Everyone experienced or will experience sleep problems at some point in their lives.
Poor sleep quality due to sleep deprivation or fragmentation may be the main cause for symptoms like reduced vigilance, memory deficits, fatigue and difficulty in maintaining equilibrium. Untreated sleep disorders have been linked to hypertension, heart disease, stroke, depression, diabetes and other chronic diseases.
According to the American Academy of Sleep Medicine, there are over 80 known sleep disorders so far, which can take many forms and can involve too little sleep, too much sleep or inadequate quality of sleep.
Currently, the gold standard in terms of sleep disorder diagnosis is overnight polysomnography (PSG). The main disadvantages with PSG are the high monitoring costs per patient, the scarcity of beds available and the uncertainty of whether the results are representative of a normal nights’ sleep. These are the main reasons why low-cost home diagnostic systems are likely to be advantageous. They aim is to reach a larger population by reducing the number of parameters recorded.
There are many monitoring modalities that have been explored for home sleep diagnostic systems which are based on analysis of EEG, ECG, body movement, oxyhemoglobin saturation level, blood pressure, respiration, temperature, audio and video recordings. Most of the times, the proposed systems combine two or more of this monitoring modalities to achieve better accuracy.
Monitoring devices designed as patches(e.g. Metria, ePatch) and textile technology(mainly by use of conductive fibers) were proposed as innovative tools for the development of comfortable devices for monitoring a variety of vital signs like ECG, bioimpedance, skin resistance, respiratory frequency.
Telemedicine is also a fresh field which raises a lot of interest in the scientific community because it promises to overcome the disadvantages of home monitoring systems( data loss mainly) and keep the advantages of in-lab monitoring(complete accurate sleep study). Telemedicine uses grid technology for analysis and recording.
The Master Thesis is tutored by Prof. Dr. Ralf Seepold (HTWG Konstanz - Germany, UC-Lab). The thesis is executed during an ERASMUS+ stay at HTWG Konstanz, Ubiquitous Computing Laboratory (UC-Lab).