Audio-based Active and Assisted Living: A review of selected applications and future trends

Vladimir Despotovic*, Peter Pocta, Andrej Zgank

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish
Article number106027
JournalComputers in Biology and Medicine
Volume149
Early online date25 Aug 2022
DOIs
Publication statusPublished - Oct 2022

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