Autors: Tonchev, K., Koleva, P. H., Manolova, A. H., Tsenov, G. T., Poulkov, V. K.
Title: Non-intrusive sleep analyzer for real time detection of sleep anomalies
Keywords: Context awareness; HMM; NREM; REM; Sleep anomaly detection; Sleep monitoring

Abstract: Solutions for caring for the elderly both efficacious and cost-effective are given by Ambient Assisted Living (AAL) systems that combine the research fields of intelligent systems and communication technologies. These systems are promising for the improvement of the quality of life of elderly and disabled people. One important characteristic of health and well-being is sleep. While sleep quantity is directly measurable, its quality has traditionally been assessed with subjective methods such as questionnaires. In this paper, we propose a non-intrusive sleep analyzer for real time detection of sleep anomalies, part of an effective AAL system. The proposed solution is based on combination of non-invasive sensors and an algorithm for sleep analysis with two stages - low and high level reasoning. It also offers the opportunity to include third party devices. Using the analyzer we can monitor basic sleep behavior and to detect sleep anomalies, which can serve as an important indicator ..

References

    Issue

    in Proceedings of International Conference on Telecommunications and Signal Processing (TSP), 27-29 June 2016, pp. 400-404, 2016, Austria, DOI 10.1109/TSP.2016.7760906

    Copyright IEEE

    Цитирания (Citation/s):
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    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science