SOLR
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1797365303599955969 |
| author |
Schmidt, Martin |
| author2 |
Kircher, Marco, Noack, Alexander, Malberg, Hagen, Zaunseder, Sebastian |
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m k mk, a n an, h m hm, s z sz |
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Schmidt, Martin, Kircher, Marco, Noack, Alexander, Malberg, Hagen, Zaunseder, Sebastian |
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|
| author_sort |
Schmidt, Martin |
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Library A |
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sid-22-col-qucosa |
| contents |
The QT interval in an electrocardiogram (ECG) reflects complex processes affecting the repolarization of ventricular myocardium. Increased QT interval variability (QTV) is thought to be caused by ventricular repolarization lability and has been associated with cardiac mortality. Recent publications have shown that template-based methods are more robust than traditional methods for QT interval extraction on a beat-to-beat basis. However, most studies are limited to non-movement ECG recordings, we want to analyze in this study the power of QT interval extraction for mobile non-stationary ECG recordings. The records of 7 test subjects are at least 65 min long and contain about 25 minutes of sport exercise such as running, cycling, sport climbing or acrobatic training. 2DSW was used to extract QT interval and best-fit distance of matched template for signal quality evaluation for each beat. Potential relations between QTV, motion and signal quality are segmentally compared. To determine motion activity we calculated normalized signal magnitude area (SMA). QTV was increased in patients during sport exercise, possibly reflects sympathetic activity in these specific physiological conditions. However, increased QTV could also be caused by low signal quality. |
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610 |
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600 - Technology (Applied sciences) |
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610 - Medicine and health |
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610 |
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610 |
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3610 |
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610 - Medicine and health |
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Online, Free |
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Technik, Medizin |
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medicine |
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eBook |
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Book, E-Book |
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Ebook |
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Book, E-Book |
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Book, E-Book |
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Buch |
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text-online-monograph-independent-conference |
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e-Book |
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Book, E-Book |
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ElectronicBook |
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Book, E-Book |
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Book, E-Book |
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E-Book |
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Konferenzschrift |
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Konferenzschrift |
| geogr_code |
not assigned |
| geogr_code_person |
not assigned |
| id |
22-14-qucosa2-331622 |
| illustrated |
Not Illustrated |
| imprint |
2015 |
| imprint_str_mv |
Online-Ausg.: 2019 |
| institution |
DE-105, DE-Gla1, DE-Brt1, DE-D161, DE-540, DE-Pl11, DE-Rs1, DE-Bn3, DE-Zi4, DE-Zwi2, DE-D117, DE-Mh31, DE-D275, DE-Ch1, DE-15, DE-D13, DE-L242, DE-L229, DE-L328 |
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| language |
English |
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2024-04-26T03:12:05.195Z |
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schmidt2015challengestoqtintervalvariabilityanalysisinmobileapplications |
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2015 |
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2015 |
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marcfinc |
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14-qucosa2-331622 |
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marcfinc |
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Yb 8000 |
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22 |
| spelling |
Schmidt, Martin, Challenges to QT Interval Variability Analysis in Mobile Applications, 2015, txt, nc, Online-Ausg. 2019 Online-Ressource (Text) Technische Universität Dresden, The QT interval in an electrocardiogram (ECG) reflects complex processes affecting the repolarization of ventricular myocardium. Increased QT interval variability (QTV) is thought to be caused by ventricular repolarization lability and has been associated with cardiac mortality. Recent publications have shown that template-based methods are more robust than traditional methods for QT interval extraction on a beat-to-beat basis. However, most studies are limited to non-movement ECG recordings, we want to analyze in this study the power of QT interval extraction for mobile non-stationary ECG recordings. The records of 7 test subjects are at least 65 min long and contain about 25 minutes of sport exercise such as running, cycling, sport climbing or acrobatic training. 2DSW was used to extract QT interval and best-fit distance of matched template for signal quality evaluation for each beat. Potential relations between QTV, motion and signal quality are segmentally compared. To determine motion activity we calculated normalized signal magnitude area (SMA). QTV was increased in patients during sport exercise, possibly reflects sympathetic activity in these specific physiological conditions. However, increased QTV could also be caused by low signal quality., Qt Interval, Ecg, Qtv, 2Dsw, Motion, Konferenzschrift, Kircher, Marco, Noack, Alexander, Malberg, Hagen, Zaunseder, Sebastian, text/html https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-331622 Online-Zugriff |
| spellingShingle |
Schmidt, Martin, Challenges to QT Interval Variability Analysis in Mobile Applications, The QT interval in an electrocardiogram (ECG) reflects complex processes affecting the repolarization of ventricular myocardium. Increased QT interval variability (QTV) is thought to be caused by ventricular repolarization lability and has been associated with cardiac mortality. Recent publications have shown that template-based methods are more robust than traditional methods for QT interval extraction on a beat-to-beat basis. However, most studies are limited to non-movement ECG recordings, we want to analyze in this study the power of QT interval extraction for mobile non-stationary ECG recordings. The records of 7 test subjects are at least 65 min long and contain about 25 minutes of sport exercise such as running, cycling, sport climbing or acrobatic training. 2DSW was used to extract QT interval and best-fit distance of matched template for signal quality evaluation for each beat. Potential relations between QTV, motion and signal quality are segmentally compared. To determine motion activity we calculated normalized signal magnitude area (SMA). QTV was increased in patients during sport exercise, possibly reflects sympathetic activity in these specific physiological conditions. However, increased QTV could also be caused by low signal quality., Qt Interval, Ecg, Qtv, 2Dsw, Motion, Konferenzschrift |
| title |
Challenges to QT Interval Variability Analysis in Mobile Applications |
| title_auth |
Challenges to QT Interval Variability Analysis in Mobile Applications |
| title_full |
Challenges to QT Interval Variability Analysis in Mobile Applications |
| title_fullStr |
Challenges to QT Interval Variability Analysis in Mobile Applications |
| title_full_unstemmed |
Challenges to QT Interval Variability Analysis in Mobile Applications |
| title_short |
Challenges to QT Interval Variability Analysis in Mobile Applications |
| title_sort |
challenges to qt interval variability analysis in mobile applications |
| title_unstemmed |
Challenges to QT Interval Variability Analysis in Mobile Applications |
| topic |
Qt Interval, Ecg, Qtv, 2Dsw, Motion, Konferenzschrift |
| topic_facet |
Qt Interval, Ecg, Qtv, 2Dsw, Motion, Konferenzschrift |
| url |
https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-331622 |
| urn |
urn:nbn:de:bsz:14-qucosa2-331622 |
| work_keys_str_mv |
AT schmidtmartin challengestoqtintervalvariabilityanalysisinmobileapplications, AT kirchermarco challengestoqtintervalvariabilityanalysisinmobileapplications, AT noackalexander challengestoqtintervalvariabilityanalysisinmobileapplications, AT malberghagen challengestoqtintervalvariabilityanalysisinmobileapplications, AT zaunsedersebastian challengestoqtintervalvariabilityanalysisinmobileapplications |
