Remote Health Monitoring Systems for Elderly People: A Survey

Sensors (Basel). 2023 Aug 10;23(16):7095. doi: 10.3390/s23167095.

Abstract

This paper addresses the growing demand for healthcare systems, particularly among the elderly population. The need for these systems arises from the desire to enable patients and seniors to live independently in their homes without relying heavily on their families or caretakers. To achieve substantial improvements in healthcare, it is essential to ensure the continuous development and availability of information technologies tailored explicitly for patients and elderly individuals. The primary objective of this study is to comprehensively review the latest remote health monitoring systems, with a specific focus on those designed for older adults. To facilitate a comprehensive understanding, we categorize these remote monitoring systems and provide an overview of their general architectures. Additionally, we emphasize the standards utilized in their development and highlight the challenges encountered throughout the developmental processes. Moreover, this paper identifies several potential areas for future research, which promise further advancements in remote health monitoring systems. Addressing these research gaps can drive progress and innovation, ultimately enhancing the quality of healthcare services available to elderly individuals. This, in turn, empowers them to lead more independent and fulfilling lives while enjoying the comforts and familiarity of their own homes. By acknowledging the importance of healthcare systems for the elderly and recognizing the role of information technologies, we can address the evolving needs of this population. Through ongoing research and development, we can continue to enhance remote health monitoring systems, ensuring they remain effective, efficient, and responsive to the unique requirements of elderly individuals.

Keywords: ambient assisted living healthcare; concept drift in healthcare; elderly people health monitoring; health edge computing; health fog computing; machine learning in healthcare; remote health monitoring system; smart health.

Publication types

  • Review

MeSH terms

  • Aged
  • Evidence Gaps*
  • Humans
  • Information Technology*
  • Recognition, Psychology

Grants and funding

This work is partially supported under Erasmus plus Capacity Building in Higher Education (CBHE) programme under SAFE-RH Project-619483-EPP-1-2020-1-UK-EPPKA2-CBHE-JP.