METHOD AND DEVICE FOR ANALYZING LIVING BODY SIGNAL
PROBLEM TO BE SOLVED: To calculate accurate power by dividing living body signal time series data of equal intervals in time generated from a living body signal into wavelet factors of the complex number of plural frequency bands by complex discrete wavelet conversion, and calculating power of a fre...
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| creator | OSHIMA SHUICHI SHIMAZU MIKIO |
| description | PROBLEM TO BE SOLVED: To calculate accurate power by dividing living body signal time series data of equal intervals in time generated from a living body signal into wavelet factors of the complex number of plural frequency bands by complex discrete wavelet conversion, and calculating power of a frequency component of the respective frequency bands. SOLUTION: An equal interval data input part 101 is provided to input living body signal time series data such as heartbeat fluctuation time series data of equal intervals in time so that time series data from here is divided into wavelet factors of the complex number of one or more frequency bands by complex discrete wavelet conversion. Power of the respective frequency bands is calculated by a square of an absolute value of the wavelet factors of the complec number by power calculating parts 103a to 103f. Accordingly, power of a frequency component in a living body signal can be captured with high time resolution, and power of an input signal can be determined with high accuracy by reflecting only amplitude information by excluding phase information. |
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SOLUTION: An equal interval data input part 101 is provided to input living body signal time series data such as heartbeat fluctuation time series data of equal intervals in time so that time series data from here is divided into wavelet factors of the complex number of one or more frequency bands by complex discrete wavelet conversion. Power of the respective frequency bands is calculated by a square of an absolute value of the wavelet factors of the complec number by power calculating parts 103a to 103f. Accordingly, power of a frequency component in a living body signal can be captured with high time resolution, and power of an input signal can be determined with high accuracy by reflecting only amplitude information by excluding phase information.</description><edition>7</edition><language>eng</language><subject>DIAGNOSIS ; HUMAN NECESSITIES ; HYGIENE ; IDENTIFICATION ; MEDICAL OR VETERINARY SCIENCE ; SURGERY</subject><creationdate>2000</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=20001024&DB=EPODOC&CC=JP&NR=2000296118A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20001024&DB=EPODOC&CC=JP&NR=2000296118A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>OSHIMA SHUICHI</creatorcontrib><creatorcontrib>SHIMAZU MIKIO</creatorcontrib><title>METHOD AND DEVICE FOR ANALYZING LIVING BODY SIGNAL</title><description>PROBLEM TO BE SOLVED: To calculate accurate power by dividing living body signal time series data of equal intervals in time generated from a living body signal into wavelet factors of the complex number of plural frequency bands by complex discrete wavelet conversion, and calculating power of a frequency component of the respective frequency bands. SOLUTION: An equal interval data input part 101 is provided to input living body signal time series data such as heartbeat fluctuation time series data of equal intervals in time so that time series data from here is divided into wavelet factors of the complex number of one or more frequency bands by complex discrete wavelet conversion. Power of the respective frequency bands is calculated by a square of an absolute value of the wavelet factors of the complec number by power calculating parts 103a to 103f. 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SOLUTION: An equal interval data input part 101 is provided to input living body signal time series data such as heartbeat fluctuation time series data of equal intervals in time so that time series data from here is divided into wavelet factors of the complex number of one or more frequency bands by complex discrete wavelet conversion. Power of the respective frequency bands is calculated by a square of an absolute value of the wavelet factors of the complec number by power calculating parts 103a to 103f. Accordingly, power of a frequency component in a living body signal can be captured with high time resolution, and power of an input signal can be determined with high accuracy by reflecting only amplitude information by excluding phase information.</abstract><edition>7</edition><oa>free_for_read</oa></addata></record> |
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| title | METHOD AND DEVICE FOR ANALYZING LIVING BODY SIGNAL |
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