Summary: Researchers have created a brain-based check that can identify excessive daytime sleepiness in only two minutes, probably replacing the long hospital procedure used today. This test measures how fast a person is likely to fall sleep, indicating their overall level of lethargy, using EEG to observe cerebral irritability.
This novel approach does aid in the evaluation of sleeping disorders and aid in the selection of people for high-arousal activities like driving or operating machinery. The test may enhance workplace safety and assist people with chronic sleep issues by offering a fast, available measure of sleepiness.
Important Information:
- In only two days, a fresh EEG-based test can identify daytime sleepiness.
- paths neuronal excitability to accurately measure lethargy.
- May increase office security by identifying sleepiness-related dangers.
Origin: University of South Australia
At some point, many of us have experienced the post-lunch weary hours, struggling to stay alert mid-afternoon, and reaching for the liquid drink to refresh a weary body.
What about those who experience “excessive nighttime somnolence,” or sleepiness, throughout the day?
It’s a recognised medical condition that is normally diagnosed by a doctor after a full-day hospital procedure, undergoing what is called the , Multiple Wakefulness Test , ( MWT).
Now, scientists from the , University of South Australia , have identified a fresh, brain-based measure of lethargy that may provide a treatment in only two days.
The electrical activity of the brain is measured by an electroencephalogram ( EEG), which is an electrical device that is attached to the scalp. This activity can determine how long it takes for someone to fall asleep.
In a separate, recent paper published in , Brain Research,  , lead researcher, UniSA neuroscientist , Dr Alex Chatburn,  , says that using fresh EEG markers linked to genetic processes may determine whether someone is healthy enough to travel, operate machinery, or even have the intellectual capacity to sit an exam.
Tiredness is a crucial genetic indicator of the body’s need for sleep, according to Dr. Chatburn, but it’s difficult to measure how well this state is in humans.
Traditional markers face significant limitations and do n’t tell the whole story, despite EEG technology having long been used to study brain activity while sleeping. They do n’t reflect the underlying biological processes, whereas our method tracks neuronal excitability, corresponding with the brain’s sleep-wake processes”.
Dr Chatburn says the analysis has wide-ranging repercussions.
A better understanding of sleepiness, according to the author,” could lead to advances in scientific knowledge and also lead to practical advantages for managing sleep disorders like insomnia, sleep apnoea, or other conditions where people experience disrupted sleep but do n’t feel sleepy.”
These findings could also be used to improve workplace protection, where detecting and managing sleepiness may help to reduce accidents in highly focused industries.
About this information about rest and neurotech study
Author: Candy Gibson
Source: University of South Australia
Contact: Candy Gibson – University of South Australia
Image: The image is credited to Neuroscience News
Original Research: Start entry.
” Factors towards a neurobiologically-informed EEG assessment of lethargy” by Alex Chatburn et cetera. Mental Research
Abstract
Factors towards a neurobiologically-informed EEG dimension of lethargy
Although humans and other species experience normal sleep, our knowledge of how and why we sleep is currently incomplete.
This is especially prevalent in studies looking at the neurophysiological basis for human sleepiness, where a number of electroencephalogram ( EEG ) phenomena have been linked to a protracted amount of wakefulness.
This makes it difficult for researchers to determine the physiological rest needed and affects our understanding of the nature of sleep.
Recent advances in theory and technology may help us better understand the physiological basis of homeostatic sleepiness. This may be a result of changes in synaptic excitability and changes in the excitation/inhibition balance in synaptic circuits, and it can possibly be instantly measured using the aperiodic component of the EEG.
We review the books on EEG-derived lethargy indicators in people and argue that changes in these electrophysiological signs may be the result of changes in synaptic activity as evidenced by changes in aperiodic signs.
We support the use of aperiodic signs from the EEG to predict tiredness and make recommendations for future studies based on these.
