Analyzing the 24-hour blood pressure and heart-rate variability with self-organizing feature maps
In this article, the self‐organizing map (SOM) is employed to analyze data describing the 24‐hour blood pressure and heart‐rate variability of human subjects. The number of observations varies widely over different subjects, and therefore a direct statistical analysis of the data is not feasible wit...
Gespeichert in:
Veröffentlicht in: | International journal of intelligent systems 2002-01, Vol.17 (1), p.63-76 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | In this article, the self‐organizing map (SOM) is employed to analyze data describing the
24‐hour blood pressure and heart‐rate variability of human subjects. The number of observations
varies widely over different subjects, and therefore a direct statistical analysis of the data is not feasible
without extensive pre‐processing and interpolation for normalization purposes. The SOM network operates
directly on the data set, without any pre‐processing, determines several important data set
characteristics, and allows their visualization on a two‐dimensional plot. The SOM results are very similar
to those obtained using classic statistical methods, indicating the effectiveness of the SOM method in accurately
extracting the main characteristics from the data set and displaying them in a readily understandable manner. In
this article, the relation is studied between the representation of each subject on the SOM, and his blood
pressure and pulse‐rate measurements. Finally, some indications are included regarding how the SOM can be
used by the medical community to assist in diagnosis tasks. © 2002 John Wiley & Sons, Inc. |
---|---|
ISSN: | 0884-8173 1098-111X |
DOI: | 10.1002/int.1003 |