Abstract:
Objective: We investigate the effect of selective single parameter personalization on the performance of multi-parameter models for pulse arrival time (PAT) based blood p...Show MoreMetadata
Abstract:
Objective: We investigate the effect of selective single parameter personalization on the performance of multi-parameter models for pulse arrival time (PAT) based blood pressure (BP) surrogates. Methods: Our data set stems from 15 surgery patients, and we selected from each patient 5 segments of 30 min length each. We evaluate the root mean squared BP tracking error of the two models with and without single parameter personalization. We further compare the BP tracking performance to a surrogate-free sample-and-hold approach, e.g., as afforded by conventional non-invasive blood pressure (NIBP) oscillometry. Results: Parameter personalization is key to realizing a tracking performance benefit of PAT-based BP surrogates. The highest tracking error reduction of about 3.7 mmHg with respect to a sample-and-hold approach was reached with a personalized model which is linear in the pulse wave velocity domain. It achieves an estimation error of 7.8 mmHg with respect to a continuously measured invasive reference.Clinical Relevance—We give a performance analysis of PAT-based BP surrogates which are personalized to a patient with a single NIBP spot measurement. We show for surgery patients that patient-specific personalization enables continuous beat-to-beat BP monitoring over 30 min intervals with a average root mean squared error of less than 8 mmHg
Published in: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Date of Conference: 01-05 November 2021
Date Added to IEEE Xplore: 09 December 2021
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PubMed ID: 34892356