Automatic computerized analysis of heart rate variability with digital filtering of ectopic beats

Abstract

Analysis of heart rate variability (HRV) has been used in studies of autonomic function and risk assessment in different patient groups such as in patients with diabetes mellitus, after myocardial infarction (MI) and other cardiovascular disease. Ectopic beats can, however, interfere with HRV analysis and give erroneous results. We have therefore studied the impact of ectopic beats on HRV analysis and the ability of a filter algorithm to correct this. Power spectral analysis of synthetic data with an increasing proportion of ectopic beats and 24-h Holter recordings from 98 healthy subjects and 93 post MI patients was done with and without digital filtering and interpolation of errors in the data stream. The analysis of HRV was seriously hampered by less than 1% of ectopic beats. A filter algorithm based on detection and linear interpolation of ectopic beats and other noise in the data stream corrected effectively for this in the synthetic data employed. In the healthy subjects and the post MI patients, filtering markedly reduced the extra variability related to non-normal beats. The software could automatically analyse over one hundred 24-h files in one batch. HRV analysis should include filtering for ectopic beats even with a small number of such beats. It is possible to make a fast analysis automatically even in huge clinical series, which makes it possible to use the method both clinically and in epidemiological studies.

Decreased heart rate variability in children born with low birth weight

“…For the frequency domain analysis, 5 min epochs of data were analyzed by custom-made software (30). The time series of RR intervals were re-sampled at a frequency of two samples/second (2 Hz).…”

Possibilities and limitations of the polar RS800 in measuring heart rate variability at rest

“…The issue with artifacts remained even if the filter power was adjusted to the highest level. This truly is one of the main drawbacks with the PPT 5 system, since individuals with a high proportion of artifacts will receive highly overestimated HRV values (Storck et al 2001). The disadvantage of HRMs to only provide QRS complexes for the detection of abnormal heart beats has been previously described by Boudet and Chamoux (Boudet and Chamoux 2000).…”

“…Since HRMs only register the QRS complexes of cardiac cycles, the possibilities of identifying non-sinoidal beats are limited. A consequence of inferior error correction is that the results of the subsequent HRV analyses will be detrimentally inflated (Storck et al 2001).…”

Stress reactions to cognitively demanding tasks and open-plan office noise

“…Analysis was performed on the same segments as described above. Since non-normal beats may signiWcantly aVect spectral analysis of the RR-period variability (Storck et al 2001;CliVord 2006), the portions of ECG of interest was carefully checked manually for ectopic beats, pauses, and electric noise not detected automatically by the software. Only one undetected non-normal beat was found.…”