Recently in developed countries, chronic conditions represented by lifestyle-related diseases have become leading causes of death. In these circumstances, primary or secondary prevention is the most effective way to avoid them. Hence, it is important to be able to monitor simply our health condition for both disease prevention and health promotion.
We have focused on autonomic nervous activity (ANA) because it responds with stress as well as changes in dietary patterns, and it correlates with heart diseases. In this work, we consider both electrocardiogram (ECG) and plethysmogram (PTG) as the physiological data that reflects ANA. ECG and PTG obtained from healthy people provide several indices including aging index and pulse transmission time, and could be available as signs of asymptomatic illness. However, it is difficult to find predictive information from raw data of ECG and PTG.
In our work, we propose an application that analyzes ECG and PTG, and visualizes their indices and waveforms and call Mavep; it offers a tailored user interface (UI) enabling users to browse the two data checking their relationship, for brief assessment of ANA. We develop the application in Java from the viewpoint of portability, independence from specific platforms, putting weight on its UI for providing it as a tool for doctors. We implement both algorithms for analyzing raw data of ECG and PTG, and tailored UI that facilitates interaction between the physiological data and users.
We propose an improved formulation of the problem of color scheme adjustment and its implementation, taking into account categorical perception and color vision deficiencies. Our work focuses on the representation of information, such as floor maps of public spaces and figures in books and papers. Because these representations carry two aspects: the aspect of art design and the aspect of media, it is difficult to adjust any color scheme, and to determine the optimal combination of colors. As an approach to the problem, we have already proposed a solution by formulating it as fuzzy constraint satisfaction problems, a framework studied in the field of artificial intelligence. In this paper, we take account the concept of categorical perception of colors, relations between color names and color vision, for improving our method. In addition, we show an application of the method for color-grayscale transformation.
© 2011 IEICE
We propose a formulation of the problem of color scheme adjustment and a prototype system that automatically solves it, taking into account color vision deficiencies. Our work focuses on the representation of information, such as floor maps of public spaces and figures in books and papers. Color schemes of these representations carry two aspects: the aspect of art design and the aspect of media. The aspect of art design allows the creation of appealing color schemes using the sensitivity to beauty or theme of the contents. The aspect of media, on the other hand, provides information easy to understand. In particular, in the second aspect, designers need to consider universal design. However, these two aspects make any color scheme adjustments difficult, and the optimal combination of colors is not easily determined. The original color scheme made by a designer should not change drastically from the viewpoint of art, and at same time, the scheme must be understandable to everyone even to those with color vision deficiencies. To solve this difficulty posed to designers, we formulate our color scheme adjustment as a fuzzy constraint satisfaction problem, a framework studied in the field of artificial intelligence. In our formulation, we employ the index of color conspicuity, which defines how easily-noticeable a color is for retaining the impression of the original color scheme. To prove the feasibility of the concept, we develop a prototype system in Java that automatically adjusts colors given by a designer.