Processing for multi-channel signals
Method and apparatus for improved processing for multi-channel signals. In an exemplary embodiment, an anomaly metric is computed for a multi-channel signal over a time window. The magnitude of the anomaly metric may be used to determine whether an anomaly is present in the multi-channel signal over...
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| creator | ECHAUZ JAVIER RAMÓN LEYDE KENT W SNYDER DAVID E |
| description | Method and apparatus for improved processing for multi-channel signals. In an exemplary embodiment, an anomaly metric is computed for a multi-channel signal over a time window. The magnitude of the anomaly metric may be used to determine whether an anomaly is present in the multi-channel signal over the time window. In an exemplary embodiment, the anomaly metric may be a condition number associated with the singular values of the multi-channel signal over the time window, as further adjusted by the number of channels to produce a data condition number. Applications of the anomaly metric computation include the scrubbing of signal archives for epileptic seizure detection/prediction/counter-prediction algorithm training, pre-processing of multi-channel signals for real-time monitoring of bio-systems, and boot-up and/or adaptive self-checking of such systems during normal operation. |
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In an exemplary embodiment, an anomaly metric is computed for a multi-channel signal over a time window. The magnitude of the anomaly metric may be used to determine whether an anomaly is present in the multi-channel signal over the time window. In an exemplary embodiment, the anomaly metric may be a condition number associated with the singular values of the multi-channel signal over the time window, as further adjusted by the number of channels to produce a data condition number. Applications of the anomaly metric computation include the scrubbing of signal archives for epileptic seizure detection/prediction/counter-prediction algorithm training, pre-processing of multi-channel signals for real-time monitoring of bio-systems, and boot-up and/or adaptive self-checking of such systems during normal operation.</description><language>eng</language><subject>DIAGNOSIS ; HUMAN NECESSITIES ; HYGIENE ; IDENTIFICATION ; MEDICAL OR VETERINARY SCIENCE ; SURGERY</subject><creationdate>2014</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20140930&DB=EPODOC&CC=US&NR=8849390B2$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76419</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20140930&DB=EPODOC&CC=US&NR=8849390B2$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>ECHAUZ JAVIER RAMÓN</creatorcontrib><creatorcontrib>LEYDE KENT W</creatorcontrib><creatorcontrib>SNYDER DAVID E</creatorcontrib><title>Processing for multi-channel signals</title><description>Method and apparatus for improved processing for multi-channel signals. In an exemplary embodiment, an anomaly metric is computed for a multi-channel signal over a time window. The magnitude of the anomaly metric may be used to determine whether an anomaly is present in the multi-channel signal over the time window. In an exemplary embodiment, the anomaly metric may be a condition number associated with the singular values of the multi-channel signal over the time window, as further adjusted by the number of channels to produce a data condition number. Applications of the anomaly metric computation include the scrubbing of signal archives for epileptic seizure detection/prediction/counter-prediction algorithm training, pre-processing of multi-channel signals for real-time monitoring of bio-systems, and boot-up and/or adaptive self-checking of such systems during normal operation.</description><subject>DIAGNOSIS</subject><subject>HUMAN NECESSITIES</subject><subject>HYGIENE</subject><subject>IDENTIFICATION</subject><subject>MEDICAL OR VETERINARY SCIENCE</subject><subject>SURGERY</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2014</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZFAJKMpPTi0uzsxLV0jLL1LILc0pydRNzkjMy0vNUSjOTM9LzCnmYWBNA1KpvFCam0HBzTXE2UM3tSA_PrW4IDE5NS-1JD402MLCxNLY0sDJyJgIJQDfWSbV</recordid><startdate>20140930</startdate><enddate>20140930</enddate><creator>ECHAUZ JAVIER RAMÓN</creator><creator>LEYDE KENT W</creator><creator>SNYDER DAVID E</creator><scope>EVB</scope></search><sort><creationdate>20140930</creationdate><title>Processing for multi-channel signals</title><author>ECHAUZ JAVIER RAMÓN ; LEYDE KENT W ; SNYDER DAVID E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US8849390B23</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2014</creationdate><topic>DIAGNOSIS</topic><topic>HUMAN NECESSITIES</topic><topic>HYGIENE</topic><topic>IDENTIFICATION</topic><topic>MEDICAL OR VETERINARY SCIENCE</topic><topic>SURGERY</topic><toplevel>online_resources</toplevel><creatorcontrib>ECHAUZ JAVIER RAMÓN</creatorcontrib><creatorcontrib>LEYDE KENT W</creatorcontrib><creatorcontrib>SNYDER DAVID E</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ECHAUZ JAVIER RAMÓN</au><au>LEYDE KENT W</au><au>SNYDER DAVID E</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Processing for multi-channel signals</title><date>2014-09-30</date><risdate>2014</risdate><abstract>Method and apparatus for improved processing for multi-channel signals. In an exemplary embodiment, an anomaly metric is computed for a multi-channel signal over a time window. The magnitude of the anomaly metric may be used to determine whether an anomaly is present in the multi-channel signal over the time window. In an exemplary embodiment, the anomaly metric may be a condition number associated with the singular values of the multi-channel signal over the time window, as further adjusted by the number of channels to produce a data condition number. Applications of the anomaly metric computation include the scrubbing of signal archives for epileptic seizure detection/prediction/counter-prediction algorithm training, pre-processing of multi-channel signals for real-time monitoring of bio-systems, and boot-up and/or adaptive self-checking of such systems during normal operation.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | DIAGNOSIS HUMAN NECESSITIES HYGIENE IDENTIFICATION MEDICAL OR VETERINARY SCIENCE SURGERY |
| title | Processing for multi-channel signals |
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