Polysomnography is regarded as the number one when it comes to monitoring sleep for diagnostic purposes. Apart from PSG, home-based sleep monitors, especially wearable sleep trackers and bed-based sleep monitors have become quite popular.
Polysomnography, or PSG for short, is regarded as the number one when it comes to monitoring sleep for diagnostic purposes, and as such, deserves the first mention in the article covering such devices. Its ability to detect markers of various milder and more severe sleep disorders like obstructive sleep apnea, periodic limb movement, and narcolepsy, to name a few, earned it much popularity and unchallenged use around the globe. Polysomnography monitors a number of functions that occur during an individual’s sleep:
Eye movements via electrooculography (EOG);
Brain activity via electroencephalography (EEG);
Heart rhythms via electrocardiography (ECG);
Muscle movements via electromyography (EMG).
Besides these aspects, PSG frequently measures blood oxygen levels, respiratory airflow, and includes video or audio recordings to detect patient’s body movements and snoring.
This study is performed in a laboratory during the night, or at a customized time window to accommodate the patient’s usual bedtime circumstances (useful for people with circadian rhythm disorders who sleep at different times of day or night compared to the average nightly bedtime), and its results are reviewed by a licensed professional.
Despite its wide utility, PSG’s high cost and the mere inconvenience a lab sleepover poses for the patients have prompted the discoveries and development of many novel devices similar in purpose, but versatile in logistic aspects and indications of use. Many of them carry potential clinical value, but the particular interest among the audience has arisen for at-home sleep monitoring gadgets. Hence will they also be the focus of our attention in this article.
Although the idea is relatively new, home-based sleep monitors are already quite a few, and the numbers are only expected to grow. They mostly target breathing abnormalities and circadian rhythm deviations; most are worn somewhere on the individual’s body, and some aren’t even initially meant for sleep scanning purposes, but their targeted aspects may also be sleep-informative. The devices we will discuss in some depth can be categorized into the following categories, depending on the way they work:
This exemplary device works via a headband that is intended to be worn during sleep. It detects electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) signals through the night and transfers them to an iPhone or similar receiver station for analysis.
Zeo was evaluated in research where healthy adult subjects underwent polysomnography while also wearing the headband. The results showed around 75% of overall matching between the screenings from PSG and Zeo. Such a study wasn’t conducted on patients with diagnosed sleep disorders, so the accuracy of Zeo monitoring isn’t known – the possible effects of medication, as well as opioids like caffeine, cigarettes or alcohol on Zeo’s precision, aren’t yet explored. Still, the device may be useful to have in a sleep disorder-free household if only to keep track of one’s general state.
A representative model in this category is M1 (SleepImage). Working via a patch containing a wire electrode that one wears on their chest, along with a small processing unit, this device records ECG signals, actigraphy, and the person’s body position. A limitation established with this model is the fact that some people don’t have a typical response to ECG – such is the case with patients experiencing autonomic dysfunction and some types of arrhythmia.
EarlySense Mattress is indicated to be placed under one’s mattress to measure snoring, coughing, heart rate, respiration, and body movement.
Air Cushion is a pressure-sensitive thin cushion that you are supposed to put on top of your mattress. It measures heart rhythm, snoring, respiratory airflow and movements you make during sleep. Compared to PSG screenings, wake and NREM stages are accurately scanned by the Air Cushion the majority of the time, while REM was correctly displayed only about 38% of the time.
Home Health Station (TERVA) is a more complex system that screens and shows heart rhythm, respiratory airflow, blood pressure, body movements and even contains a diary for subjective entries of the individual who is only to position this station somewhere in their house. It has been shown to provide accurate results for sleep-wake differentiating and also was able to record a significantly increased disordered breathing rate in sleep apnea patients versus the people who don’t have this disorder.
SleepMinder is a sleep monitor placed above and near the bed, preferably in the radius of less than a meter away. It works by measuring movements through a radiofrequency monitor and is estimated to recognize slow wave sleep in 96% of the cases, although it has some issues with identifying REM and NREM sleep phases. Much like other movement-measuring devices, SleepMinder overestimates the amount of time a person spends asleep, which makes sense seeing as how one usually stays still while first attempting to fall asleep.
Touch-Free Life Care (TLC) is a wireless data transmitting system that works via a device placed below one’s mattress. It screens heart and respiratory rate as well as one’s activity during sleep but requires a more careful examination and validation from experts.
This category includes many gadgets that weren’t initially intended for sleep surveillance like SmartShirt or Zio. SmartShirt is a T-shirt that has sensors in the cotton material which track heart rhythm, body movement and one’s temperature in real-time. Zio is a gadget designed to scan cardiac arrhythmias and heart rate via a patch with two electrodes intended to be worn on one’s chest for up to 14 days.
