On better estimating and normalizing the relationship between clinical parameters: comparing respiratory modulations in the photoplethysmogram and blood pressure signal (DPOP versus PPV).

Publisher: Hindawi Country of Publication: United States NLM ID: 101277751 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1748-6718 (Electronic) Linking ISSN: 1748670X NLM ISO Abbreviation: Comput Math Methods Med Subsets: MEDLINE

Publication: 2011- : New York : Hindawi
Original Publication: London : Taylor & Francis, c2006-

Respiration* ; Signal Processing, Computer-Assisted*; Blood Pressure Determination/*methods ; Photoplethysmography/*methods; Algorithms ; Blood Pressure ; Humans ; Hypovolemia/diagnosis ; Least-Squares Analysis ; Linear Models ; Oximetry/methods ; Regression Analysis ; Reproducibility of Results ; Respiratory Rate

DPOP (ΔPOP or Delta-POP) is a noninvasive parameter which measures the strength of respiratory modulations present in the pulse oximeter waveform. It has been proposed as a noninvasive alternative to pulse pressure variation (PPV) used in the prediction of the response to volume expansion in hypovolemic patients. We considered a number of simple techniques for better determining the underlying relationship between the two parameters. It was shown numerically that baseline-induced signal errors were asymmetric in nature, which corresponded to observation, and we proposed a method which combines a least-median-of-squares estimator with the requirement that the relationship passes through the origin (the LMSO method). We further developed a method of normalization of the parameters through rescaling DPOP using the inverse gradient of the linear fitted relationship. We propose that this normalization method (LMSO-N) is applicable to the matching of a wide range of clinical parameters. It is also generally applicable to the self-normalizing of parameters whose behaviour may change slightly due to algorithmic improvements.

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Date Created: 20150219 Date Completed: 20151027 Latest Revision: 20181113

20221213

PMC4322304

10.1155/2015/576340

25691912