Lowpass filtering method for heart rate variability analysis

✍ Scribed by Yasuaki Noguchi; Hiroshi Hataoka; Suguru Sugimoto

• Publisher: John Wiley and Sons
• Year: 1992
• Tongue: English
• Weight: 746 KB
• Volume: 23
• Category: Article
• ISSN: 0882-1666
• DOI: 10.1002/scj.4690231009

✦ Synopsis

Abstract

Various methods have been proposed for the spectral analysis of heart rate variability (HRV). Such methods always require constant period data in time series. However, since the R‐R interval of HRV is, in general, irregular, somehow the experimental data must be converted to constant period data. Assuming an integral pulse frequency modulation (IPFM) model, constant period data can be obtained by passing the heartbeat impulse train through a digital filter using the alias‐free method proposed by French and Holden.

However, the forementioned method has two problems; that is: (1) the frequency characteristics of the lowpass filter are assumed to be ideal, hence the impulse response function of the filter spreads infinitely with respect to time; and (2) only pulses inside the analyzing section are considered while those outside the analyzing section in the convolution integral are ignored.

To solve those problems, the method of French and Holden has been modified in the following three points: (1) such a finite impulse response digital filter was used that the sidelobe of the filter decays rapidly in its impulse response function; (2) the analyzing section as well as its impulse response time were lengthened, thus the pulses outside the analyzing section were considered; and (3) an appropriate window was used.

With these improvements, the truncation error and the computation time could be reduced. Furthermore, as a result of simulation, a much higher accuracy in the demodulation of the heartbeat signal was obtained.