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Digitalisation of subjective sleep assessment methods

  • Sleep is a crucial aspect of human well-being, with significant implications for overall health and quality of life. In response to the growing concern over sleep-related issues and the need for innovative solutions, this paper presents ‘Sleep Sheep’, an innovative system designed to monitor sleep and promote healthy sleep habits. The motivation behind Sleep Sheep stems from recognizing the vital role sleep plays in our daily lives. Inadequate sleep has been associated with various health problems, including cognitive impairments, mood disorders, and compromised immune function. Thus, addressing sleep-related concerns has become a pressing priority. To achieve its objectives, Sleep Sheep utilizes a smartphone application monitored by a doctor, to collect and analyze comprehensive sleep data, including sleep duration, sleep stages, and sleep disturbances. The collected data is then processed using several algorithms to provide results, which demonstrate its potential to impact sleep quality and overall well-being. By providing users with personalized sleep reports and actionable recommendations, Sleep Sheep makes individuals aware that they should adopt healthier sleep practices. These reports and recommendations, in turn, can lead to improved sleep duration, enhanced sleep efficiency, and a better overall sleep experience. By fostering awareness about the importance of sleep and providing individuals with the tools for being monitored by their doctors and improving their sleep, Sleep Sheep has the potential to make a substantial impact on public health. Ultimately, this innovative system aims to contribute to the well-being and quality of life of individuals by encouraging healthy sleep habits and optimizing sleep outcomes.

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Author:Joaquín Martín Acuña, Claudia Trancón Jiménez, Carlos Baquero Villena, Juan Antonio Ortega, Ralf SeepoldORCiDGND, Maksym GaidukORCiD
DOI:https://doi.org/10.1016/j.procs.2024.09.451
ISSN:1877-0509
Parent Title (English):28th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES2024, 11 - 13 September, Seville, Spain (Procedia Computer Science, Vol. 246)
Volume:246
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Conference Proceeding
Language:English
Year of Publication:2024
Release Date:2024/11/29
Tag:Sleep monitoring; Sleep quality; Subjective sleep measurement
First Page:4942
Last Page:4950
Note:
Corresponding authors: Antonio Ortega, Maksym Gaiduk
Institutes:Institut für Angewandte Forschung - IAF
DDC functional group:500 Naturwissenschaften und Mathematik
600 Technik, Medizin, angewandte Wissenschaften
Open Access?:Ja
Relevance:Konferenzbeitrag: h5-Index > 30
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International