Blood Pressure Measurement Device Accuracy Evaluation: Statistical Considerations with an Implementation in R
| aut.relation.endpage | 44 | |
| aut.relation.issue | 4 | |
| aut.relation.journal | Technologies | |
| aut.relation.startpage | 44 | |
| aut.relation.volume | 12 | |
| dc.contributor.author | Chandel, Tanvi | |
| dc.contributor.author | Miranda, Victor | |
| dc.contributor.author | Lowe, Andrew | |
| dc.contributor.author | Lee, Tet Chuan | |
| dc.date.accessioned | 2024-06-04T23:12:20Z | |
| dc.date.available | 2024-06-04T23:12:20Z | |
| dc.date.issued | 2024-03-25 | |
| dc.description.abstract | Inaccuracies from devices for non-invasive blood pressure measurements have been well reported with clinical consequences. International standards, such as ISO 81060-2 and the seminal AAMI/ANSI SP10, define protocols and acceptance criteria for these devices. Prior to applying these standards, a sample size of N >= 85 is mandatory, that is, the number of distinct subcjects used to calculate device inaccuracies. Often, it is not possible to gather such a large sample. Many studies apply these standards with a smaller sample. The objective of the paper is to introduce a methodology that broadens the method first developed by the AAMI Sphygmomanometer Committee for accepting a blood pressure measurement device. We study changes in the acceptance region for various sample sizes using the sampling distribution for proportions and introduce a methodology for estimating the exact probability of the acceptance of a device. This enables the comparison of the accuracies of existing device development techniques even if they were studied with a smaller sample size. The study is useful in assisting BP measurement device manufacturers. To assist clinicians, we present a newly developed “bpAcc” package in R to evaluate acceptance statistics for various sample sizes. | |
| dc.identifier.citation | Technologies, ISSN: 2227-7080 (Print); 2227-7080 (Online), MDPI AG, 12(4), 44-44. doi: 10.3390/technologies12040044 | |
| dc.identifier.doi | 10.3390/technologies12040044 | |
| dc.identifier.issn | 2227-7080 | |
| dc.identifier.issn | 2227-7080 | |
| dc.identifier.uri | http://hdl.handle.net/10292/17617 | |
| dc.language | en | |
| dc.publisher | MDPI AG | |
| dc.relation.uri | https://www.mdpi.com/2227-7080/12/4/44 | |
| dc.rights | © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | |
| dc.rights.accessrights | OpenAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | 40 Engineering | |
| dc.subject | 4008 Electrical Engineering | |
| dc.subject | Bioengineering | |
| dc.subject | 4 Detection, screening and diagnosis | |
| dc.subject | 4.2 Evaluation of markers and technologies | |
| dc.subject | 4008 Electrical engineering | |
| dc.title | Blood Pressure Measurement Device Accuracy Evaluation: Statistical Considerations with an Implementation in R | |
| dc.type | Journal Article | |
| pubs.elements-id | 546501 |
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