Authors:
Wenxi Chen
1
and
Toshiyo Tamura
2
Affiliations:
1
The University of Aizu, Japan
;
2
Osaka Electro-Communication University, Japan
Keyword(s):
Health Condition, Biorhythm, Long-term Monitoring, Monthly Change, Daily Measurement, Systolic Blood Pressure, Healthcare, Dynamic Time Warping.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Management and Quality
;
Data Manipulation
;
Data Mining
;
Data Visualization
;
Databases and Information Systems Integration
;
Datamining
;
Design and Development Methodologies for Healthcare IT
;
Enterprise Information Systems
;
Evaluation and Use of Healthcare IT
;
Health Information Systems
;
Pervasive Health Systems and Services
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
This paper presents an approach to detect monthly biorhythmic change using daily measurement of systolic
blood pressure (SBP) at home. As a part of health promotion campaign initiated in 1994, more than 600
households in West Aizu village of northern Japan were provided devices for daily measurement of blood
pressure, electrocardiogram, body temperature and body weight. This paper demonstrates an outcome of
data analysis of daily SBP collected in two years from an elder couple at age of seventies. The personal
reference profile is gained by averaging individual monthly profiles over 24 months. Dynamic time warping
algorithm estimates the similarity between personal reference profile and monthly SBP profile. The results
show that an extraordinary deviation from usual biorhythmicity can be found in both the wife and the
husband happened in July and February which respectively indicates individual health condition change
confirmed by personal medical record. The results suggest that eve
n it is difficult to identify any significant
variation from the daily SBP directly, proper analysis of the raw SBP measured over a long-term period
helps tracking functional information of health condition change and serving as an effective evidence for
health management.
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