Getting to grips with seizure prediction

November 7, 2013

A device that could predict when a person with epilepsy might next have a seizure is one step closer to reality thanks to the development of software by researchers in the USA. Details are to be published in a forthcoming issue of the International Journal of Data Mining and Bioinformatics.

Seizure prediction is an important medical aim for the many people who suffer from epilepsy and related neurological disorders. Medication is available for controlling seizures but a way to determine in advance when an attack might occur would allow sufferers to live a normal life safe, drive vehicles and operate hazardous machinery etc, safe in the knowledge that they will know when a seizure is about to occur and they can move out of harm's way in plenty of time.

Shouyi Wang of the Department of Industrial and Manufacturing Systems Engineering, at University of Texas at Arlington, Arlington, TX, and Wanpracha Art Chaovalitwongse of the University of Washington, Seattle and Stephen Wong of the University of Medicine and Dentistry of New Jersey, in New Brunswick, explain that current epileptic seizure prediction algorithms require much prior knowledge of a patient's pre-seizure electroencephalogram (EEG) patterns. This usually makes them entirely impractical as pre-seizure EEGs are rarely available in the requisite detail or number.

The team has now developed software that can learn about the patient's normal and seizure electrical activity from long-term EEG recordings after diagnosis. The learning process then allows the software to predict when another seizure may occur based on the learned patterns. Ultimately, a portable device with discrete electrodes, perhaps worn under a cap or hat would utilize this algorithm to give the patient an early warning of an imminent seizure. This would allow them to pull over safely if driving or otherwise move out of hazardous situation and into a safe environment well before the seizure begins.

"Our experimental results showed that the adaptive prediction scheme could achieve a consistent better prediction performance than a chance model and the non-updating system," the team says. "This study confirmed that the concept of using adaptive learning algorithms to improve the adaptability of seizure prediction is conceivable," the researchers add. "If a seizure-warning device is ever to become a reality, adaptive learning techniques will play an important role."

Explore further: Surprising results from study of non-epileptic seizures

More information: "A gradient-based adaptive learning framework for online seisure prediction," International Journal of Data Mining and Bioinformatics, in 2014, 10, 49-64

Related Stories

Surprising results from study of non-epileptic seizures

December 2, 2012
A Loyola University Medical Center neurologist is reporting surprising results of a study of patients who experience both epileptic and non-epileptic seizures.

World-first study predicts epilepsy seizures in humans

May 2, 2013
A small device implanted in the brain has accurately predicted epilepsy seizures in humans in a world-first study led by Professor Mark Cook, Chair of Medicine at the University of Melbourne and Director of Neurology at St ...

Important breakthrough in identifying effect of epilepsy treatment

October 31, 2013
50 years after valproate was first discovered, research published today in the journal Neurobiology of Disease, reports how the drug works to block seizure progression.

Progress in the prediction of epilepsy surgery

October 3, 2013
According to this research, developed by researchers of the UPM, CSIC and the Princesa Hospital, personality style, intelligence quotient and hemisphere of seizure origin are factors that would help to predict successfully ...

Implanted device predicts epilepsy seizures in humans

May 1, 2013
For the first time, a small device implanted in the brain has accurately predicted the onset of seizures in some adults who have epilepsy that doesn't respond to drugs, according to a small proof-of-concept study published ...

Recommended for you

In witnessing the brain's 'aha!' moment, scientists shed light on biology of consciousness

July 27, 2017
Columbia scientists have identified the brain's 'aha!' moment—that flash in time when you suddenly become aware of information, such as knowing the answer to a difficult question. Today's findings in humans, combined with ...

Scientists block evolution's molecular nerve pruning in rodents

July 27, 2017
Researchers investigating why some people suffer from motor disabilities report they may have dialed back evolution's clock a few ticks by blocking molecular pruning of sophisticated brain-to-limb nerve connections in maturing ...

Social influences can override aggression in male mice, study shows

July 27, 2017
Stanford University School of Medicine investigators have identified a cluster of nerve cells in the male mouse's brain that, when activated, triggers territorial rage in a variety of situations. Activating the same cluster ...

Scientists become research subjects in after-hours brain-scanning project

July 27, 2017
A quest to analyze the unique features of individual human brains evolved into the so-called Midnight Scan Club, a group of scientists who had big ideas but almost no funding and little time to research the trillions of neural ...

Researchers reveal unusual chemistry of protein with role in neurodegenerative disorders

July 27, 2017
A common feature of neurodegenerative diseases is the formation of permanent tangles of insoluble proteins in cells. The beta-amyloid plaques found in people with Alzheimer's disease and the inclusion bodies in motor neurons ...

Mother's brain reward response to offspring reduced by substance addiction

July 27, 2017
Maternal addiction and its effects on children is a major public health problem, often leading to high rates of child abuse, neglect and foster care placement. In a study published today in the journal Human Brain Mapping, ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.