Sleep Tracker and Smartphone: Strengths and Limits to Estimate Sleep and Sleep-Disordered Breathing

An increasing number of customers are using wearable devices, sleep trackers, or smartphones apps to monitor and measure a variety of body functions. These devices claim to measure different physiological parameters such as sleep quality, snoring, or sleep-disordered breathing (SDR). Here, we present a review of validation studies of sleep applications to providing some guidance in terms of their reliability to assess sleep in healthy and clinical populations. A review was conducted on PubMed. Twelve validation studies were identified, evaluating sleep trackers and smartphone app performances compared to polysomnography (PSG) or actigraphy for sleep assessment in healthy and clinical samples. Validation studies in healthy children, adolescent, and adult show that sleep trackers overestimate sleep time, sleep efficiency, and the latency to fall asleep. "Jawbone UP 3" and "Fitbit Charge" sleep trackers show good equivalence with the sleep diary total sleep time (effect size = 0.09 and 0.23, respectively). Compared to electrocardiography in determining HR during sleep, the "Fitbit Charge 2" reports no significant difference in the mean HR (0.09 beats per minute, P = 0.426). Most of the smartphone apps based on body movements, measured by accelerometers, show a weak correlation between PSG and apps sleep parameters. A multiple parameter-based smartphone app using the EarlySense contact-free sleep monitoring system shows that total sleep time estimates with the contact-free system were closely correlated with PSG. More experimental studies are warranted to assess the validity of sleep trackers or smartphones apps for clinical applications and their reliability in sleep-wake detection particularly.