Abstract
With the world population aging at a fast rate, ambient assisted living systems focused on elderly people gather more attention. Human activity recognition (HAR) is a component connected to those systems, as it allows identification of the actions performed and their utilization on behavioral analysis. This paper aims to provide a review on recent studies focusing on HAR and abnormal behavior detection specifically for seniors. The frameworks proposed in the literature are presented. The results are also discussed and summarized, along with the datasets and metrics used. The absence of a universal evaluation framework makes direct comparison not feasible, thus an analysis is made trying to divide the literature using a taxonomy. Solutions on the challenges identified are proposed, while discussing future work.
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Acknowledgements
This work has been funded by the ΕΣΠΑ (2014–2020) Erevno—Dimiourgo—Kainotomo 2018/EPAnEK Program ‘Energy Controlling Voice Enabled Intelligent Smart Home Ecosystem’, General Secretariat for Research and Technology, Ministry of Education, Research and Religious Affairs.
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Lentzas, A., Vrakas, D. Non-intrusive human activity recognition and abnormal behavior detection on elderly people: a review. Artif Intell Rev 53, 1975–2021 (2020). https://doi.org/10.1007/s10462-019-09724-5
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DOI: https://doi.org/10.1007/s10462-019-09724-5