Influence of respiratory rate on the variability of blood volume pulse characteristics

Selvaraj, Nandakumar; Jaryal, Ashok Kumar; Santhosh, Jayasree; Deepak, K K; Anand, Sneh

doi:10.1080/03091900802454483

Cited by 7 publications

(1 citation statement)

References 19 publications

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“…27,[35][36][37][38][39][40][41][42][43][44][45] Probe position is also an important factor in acquiring good data. These are well documented more fully in the work of others.…”

Section: Reported Physiological Influences On the Pleth And Probe Posmentioning

confidence: 99%

A Review of Signal Processing Used in the Implementation of the Pulse Oximetry Photoplethysmographic Fluid Responsiveness Parameter

Addison

2014

Anesthesia &Amp; Analgesia

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ΔPOP is a physiological parameter derived from the respiration-induced change in the pulse oximetry plethysmographic (POP) waveform or "pleth." It has been proposed as a proxy for pulse pressure variation used in the determination of the response to intravascular volume expansion in hypovolemic patients. Many studies have now reported on the parameter, and many research groups have constructed algorithms for its computation from the first principles where the implementation details have been described. This review focuses on the signal processing aspects of ΔPOP, as reported in the literature, and aims to provide a comprehensive summary of the wide-ranging algorithmic strategies that have been attempted in its computation. A search was conducted for articles concerning the use of ΔPOP as a fluid responsiveness parameter. In particular, articles concerning the correlation between ΔPOP and pulse pressure variation were targeted. Comments and replies to comments by the authors in which signal processing aspects were discussed were also included in the review. The parameter is first defined, and a history of the early work surrounding pleth-based fluid responsiveness parameters is presented. This is followed by an overview of the signal processing methods used in the reported studies, including details of exclusion criteria, manual filtering (preprocessing), gain change issues, acquisition details, selection of registration periods, averaging methods, physiological influences on the pleth, and comments by the investigators themselves. It is concluded that to develop a robust, fully automated ΔPOP algorithm for use in the clinical environment, more rigorous signal processing is required. Specifically, signals should be evaluated over significant periods of time, with emphasis on the quality and temporal relevance of the information.

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“…27,[35][36][37][38][39][40][41][42][43][44][45] Probe position is also an important factor in acquiring good data. These are well documented more fully in the work of others.…”

Section: Reported Physiological Influences On the Pleth And Probe Posmentioning

confidence: 99%

A Review of Signal Processing Used in the Implementation of the Pulse Oximetry Photoplethysmographic Fluid Responsiveness Parameter

Addison

2014

Anesthesia &Amp; Analgesia

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Physiology of Cardiovascular System

Jaryal

Singh

Deepak

2020

Brain and Heart Crosstalk

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Pulse oximetry-derived respiratory rate in general care floor patients

Addison

Watson

Mestek³

et al. 2014

J Clin Monit Comput

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Respiratory rate is recognized as a clinically important parameter for monitoring respiratory status on the general care floor (GCF). Currently, intermittent manual assessment of respiratory rate is the standard of care on the GCF. This technique has several clinically-relevant shortcomings, including the following: (1) it is not a continuous measurement, (2) it is prone to observer error, and (3) it is inefficient for the clinical staff. We report here on an algorithm designed to meet clinical needs by providing respiratory rate through a standard pulse oximeter. Finger photoplethysmograms were collected from a cohort of 63 GCF patients monitored during free breathing over a 25-min period. These were processed using a novel in-house algorithm based on continuous wavelet-transform technology within an infrastructure incorporating confidence-based averaging and logical decision-making processes. The computed oximeter respiratory rates (RRoxi) were compared to an end-tidal CO2 reference rate (RRETCO2). RRETCO2 ranged from a lowest recorded value of 4.7 breaths per minute (brpm) to a highest value of 32.0 brpm. The mean respiratory rate was 16.3 brpm with standard deviation of 4.7 brpm. Excellent agreement was found between RRoxi and RRETCO2, with a mean difference of −0.48 brpm and standard deviation of 1.77 brpm. These data demonstrate that our novel respiratory rate algorithm is a potentially viable method of monitoring respiratory rate in GCF patients. This technology provides the means to facilitate continuous monitoring of respiratory rate, coupled with arterial oxygen saturation and pulse rate, using a single non-invasive sensor in low acuity settings.

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Influence of respiratory rate on the variability of blood volume pulse characteristics

Cited by 7 publications

References 19 publications

A Review of Signal Processing Used in the Implementation of the Pulse Oximetry Photoplethysmographic Fluid Responsiveness Parameter

A Review of Signal Processing Used in the Implementation of the Pulse Oximetry Photoplethysmographic Fluid Responsiveness Parameter

Physiology of Cardiovascular System

Pulse oximetry-derived respiratory rate in general care floor patients

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