As a result, the importance of precise measurements cannot be overstated.

This happens because most patients do not realize that the claims of these devices typically outweigh the science to support them as devices to measure and improve sleep. Therefore, wearing sleep trackers with incorrect readings could have adverse effects on these patients. Patients with sleep disorders, or those who are chronically sleep-deprived, are more likely to suffer from fragmented sleep and reduced ability to understand their functional impairment. These devices often tend to underestimate or overestimate some key parameters such as TST, sleep efficiency, wake, or the transition between the sleep stages. This is because even in healthy adults accelerometry has high sensitivity but low specificity for sleep detection. It is shown that the use of wearable devices for sleep-cycle monitoring is feasible but inaccurate compared to the gold standard PSG. Actigraphy devices enable the user to wear dedicated sensors to help track vital signs and movements while sleeping. That said, the ease and relative performance of actigraphy-based devices for sleep and sleep-cycle monitoring has given rise to numerous wearable devices and smartphone-based technologies. It makes sense because EEG-based systems are the most accurate for detecting all the stages of sleep. Although the results from the abovementioned studies are encouraging in terms of accuracy, commercial devices cannot produce identical results to PSG. It was also observed that the majority of the proposed systems are limited to three-stage sleep classification. Generally, proposed sleep monitoring methods are based on one or a combination of the following: respiratory cycle, cardiac cycle, body movement. Due to the unsuitability of PSG for in-home monitoring, researchers have developed and are developing various unobtrusive systems as alternatives, leveraging on recent technological advancements.

It can be noted that there is an increasing interest in sleep monitoring (in particular, sleep cycles) using unobtrusive sensors. Current Insights of Sleep Monitoring Methods An illustration showing the location of a contactless sensor under the mattress of a monitored individual. However, the process requires trained sleep technicians to perform polysomnography (PSG).įigure 2. A major motivation for sleep monitoring is the effect it has on health and well-being. Sleep monitoring is important and could be a lifesaver for people with undiagnosed sleep disorders. This is reflective of the global populace as sleep disorders are rapidly becoming a global concern, leading to a range of societal problems. A similar statistic was reported by the Canadian Men’s Health Foundation (2016) stating that 30% of Canadian men are sleep deprived. The Centers for Disease Control and Prevention (CDC) reported that a third of the United States population does not get enough sleep. The fast pace of modern society and the rapid increase in the aging population have contributed to the population of people being affected by sleep disorders. The quantity and quality of sleep are generally associated with chronic diseases and health risks such as diabetes, cardiovascular diseases, renal failure, anxiety, and depression. How this device defines deep sleep and dream sleep is unclear, but I'm guessing it is simply combining deep sleep and REM sleep under the title 'deep sleep.' In looking at the data, the results of the Jawbone bear little resemblance to my actual night of sleep.Sleep is important for the physical and mental well-being of an individual. The device attempted to differentiate between light sleep (2 hours and 4 minutes in my case) and deep sleep (2 hours and 26 minutes), but does not account for REM/dream sleep.

It estimated my total sleep time as being 4 hours and 31 minutes and my sleep latency as 11 minutes. The Jawbone produced an impressive amount of data. I am floored that this device accurately staged sleep based solely upon wrist inputs. The arousals during my second REM cycle were spot on as was my awakening around 3:30 a.m. The Basis did not detect my final REM cycle and it added a REM cycle early in the night. Even without my indication that I had gone to sleep, the sleep onset was almost perfect, and it accurately detected two of my three REM cycles. The Basis did an amazing job of characterizing my sleep stages.

S plus sleep monitor