A Statistically Based Acute Ischemia Detection Algorithm Suitable for an Implantable Device.
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| Title: | A Statistically Based Acute Ischemia Detection Algorithm Suitable for an Implantable Device. |
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| Authors: | Hopenfeld, Bruce1 brhopenfeld@yahoo.com, John, M., Fischell, Tim, Johnson, Steven1 |
| Source: | Annals of Biomedical Engineering. Dec2012, Vol. 40 Issue 12, p2627-2638. 12p. |
| Subjects: | Ischemia diagnosis, Medical statistics, Algorithms, Artificial implants, Electrocardiography, Heart beat, Arterial occlusions, Transluminal angioplasty |
| Abstract: | This study investigates the performance of a new statistically driven acute ischemia detection algorithm that can process data from two bipolar cutaneous or subcutaneous leads. During a start-up phase, the algorithm processes electrocardiogram signals to determine a normal range of ST-segment deviation as a function of heart rate. The algorithm then generates upper and lower ST-deviation thresholds based on the dispersion of the baseline ST-deviation data. After the start-up phase, persistent ST-deviation that is beyond either the upper or lower thresholds results in detection of acute ischemia. To test the algorithm, we performed long-term (10 day) Holter monitoring in a control group of 14 subjects. We also performed Holter monitoring during balloon angioplasty, and for 2 days after surgery, in 30 subjects who underwent elective percutaneous coronary interventions ('PCI'). We determined the percentage of balloon inflations the algorithm detected without producing false positive detections within the control group 10-day daily life data. The algorithm detected 17/17 LAD occlusions, 7/8 LCX occlusions, and 8/9 RCA occlusions. Our results suggest that automatically generated, subject-specific, heart-rate dependent ST-deviation thresholds can detect PCI induced myocardial ischemia without resulting in false positive detections in a small control group. [ABSTRACT FROM AUTHOR] |
| Copyright of Annals of Biomedical Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 83635420 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Statistically Based Acute Ischemia Detection Algorithm Suitable for an Implantable Device. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hopenfeld%2C+Bruce%22">Hopenfeld, Bruce</searchLink><relatesTo>1</relatesTo><i> brhopenfeld@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22John%2C+M%2E%22">John, M.</searchLink><br /><searchLink fieldCode="AR" term="%22Fischell%2C+Tim%22">Fischell, Tim</searchLink><br /><searchLink fieldCode="AR" term="%22Johnson%2C+Steven%22">Johnson, Steven</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Annals+of+Biomedical+Engineering%22">Annals of Biomedical Engineering</searchLink>. Dec2012, Vol. 40 Issue 12, p2627-2638. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Ischemia+diagnosis%22">Ischemia diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+statistics%22">Medical statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+implants%22">Artificial implants</searchLink><br /><searchLink fieldCode="DE" term="%22Electrocardiography%22">Electrocardiography</searchLink><br /><searchLink fieldCode="DE" term="%22Heart+beat%22">Heart beat</searchLink><br /><searchLink fieldCode="DE" term="%22Arterial+occlusions%22">Arterial occlusions</searchLink><br /><searchLink fieldCode="DE" term="%22Transluminal+angioplasty%22">Transluminal angioplasty</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study investigates the performance of a new statistically driven acute ischemia detection algorithm that can process data from two bipolar cutaneous or subcutaneous leads. During a start-up phase, the algorithm processes electrocardiogram signals to determine a normal range of ST-segment deviation as a function of heart rate. The algorithm then generates upper and lower ST-deviation thresholds based on the dispersion of the baseline ST-deviation data. After the start-up phase, persistent ST-deviation that is beyond either the upper or lower thresholds results in detection of acute ischemia. To test the algorithm, we performed long-term (10 day) Holter monitoring in a control group of 14 subjects. We also performed Holter monitoring during balloon angioplasty, and for 2 days after surgery, in 30 subjects who underwent elective percutaneous coronary interventions ('PCI'). We determined the percentage of balloon inflations the algorithm detected without producing false positive detections within the control group 10-day daily life data. The algorithm detected 17/17 LAD occlusions, 7/8 LCX occlusions, and 8/9 RCA occlusions. Our results suggest that automatically generated, subject-specific, heart-rate dependent ST-deviation thresholds can detect PCI induced myocardial ischemia without resulting in false positive detections in a small control group. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Annals of Biomedical Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10439-012-0612-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 2627 Subjects: – SubjectFull: Ischemia diagnosis Type: general – SubjectFull: Medical statistics Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Artificial implants Type: general – SubjectFull: Electrocardiography Type: general – SubjectFull: Heart beat Type: general – SubjectFull: Arterial occlusions Type: general – SubjectFull: Transluminal angioplasty Type: general Titles: – TitleFull: A Statistically Based Acute Ischemia Detection Algorithm Suitable for an Implantable Device. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hopenfeld, Bruce – PersonEntity: Name: NameFull: John, M. – PersonEntity: Name: NameFull: Fischell, Tim – PersonEntity: Name: NameFull: Johnson, Steven IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2012 Type: published Y: 2012 Identifiers: – Type: issn-print Value: 00906964 Numbering: – Type: volume Value: 40 – Type: issue Value: 12 Titles: – TitleFull: Annals of Biomedical Engineering Type: main |
| ResultId | 1 |
