Comparison between Hilbert–Huang transform and scalogram methods on non-stationary biomedical signals: application to laser Doppler flowmetry recordings
A significant transient increase in laser Doppler flowmetry (LDF) signals is observed in response to a local and progressive cutaneous pressure application on healthy subjects. This reflex may be impaired in diabetic patients. The work presents a comparison between two signal processing methods that...
Gespeichert in:
Veröffentlicht in: | Physics in medicine & biology 2005-11, Vol.50 (21), p.5189-5202 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | A significant transient increase in laser Doppler flowmetry (LDF) signals is observed in response to a local and progressive cutaneous pressure application on healthy subjects. This reflex may be impaired in diabetic patients. The work presents a comparison between two signal processing methods that provide a clarification of this phenomenon. Analyses by the scalogram and the Hilbert-Huang transform (HHT) of LDF signals recorded at rest and during a local and progressive cutaneous pressure application are performed on healthy and type 1 diabetic subjects. Three frequency bands, corresponding to myogenic, neurogenic and endothelial related metabolic activities, are studied at different time intervals in order to take into account the dynamics of the phenomenon. The results show that both the scalogram and the HHT methods lead to the same conclusions concerning the comparisons of the myogenic, neurogenic and endothelial related metabolic activities-during the progressive pressure and at rest-in healthy and diabetic subjects. However, the HHT shows more details that may be obscured by the scalogram. Indeed, the non-locally adaptative limitations of the scalogram can remove some definition from the data. These results may improve knowledge on the above-mentioned reflex as well as on non-stationary biomedical signal processing methods. |
---|---|
ISSN: | 0031-9155 1361-6560 |
DOI: | 10.1088/0031-9155/50/21/016 |