Literature DB >> 7334880

Pulse arrival time as a method of obtaining systolic and diastolic blood pressure indirectly.

L A Geddes, M Voelz, S James, D Reiner.   

Abstract

Mesh：

Year:  1981        PMID： 7334880     DOI： 10.1007/bf02442787

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN： 0140-0118            Impact factor:   2.602


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  8 in total

1.  Dual-channel photoplethysmography to monitor local changes in vascular stiffness.

Authors:  Jong Yong Abdiel Foo; Chu Sing Lim
Journal:  J Clin Monit Comput       Date:  2006-06-15       Impact factor: 2.502

2.  Pulse transit time as a tool to characterize obstructive and central apneas in children.

Authors:  Lucie Griffon; Alessandro Amaddeo; Jorge Olmo Arroyo; Rossana Tenconi; Serena Caggiano; Sonia Khirani; Brigitte Fauroux
Journal:  Sleep Breath       Date:  2017-03-09       Impact factor: 2.816

3.  Continuous blood pressure measurement by using the pulse transit time: comparison to a cuff-based method.

Authors:  Heiko Gesche; Detlef Grosskurth; Gert Küchler; Andreas Patzak
Journal:  Eur J Appl Physiol       Date:  2011-05-10       Impact factor: 3.078

4.  Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Theory and Practice.

Authors:  Ramakrishna Mukkamala; Jin-Oh Hahn; Omer T Inan; Lalit K Mestha; Chang-Sei Kim; Hakan Töreyin; Survi Kyal
Journal:  IEEE Trans Biomed Eng       Date:  2015-06-05       Impact factor: 4.538

5.  Theory and developments in an unobtrusive cardiovascular system representation: ballistocardiography.

Authors:  Eduardo Pinheiro; Octavian Postolache; Pedro Girão
Journal:  Open Biomed Eng J       Date:  2010-10-10

6.  Comparison of noninvasive pulse transit time estimates as markers of blood pressure using invasive pulse transit time measurements as a reference.

Authors:  Mingwu Gao; N Bari Olivier; Ramakrishna Mukkamala
Journal:  Physiol Rep       Date:  2016-05

7.  Feasibility study for the non-invasive blood pressure estimation based on ppg morphology: normotensive subject study.

Authors:  Hangsik Shin; Se Dong Min
Journal:  Biomed Eng Online       Date:  2017-01-10       Impact factor: 2.819

8.  Combined deep CNN-LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features.

Authors:  Da Un Jeong; Ki Moo Lim
Journal:  Sci Rep       Date:  2021-06-29       Impact factor: 4.379
  8 in total

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