心跳间期的实时校正

Real-time correction of heart interbeat intervals.

作者信息

Rand Jeromie, Hoover Adam, Fishel Stephanie, Moss Jason, Pappas Jennifer, Muth Eric

机构信息

Electrical and Computer Engineering Department, Clemson University, Clemson, SC 29634-0915, USA.

出版信息

IEEE Trans Biomed Eng. 2007 May;54(5):946-50. doi: 10.1109/TBME.2007.893491.

DOI:10.1109/TBME.2007.893491

PMID:17518294

Abstract

Heart rate variability (HRV) is traditionally analyzed while a subject is in a controlled environment, such as at rest in a clinic, where it can be used as a medical indicator. This paper concerns analyzing HRV outside of controlled environments, such as on an actively moving person. We describe automated methods for inter-heartbeat interval (IBI) error detection and correction. We collected 124,998 IBIs from 18 subjects, undergoing a variety of active motions, for use in evaluating our methods. Two human graders manually labeled each IBI, evaluating 10% of the IBIs as having an error, which is a far greater error percentage than has been examined in any previous study. Our automated method had a 96% agreement rate with the two human graders when they themselves agreed, with a 49% rate of matching specific error corrections and a 0.01% false alarm rate.

摘要

传统上，心率变异性（HRV）是在受控环境下对受试者进行分析的，比如在诊所静息状态时，此时它可用作一项医学指标。本文关注的是在受控环境之外分析HRV，比如在一个处于主动运动状态的人身上进行分析。我们描述了用于心跳间期（IBI）错误检测和校正的自动化方法。我们从18名受试者身上收集了124,998个IBI，这些受试者正在进行各种主动运动，以用于评估我们的方法。两名人工评分员对每个IBI进行手动标注，评估出10%的IBI存在错误，这一错误百分比远远高于以往任何研究中所考察的比例。当两名人工评分员意见一致时，我们的自动化方法与他们的意见一致率为96%，在匹配特定错误校正方面的准确率为49%，误报率为0.01%。