Bioinformatics Platform, Luxembourg Institute of Health, Strassen, Luxembourg.
Department of Multimedia and Information-Communication Technology, Faculty of Electrical Engineering and Information Technology, University of Zilina, Zilina, Slovakia.
Comput Biol Med. 2022 Oct;149:106027. doi: 10.1016/j.compbiomed.2022.106027. Epub 2022 Aug 25.
The development of big data, machine learning, and the Internet of Things has led to rapid advances in the research field of Active and Assisted Living (AAL). A human is placed in the center of such an environment, interacting with different modalities while using the system. Although video still plays a dominant role in AAL technologies, audio, as the most natural means of interaction, is also used commonly, either as a single source of information, or in combination with other modalities. Despite the rapidly increased research efforts in the last decade, there is a lack of systematic overview of audio based technologies and applications in AAL. This review tries to fill this gap, and identifies five major topics where audio is an essential AAL building block: Physiological monitoring, emotion recognition in the context of AAL, human activity recognition, fall detection, and food intake monitoring. We address the data work flow and standard sensing technologies for capturing audio in the AAL environment, provide a comprehensive overview of audio-based AAL applications, and identify datasets available to the research community. Finally, we address the main challenges that should be handled in the upcoming years, and try to identify the potential future trends in audio-based AAL.
大数据、机器学习和物联网的发展推动了积极和辅助生活（AAL）研究领域的快速发展。人处于这样的环境的中心，与不同的模式交互，同时使用系统。尽管视频在 AAL 技术中仍然占据主导地位，但音频作为最自然的交互方式，也经常被使用，无论是作为单一的信息源，还是与其他模式结合使用。尽管在过去十年中研究工作迅速增加，但在 AAL 中基于音频的技术和应用缺乏系统的概述。本综述试图填补这一空白，并确定了音频作为 AAL 基本构建块的五个主要主题：生理监测、AAL 背景下的情感识别、人体活动识别、跌倒检测和食物摄入监测。我们讨论了在 AAL 环境中捕获音频的数据工作流程和标准传感技术，全面概述了基于音频的 AAL 应用，并确定了可供研究界使用的数据集。最后，我们讨论了未来几年应处理的主要挑战，并尝试确定基于音频的 AAL 的潜在未来趋势。
