Processing EEG signals to predict brain damage

Surgery – Diagnostic testing – Detecting brain electric signal

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Reexamination Certificate

active

06931274

ABSTRACT:
Rapid and accurate in-vivo assessment of cerebral white matter injury particularly for pre-term infants, for timely treatment and/or prediction of outcomes has been very limited. This invention exploits the discovery that reduced high-frequency EEG intensity, particularly as shown by the upper spectral edge frequency, is a good indicator of cerebral white matter neural injury and is well correlated with MRI results. With more experience of clinical cases, a set of simple rules such as “if the spectral edge value is below 8 Hz there is a high likelihood of injury” may be validated, yet the EEG technology involved is largely invisible to the user. In the invention, EEG signals are processed by software to obtain, store, and graphically display bilaterally collected EEG spectral edge and intensity values over from hours to weeks. Rejection of corrupted signals by filtering and gating means is responsive to incoming signal characteristics, to additional inputs such as motion sensors or impedance tests, and to patient data (gestational age in particular). The invention includes the software and methods of use.

REFERENCES:
patent: 5309923 (1994-05-01), Leuchter et al.
patent: 6493577 (2002-12-01), Williams

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Processing EEG signals to predict brain damage does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Processing EEG signals to predict brain damage, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Processing EEG signals to predict brain damage will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3453033

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.