Journal article
Stimulus artifact cancellation in the serosal recordings of gastric myoelectric activity using wavelet transform
IEEE transactions on biomedical engineering, v 49(7), pp 681-688
Jul 2002
PMID: 12083302
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Previous studies have shown that electrical stimulation of the stomach (i.e., gastric pacing) with appropriate parameters is a promising method for treatment of gastroparetic patients. The recording of gastric myoelectric activity (GMA) by serosal electrodes is often used to evaluate the effect of stimulation. However, the major problem with the measurement of GMA during gastric pacing is the stimulus artifacts which are often superimposed on the serosal recording and make analysis difficult. The frequency-domain adaptive filter has been used to reduce the stimulus artifacts but only with limited success. This paper describes a wavelet transform-based method for the reduction of stimulus artifacts in the serosal recordings of GMA. The key of this method lies in the use of the fuzzy set theory to select the stimulus artifact-related modulus maxima in the wavelet domain. Both quantitative and qualitative measures show that significant stimulus artifact cancellation was achieved through a series of computer simulations. Results from both single- and multichannel serosally recorded myoelectric signals during gastric pacing are presented to demonstrate the efficiency of the proposed method for the cancellation of stimulus artifacts.
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Details
- Title
- Stimulus artifact cancellation in the serosal recordings of gastric myoelectric activity using wavelet transform
- Creators
- Hualou Liang - Center for Computational Biomedicine, School of Health Information Sciences, The University of Texas Health Sciences Center, Houston 77030, USA. hualou.liang@uth.tmc.eduZhiyue Lin
- Publication Details
- IEEE transactions on biomedical engineering, v 49(7), pp 681-688
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE); United States
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000176245000006
- Scopus ID
- 2-s2.0-0036086083
- Other Identifier
- 991014878002404721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Biomedical