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A System of Recognition Services for Clinical Assessment

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RADIO--Robots in Assisted Living

Abstract

As smart interconnected sensing devices are becoming increasingly ubiquitous, more applications are becoming possible by re-arranging and re-connecting sensing and sensor signal analysis in different pipelines. Naturally, this is best facilitated by extremely thin services that expose minimal functionality and are extremely flexible regarding the ways in which they can be re-arranged. On the other hand, this ability to reuse might be purely theoretical since there are established patterns in the ways processing pipelines are assembled. By adding privacy and technical requirements, the re-usability of some functionalities is further restricted, making it even harder to justify the communication and security overheads of maintaining them as independent services. This creates a design space that each application must explore using its own requirements. In this article, we focus on detecting Activities of Daily Life (ADL) for medical applications and especially independent living applications, but our setting also offers itself to sharing devices with home automation and home security applications. By studying the methods and pipelines that dominate the audio and visual analysis literature, we observe that there are several multicomponent subsystems that can be encapsulated by a single service without substantial loss of re-usability . We then use this observation to propose a design for our ADL recognition application that satisfies our medical and privacy requirements, makes efficient use of processing and transmission resources and is also consistent with home automation and home security extensions.

This chapter is a reprint of ‘Design for a System of Multimodal Interconnected ADL Recognition Services’ in Components and services for IoT platforms: Paving the way for IoT standards, Springer, September 2016.

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References

  1. Bencina, R., & Burk, P. (2001). PortAudio—an open source cross platform audio API. In Proceedings of the International Computer Music Conference, Havana (pp. 263–266).

    Google Scholar 

  2. Kim, H. G., Moreau, N., & Sikora, T. (2006). MPEG-7 audio and beyond: Audio content indexing and retrieval. Hoboken, NJ: Wiley.

    Google Scholar 

  3. Giannakopoulos, T (2015). pyAudioAnalysis: An open-source Python library for audio signal analysis. PloS One, 10(12).

    Google Scholar 

  4. Giannakopoulos, T., & Pikrakis, A. (2014). Introduction to audio analysis: A MATLAB approach. Academic Press.

    Google Scholar 

  5. Siantikos, G., Sgouropoulos, D., Giannakopoulos, T., & Spyrou, E. (2015). Fusing multiple audio sensors for acoustic event detection. In Proceedings of the 9th International Symposium on Image and Signal Processing and Analysis (ISPA 2015) (pp. 265–269). IEEE.

    Google Scholar 

  6. Giannakopoulos, T., & Petridis, S. (2015). Fisher linear semi-discriminant analysis for speaker diarization. IEEE Transactions on Audio, Speech, and Language Processing, 20(7).

    Google Scholar 

  7. KaewTraKulPong, P., & Bowden, R. (2002). An improved adaptive background mixture model for real-time tracking with shadow detection. In Video-based surveillance systems (pp. 135–144). Berlin: Springer.

    Google Scholar 

  8. Sgouropoulos, D., Spyrou, E., Siantikos, G., & Giannakopoulos, T. (2015). Counting and tracking people in a smart room: An IoT approach. In Proceedings of the 10th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP 2015). IEEE.

    Google Scholar 

  9. Sgouropoulos, D., Giannakopoulos, T., Siantikos, G., Spyrou, E., & Perantonis, S. (2014). Detection of clothes change fusing color, texture, edge and depth information. In E-Business and Telecommunications (pp. 383–392). Berlin: Springer.

    Google Scholar 

  10. Sarafianos, N., Giannakopoulos, T., & Petridis, S. (2014). Audio-visual speaker diarization using Fisher linear semi-discriminant analysis. Multimedia Tools and Applications, 1–16.

    Google Scholar 

  11. RADIO project: Deliverable 2.2: Early detection methods and relevant system requirements. Tech. Rep. (2015). http://radio-project.eu/deliverables.

  12. Siantikos, G., Giannakopoulos, T., & Konstantopoulos, S. (2016). A low-cost approach for detecting activities of daily living using audio information: A use case on bathroom activity monitoring. In Proceedings of the 2nd International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2016), Rome, Italy.

    Google Scholar 

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Correspondence to Vangelis Karkaletsis .

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Giannakopoulos, T., Konstantopoulos, S., Siantikos, G., Karkaletsis, V. (2019). A System of Recognition Services for Clinical Assessment. In: Karkaletsis, V., Konstantopoulos, S., Voros, N., Annicchiarico, R., Dagioglou, M., Antonopoulos, C. (eds) RADIO--Robots in Assisted Living. Springer, Cham. https://doi.org/10.1007/978-3-319-92330-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-92330-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92329-1

  • Online ISBN: 978-3-319-92330-7

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