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Review
. 2023 Oct 2:17:1256682.
doi: 10.3389/fnins.2023.1256682. eCollection 2023.

Ambient assisted living for frail people through human activity recognition: state-of-the-art, challenges and future directions

Bruna Maria Vittoria Guerra  1 , Emanuele Torti  2 , Elisa Marenzi  2 , Micaela Schmid  1 , Stefano Ramat  1 , Francesco Leporati  2 , Giovanni Danese  2
Affiliations
Review

Ambient assisted living for frail people through human activity recognition: state-of-the-art, challenges and future directions

Bruna Maria Vittoria Guerra et al. Front Neurosci. .

Abstract

Ambient Assisted Living is a concept that focuses on using technology to support and enhance the quality of life and well-being of frail or elderly individuals in both indoor and outdoor environments. It aims at empowering individuals to maintain their independence and autonomy while ensuring their safety and providing assistance when needed. Human Activity Recognition is widely regarded as the most popular methodology within the field of Ambient Assisted Living. Human Activity Recognition involves automatically detecting and classifying the activities performed by individuals using sensor-based systems. Researchers have employed various methodologies, utilizing wearable and/or non-wearable sensors, and employing algorithms ranging from simple threshold-based techniques to more advanced deep learning approaches. In this review, literature from the past decade is critically examined, specifically exploring the technological aspects of Human Activity Recognition in Ambient Assisted Living. An exhaustive analysis of the methodologies adopted, highlighting their strengths and weaknesses is provided. Finally, challenges encountered in the field of Human Activity Recognition for Ambient Assisted Living are thoroughly discussed. These challenges encompass issues related to data collection, model training, real-time performance, generalizability, and user acceptance. Miniaturization, unobtrusiveness, energy harvesting and communication efficiency will be the crucial factors for new wearable solutions.

Keywords: ambient assisted living; deep learning; frail people; human activity recognition; wearable systems.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
Evolution of AAL systems: four generations from the 1990s to the present day.
Figure 2
Figure 2
Processing chain illustrating the general steps of HAR.
See this image and copyright information in PMC

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