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Recognising Daily Functioning Activities in Smart Homes

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This paper details an end-to-end system for recognising activity in smart homes for e-care. It discusses the hardware options to be considered when designing the smart home, and the particular decisions takes at the eWALL system. It then considers the necessary signal processing algorithms that turn measurements into metadata describing the context of the care recipient. Since activity recognition implementation and testing need long-term measurements and metadata, a realistic simulator is also built for providing input to the activity recognition module. The activity recognition algorithm utilises two models, one for location estimation and another for activity estimation in the given location. They both give correct recognition for 96 and 94% of the time.

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  1. Astaras, S., & Pnevmatikakis, A. (2015). Context extraction in the caring home: Infrastructure and algorithms. In IEEE ICC 2015 Workshop on ICT-enabled services and technologies for eHealth and Ambient Assisted Living (pp. 228–233). London, UK.

  2. Bardas, G., & Pnevmatikakis, A. (2016). Real-time face tracker yielding 3d pose and position. In Global Wireless Summit. Aarhus, DK.

  3. Mihovska, A., Kyriazakos, S.A., & Prasad, R. (2014). eWall for active long living: Assistive ICT services for chronically ill and elderly citizens. In SMC (pp. 2204–2209).

  4. Shah, G., Koch, P., & Papadias, C. B. (2015). On the blind recovery of cardiac and respiratory sounds. IEEE Journal of Biomedical and Health Informatics, 19(1), 151–157.

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Correspondence to Aristodemos Pnevmatikakis.

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Part of this work has been carried out in the scope of the EC co-funded project eWALL (FP7-610658).

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Pnevmatikakis, A. Recognising Daily Functioning Activities in Smart Homes. Wireless Pers Commun 96, 3639–3654 (2017).

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