WAVEFRONT
Novel Algorithm WAVEFRONT[TM] enables automatic detection of “Neural Silences” called CSDs, which are a leading cause of previously unknown brain conditions.
What are Cortical Spreading Depolarizations (CSDs)?
CSDs are slow-moving waves of electrical shutdown in the brain that can silently damage tissue after injuries like a concussion or stroke.
Cortical
On the surcace of the Brain
Spreading
Like. a ripple effect in water
Depolarizations
Cells lose their Electrical balance
In 2018, CSDs were found to cause a metabolic crisis in the brain, as they use more energy in the brain than a seziure
WAVEFRONT is the world’s first algorithm for automatically detecting CSDs using non-invasive brain recordings from electroencephalogram (EEG) signals.
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Reliable CSD detection is critical, specifically for TBI patients, as CSD occurrence and frequency can be read as biomarkers by clinicians to determine appropriate treatment.
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Currently, CSDs are detected invasively using Electrocorticography (ECoG) signals. ECoG has limited spatial coverage, and its highly invasive nature limits its diagnostic utility.
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The introduction of an automated EEG-based method for detecting CSDs will lead to increased detection rates and improved patient outcomes, while simultaneously decreasing time and cost strains on healthcare networks.
WAVEFRONT[TM] Detection Algorithm
Researchers: WAVEFRONT[TM] is now available for download on GitHub!
Click here to download WAVEFRONT[TM]
Introducing the first Graphical User Interface built around WAVEFRONT[TM]
This GUI allows users to use the WAVEFRONT Algorithm in a user-friendly, and intuitive manner. This GUI is built similarly to existing eeg analysis platforms, for seamless integration into existing workflows, while displaying algorithm outputs clearly and intuitively. By displaying the temporal detection information in parallel with the data, end users have full transparency regarding how the algorithm reaches its results.
Additionally, our team is developing an ONLINE version of WAVEFRONT, identical to our OFFLINE version. This version is useful for comparing algorithmic results to existing methods and analyzing existing data sets.
In this example of our OFFLINE version, the dotted green line represents a ‘Ground Truth’ CSD determined by existing methodologies (time-intensive ECoG analysis performed by trained specialists). The red lines represent automated CSD detections from WAVEFRONT.
Our ONLINE version will be able to perform the exact sample processing and analysis shown as our OFFLINE version but is designed for analyzing live data streams. This version will allow for optimizing the pipeline to accommodate a continuous input of data and will allow for rapid integration into existing care settings.