Detection of Slow Wave Propagation Direction Using Bipolar High-Resolution Recordings.

Show simple item record

dc.contributor.author Han, Henry
dc.contributor.author Cheng, Leo K
dc.contributor.author Avci, Recep
dc.contributor.author Paskaranandavadivel, Niranchan
dc.date.accessioned 2020-12-08T02:29:33Z
dc.date.available 2020-12-08T02:29:33Z
dc.date.issued 2020-7
dc.identifier.isbn 9781728119908
dc.identifier.issn 2375-7477
dc.identifier.uri http://hdl.handle.net/2292/53825
dc.description.abstract Gastric motility is in part coordinated by bio-electrical slow waves. The wavefront orientation of the slow wave contains vital physiological information about the motility condition of the gastrointestinal system. Dysmotility was shown to be associated with dysrhythmic propagation of the slow wave. The most commonly used method to detect wavefront orientation is computationally expensive because of the involvement of activation time identification. The information of local directionality contained in bipolar slow wave recordings could be used to detect the wavefront orientation. An algorithm called bipolar direction detection was developed to utilize the information contained in the bipolar slow wave recordings. Bipolar recordings were constructed by subtracting the unipolar in vivo recordings of directional electrode pairs. Then, time delay information was used to detect the wavefront direction. The algorithm was verified using synthetic data and validated using experimental data. Ten high-resolution in vivo slow wave signals from 5 pigs were recorded for a duration of 2 minutes. The performance was compared against the semi-automated approach, resulting in an average angle error of 20° for the experimental data. The algorithm was able to detect slow wave wavefront orientation with minimal errors rapidly.Clinical relevance-The ability to rapidly detect slow wave propagation direction will enable effective analysis of large data sets, through which we can obtain a better understanding of functional motility disorders and help with diagnosis and treatment.
dc.format.medium Print
dc.publisher IEEE
dc.relation.ispartof 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) in conjunction with the 43rd Annual Conference of the Canadian Medical and Biological Engineering Society
dc.relation.ispartofseries Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
dc.subject Stomach
dc.subject Animals
dc.subject Swine
dc.subject Electrodes
dc.subject Bipolar Disorder
dc.subject Reproduction
dc.subject Algorithms
dc.title Detection of Slow Wave Propagation Direction Using Bipolar High-Resolution Recordings.
dc.type Conference Item
dc.identifier.doi 10.1109/embc44109.2020.9175303
pubs.begin-page 837
pubs.volume 2020
dc.date.updated 2020-11-18T03:31:22Z
dc.rights.holder Copyright: The author en
pubs.end-page 840
pubs.finish-date 2020-7-24
pubs.publication-status Published
pubs.start-date 2020-7-20
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.elements-id 817613
dc.identifier.eissn 2694-0604


Files in this item

There are no files associated with this item.

Find Full text

This item appears in the following Collection(s)

Show simple item record

Share

Search ResearchSpace


Browse

Statistics