File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/CIVEMSA.2013.6617398
- Scopus: eid_2-s2.0-84886808533
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: Automatic ECG artifact removal in the real-time SEMG recording system
| Title | Automatic ECG artifact removal in the real-time SEMG recording system |
|---|---|
| Authors | |
| Keywords | Surface electromyography Electrocardiography Low back muscle Independent component analysis |
| Issue Date | 2013 |
| Publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6598376 |
| Citation | The 2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA 2013), Milan, Italy, 15-17 July 2013. In Conference Proceedings, 2013, p. 72-77 How to Cite? |
| Abstract | The contaminated electrocardiography (ECG) is a big problem in the surface electromyography (SEMG) signal detection and analysis. The objective of the current study is to propose and validate an algorithm for the automated feature cognition and identification for eliminating ECG artifact from the raw SEMG signals. The utilization of Independent Component Analysis (ICA) method is to decompose the raw SEMG signals into individual independent source components. After that, some of the independent source components with the characteristics of ECG artifact were detected by the automated identification algorithm and thereafter eliminated. The sensitivity and specificity of the algorithm for distinguishing ECG source components from independent source components are 100% and 99% respectively. The automated identification algorithm exhibits the prominent performance of recognition for ECG artifact and can be considered reliable and effective. |
| Persistent Identifier | http://hdl.handle.net/10722/186876 |
| ISBN |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Hu, Y | en_US |
| dc.contributor.author | Kwok, J | en_US |
| dc.contributor.author | Tse, J | en_US |
| dc.date.accessioned | 2013-08-20T12:22:54Z | - |
| dc.date.available | 2013-08-20T12:22:54Z | - |
| dc.date.issued | 2013 | en_US |
| dc.identifier.citation | The 2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA 2013), Milan, Italy, 15-17 July 2013. In Conference Proceedings, 2013, p. 72-77 | en_US |
| dc.identifier.isbn | 978-1-4673-4703-7 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/186876 | - |
| dc.description.abstract | The contaminated electrocardiography (ECG) is a big problem in the surface electromyography (SEMG) signal detection and analysis. The objective of the current study is to propose and validate an algorithm for the automated feature cognition and identification for eliminating ECG artifact from the raw SEMG signals. The utilization of Independent Component Analysis (ICA) method is to decompose the raw SEMG signals into individual independent source components. After that, some of the independent source components with the characteristics of ECG artifact were detected by the automated identification algorithm and thereafter eliminated. The sensitivity and specificity of the algorithm for distinguishing ECG source components from independent source components are 100% and 99% respectively. The automated identification algorithm exhibits the prominent performance of recognition for ECG artifact and can be considered reliable and effective. | - |
| dc.language | eng | en_US |
| dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6598376 | - |
| dc.relation.ispartof | Proceedings of IEEE International Conference on Computational Intelligence & Virtual Environments for Measurement Systems & Applications, CIVEMSA 2013 | en_US |
| dc.subject | Surface electromyography | - |
| dc.subject | Electrocardiography | - |
| dc.subject | Low back muscle | - |
| dc.subject | Independent component analysis | - |
| dc.title | Automatic ECG artifact removal in the real-time SEMG recording system | en_US |
| dc.type | Conference_Paper | en_US |
| dc.identifier.email | Hu, Y: yhud@hku.hk | en_US |
| dc.identifier.email | Kwok, J: jerrykwl@hku.hk | en_US |
| dc.identifier.authority | Hu, Y=rp00432 | en_US |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1109/CIVEMSA.2013.6617398 | - |
| dc.identifier.scopus | eid_2-s2.0-84886808533 | - |
| dc.identifier.hkuros | 220336 | en_US |
| dc.identifier.spage | 72 | - |
| dc.identifier.epage | 77 | - |
| dc.publisher.place | United States | en_US |
| dc.customcontrol.immutable | sml 131016 | - |