UCC research a gamechanger in monitoring newborns

Using Artificial Intelligence, UCC scientists have pioneered a new approach which uses sound, rather than visual images, to analyse brainwaves
UCC research a gamechanger in monitoring newborns

The new AI-driven mechanism pioneered by the UCC team converts brainwaves to sound.

RESEARCHERS at UCC have discovered a new and potentially life-saving method of analysing new-born babies’ brainwaves.

Using Artificial Intelligence (AI), UCC scientists have pioneered a new approach which uses sound, rather than visual images, to analyse brainwaves.

The new method, which converts brainwaves to sound, has been hailed as a potential game-changer in the monitoring of brainwaves or Electroencephalograms (EEG).

The UCC researchers say the new approach brings both accuracy and speed while requiring no training to be adopted in clinical settings.

Analysing EEG is the gold standard in detecting anomalies in brain activity such as seizures.

This ground-breaking research has the potential to make EEG monitoring more prevalent in medical settings — including those in disadvantaged communities — leading to faster response times and the potential to save many vulnerable lives.

The new approach also reduces the burden of analysing EEG data, allowing two hours of EEG to be screened in just three seconds.

The new method of analysis extends the concept of the stethoscope to listen to heart, lung, or other sounds from a patient’s body to also listen to brainwaves.

While neurophysiologists use EEG recordings to identify seizures visually, this is a slow and cumbersome process for the medic, which involves scrolling through thousands of images.

This expertise also requires a significant amount of training that is not readily available on a continuous basis in all hospitals.

The new AI-driven mechanism pioneered by the UCC team converts brainwaves to sound.

Human ears are more sensitive to changes in frequency, which can be a signature of many seizures, so by focusing the listener’s attention to interesting segments in the recording, EEG seizures can be distinctly heard.

Feedback from medical professionals with no training in interpreting raw neonatal EEG suggests that the accuracy of detecting the presence of a seizure in a long recording using this method is on par with experienced neurophysiologists trained to visually interpret neonatal EEG.

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