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A Real-Time Weighted-Eigenvector MUSIC Method for Time-Frequency Analysis of Electrogastrogram Slow Wave
Qin SJ(秦书嘉); Miao L(缪磊); Xi N(席宁); Wang YC(王越超); Yang, Chunmin
Department机器人学研究室
Conference Name32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)
Conference DateAugust 30 - September 4, 2010
Conference PlaceBuenos Aires, ARGENTINA
Author of SourceIEEE Engn Med & Biol Soc (EMBS)
Source Publication2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2010
Pages867-870
Indexed ByEI ; CPCI(ISTP)
EI Accession number20110113553808
WOS IDWOS:000287964001068
Contribution Rank1
ISSN1557-170X
ISBN978-1-4244-4124-2
KeywordMultiple Signal Classification (Music) Time-frequency Analysis Electrogastrogram (Egg) Slow Wave
AbstractThe surface electrogastrogram (EGG) records the electrical slow wave of the stomach noninvasively, whose frequency is a useful clinical indicator of the state of gastric motility. Estimators based on the periodogram method are widely adopted to obtain this parameter. But they are with a poor frequency domain resolution when the data window is short in time-frequency analysis, and have not taken full advantage of the slow wave model. We present a modified multiple signal classification (MUSIC) method for computing the frequency from surface EGG records, developing it into a real-time time-frequency analysis algorithm. Simulations indicate that the modified MUSIC method has better performance in resolution and precision in the sinusoid-like resultant signal frequency detecting than periodogram. Volunteer data tests show that the modified MUSIC method is stable and efficient for clinical applications, and reduces the danger of pseudo peaks for the diagnosis.
Language英语
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/8517
Collection机器人学研究室
Affiliation1.Graduate School of the Chinese Academy of Sciences, China
2.State Key Lab. of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, China
3.Department of Electrical and Computer Engineering, Michigan State University, United States
4.Gastrointestinal Department of Air Force General Hospital, Australia
Recommended Citation
GB/T 7714
Qin SJ,Miao L,Xi N,et al. A Real-Time Weighted-Eigenvector MUSIC Method for Time-Frequency Analysis of Electrogastrogram Slow Wave[C]//IEEE Engn Med & Biol Soc (EMBS). Piscataway, NJ, USA:IEEE,2010:867-870.
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