Periodic Reporting for period 1 - BetterSleep (Wearable Neurotechnology for Sleep Quality Improvement)
Reporting period: 2021-02-28 to 2022-02-27
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.
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.
As part of the CSA-funded project, Bitbrain hired an innovation associate to lead the research and development (R&D) efforts in the field of sleep. This associate was an internationally recognized expert on sleep and its benefits on cognition working at Princeton University in the United States. The associate was integrated into the company through a tailored program that included introductions into all departments of Bitbrain, training in additional skills, and an intense Spanish course. This training enabled the innovation associate to soon start implementing the CSA project. This included performing a comprehensive feasibility study that included an assessment of the potential of Bitbrain's technology, market research, business planning, technical assessments of likely future developments, communication with partner companies, legal, regulatory and financial issues etc. Furthermore, a large research trial was conducted, evaluating Bitbrain's innovative technology against established medical sleep monitoring solutions. Based on the insights derived from both the feasibility study and the research trial, the innovation associate developed a plan for an extended R&D roadmap that includes important developments in the realm of sleep monitoring, sleep health, and sleep improvement.
In close cooperation with all departments of Bitbrain, the innovation associate has helped put Bitbrain on track for a sustainable, innovation-driven participation in the market of sleep monitoring, diagnostics, and improvement.
In close cooperation with all departments of Bitbrain, the innovation associate has helped put Bitbrain on track for a sustainable, innovation-driven participation in the market of sleep monitoring, diagnostics, and improvement.
The developed R&D project will push the boundaries of sleep monitoring and diagnostics. It will bring these important tools of sleep medicine closer to the patients, helping them receive the medical help they require. Furthermore, our technology will be part of the emerging field of sleep improvement.
Furthermore, we created valuable data for the project that demonstrated the accuracy of our technology, which is an essential step to enter the medical market with our technology. The data is currently being used to optimize our machine learning-based data analysis algorithms, which will be key for the data-driven innovations that will enable future sleep products. These will go beyond sleep monitoring and diagnostics. At the moment, most interventions for sleep problems are pharmacological and come with substantial side effects. We set out to change that with our technology.
Furthermore, we created valuable data for the project that demonstrated the accuracy of our technology, which is an essential step to enter the medical market with our technology. The data is currently being used to optimize our machine learning-based data analysis algorithms, which will be key for the data-driven innovations that will enable future sleep products. These will go beyond sleep monitoring and diagnostics. At the moment, most interventions for sleep problems are pharmacological and come with substantial side effects. We set out to change that with our technology.