Heart rate variability (HRV) measurement is an established technology for t
he assessment of cardiac autonomic status. Recently 24 h HRV has been shown
to correlate with disease severity in heart failure. This potentially make
s continuous 24 h HRV measurement suitable for monitoring of heart-failure
patients. Day-to-day 24 h measurement of HRV is, in principle, feasible whe
n implemented using implanted devices (pacemakers and defibrillators) used
in patients who are predominantly in the sinus rhythm. However, a number of
such devices used in heart-failure patients are single-chamber devices, in
which the distinction between sinus rhythm beats and ectopic beats is prob
lematic. The study investigates whether a reasonably accurate 24 h HRV meas
urement can be achieved by automatic algorithms, suitable for implementatio
n using implanted devices, without the need for identification of ectopic b
eats. A set of 5321 nominal 24 h Holter recordings of cardiac patients are
used. Each of the recordings contains at least one ectopic beat; approximat
ely 30% of the recordings have more than 1% of ectopic beats. Conventional
24 h measures of HRV, that is the SDNN, HRV index, and SDANN indices, are o
btained from each recording after elimination of the ectopic beats and are
approximated by HRV measures computed by the same formulas without exclusio
n of the ectopic beats. The SDANN values are also approximated by the stand
ard deviation of 5 min medians of all RR intervals (SDMRR measure). The err
ors introduced by including the ectopic beats in the HRV computation were e
valuated using the Bland-Altman statistics and by Cohen's kappa statistics
investigating the precision of identifying patients with depressed and pres
erved 24 h HRV. The SDNN measure is very sensitive to the quality of the RR
interval sequence and cannot be reasonably used without the distinction be
tween sinus rhythm and ectopic beats. The HRV index measure is marginally m
ore acceptable when used without ectopic elimination. The SDANN is rather i
nsensitive, and its replacement by SDMRR values leads to relative errors in
the region of 2-5% that are almost independent of the number of ectopic be
ats included. Even in recordings with a substantial proportion of ectopic b
eats, a practically acceptable (kappa > 0.9) identification of depressed an
d preserved SDANN values is possible without ectopic elimination. Thus, con
tinuous monitoring of 24 h HRV is technically feasible within implanted dev
ices, provided the SDANN measure is monitored and either computed from the
sequence of all RR intervals or, potentially preferably, replaced by the SD
MRR measure.