For an at-home sleep surveillance method to work, it needs to live up to certain standards. Cost and convenience are two essential factors to keep in mind, as patients could simply undertake PSG if these two didn’t present as difficulties. A device that is to be worn by a person needs to be light in weight and comfortable to a degree to ensure they won’t be reluctant to keep using it after the initial time. Further, the software needs to provide information in a form that anybody could understand with minimum guidance. If a person is to receive their results in a complicated, technical language, they will get discouraged from using the device or misinterpret the feedback it provided. Clarity is key with such sensitive information.
Doctors are used to complementing PSG with a sleep diary to make up for the personal angle that PSG lacks. Not only does the sleep log make sure patients don’t forget to mention an important medical event, but its two or three weeks minimum duration creates enough of a chance for a visible pattern to form. Potential circumstantial events that would have been confusing in a single-day model can thus easily be spotted and disregarded. This harmonious combination should be the aim of all home-based sleep monitoring systems. The setting in the patient’s home would automatically eliminate the sterile atmosphere encountered during a lab sleepover while keeping track of specific bodily functions and their fluctuations. On top of that, a sleep log provided as a second part of the procedure would cover for the personal outlook moment, and the whole system would be able to last as long as necessary to eliminate “accidentals” and leave only real, contributing factors.
Of course, such an ideal mechanism remains out of reach so far but is a goal in mind for the development of future tools and devices.
By now, everybody knows the rule of thumb that adults need an average of eight hours of sleep per night in order to function to their best ability. Uninterrupted, quality sleep is what we are all going for, but measuring how long a person has been asleep, or how long they spent in various stages per night isn’t enough to tell whether their sleep is normal, let alone optimal. The tendency of researchers to combine the total of time one had spent in each stage during sleep and view them as blocks to compare amongst one another is still present and often harmful. Such a practice disregards the importance of the number of transitions between phases and their order, which can very well be the indicator that something is wrong and help with diagnosing a sleep disorder. For instance, patients with sleep apnea tend to rush through sleep stages and switch between them many times during the night. However, the total amount of time the person cumulatively spent in each phase will summarize to the same amount as that of healthy sleep and their apnea, characterized by fragmented sleep, might pass under the radar.
Furthermore, many medications and stimulants have been shown to interfere with and even suppress some sleep phases (REM and slow wave most commonly). Other factors like a person’s age, overall health state, other present conditions, immediate environment, etc. must all be taken into account as well to neutralize the otherwise out of context results, but these variables have their own dimensions, and it’s their average that’s used as the reference.
To summarize, perfectly correct algorithms don’t exist, and we can only get so close to calculating exact measurements of optimal sleep. Experience-based predictions and statistics are all we’ve really got in our arsenal when faced with such issues.
All measuring devices are evaluated based on how they compare to the “golden standard” which is PSG. Although the best we’ve got at the moment, PSG itself scores about 85% when it comes to precision and reliability, which automatically affects the validity of other devices measured against it.
Other than that, all of these devices simply register the events in one’s body, but don’t necessarily indicate as to why they might occur, or take into account the influence of another present condition or external factors such as age, sex, body mass index (BMI) and so forth.
Most of these devices measure relatively correctly the time spent awake and asleep but have issues distinguishing between exact stages, the REM stage being particularly tricky. A generally accepted time frame of stage duration is thirty consecutive seconds. If a monitor measures intervals as longer or shorter than that, the results might present differently, and comparison to PSG will be more difficult.
Finally, it is crucial to note that these devices get developed faster than specialists are able to test them thoroughly and validate them. Using a monitoring device at home can be helpful for an individual to grasp some basic knowledge about what goes on in their sleep, experiment with their routine and potentially notice when something goes downhill, but these gadgets, in reality, are as efficient as a weight scale or a thermometer (but less accurate). They are by no means intended to replace sleep clinic appointments, studies, and diagnostic procedures! Even if there were a home-based sleep screening system as sophisticated as PSG, sleep specialists would be the ones to review and analyze the collected data, diagnose patients and plan any future action.
The verdict on at-home sleep tracking systems is that, albeit more lazy and practical, they aren’t to be overestimated and used without consultation with professionals. Most of the gadgets one comes across on internet platforms haven’t yet been validated, so patients need to be cautious and responsible. If you suspect an issue, reach out to a sleep doctor. Not only are they trained to know all the problems related to the individual aspects of diagnostic criteria you may have only heard of, but they will also know how best to combine them in order to take the most advantage of them, all in your benefit.