Background: Hemodynamic optimization of cardiac resynchronization therapy (CRT) can be achieved reproducibly and--with bulky, nonimplantable equipment--noninvasively. We explored whether a simple photoplethysmogram signal might be used instead.
Method: Twenty patients (age 65 ± 12) with CRT underwent automatic atrioventricular (AV) delay optimization, using a multiple-transitions protocol, at two atrially paced heart rates: just above sinus rate ("slow ApVp," 77 ± 11 beats per minute [bpm]) and 100 bpm ("fast ApVp"). We then retested to assess short-term reproducibility.
Results: All 80 optimizations identified an optimum (correctly oriented parabola). At 100 bpm, the simple photoplethysmogram had wider scatter between repeat optimizations than did Finometer: standard deviation of difference (SDD) 22 ms versus 14 ms, respectively, P = 0.028. The simple photoplethysmogram improved in reproducibility when slope (instead of peak) of its signal was used for optimization, becoming as reproducible as Finometer (SDD 14 ms vs 14 ms, P = 0.50). At slow heart rate, reproducibility of simple photoplethysmogram-based optimization worsened from 14 to 22 ms (P = 0.028), and Finometer-based optimization from 14 to 26 ms (P = 0.005). Increasing the number of replicates averaged improved reproducibility. For example, SDD of simple photoplethysmogram optimization (using peak) fell from 62 ms with two replicates to 22 ms with eight replicates (P < 0.0001). At 100 bpm, the eight-replicate protocol takes ∼12 minutes.
Conclusions: A 12-minute protocol of simple photoplethysmographic AV optimization can be processed fully automatically. Blinded test-retest reproducibility of the optimum AV is good and improves with more replicates. If benefits to some patients are not to be neutralized by harm to others, endpoint studies should first test check narrowness of "within-patient error bars."
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http://dx.doi.org/10.1111/j.1540-8159.2012.03435.x | DOI Listing |
J Pak Med Assoc
October 2024
Department of Physiology, Mustansiriyah University.
Objective: To determine the correlation between the second derivative of digital pulse wave and the QT variability index.
Methods: The cross-sectional study was conducted from October 2021 to May 2022 at the Department of Physiology, College of Medicine, University of Mustansiriyah, Baghdad, Iraq, and comprised healthy women. Samples were raised by simple random technique.
Adv Exp Med Biol
October 2024
Division of Biomedical Engineering, School of Engineering, University of Glasgow, Glasgow, UK.
Oximetry is used to quantify the presence of oxygen in soft tissues. It can be expressed as, for example, tissue oxygen saturation (StO), arterial oxygen saturation (SaO) and pulsatile oxygen saturation (SpO), among others. Non-invasive medical devices are used to estimate (SaO).
View Article and Find Full Text PDFComput Methods Programs Biomed
August 2024
School of Mechanical and Aerospace Engineering, Nanyang Technological University (NTU), Singapore. Electronic address:
Background & Objectives: Measurement of blood pressure (BP) in ambulatory patients is crucial for at high-risk cardiovascular patients. A non-obtrusive, non-occluding device that continuously measures BP via photoplethysmography will enable long-term ambulatory assessment of BP. The aim of this study is to validate the metasense 2PPG cuffless wearable design for continuous BP estimation without ECG.
View Article and Find Full Text PDFSensors (Basel)
July 2023
Department of Electrical Engineering, Center for Innovative Research on Aging Society (CIRAS), and Advanced Institute of Manufacturing with High-Tech Innovations (AIM-HI), National Chung Cheng University, Chia-Yi 621, Taiwan.
This paper presents an RGB-NIR (Near Infrared) dual-modality technique to analyze the remote photoplethysmogram (rPPG) signal and hence estimate the heart rate (in beats per minute), from a facial image sequence. Our main innovative contribution is the introduction of several denoising techniques such as Modified Amplitude Selective Filtering (MASF), Wavelet Decomposition (WD), and Robust Principal Component Analysis (RPCA), which take advantage of RGB and NIR band characteristics to uncover the rPPG signals effectively through this Independent Component Analysis (ICA)-based algorithm. Two datasets, of which one is the public PURE dataset and the other is the CCUHR dataset built with a popular Intel RealSense D435 RGB-D camera, are adopted in our experiments.
View Article and Find Full Text PDFBioengineering (Basel)
February 2023
Biomedical and Mobile Health Technology Lab, ETH Zurich, 8008 Zurich, Switzerland.
Remote photoplethysmography (rPPG) is a promising contactless technology that uses videos of faces to extract health parameters, such as heart rate. Several methods for transforming red, green, and blue (RGB) video signals into rPPG signals have been introduced in the existing literature. The RGB signals represent variations in the reflected luminance from the skin surface of an individual over a given period of time.
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