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Monitoring Activities of Daily Living Using Audio Analysis and a RaspberryPI: A Use Case on Bathroom Activity Monitoring

Part of the Communications in Computer and Information Science book series (CCIS,volume 736)

Abstract

A framework that utilizes audio information for recognition of activities of daily living (ADLs) in the context of a health monitoring environment is presented in this chapter. We propose integrating a Raspberry PI single-board PC that is used both as an audio acquisition and analysis unit. So Raspberry PI captures audio samples from the attached microphone device and executes a set of real-time feature extraction and classification procedures, in order to provide continuous and online audio event recognition to the end user. Furthermore, a practical workflow is presented, that helps the technicians that setup the device to perform a fast, user-friendly and robust tuning and calibration procedure. As a result, the technician is capable of “training” the device without any need for prior knowledge of machine learning techniques. The proposed system has been evaluated against a particular scenario that is rather important in the context of any healthcare monitoring system for the elder: In particular, we have focused on the “bathroom scenario” according to which, a Raspberry PI device equipped with a single microphone is used to monitor bathroom activity on a 24/7 basis in a privacy-aware manner, since no audio data is stored or transmitted. The presented experimental results prove that the proposed framework can be successfully used for audio event recognition tasks.

Keywords

  • Audio analysis
  • Activities of daily living
  • Health monitoring
  • Remote monitoring
  • Audio sensors
  • RaspberryPI
  • Audio event recognition

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Notes

  1. 1.

    Please cf. https://www.raspberrypi.org.

  2. 2.

    https://bitbucket.org/radioprojectanalysis/ict4awe2016.

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Acknowledgements

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 643892. Please see http://www.radio-project.eu for more details.

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Correspondence to Georgios Siantikos .

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Siantikos, G., Giannakopoulos, T., Konstantopoulos, S. (2017). Monitoring Activities of Daily Living Using Audio Analysis and a RaspberryPI: A Use Case on Bathroom Activity Monitoring. In: Röcker, C., O'Donoghue, J., Ziefle, M., Helfert, M., Molloy, W. (eds) Information and Communication Technologies for Ageing Well and e-Health. ICT4AWE 2016. Communications in Computer and Information Science, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-62704-5_2

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  • DOI: https://doi.org/10.1007/978-3-319-62704-5_2

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