Lomb algorithm versus fast fourier transform in heart rate variability analyses of pain in premature infants
- Anas Delaned(Author),
- Jorge Bohórquezc(Author),
- Subhanshu Guptaa(Author),
- aWashington State University,
- bWashington State University College of Nursing,
- cUniversity of Miami College of Engineering,
- dUnknown name
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution
Abstract
Heart rate variability analysis is a promising method for measuring pain in premature infants. The Lomb algorithm was adapted and compared with fast Fourier transform (FFT) for the purposes of PSD estimation. Both FFT and the Lomb algorithm had similar low frequency (LF) estimation error rates. However, the Lomb algorithm had a significant smaller error rate than FFT when estimating high frequency (HF). In addition, the ECG signals of two premature infants in the newborn intensive care unit were analyzed while undergoing a routine heel stick, a common painful procedure. The Lomb algorithm performed as expected marking a decrease in both LF and HF power in the presence of pain.