Authors:
Mayumi Oyama-Higa
1
and
Tiejun Miao
2
Affiliations:
1
Kwansei Gakuin University, Japan
;
2
CCI Corporation and Chaos Technology Research Laboratory, Japan
Keyword(s):
Chaotic analysis, divergence, fingertip pulse waves, Lyapunov exponent, PC mouse, mental health.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics
;
Real-Time Systems
;
Sensor Networks
;
Soft Computing
;
Wavelet Transform
Abstract:
We conducted a nonlinear analysis of fingertip pulse waves and found that the Lyapunov exponent having the “divergence” property of attractor trajectory was an effective index for estimating human mental health. We showed that this method is effective for an early detection of dementia and depression, as well as in the detection of changes in mental status. In addition, based on these results obtained from time series analysis of the recorded pulse waves, we developed an application device allowing easily installed and convenient measurement for daily check and monitoring mental/physical status. It was an easy-to-use and cost-less device installed in a PC mouse. Also, we studied a representation method of constellation graphs to disclose the fluctuation details of the Lyapunov exponents. In the representation, changes in mental status were assessed and graphically visible by using of the fluctuation factor of the Lyapunov exponents.