Yumi Ogura

Noninvasive Biological Sensor System for Detection of Drunk Driving

Systems capable of monitoring the biological condition of a driver and issuing warnings during instances of drowsiness have recently been studied. Moreover, many researchers have reported that biological signals, such as brain waves, pulsation waves, and heart rate, are different between people who have and have not consumed alcohol. Currently, we are developing a noninvasive system to detect individuals driving under the influence of alcohol by measuring biological signals. We used the frequency time series analysis to attempt to distinguish between normal and intoxicated states of a person as the basis of the sensing system.

Noninvasive biological sensor system for detection of drunk driving

Systems capable of monitoring the biological condition of a driver and issuing warnings during instances of drowsiness have recently been studied. Moreover, many researchers have reported that biosignals, such as brain waves, pulsation waves, and heart beat are different between people who have and have not consumed alcohol. Currently, we are developing a noninvasive system to detect individuals driving under the influence of alcohol by measuring biosignals. In this paper, a new algorithm to distinguish between the normal and intoxicated state of a person is proposed as the basic theory of the sensing system.

Moving simulation of vibration systems using permanent magnets

This paper presents results obtained in moving simulations for a new vibration system with permanent magnets. The magnetic field distributions, the force acting upon the permanent magnets and the vibration mechanism of the magneto-spring are made clear in solving the coupled problem of the magnetic field and motion equations. The developed magneto-spring works to keeping a constant resonance frequency without active control.

Development of a condition monitoring system using an air-pack type pressure sensor for bedridden patients in a supine position

This paper proposes an online biological signal measurement system with an air-pack-type pressure sensor (APS) to monitor the condition of supine patients from pulse activity. The system enables estimation of three physiological signals corresponding to pulse pressure waves, pulse beats and respiratory waves from measurements taken and filtered using the APS, which has mechanical characteristics similar to the impedance characteristics of human muscle and can also be fitted with a mattress pad to prevent decubitus. In this study, the physiological significance of signals obtained through the APS was determined by comparing them with signals measured using commercial medical devices. The results showed that the correlations of pulse pressure waves, pulse beats and power spectral densities for respiratory waves between signals measured using the APS and those measured using commercial sensors were 0.84, 0.84 and 0.98, respectively. It was therefore concluded that the proposed system is suitable for outputting pulse pressure waves, pulse beats and respiratory waves.

Fluctuation analysis of finger plethysmograms related to various conditions

This study developed an analytical method for estimating and presenting the rating of perceived exertion (RPE) by using fluctuation analysis of largest Lyapunov exponent and heart rate variability. The method was applied to method to analyze a series of experiments conducted in various conditions including the use of a variety of driving seats to observing exertion and fatigue processes during a longer sitting a seat. We described the generating rate of and driving cause of the fatigue processes, respectively, by differentiation and acceleration of the RPE relations. We further explored the acceleration by wavelet analysis and found characterizing categories in relation to individuals and conditions.