Correlation-based classification of heartbeats for individual identification
Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Singh, Yogendra Narain [verfasserIn] Gupta, Phalguni [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2009 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Soft Computing - Springer-Verlag, 2003, 15(2009), 3 vom: 05. Nov., Seite 449-460 |
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| Übergeordnetes Werk: |
volume:15 ; year:2009 ; number:3 ; day:05 ; month:11 ; pages:449-460 |
| Links: |
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| DOI / URN: |
10.1007/s00500-009-0525-y |
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| 520 | |a Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. | ||
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10.1007/s00500-009-0525-y doi (DE-627)SPR006478646 (SPR)s00500-009-0525-y-e DE-627 ger DE-627 rakwb eng Singh, Yogendra Narain verfasserin aut Correlation-based classification of heartbeats for individual identification 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. Heartbeat (dpeaa)DE-He213 Biometrics (dpeaa)DE-He213 Individual identification (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Gupta, Phalguni verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 15(2009), 3 vom: 05. Nov., Seite 449-460 (DE-627)SPR006469531 nnns volume:15 year:2009 number:3 day:05 month:11 pages:449-460 https://dx.doi.org/10.1007/s00500-009-0525-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 15 2009 3 05 11 449-460 |
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10.1007/s00500-009-0525-y doi (DE-627)SPR006478646 (SPR)s00500-009-0525-y-e DE-627 ger DE-627 rakwb eng Singh, Yogendra Narain verfasserin aut Correlation-based classification of heartbeats for individual identification 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. Heartbeat (dpeaa)DE-He213 Biometrics (dpeaa)DE-He213 Individual identification (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Gupta, Phalguni verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 15(2009), 3 vom: 05. Nov., Seite 449-460 (DE-627)SPR006469531 nnns volume:15 year:2009 number:3 day:05 month:11 pages:449-460 https://dx.doi.org/10.1007/s00500-009-0525-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 15 2009 3 05 11 449-460 |
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10.1007/s00500-009-0525-y doi (DE-627)SPR006478646 (SPR)s00500-009-0525-y-e DE-627 ger DE-627 rakwb eng Singh, Yogendra Narain verfasserin aut Correlation-based classification of heartbeats for individual identification 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. Heartbeat (dpeaa)DE-He213 Biometrics (dpeaa)DE-He213 Individual identification (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Gupta, Phalguni verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 15(2009), 3 vom: 05. Nov., Seite 449-460 (DE-627)SPR006469531 nnns volume:15 year:2009 number:3 day:05 month:11 pages:449-460 https://dx.doi.org/10.1007/s00500-009-0525-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 15 2009 3 05 11 449-460 |
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10.1007/s00500-009-0525-y doi (DE-627)SPR006478646 (SPR)s00500-009-0525-y-e DE-627 ger DE-627 rakwb eng Singh, Yogendra Narain verfasserin aut Correlation-based classification of heartbeats for individual identification 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. Heartbeat (dpeaa)DE-He213 Biometrics (dpeaa)DE-He213 Individual identification (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Gupta, Phalguni verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 15(2009), 3 vom: 05. Nov., Seite 449-460 (DE-627)SPR006469531 nnns volume:15 year:2009 number:3 day:05 month:11 pages:449-460 https://dx.doi.org/10.1007/s00500-009-0525-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 15 2009 3 05 11 449-460 |
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10.1007/s00500-009-0525-y doi (DE-627)SPR006478646 (SPR)s00500-009-0525-y-e DE-627 ger DE-627 rakwb eng Singh, Yogendra Narain verfasserin aut Correlation-based classification of heartbeats for individual identification 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. Heartbeat (dpeaa)DE-He213 Biometrics (dpeaa)DE-He213 Individual identification (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Gupta, Phalguni verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 15(2009), 3 vom: 05. Nov., Seite 449-460 (DE-627)SPR006469531 nnns volume:15 year:2009 number:3 day:05 month:11 pages:449-460 https://dx.doi.org/10.1007/s00500-009-0525-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 15 2009 3 05 11 449-460 |
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Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. |
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Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. |
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Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR006478646</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20201124002732.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2009 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00500-009-0525-y</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR006478646</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00500-009-0525-y-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Singh, Yogendra Narain</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Correlation-based classification of heartbeats for individual identification</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2009</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper proposes new techniques to delineate P and T waves efficiently from heartbeats. The delineation results have been found to be optimum and stable in comparison to other published results. These delineators are used along with QRS complex to extract various features of classes time interval, amplitude and angle from clinically dominant fiducials on each heartbeat of the electrocardiogram (ECG). A new identification system has been proposed in this study, which uses these features and makes the decision on the identity of an individual with respect to a given database. The system has been tested against a set of 250 ECG recordings prepared from 50 individuals of Physionet. The matching decisions are made on the basis of correlation between heartbeat features among individuals. The proposed system has achieved an equal error rate of less than 1.01 with an accuracy of 99%.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Heartbeat</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Biometrics</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Individual identification</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Correlation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gupta, Phalguni</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Soft Computing</subfield><subfield code="d">Springer-Verlag, 2003</subfield><subfield code="g">15(2009), 3 vom: 05. Nov., Seite 449-460</subfield><subfield code="w">(DE-627)SPR006469531</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:15</subfield><subfield code="g">year:2009</subfield><subfield code="g">number:3</subfield><subfield code="g">day:05</subfield><subfield code="g">month:11</subfield><subfield code="g">pages:449-460</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s00500-009-0525-y</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">15</subfield><subfield code="j">2009</subfield><subfield code="e">3</subfield><subfield code="b">05</subfield><subfield code="c">11</subfield><subfield code="h">449-460</subfield></datafield></record></collection>
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