Department of Radiation Sciences, Biomedical Engineering, and Centre of Biomedical Engineering and Physics, Umeå University, Umeå, Sweden.
Biomed Eng Online. 2012 Jan 11;11:2. doi: 10.1186/1475-925X-11-2.
Undetected arrhythmic beats seriously affect the power spectrum of the heart rate variability (HRV). Therefore, the series of RR intervals are normally carefully edited before HRV is analysed, but this is a time consuming procedure when 24-hours recordings are analysed. Alternatively, different methods can be used for automatic removal of arrhythmic beats and artefacts. This study compared common frequency domain indices of HRV when determined from manually edited and automatically filtered RR intervals.
Twenty-four hours Holter recordings were available from 140 healthy subjects of age 1-75 years. An experienced technician carefully edited all recordings. Automatic filtering was performed using a recursive procedure where RR intervals were removed if they differed from the mean of the surrounding RR intervals with more than a predetermined limit (ranging from 10% to 50%). The filtering algorithm was evaluated by replacing 1% of the beats with synthesised ectopic beats. Power spectral analysis was performed before and after filtering of both the original edited data and the noisy data set. The results from the analysis using the noisy data were used to define an age-based filtering threshold. The age-based filtration was evaluated with completely unedited data, generated by removing all annotations from the series of RR intervals, and then comparing the resulting HRV indices with those obtained using edited data. The results showed equivalent results after age-based filtration of both the edited and unedited data sets, where the differences in HRV indices obtained by different preprocessing methods were small compared to the mean values within each age group.
The study showed that it might not be necessary to perform the time-consuming careful editing of all detected heartbeats before HRV is analysed in Holter recordings.In most subjects, it is sufficient to perform the regular editing needed for valid arrhythmia analyses, and then remove undetected ectopic beats and artefacts by age-based filtration of the series of RR intervals, particularly in subjects older than 30 years.
未检测到的心律失常会严重影响心率变异性（HRV）的功率谱。因此，在分析 HRV 之前，通常需要仔细编辑 RR 间期序列，但在分析 24 小时记录时，这是一个耗时的过程。或者，可以使用不同的方法自动去除心律失常和伪迹。本研究比较了手动编辑和自动滤波 RR 间期确定时 HRV 的常见频域指标。
从 140 名年龄在 1-75 岁的健康受试者中获得 24 小时动态心电图记录。一名经验丰富的技术人员仔细编辑了所有记录。使用递归程序自动滤波，如果 RR 间期与周围 RR 间期的平均值相差超过预定限值（范围为 10%至 50%），则会删除 RR 间期。通过用合成的异位搏动替换 1%的搏动来评估滤波算法。在滤波前后，对原始编辑数据和噪声数据集都进行了功率谱分析。使用分析噪声数据的结果来定义基于年龄的滤波阈值。通过从 RR 间期序列中删除所有注释来生成完全未编辑的数据，然后使用未编辑数据评估基于年龄的过滤，最后将得到的 HRV 指数与使用编辑数据获得的指数进行比较。结果表明，在动态心电图记录中分析 HRV 之前，不必对所有检测到的心跳进行耗时的仔细编辑。在大多数受试者中，仅需进行心律失常分析所需的常规编辑，然后通过基于年龄的 RR 间期序列滤波去除未检测到的异位搏动和伪迹，特别是在年龄大于 30 岁的受试者中。
该研究表明，在分析动态心电图记录中的 HRV 之前，可能不需要对所有检测到的心跳进行耗时的仔细编辑。在大多数受试者中，仅需进行心律失常分析所需的常规编辑，然后通过基于年龄的 RR 间期序列滤波去除未检测到的异位搏动和伪迹，特别是在年龄大于 30 岁的受试者中。
