AI Can Predict Brain Age with EEG Recorded Data

Jun, 2021 - By WMR

AI Can Predict Brain Age with EEG Recorded Data

The use of brain age directories as analytical biomarkers and 'vital signs' of brain health has the potential to be beneficial.

According to a study, during an overnight sleep study, based on electroencephalogram data recorded, a profound neural network ideal can precisely predict the age of the brain of healthy person, and EEG-forecasted brain age directories demonstrate distinctive patterns within people with different illnesses.

According to the study the algorithm correctly projected age with a complete inaccuracy of only 4.6 years. Seizure disorders and epilepsy, stroke, higher indications of insomnia, breathing disorder that is apnea-hypopnea index and arousal index and impaired sleep efficiency all had a statistically significant connection with the Absolute Brain Age Index. In respect to the healthy population sample, patients with depression, diabetes, hypertension and severe excessive daytime drowsiness and one with memory and concentration issues had an elevated Brain Age Index on average. Thus the findings, according to the scientists of American Academy of Sleep Medicine, presented that these health issues are linked to differences between one's projected and chronological ages.

Yoav Nygate, a senior AI engineer at EnsoData said that the doctor can only estimate or quantify a patient's age based on their EEG, and the study also specifies that an artificial intelligence algorithm can correctly predict an age of the patient. He also said that as of the model's precision, it is possible to express associations with major disease families and comorbidities by shifting the predicted age from the chronological age. Using AI model deviations, this has the ability to detect unique clinical abnormalities that exist within physiological signals.

Thus utilizing raw EEG data obtained during clinical sleep tests using overnight polysomnography, the researchers of American Academy of Sleep Medicine developed a deep neural network model to predict the age of patients. The brain age index was calculated by subtracting an individual's consecutive age from their EEG-forecasted age and then compelling the total value of this variable which is also known as absolute brain age index. Thus a brain age index, similar to high blood pressure, will one day become a diagnostic biomarker of brain health, indicating the risk of stroke and other cardiovascular illnesses.

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