A Linear Transformation Approach for Estimating Pulse Arrival Time
We propose a new mathematical framework for estimating pulse arrival time (PAT). Existing methods of estimating PAT rely on local characteristic points or global parametric models: local characteristic point methods detect points such as foot points, max points, or max slope points, while global par...
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doaj-b4329e5981664c4abf27370ad25004fc2020-11-24T22:11:51ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/643653643653A Linear Transformation Approach for Estimating Pulse Arrival TimeDohyun Kim0Jong-Hoon Ahn1Jongshill Lee2Hoon Ki Park3In Young Kim4Department of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro Seongdong-gu, Seoul 133-791, Republic of KoreaDepartment of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro Seongdong-gu, Seoul 133-791, Republic of KoreaDepartment of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro Seongdong-gu, Seoul 133-791, Republic of KoreaFamily Medicine, College of Medicine, Hanyang University, 222 Wangsimni-ro Seongdong-gu, Seoul 133-791, Republic of KoreaDepartment of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro Seongdong-gu, Seoul 133-791, Republic of KoreaWe propose a new mathematical framework for estimating pulse arrival time (PAT). Existing methods of estimating PAT rely on local characteristic points or global parametric models: local characteristic point methods detect points such as foot points, max points, or max slope points, while global parametric methods fit a parametric form to the anacrotic phase of pulse signals. Each approach has its strengths and weaknesses; we take advantage of the favorable properties of both approaches in our method. To be more precise, we transform continuous pulse signals into scalar timing codes through three consecutive transformations, the last of which is a linear transformation. By training the linear transformation method on a subset of data, the proposed method yields results that are robust to noise. We apply this method to real photoplethysmography (PPG) signals and analyze the agreement between our results and those obtained using a conventional approach.http://dx.doi.org/10.1155/2012/643653 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dohyun Kim Jong-Hoon Ahn Jongshill Lee Hoon Ki Park In Young Kim |
spellingShingle |
Dohyun Kim Jong-Hoon Ahn Jongshill Lee Hoon Ki Park In Young Kim A Linear Transformation Approach for Estimating Pulse Arrival Time Journal of Applied Mathematics |
author_facet |
Dohyun Kim Jong-Hoon Ahn Jongshill Lee Hoon Ki Park In Young Kim |
author_sort |
Dohyun Kim |
title |
A Linear Transformation Approach for Estimating Pulse Arrival Time |
title_short |
A Linear Transformation Approach for Estimating Pulse Arrival Time |
title_full |
A Linear Transformation Approach for Estimating Pulse Arrival Time |
title_fullStr |
A Linear Transformation Approach for Estimating Pulse Arrival Time |
title_full_unstemmed |
A Linear Transformation Approach for Estimating Pulse Arrival Time |
title_sort |
linear transformation approach for estimating pulse arrival time |
publisher |
Hindawi Limited |
series |
Journal of Applied Mathematics |
issn |
1110-757X 1687-0042 |
publishDate |
2012-01-01 |
description |
We propose a new mathematical framework for estimating pulse arrival time (PAT). Existing methods of estimating PAT rely on local characteristic points or global parametric models: local characteristic point methods detect points such as foot points, max points, or max slope points, while global parametric methods fit a parametric form to the anacrotic phase of pulse signals. Each approach has its strengths and weaknesses; we take advantage of the favorable properties of both approaches in our method. To be more precise, we transform continuous pulse signals into scalar timing codes through three consecutive transformations, the last of which is a linear transformation. By training the linear transformation method on a subset of data, the proposed method yields results that are robust to noise. We apply this method to real photoplethysmography (PPG) signals and analyze the agreement between our results and those obtained using a conventional approach. |
url |
http://dx.doi.org/10.1155/2012/643653 |
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