Naoaki Itakura

A new method for calculating eye movement displacement from AC coupled electro-oculographic signals in head mounted eye–gaze input interfaces

Abstract Various eye movement measurement devices used in eye–gaze input interfaces are generally expensive or necessarily restrict the users head motion. We proposed a novel eye–gaze input interface that combined a head mounted display with an electro-oculograph amplified via an AC coupling. Experiments were carried out to create a necessary calculation method for the displacement of an eye movement from an electro-oculograph amplified via an AC coupling. Offline and online analyses were performed to compare the new method of using integration to the previous method of using the maximum amplitude during an interval from 0 to 0 of the derivative AC-EOG. The mean accuracies of the choices increased from 88.8% to 96.7% in the case of 8 possible choices and from 72.8% to 86.4% in the case of 12 possible choices by using the integration instead of the maximum amplitude by the offline analyses. Moreover, the online analyses were done for confirmation of the calculation method of the displacement that was used with only the maximum displacement. For the designs with 8 and 12 possible choices, the mean accuracies of the choices were 95.3% and 88.5%, respectively.

Study of function of fingers by physiological tremor

Abstract 1. 1. Physiological tremor is invisible mechanical vibration of body parts. 2. 2. It has two peak frequencies in the p ower spectrum. The origin of the peaks has not been well elucidated. Therefore, the mechanism and its application to labor science is studied in the paper. 3. 3. The effect of immersion of fingers in water and of loading weights on fingers are performed to elucidate the mechanism involved. 4. 4. It is found that the power spectrum output has two bands from the lower frequency band (1.5–18 Hz) from the CNS and the higher frequency band (18–50 Hz). 5. 5. These results are applied to the evaluation of fatigue of fingers in tapping and typing work. 6. 6. The total power, which is the sum of power spectrum in frequency range between 1.5 and 50 Hz, is employed as evaluational index. The change of total power explains finger fatigue during tapping and typing loads. 7. 7. Physiological tremor is an effective way of evaluating the function of fingers in human work.

Computer Input System Using Eye Glances

We have developed a real-time Eye Glance input interface using a Web camera to capture eye gaze inputs. In previous studies, an eye control input interface was developed using an electro-oculograph (EOG) amplified by AC coupling. Our proposed Eye Gesture input interface used a combination of eye movements and did not require the restriction of head movement, unlike conventional eye gaze input methods. However, this method required an input start operation before capturing could commence. This led us to propose the Eye Glance input method that uses a combination of contradirectional eye movements as inputs and avoids the need for start operations. This method required the use of electrodes, which were uncomfortable to attach. The interface was therefore changed to a camera that used facial pictures to record eye movements to realize an improved noncontact and low-restraint interface. The Eye Glance input method measures the directional movement and time required by the eye to move a specified distance using optical flow with OpenCV from Intel. In this study, we analyzed the waveform obtained from eye movements using a purpose-built detection algorithm. In addition, we examined the reasons for detecting a waveform when eye movements failed.

Analysis of trends in the occurrence of eyeblinks for an eyeblink input interface

This paper presents the results of the analysis of trends in the occurrence of eyeblinks for devising new input channels in handheld and wearable information devices. However, engineering a system that can distinguish between voluntary and spontaneous blinks is difficult. The study analyzes trends in the occurrence of eyeblinks of 50 subjects to classify blink types via experiments. However, noticeable differences between voluntary and spontaneous blinks exist for each subject. Three types of trends based on shape feature parameters (duration and amplitude) of eyeblinks were discovered. This study determines that the system can automatically and effectively classify voluntary and spontaneous eyeblinks.

Study of eye-glance input interface

Optical measurement devices for eye movements are generally expensive and it is often necessary to restrict user head movements when various eye-gaze input interfaces are used. Previously, we proposed a novel eye-gesture input interface that utilized electrooculography amplified via an AC coupling that does not require a head mounted display[1]. Instead, combinations of eye-gaze displacement direction were used as the selection criteria. When used, this interface showed a success rate approximately 97.2%, but it was necessary for the user to declare his or her intention to perform an eye gesture by blinking or pressing an enter key. In this paper, we propose a novel eye-glance input interface that can consistently recognize glance behavior without a prior declaration, and provide a decision algorithm that we believe is suitable for eye-glance input interfaces such as small smartphone screens. In experiments using our improved eye-glance input interface, we achieved a detection rate of approximately 93% and a direction determination success rate of approximately 79.3%. A smartphone screen design for use with the eye-glance input interface is also proposed.

