U.S. Patent No. 8,187,181: Scoring of sensed neurological signals for use with a medical device system
- Assignee(s): Medtronic, Inc.
- Inventor(s): Ivan Osorio, Mark G. Frei, Nina M. Graves, Jonathon E. Giftakis
- Technology Category: Neuro-monitoring
- Issue Date: May 29, 2012
While some events caused by neurological disorders are readily apparent, other undesirable neurological activity may still occur but be less visible with the patient not exhibiting symptoms. Such activity may go undetected and result in disorders worsening due to lack of treatment. The ‘181 patent describes techniques for detecting, ranking and presenting neurological events of varying severity, in some cases enabling more subtle afflictions to be discerned. A specification spanning 33 illustration sheets and 22 pages of written material discloses various aspects of detecting features of such events including identifying the severity of activity based on the intensity, duration or spreading of neural clustering activity (see illustrative image above). The importance of the addressed problem space, independent claim coverage of the inventive concept, extensive specification and 80+ forward citations are among that contribute to making the ‘181 patent as a key non-invasive neurotechology patent.
A medical device system capable of scoring a severity of sensed neurological signals relating to a nervous system disorder. The system comprises a monitoring element that receives a neurological signal having at least one event to be scored. The medical device system identifies one or more features of the neurological signal to use in scoring and computes a score of relative severity of the event using the identified feature. Once two or more events have been scored, the events may be ranked by severity relative to each other.
Illustrative Claim 12. A computer-implemented method for determining the severity of a detection cluster comprising:
- determining using a processor that one or more sensed neurological signals represent a plurality of detection clusters;
- identifying using a processor at least one feature of each of the detection clusters;
- computing using a processor a relative severity score for each of the detection clusters using the identified at least one feature; and
- ranking using a processor the plurality of detection clusters by severity using the relative severity scores.
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