Conception of a home-based sleep apnoea identification and monitoring system
- Healthy sleep is one of the prerequisites for a good human body and brain condition, including general well-being. Unfortunately, there are several sleep disorders that can negatively affect this. One of the most common is sleep apnoea, in which breathing is impaired. Studies have shown that this disorder often remains undiagnosed. To avoid this, developing a system that can be widely used in a home environment to detect apnoea and monitor the changes once therapy has been initiated is essential. The conceptualisation of such a system is the main aim of this research. After a thorough analysis of the available literature and state of the art in this area of knowledge, a concept of the system was created, which includes the following main components: data acquisition (including two parts), storage of the data, apnoea detection algorithm, user and device management, data visualisation. The modules are interchangeable, and interfaces have been defined for data transfer, most of which operate using the MQTT protocol. System diagrams and detailed component descriptions, including signal requirements and visualisation mockups, have also been developed. The system's design includes the necessary concepts for the implementation and can be realised in a prototype in the next phase.
Author: | Maksym GaidukORCiD, Ángel Serrano AlarcónORCiD, Ralf SeepoldORCiDGND, Natividad Martínez MadridORCiD |
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DOI: | https://doi.org/10.1016/j.procs.2023.10.375 |
ISSN: | 1877-0509 |
Parent Title (English): | 27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES2023, 6 - 8 September, Athens, Greece (Procedia Computer Science, Vol. 225) |
Volume: | 225 |
Publisher: | Elsevier |
Place of publication: | Amsterdam |
Document Type: | Conference Proceeding |
Language: | English |
Year of Publication: | 2023 |
Release Date: | 2023/12/14 |
Tag: | Sleep efficiency; Sleep study; Subjective sleep assessment |
First Page: | 3795 |
Last Page: | 3804 |
Note: | Corresponding author: Maksym Gaiduk |
Institutes: | Institut für Angewandte Forschung - IAF |
DDC functional group: | 500 Naturwissenschaften und Mathematik |
600 Technik, Medizin, angewandte Wissenschaften | |
Open Access?: | Ja |
Relevance: | Peer reviewed nach anderen Listungen (mit Nachweis zum Peer Review Verfahren) |
Licence (German): | Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |