TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Vélez Gutiérrez, Daniel
A1  - Martínez Madrid, Natividad
A1  - Seepold, Ralf
T1  - Non-Invasive System for Measuring Parameters Relevant to Sleep Quality and Detecting Sleep Diseases: The Data Model
JF  - Non-Invasive Health Systems based on Advanced Biomedical Signal and Image Processing
N2  - Healthy and good sleep is a prerequisite for a rested mind and body. Both form the basis for physical and mental health. Healthy sleep is hindered by sleep disorders, the medically diagnosed frequency of which increases sharply from the age of 40. This chapter describes the formal specification of an on-course practical implementation for a non-invasive system based on biomedical signal processing to support the diagnosis and treatment of sleep-related diseases. The system aims to continuously monitor vital data during sleep in a patient’s home environment over long periods by using non-invasive technologies. At the center of the development is the MORPHEUS Box (MoBo), which consists of five main conceptualizations: the MoBo core, the MoBo-HW, the MoBo algorithm, the MoBo API, and the MoBo app. These synergistic elements aim to support the diagnosis and treatment of sleep-related diseases. Although there are related developments in individual aspects concerning the system, no comparative approach is known that gives a similar scope of functionality, deployment flexibility, extensibility, or the possibility to use multiple user groups. With the specification provided in this chapter, the MORPHEUS project sets a good platform, data model, and transmission strategies to bring an innovative proposal to measure sleep quality and detect sleep diseases from non-invasive sensors.
KW  - Data Model
KW  - Sleep
Y1  - 2024
SN  - 9781003346678
SB  - 9781003346678
U6  - https://doi.org/10.1201/9781003346678-6
DO  - https://doi.org/10.1201/9781003346678-6
SP  - 113
EP  - 127
PB  - CRC Press, Taylor & Francis Group
CY  - Boca Raton
ER  -