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http://nopr.niscpr.res.in/handle/123456789/6132Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lahiri, Tapobrata | - |
| dc.contributor.author | Kumar, Upendra | - |
| dc.contributor.author | Mishra, Hrishikesh | - |
| dc.contributor.author | Sarkar, Subrata | - |
| dc.contributor.author | Roy, Arunava Das | - |
| dc.date.accessioned | 2009-10-09T04:26:03Z | - |
| dc.date.available | 2009-10-09T04:26:03Z | - |
| dc.date.issued | 2009-10 | - |
| dc.identifier.issn | 0975-1084 (Online); 0022-4456 (Print) | - |
| dc.identifier.uri | http://hdl.handle.net/123456789/6132 | - |
| dc.description | 866-870 | en_US |
| dc.description.abstract | Chaotic behavior of electrocardiogram (ECG) signal of myocardial and non-myocardial infarctions is differentiated using neuro-GA approach, incorporating heuristically chosen phase space fractal dimension (PSFD) of ECG data. A remarkable improvement of diagnostic efficiency, sensitivity and specificity was observed in case study. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | CSIR | en_US |
| dc.source | JSIR Vol.68(10) [October 2009] | en_US |
| dc.subject | Electrocardiogram | en_US |
| dc.subject | Myocardial infarction | en_US |
| dc.subject | Neuro-GA | en_US |
| dc.subject | chaos | en_US |
| dc.subject | Phase space fractal dimension | en_US |
| dc.subject | Signal processing | en_US |
| dc.title | Analysis of ECG signal by chaos principle to help automatic diagnosis of myocardial infarction | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | JSIR Vol.68(10) [October 2009] | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JSIR 68(10) 866-870.pdf | 153.03 kB | Adobe PDF | View/Open |
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