Poor sleep creates human suffering, impairs mental and physical performance, and predicts later morbidities. Poor sleep also can become clinically relevant in the form of serious sleep disorders, which are widespread and have severe public health consequences.
Currently, two opposing approaches exist for monitoring sleep. On the one hand, there are rather non-intrusive wearable devices on the market that do not rely on neural data, e.g. fitness watches, wrist actigraphy, rings etc. While these devices claim to provide information in sleep structure, they notoriously underperform in accuracy and specificity when detecting sleep and especially when classifying different sleep stages. These shortcomings preclude a more detailed analysis of sleep quality. On the other hand, there are full polysomnographic devices that use an array of sensors to collect a large number of physiological parameters and thus allow an accurate description of sleep physiology and structure. These devices are the current gold standard for diagnosis of sleep disorders. However, they are very intrusive and usually require elaborate in-patient monitoring or clunky ambulatory monitoring setups. Concerning the in-patient case, sleep laboratories work at capacity and waiting times in many countries range from several months to up to two years. Ambulatory sleep studies usually require the assistance of an EEG technologist since they are too complex to be self-applied. As a result, both the in-patient and ambulant solutions are associated with high costs, mainly due to personnel and expensive equipment, and are likely to not represent the patient’s natural sleeping habits.
To address these problems, Bitbrain develops a comfortable and easy-to-use sleep monitoring device that assesses a wealth of neuronal and other physiological signals during sleep. It can be used independently at home and does not require professional assistance. By offering extensive data analysis, including automated sleep staging, we will support examiners in their work and further reduce personnel costs. We will offer a non-medical setup for high-throughput screening for poor sleep (e.g. in the context of company health management). A second more complex setup, which will be the focus of this project, will be designed to help healthcare professionals with diagnosing sleep disorders.
