Lomb algorithm versus fast fourier transform in heart rate variability analyses of pain in premature infants
- Anas Delane,
- Jorge Bohórquez,
- Subhanshu Gupta,
- Martin Schiavenato(corresponding author)
- University of Miami College of Engineering,
- Washington State University,
- Washington State University College of Nursing
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.
Bibliographic Information
Output type
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Original language
EnglishArticle number
7590857Pages from-to (Number of pages)
Pages 944-947 (4 pages)Publication milestones
- Published - 13/10/2016
Publication status
Published - 13/10/2016
Publisher
Institute of Electrical and Electronics Engineers Inc.Publication series
- Publication series name: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print): 1557-170X
Volume: 2016-October
ISBN (Electronic)
9781457702204Publication IDs
- Scopus: 85009152878
- PubMed: 28268480
