In our commitment to providing clinicians and researchers with clinical-grade digital measures from patients’ homes, our sleep algorithm was validated against a gold-standard Polysomnography (PSG) system, in a diverse population of older adults with a variety of health conditions.
The algorithm was evaluated in terms of three main objectives: sleep period identification, sleep/wake scoring, and sleep quality assessment. Our validation study was the first to validate an algorithm against these three measures simultaneously.
In the study, the algorithm showed 100% sensitivity in recognizing sleep periods, as identified by the PSG system. The “sleep stage” vs. “wake stage” classification reached an impressive accuracy (F-score) of 90%. On average, the algorithm detected the sleep onset and offset within 5 minutes of the PSG system and estimated the sleep duration within 10
minutes of the duration determined by the PSG system.
For more detailed information on the algorithm validation, you can refer to our paper, Sleep assessment by means of a wrist actigraphy-based algorithm: agreement with polysomnography in an ambulatory study on older adults, published in The Journal of Biological and Medical Rhythm Research.
Studying and tracking sleep is important both for physical and mental health biomedical research, and also for providing more effective patient care and treatment strategies. Sleep duration and quality have been known to be associated with multiple conditions such as obesity, diabetes, depression, and hypertension, and to affect a person’s key cognitive functions, mental health status, as well as their hormonal and inflammatory levels. The ability to measure sleep patterns with a non-invasive device such as EmbracePlus allows for a more comfortable, unobtrusive patient experience, which can increase the number of participants in studies and allow researchers to collect data from a number of consecutive days or weeks, and thus increase the reliability of the results.
If you are a user of the Empatica Health Monitoring Platform, you can access the data of the Sleep digital biomarker directly from your S3 data bucket. If you have further questions or wondering how your study can benefit from the Sleep digital biomarker, our team will be happy to help you.
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