Akio Nozawa

Correlation analysis on alpha attenuation and nasal skin temperature

Some serious accidents caused by declines in arousal level, such as traffic accidents and mechanical control mistakes, have become issues of social concern. The physiological index obtained by human body measurement is expected to offer a leading tool for evaluating arousal level as an objective indicator. In this study, declines in temporal arousal levels were evaluated by nasal skin temperature. As arousal level declines, sympathetic nervous activity is decreased and blood flow in peripheral vessels is increased. Since peripheral vessels exist just under the skin on the fingers and nose, the psychophysiological state can be judged from the displacement of skin temperature caused by changing blood flow volume. Declining arousal level is expected to be observable as a temperature rise in peripheral parts of the body. The objective of this experiment was to obtain assessment criteria for judging declines in arousal level by nasal skin temperature using the alpha attenuation coefficient (AAC) of electroencephalography (EEG) as a reference benchmark. Furthermore, a psychophysical index of sleepiness was also measured using a visual analogue scale (VAS). Correlations between nasal skin temperature index and EEG index were analyzed. AAC and maximum displacement of nasal skin temperature displayed a clear negative correlation, with a correlation coefficient of −0.55.

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 %.

Analysis of 1/f fluctuation of keystroke dynamics and heart rate variability

Mental stress has been an issue in modern society. Several studies have investigated the detection of mental stress using physiological indices. However, measurement of these indices would itself impart a certain level of stress to subjects. The temporal dynamics of key typing are called “keystroke dynamics”. Keystroke dynamics show variations with psychological subtlety. The objective of this study was to develop a technique for ambient, unconscious measurement of mental stress based on keystroke dynamics. The relationship between fluctuations in keystroke dynamics and cardiac activity, in the form of heart rate variability, was analyzed. Intervals between key strokes were measured while using a computer under conditions of auditory stimulus or cognitive stress was determined. Power exponent β of the regression curve of the power spectrum for the time series of inter-stroke time (IST), and the power spectrum density of the high-frequency component (HF) for the time series of the R-R interval extracted from electrocardiography were calculated. As a result, the power spectrum of IST approached 1/f with auditory stimulus or cognitive stress, and a significant correlation existed between β and HF.

Dynamic analysis of dorsal thermal images

A dynamic analysis was performed on thermal images of the dorsum of the foot. The psychophysiological effects of a facial massage by an esthetician were evaluated. First, the psychophysiological effects of facial massage were assessed using a proprietary stress test. The physiological indices measured were the α-wave power spectrum, the dorsal skin temperature variations, and the high frequency (HF) component of the heart-rate variability (HRV). A state-trait anxiety inventory (STAI), a profile of mood states (POMS), and the level of sensory awareness were administered to evaluate the psychological status. The aspects of the level of sensory awareness examined were comfort, awakening, and the effects of massage. We then assessed the stress responses according to thermal imaging of the dorsal side of the foot using infrared thermography.

Emotion spectrum analysis for a daily repetitive mental workload

In this study, a mental workload of daily mental arithmetic training was objectively evaluated by physiological indices using the emotion spectrum analysis for a group with such training. Physiological measurements of the mental arithmetic task were conducted once a week for each subject. The physiological indices measured were the α-wave power spectrum, the β-wave power spectrum, the θ-wave power spectrum, variations in nasal skin temperature, and the high-frequency component of heart rate variability. Any depressive tendency during the mental arithmetic task was measured as a psychophysical index by using the Profile of Mood States (POMS) (brief form), and the time taken for the mental arithmetic task was also measured as a performance index. Correlations among physiological indices, the psychological index, the performance index, and the emotion spectrum were analyzed in relation to the mental workload.

Autonomous reconfiguration of robot shape by using Q-learning

A modular robot can be built with a shape and function that matches the working environment. We developed a four-arm modular robot system which can be configured in a planar structure. A learning mechanism is incorporated in each module constituting the robot. We aim to control the overall shape of the robot by an accumulation of the autonomous actions resulting from the individual learning functions. Considering that the overall shape of a modular robot depends on the learning conditions in each module, this control method can be treated as a dispersion control learning method. The learning object is cooperative motion between adjacent modules. The learning process proceeds based on Q-learning by trial and error. We confirmed the effectiveness of the proposed technique by computer simulation.

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.

Enhancing cardiac parasympathetic nervous activity using a posture respiration ambient biofeedback system: a pilot study

A respiration–posture feedback system was developed to control breathing involuntarily. A small air chamber placed under a subject’s back deflates and inflates to make a subject’s upper body move vertically while lying on a bed. By regulating the deflation/inflation of the air chamber in synchronization with actual respiration, the subject’s respiration was successfully lengthened and deepened. The modulation of the respiration acted as a physiological sedative for the subject as the heart rate variability index suggested that the subject’s parasympathetic nervous system activity was enhanced.

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.