusses the development of a comprehensive wearable device system designed to monitor and care for elderly individuals with dementia. This study focuses on the identification of relevant functional requirements and presents an initial prototype of the envisioned device. By integrating advanced sensor technologies and artificial intelligence, the system aims to ensure accurate and continuous monitoring of health indicators and daily activities. Its design approach emphasizes usability and non-intrusiveness, making it suitable for continuous wear by elderly users. The device incorporates sensors to collect data on heart rate, blood oxygen levels, and daily activities. These data are processed using a variety of machine learning techniques to provide reliable activity recognition and health monitoring, aiming to enhance the quality of life and facilitate timely medical interventions for both patients and caregivers. Preliminary results demonstrate the system’s potential in providing dependable health monitoring and activity detection, which could significantly aid in managing dementia.