Emerging Technologies and Wearables for Monitoring and Managing Sleep Disorders in Patients with Cardiovascular Disease

Wearable technologies, both clinical and consumer devices, have gained tremendous popularity in recent years. They can monitor various parameters including sleep. Sleep physicians are now commonly presented with data from these devices. In this paper, we review the available technologies and the evidence behind their validity to detect sleep disorders associated with cardiovascular diseases.

Newer-generation consumer wearables utilize accelerometry and photoplethysmography (PPG) to estimate sleep duration and sleep staging. Studies have found that these devices frequently overestimate sleep duration, particularly in poor sleepers. Technologies used to detect sleep apnea, including PPG, convolutional neural network (CNN), heart rate variability (HRV), and acoustic sensing, among others, show promising results. There is limited data about wearables for the diagnosis of restless leg syndrome and circadian disorders.

Wearable consumer and clinical devices that detect sleep parameters using a variety of newer technologies are being produced at a staggering rate. A wealth of literature can be found about the validity of the generated data against gold standard methods. This body of knowledge aids clinicians in interpreting information from these devices. Longitudinal data generated by wearables holds transformative potential for sleep medicine practice and research. Nevertheless, caution is crucial, especially as consumer devices lack validation for diagnosing and monitoring sleep disorders in clinical settings, particularly among patients with cardiovascular diseases. While judicious use may enhance sleep health involvement and enable longitudinal disease monitoring, further research is needed before routinely integrating these devices into clinical practice.