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

Abstract

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.

Journal of clinical monitoring and computing 2016 end of year summary: monitoring cerebral oxygenation and autoregulation

“…Obviously, the low and high frequency components of both the PPG and NIRS waveforms contain contributions from both arterial and venous blood, the relative amounts of which are not known. Of note, since the NIRS waveforms show the same respiratory variations as the arterial pressure [5] or PPG waveforms [6, 7], they might be used to non-invasively determine fluid responsiveness as well, particularly when peripheral perfusion is compromised.…”

Pulse Oximetry: Beyond SpO2

“…With vasodilatation, the plethysmogram amplitude is increased. 39 Addison 40 wrote a critical assessment of the use of the pulse oximetry plethysmogram waveform to assess fluid responsiveness. He provides a detailed overview of the signal processing methods used in individual studies, such as the details of exclusion criteria, manual filtering and preprocessing, gain change issues, acquisition details, selection of registration periods, averaging methods, and physiological influences on the plethysmogram.…”

“…39 Without the option to turn off this automatic resizing function, it is impossible to analyze the amplitude changes of the plethysmogram. Addison 40 suggests that more rigorous signal processing is required for a robust, fully automated ⌬POP algorithm for use in the clinical environment.…”

On Better Estimating and Normalizing the Relationship between Clinical Parameters: Comparing Respiratory Modulations in the Photoplethysmogram and Blood Pressure Signal (DPOP versus PPV)

“…Through sophisticated signal processing it has been shown that these perturbations may be used to determine frequency of respiration (respiratory rate) using commercially available hardware [ 1 ]. DPOP (ΔPOP or Delta-POP) is a noninvasive parameter which measures the strength of respiratory modulations present in the pleth waveform [ 2 ]. It is defined as [ 3 ] where AMP max⁡ and AMP min⁡ are the maximum and minimum amplitudes of the cardiac pulse waveform in the pleth during a respiratory cycle.…”

“…As such it represents a noninvasive alternative for pulse pressure variation [ 4 ], a parameter derived from a blood pressure signal and widely used in practice for the prediction of the response to volume expansion in hypovolemic patients. PPV has the same mathematical formulation as DPOP [ 5 ] and many studies have shown favourable correlation between the two parameters [ 2 , 6 – 12 ]. The role of PPV as a surrogate parameter for stroke volume variation (SVV) and its use in determining where on the Frank-Starling curve the patient is operating is not described here; rather the reader is referred to [ 2 ] by the author which contains an in-depth treatment of the subject.…”