Shizuka Bando

Driver's drowsiness inhibition by subcutaneous stimulation based on SNS activity

The overall aim of the study is to develop the ambient drowsiness control programs based on driver’s physiological states. this study is developed and verified of a system that controls a driver’s drowsiness a stimulus that is too small to be noticed by a driver. Most studies on driver drowsiness have focused on the detection or evaluation of psychological states in some way. Our system assumes that a small change in temperature affects peripheral thermoreceptors and that afferent fibers transmit this stimulus to the cerebral center via the spinal nerves. To evaluate the system, we constructed a virtual reality system for automobile driving using an experimental method described in our previous studies. In this study, drowsiness was controlled by our system, and the effectiveness of the system was tested. The results suggest that this is an efficient method for controlling driver drowsiness.

Detection of driver inattention from fluctuations in vehicle operating data

Drivers have to drive their vehicle safely by properly using steering, throttling, and braking controls. However, drivers do not always maintain their concentration on managing their vehicles. The primary causes of driver inattention are distracting activities and drowsiness. Such driver inattention is thought to be one of the major causes of traffic accidents, and so the objective of the present study is to develop a new method for detecting driver inattention from fluctuations in vehicle operating data. Steering and throttle operations while driving were measured by acceleration sensors and respiration rhythm and an electrocardiogram were measured as physiological indices. The result of correlation between the estimative value, peaks and exponent values of frequency characteristics of vehicle operating data, and physiological indices, an association of sympathetic nervous system activation was indicated. The performance of detecting normal state, under cognitive stress state, and drowsy state by this method was an average correct discriminatory rate of 70 %.

Contactless blood pressure sensing using facial visible and thermal images

Hypertension is one of the leading risk factors for several diseases. Measurement and monitoring of blood pressure anytime and anywhere are important to lower blood pressure and prevent pathogenesis of diseases. Non-contact blood pressure measurement is desired to monitor blood pressure anytime and anywhere. The aim of this study was to develop a non-contact blood pressure sensing system. A previous study reported that amplitude and time differences of facial photoplethysmogram (PPG) components extracted using brightness variation of facial skin color in facial visible images could be useful indices for estimating blood pressure. The maximum error between measured and estimated blood pressure using facial PPG components was 12 mmHg. An additional signal processing algorithm is desired to increase the accuracy for estimating blood pressure using facial PPG components. By contrast, facial skin temperature also reflects changes in the facial blood circulation. High-accuracy estimation of blood pressure could be expected using both facial PPG components and facial skin temperature. In this study, improvement of accuracy for estimating blood pressure using facial PPG components by attempting to apply additional signal processing to facial skin color variation. Furthermore, a correlation analysis between facial skin temperature and measured blood pressure was performed, and individual models for blood pressure estimation were created.

Psychophysiological assessment of an adaptive asynchronous human---machine system with the dual-task method

Human error is one of the leading causes of industrial accidents at modern manufacturing production sites. An adaptive asynchronous human–machine system (Async-HMS) was previously proposed as a new mechanism for preventing the reduction of cognitive level by controlling the actual operation period of machines that lead to monotonous behavior. The objective of this paper is to assess Async-HMS from the aspects of person’s current capacity for performing processing resources. A dual-task method consisting of a synchronization task with three periodic fluctuations and four levels of difficulties of mental arithmetic tasks was conducted with Async-HMS on a PC. The three periodic fluctuations are constant periodic fluctuation (Cnst), perceptible periodic fluctuation (Supraliminal), and imperceptible periodic fluctuation (Subliminal). The task performance and the psychophysiological state were assessed through the dual-task method. In an ANOVA analysis, the time shared fraction, which is an index of processing resources devoted to an arithmetic task, had no significant effect on the synchronization task. The mean blood pressure in Subliminal had a significant increase compared with that in Cnst and Supraliminal. These results indicate that subliminal fluctuation evokes sympathetic hyperactivity without affecting processing resources. Implementation of subliminal operation period into industrial machines performing periodic behavior might inhibit monotony and, therefore, prevent human error.

Multidimensional directed coherence analysis of keystroke dynamics and physiological responses

Techno-stress has been a problem in recent years with a development of information technology. Various studies have been reported about a relationship between key typing and psychosomatic state. Keystroke dynamics are known as dynamics of a key typing motion. The objective of this paper is to clarify the mechanism between keystroke dynamics and physiological responses. Inter-stroke time (IST) that was the interval between each keystroke was measured as keystroke dynamics. The physiological responses were heart rate variability (HRV) and respiration (Resp). The system consisted of IST, HRV, and Resp was applied multidimensional directed coherence in order to reveal a causal correlation. As a result, it was observed that strength of entrainment of physiological responses having fluctuation to IST differed in surround by the noise and a cognitive load. Specifically, the entrainment became weak as a cognitive resource devoted to IST was relatively increased with the keystroke motion had a robust rhythm. On the other hand, the entrainment became stronger as a cognitive resource devoted to IST was relatively decreased since the resource also devoted to the noise or the cognitive load.

Causal analysis between vehicle operating data and physiological responses

The objective of this paper is to clarify the interrelation between vehicle operating data and physiological responses to different psychological states. Multidimensional directed coherence (MDC) analysis was applied to the human–machine system, as observed by vehicle operating data and physiological indices to reveal the mechanism of the interrelation. The MDC analysis is one way to visualize the information flow between an arbitrary number of time series signals in the frequency domain. As a result, it was found that the entrainment of physiological indices on vehicle operating data is different depending on the cognitive resources devoted to driving motion. In particular, it was clarified that driving motion is easily influenced by physiological indices when the cognitive resources devoted to driving motion are few either absolutely or relatively.