Research Projects
Study on the biometric signal and the complex fluctuation
Our body has various organs that work in solidarity with each other in order for life to be maintained, and its aspect is very complex. In the field of mathematical science, the fluctuation caused by the interaction of many components in the system is called complex system fluctuation, and its basic characteristics have been studied.
In our laboratory, we are focusing on researching the similarity of complex fluctuations and biometric signals. For example, the heartbeat rhythm of a healthy person is not constant even at rest, the rhythm features a complex fluctuation that is caused by the beat interval that changes irregularly. However, this characteristic is lost due to illness and there is a tendency for the rhythm to be monotonous when a person is unhealthy. Since this complex fluctuations are closely related to health, we are developing technologies to understand the structure of biometric signals, to evaluate biological functions and to diagnose diseases.
Construction and Application of Analysis of Big Data by Focusing on Information Theory
In recent years,the discovery of diagnosis and treatment by using data from electronicized medical treatment and large scale biometric information has brought improvement to things such as the efficiency of medical treatment and the application to medical health policy are gaining attention due to the new possibilities that comes from it. This is not only true for medical professionals but also true to the public as various kinds of biometric informations can be stored through the internet in their daily life. In order to utilize such data and use it for the prevention of illness or to get an early detection, it is necessary to have the technology to understand the meaning that is hidden in the data. Therefore,in this research project we are developing methods to discover the knowledge regarding health and diseases from the ‘Big Data’ of the biometric information and are also conducting research to use it for the prediction of the health risks.
