Sleep is closely linked with mental and physical health. Measuring sleep parameters can provide insights into a patient’s condition and their responses to treatment. However, conventional sleep measurement is not practical for many patients in inpatient settings. Contact-free sleep measurement would allow sleep insights to be made available to clinicians caring for patients in a wider range of settings.
Conventional sleep measurement involves sensors being attached to a patient to record signals such as the electroencephalogram (EEG). These sensors are connected by wires to a recording device near the bed or worn by the patient. The signals from these sensors are reviewed by a human expert and “scored” to produce a timeline showing the sleep architecture for that night of sleep. Particular metrics can then be derived such as the time taken to fall asleep.
This conventional approach has several inherent drawbacks. Wearing the sensors may itself affect the person’s sleep. The sleep recordings often take place in a dedicated sleep lab setting with a different bed and environment from the person’s usual bedroom, which may impact their sleep. These factors may also make it impractical or unsafe for a person with severe mental illness or a neurodegenerative condition. Furthermore, this conventional approach usually involves recording 1-2 nights of sleep, which may not represent a typical night’s sleep for that person and does not allow changes over many nights to be observed.
This project aims to offer contact-free sleep insights without requiring the steps in the conventional process noted above. Novel software is being developed to provide sleep architecture information and derived metrics within the existing Oxevision platform. The Oxevision hardware would not need to be modified and there would be no sensors attached to the patient. Patents have been filed on some of the work. The researchers are collecting data to support this work within a study which has been approved by a Health Research Authority Research Ethics Committee.
Alongside the software development, the researchers are working with clinical collaborators to explore how sleep insights could best be provided in a ward setting to support clinicians caring for patients. For example, objective information about how well a patient has slept may help clinicians to work with the patient to optimise their care plan and support their recovery.
Software to provide sleep insights is under development by Oxehealth researchers working with Professor Michael Polkey and other clinical and academic collaborators. Subject to appropriate medical device clearance, the ambition is to launch sleep architecture insights for every room equipped with Oxevision. These insights would be made available to clinicians to support them in understanding each patient’s condition, selecting the right treatment and assessing its effects, and improving patients’ wellbeing in relation to sleep.
