Analyzing the 24-hour blood pressure and heart-rate variability with self-organizing feature maps

• Published in: International journal of intelligent systems Vol. 17; no. 1; pp. 63 - 76
• Main Authors: Tambouratzis, G., Papakonstantinou, G., Stamatelopoulos, S., Zakopoulos, N., Moulopoulos, S.
• Format: Journal Article
• Language: English
• Published: New York John Wiley & Sons, Inc 01.01.2002; Wiley
• Subjects: Applied sciences; Artificial intelligence; Biological and medical sciences; Computer science; control theory; systems; Computerized, statistical medical data processing and models in biomedicine; Connectionism. Neural networks; Exact sciences and technology; Medical sciences; Models and simulation; Visualization; Data analysis; Statistical analysis; Variability; Data transmission; Data processing; Neural network; Statistical data; Heart rate; Self organization; Telecommunication network; Blood pressure; Diagnosis; Pressure measurement; Medical application
• ISSN: 0884-8173; 1098-111X
• DOI: 10.1002/int.1003

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.