Eye-glance input interface for a small screen

Optical measurement devices for eye movements are generally expensive and it is often necessary to restrict user head movements when various eye-gaze input interfaces are used. Previously, we proposed a novel eye-gesture input interface that utilized electrooculography amplified via an AC coupling that does not require a head mounted display [1] . Instead, combinations of eye-gaze displacement direction were used as the selection criteria. When used, this in- terface showed a success rate approximately 97.2%, but it was necessary for the user to declare his or her intention to perform an eye gesture by blinking or pressing an enter key. In this paper, we propose a novel eye-glance input in- terface that can consistently recognize glance behavior without a prior declaration, and provide a decision algorithm that we believe is suitable for eye-glance input interfaces such as small smartphone screens. In experiments using our improved eye-glance input interface, we achieved a detection rate of approximately 93% and a direction determina- tion success rate of approximately 79.3%. A smartphone screen design for use with the eye-glance input interface is also proposed.

Physiological and Psychological Evaluation by Skin Potential Activity Measurement Using Steering Wheel While Driving

This paper proposes a new method for practical skin potential activity (SPA) measurement while driving a car by installing electrodes on the outer periphery of the steering wheel. Evaluating the psychophysiological state of the driver while driving is important for accident prevention. We investigated whether the physiological and psychological state of the driver can be evaluated by measuring SPA while driving. Therefore, we have devised a way to measure SPA measurement by installing electrodes in a handle. Electrodes are made of tin foil and are placed along the outer periphery of the wheel considering that their position while driving is not fixed. The potential difference is increased by changing the impedance through changing the width of electrodes. Moreover we try to experiment using this environment. An experiment to investigate the possibility of measuring SPA using the conventional and the proposed methods were conducted with five healthy adult males. A physical stimulus was applied to the forearm of the subjects. It was found that the proposed method could measure SPA, even though the result was slightly smaller than that of the conventional method of affixing electrodes directly on hands.

Differentiating Conscious and Unconscious Eyeblinks for Development of Eyeblink Computer Input System

In this paper, we propose and evaluate a new conscious eyeblink differentiation method, comprising an algorithm that takes into account differences in individuals, for use in a prospective eyeblink user interface. The proposed method uses a frame-splitting technique that improves the time resolution by splitting a single interlaced image into two fields—even and odd. Measuring eyeblinks with sufficient accuracy using a conventional NTSC video camera (30 fps) is difficult. However, the proposed method uses eyeblink amplitude as well as eyeblink duration as distinction thresholds. Further, the algorithm automatically differentiates eyeblinks by considering individual differences and selecting a large parameter of significance in each user. The results of evaluation experiments conducted using 30 subjects indicate that the proposed method automatically differentiates conscious eyeblinks with an accuracy rate of 83.6 % on average. These results indicate that automatic differentiation of conscious eyeblinks using a conventional video camera incorporated with our proposed method is feasible.

Evaluation method using chaotic analysis for the model of vehicles' behavior in road traffic system

We have already proposed a simulator of a road traffic system, and called it MITRAM. The MITRAM consists of microscopic models for vehicles which have the capability of their own decision-making through the application of fuzzy logic. This microscopic model is called a fuzzy model vehicle (FMV). We have simulated the driving operation of a following vehicle through the FMV. Data of the following vehicle speed, the relative speed of the following one to the leading vehicle, and so on, were obtained as the simulation data of the FMV. To calculate only the mean and the variance of the simulation data was not sufficient to describe the logic inferences of the FMV. In this paper, we propose an evaluating method by using a chaotic analysis. Correlation exponents and Lyapunov exponents were calculated for the data of the following vehicle speed, the relative speed of the following one to the leading vehicle, and the spacing distance between the following and the leading vehicles. We also calculated both the exponents of the data normalized by the standard deviation, in order to evaluate the effect of the variance. The correlation exponents and the maximum Lyapunov exponents of the relative speed were different from those of the following vehicle speed and the spacing distance. Differences between the simulation and the measurement data were found at both the correlation exponents and the Lyapunov exponents. The variance had a larger effect on the correlation exponents for the simulation data than for the measurement data.

Functional analysis of nonstationary EMG signals during a quick movement

An analysis is presented of the functional characteristics of the electromyogram (EMG) for a quick movement of the hand. The EMG signals resulting from a quick movement are represented by an autoregressive (AR) model. The AR parameters are estimated by the forward-backward model method, which is useful in the estimation of a nonstationary or dynamic signal. The prediction error variance, which is a peak frequency of EMG power spectrum, and the zero crossing rate are analyzed. The angular velocity of the hand during a quick movement is measured directly by placing an angular sensor on the joint axis of the wrist. Experimental results for five normal subjects are presented. They show the advantages of using the proposed method for nonstationary EMG signals.<<ETX>>