Corrigendum to “Arterial blood pressure feature estimation using photoplethysmography” [Comput. Biol. Med. 102 (2018) 104–111](S0010482518302750)(10.1016/j.compbiomed.2018.09.013)

Armin Soltan Zadi, Raichel Alex, Rong Zhang, Donald E. Watenpaugh, Khosrow Behbehani

Research output: Contribution to journalComment/debate

Abstract

The authors regret, after the publication of the above-referenced paper, an inadvertent error in the computation of the initial conditions that were used with Equation (2) of the paper was discovered. The changes resulting from correcting the initial conditions are described below. 1) In the Abstract on page 104 the following sentence: The level of error in the estimates, as measured by the root mean square of the model residuals, was less than 5 mmHg during normal breathing and less than 8 mmHg during the breath-hold maneuver. is corrected as: The level of error in the modeling and prediction estimates during normal breathing and breath-hold maneuvers, as measured by the root mean square of the residuals, were less than 5 mmHg and 11 mm Hg, respectively. 2) The entries for Tables 3 and 4 on page 108 are corrected as follows.[Table presented] 3) Fig. 4 on page 108 is corrected as follows: [Figure presented] Fig. 4- Mean of errors for DBP, SBP, and MAP in both NB and BH interval. Each model is evaluated by all other congruent models. 4) Fig. 5 on page 109 is corrected as: [Figure presented] Fig. 5- Standard deviation of errors for DBP, SBP and MAP in both NB and BH intervals. Each model is evaluated by all other congruent models. 5) On page 109 in the last paragraph of the left column, the second and third sentences in the paragraph: Indeed, comparing the rMSE values in Tables 1 and 2 with those in Tables 3 and 4 shows that rMSE values have a max mean of approximately 8 mmHg. Therefore, if rMSE is used to gauge the level of the error, for both model errors and prediction errors, an overall error of less than 8 mmHg can be expected. are modifies as: Indeed, comparing the rMSE values in Tables 1 and 2 with those in Tables 3 and 4 shows that rMSE values have a max mean of approximately 11 mmHg. Therefore, if rMSE is used to gauge the level of the error, for both model errors and prediction errors, an overall error of less than 11 mmHg can be expected. The authors would like to apologise for any inconvenience caused.

Original languageEnglish (US)
Pages (from-to)196-199
Number of pages4
JournalComputers in Biology and Medicine
Volume108
DOIs
StatePublished - May 1 2019

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ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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