Are you unable to get seven to eight hours of sleep at night? Are your everyday activities completely hindered because of your tiredness or sleepiness throughout the day?
If so, you might have a sleeping disorder!
The evaluation process is quite extensive. But because of some new advancements in technology, doctors can speed up the process of testing.
It helps them carry on with your treatment, so you can know how to sleep better. Early diagnosis is particularly essential when it comes to sleeping anomalies.
If you don’t resolve them soon, the situation can worsen in the long run.
What Are Some Common Sleep Disorders?
When a person’s quality and duration of sleep has a lasting negative impact on their life as they are awake, it is classified as a sleep disorder.
The most common symptom of sleep disorders is chronic sleeplessness and having highly intrusive thoughts at night for prolonged periods.
The classification system for the diagnosis of a sleep disorder is a highly tedious process. It requires several months of doctor visits and extensive examinations. Luckily, a new Artificial Intelligence (AI) algorithm may help improve the diagnosis, treatment, and analysis of these sleep disorders.
Sleep Disorders Cause Mental Illnesses
Though sleep disorders may be a disorder of their own, they are often underlying precursors of something else. For example, they can be symptoms of other mental health problems such as ADHD or clinical depression.
Sleep disorders disrupt a person’s life entirely if they go undiagnosed. Furthermore, they can often lead to mental health issues such as anxiety.
Both sleep and mental health are complicated problems influenced by a variety of circumstances.
But given their close relationship, there is reason to assume that enhancing sleep can positively impact mental health. Moreover, you can also use it to treat a variety of psychiatric diseases.
Sleep disorders such as insomnia, sleep apnea, restless leg syndrome, and narcolepsy are most common. They have long, complicated processes of screening, spanning several months.
To make a correct diagnosis, doctors evaluate patients’ sleep patterns for several months.
An evaluation of sleep stages is crucial to the early steps of the treatment.
Students at the University of Copenhagen have found a possible means to make these evaluations more efficient.
What is Polysomnography?
Tests to evaluate sleep disorders include overnight oximetry, polysomnography, Multiple Sleep Latency Testing (MSLT), and actigraphy. Conducting home studies is also an option, but it is not always very effective.
One of the most common tests for diagnosing and evaluating a sleep disorder is polysomnography (PSG).
A PSG, also known as a sleep study, is a method in which you admit a patient to a sleep clinic, usually overnight.
Experts use several instruments to detect the heart rate, oxygen levels, neural waves, and blood pressure. On top of that, they even observe the eye movements of patients as they sleep.
The primary objective of the PSG is to detect any form of disruption in the mentioned variables to identify the causes behind these disruptions.
The test evaluates the Rapid-Eye-Movement (REM) and Non-Rapid-Eye movement cycles. Since the brain-wave shifts indicate a shift in a process, patients with a sleep disorder would have disruptions in their cycles or incomplete cycles.
Doctors recommend the test for both post-diagnosis and suspect disorders such as narcolepsy, chronic insomnia, limb movement disorder, or REM sleep behavior disorder.
A New Standard for Testing
The University of Copenhagen’s Department of Computer Science has collaborated with the Danish Center for Sleep Medicine, Denmark. They are developing an algorithm with data of polysomnography (PSG) tests from over 15,000 patients. It will help with not only the treatment of sleep disorders but our knowledge of them.
The researchers that created the program were able to assure optimal functionality by collecting data from several sources.
In total, 15,660 nights of sleep were collected and utilized to train the algorithm from the United States and several European countries.
This new algorithm is a neural network providing data that can be used to develop new methods for assessing sleep stages, created with over 15,000 participants over 16 clinical studies
The neural network that drives the algorithm was trained and tested on the most large-scale PSG study history.
More than 800,000 polysomnography examinations were performed in 2014 on patients with sleep apnea and other more difficult sleeping problems in the US alone.
Does it Work Better Than the Existing Tech?
A doctor’s analysis of a PSG scan takes hours. By implementing the new algorithm, several thousand medical hours might be freed.
“Achieving this kind of generalization is one of the greatest challenges in medical data analysis.” Said one of the professionals overseeing the development of the algorithm.
They believe that, in the future, the algorithm will aid clinicians and researchers all over the world in learning more about sleep problems.
The sleep analysis program is free to download and use at sleep.ai.ku.dk, and it can be used by anybody, anywhere — even if there isn’t a sleep clinic nearby.
AI has a lot of potential and may result in considerable advances in sleep medicine.
The capacity of this algorithm to categorize and track sleep cycles at an expert level would help sleep researchers to collect more data on sleep disorders while also freeing up resources for other experiments and research.
This system has the potential to become a global standard for sleep staging. The algorithm developers, along with Doctors specializing in sleep disorders, hope that this new algorithm is regarded as an official standard.
A lack of sleep completely ruins the brain’s chemistry and functioning. Therefore, sleep disorders are a significant issue since they are increasing day by day.
The new AI developed by the team at Copenhagen still has room for improvement. But there is no doubt that it will help millions of patients suffering from these problems and are wondering how to sleep better.