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

Frontiers in Neuroscience

Neuroscience

Bruna Maria Vittoria Guerra¹  Stefano Ramat¹  Micaela Schmid¹  Giovanni Danese²  Elisa Marenzi²  Francesco Leporati²  Emanuele Torti² 

[1] Bioengineering Laboratory, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy;Custom Computing and Programmable Systems Laboratory, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy;

关键词: human activity recognition;    ambient assisted living;    wearable systems;    frail people;    deep learning;   

DOI  :  10.3389/fnins.2023.1256682

 received in 2023-07-11, accepted in 2023-09-18,  发布年份 2023

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

Unknown   
Copyright © 2023 Guerra, Torti, Marenzi, Schmid, Ramat, Leporati and Danese.