Vertical Electrooculogram Research Articles

EOG-based eye movement detection and gaze estimation for an asynchronous virtual keyboard

Abstract This work aims to develop a novel electrooculography (EOG)-based virtual keyboard with a standard QWERTY layout which, unlike similar state-of-the-art systems, allows users to reach any icon from any location directly and asynchronously. The saccadic EOG potential displacement is mapped to angular gaze displacement using a novel two-channel input linear regression model, which considers features extracted from both the horizontal and vertical EOG signal components jointly. Using this technique, a gaze displacement estimation error of 1.32 ± 0.26° and 1.67 ± 0.26° in the horizontal and vertical directions respectively was achieved, a performance which was also found to be generally statistically significantly better than the performance obtained using one model for each EOG component to model the relationship in the horizontal and vertical directions separately, as typically used in the literature. Furthermore, this work also proposes a threshold-based method to detect eye movements from EOG signals in real-time, which are then classified as saccades or blinks using a novel cascade of a parametric and a signal-morphological classifier based on the EOG peak and gradient features. This resulted in an average saccade and blink labelling accuracy of 99.92% and 100.00% respectively, demonstrating that these two eye movements could be reliably detected and discriminated in real-time using the proposed algorithms. When these techniques were used to interface with the proposed asynchronous EOG-based virtual keyboard, an average writing speed across subjects of 11.89 ± 4.42 characters per minute was achieved, a performance which has been shown to improve substantially with user experience.

In the Blink of an Eye: Ocular Proxies of Neurotransmitters Predict Creative Ability

Previous research suggests that eye blink rates (EBR) can be used as an index for dopamine activity (DA) and therefore a potential marker of creative aptitude. In addition, another putative index of creativity has been linked to the neurotransmitter serotonin (5-HT) and eye blink duration (EBD). The current pilot study aimed to investigate whether both EBR and EBD could be used as predictors of creativity and if mood would influence these measures. Vertical electrooculograms were gathered from 12 participants, during three conditions, to enable subsequent EBR and EBD to be calculated. The three conditions comprised eyes open baseline, viewing images from the International Affective Picture System (IAPS) of positive and finally negative valence. Dispositional measures of creativity were measured post task using the Creative Styles Questionnaire-revised. Higher EBR was significantly related to higher scores on subcategories ‘Use of Techniques’ and ‘Use of Other People’. In addition, shorter EBD significantly correlated with higher scores of global creativity, ‘Use of Techniques’ and ‘Use of the Senses’. Results confirm that EBR and EBD can be used as predictors for creativity and may reflect DA/5-HT activity. Implications of the results are discussed in relation to specific characteristics, techniques and underlying mechanisms of creativity and how neurotransmitters drive such ability.

Development of an electrooculogram-based eye-computer interface for communication of individuals with amyotrophic lateral sclerosis

BackgroundElectrooculogram (EOG) can be used to continuously track eye movements and can thus be considered as an alternative to conventional camera-based eye trackers. Although many EOG-based eye tracking systems have been studied with the ultimate goal of providing a new way of communication for individuals with amyotrophic lateral sclerosis (ALS), most of them were tested with healthy people only. In this paper, we investigated the feasibility of EOG-based eye-writing as a new mode of communication for individuals with ALS.MethodsWe developed an EOG-based eye-writing system and tested this system with 18 healthy participants and three participants with ALS. We also applied a new method for removing crosstalk between horizontal and vertical EOG components. All study participants were asked to eye-write specially designed patterns of 10 Arabic numbers three times after a short practice session.ResultsOur system achieved a mean recognition rates of 95.93% for healthy participants and showed recognition rates of 95.00%, 66.67%, and 93.33% for the three participants with ALS. The low recognition rates in one of the participants with ALS was mainly due to miswritten letters, the number of which decreased as the experiment proceeded.ConclusionOur proposed eye-writing system is a feasible human-computer interface (HCI) tool for enabling practical communication of individuals with ALS.

EOG feature relevance determination for microsleep detection

Abstract Automatic relevance determination (ARD) was applied to two-channel EOG recordings for microsleep event (MSE) recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC) and logarithmic power spectral densities (PSD) averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ) was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM), in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 - 4.9 % and 1.9 - 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 - 0.006 % and 0.002 - 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respec-tively. GRLVQ permits objective feature reduction by inclu-sion of all processing stages, but is not as accurate as SVM.

EOG feature relevance determination for microsleep detection

Abstract Automatic relevance determination (ARD) was applied to two-channel EOG recordings for microsleep event (MSE) recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC) and logarithmic power spectral densities (PSD) averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ) was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM), in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 – 4.9 % and 1.9 – 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 – 0.006 % and 0.002 – 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respectively. GRLVQ permits objective feature reduction by inclusion of all processing stages, but is not as accurate as SVM.

An EOG-Based Human-Machine Interface for Wheelchair Control.

Nonmanual human-machine interfaces (HMIs) have been studied for wheelchair control with the aim of helping severely paralyzed individuals regain some mobility. The challenge is to rapidly, accurately, and sufficiently produce control commands, such as left and right turns, forward and backward motions, acceleration, deceleration, and stopping. In this paper, a novel electrooculogram (EOG) based HMI is proposed for wheelchair control. A total of 13 flashing buttons, each of which corresponds to a command, are presented in the graphical user interface. These buttons flash on a one-by-one manner in a predefined sequence. The user can select a button by blinking in sync with its flashes. The algorithm detects the eye blinks from a channel of vertical EOG data and determines the user's target button based on the synchronization between the detected blinks and the button's flashes. For healthy subjects/patients with spinal cord injuries, the proposed HMI achieved an average accuracy of 96.7%/91.7% and a response time of 3.53 s/3.67 s with 0 false positive rates (FPRs). Using one channel of vertical EOG signals associated with eye blinks, the proposed HMI can accurately provide sufficient commands with a satisfactory response time. The proposed HMI provides a novel nonmanual approach for severely paralyzed individuals to control a wheelchair. Compared with a newly established EOG-based HMI, the proposed HMI can generate more commands with higher accuracy, lower FPR, and fewer electrodes.

Bereitschaftspotential preceding spontaneous and voluntary eyelid blinks in normal individuals.

To investigate the Bereitschaftspotential (BP) preceding spontaneous and voluntary eyelid blinks in normal subjects. Eighteen healthy individuals (10 female) between 17 and 60years (mean 35) were studied. The EEG was recorded from 11 scalp positions of the 10-20 international electrode placement system referenced to linked mastoids. The vertical electrooculogram (VEOG) was recorded from two electrodes positioned above and below the right eye. The ground electrode was placed in the right clavicle. The recordings were obtained during spontaneous and voluntary eyelid blinks. Two-second EEG segments before the onset of the blink potential (visually identified at the VEOG channel) were averaged and analyzed off-line. The statistical significance of differences was evaluated by repeated-measures analysis of variance with Geisser-Greenhouse correction for violation of sphericity and the Newman-Keuls test was used for post hoc comparisons. A BP starting around -1700ms prior to the onset of voluntary blink was observed; it had average amplitude in the negative peak of 3.3μV. There was no BP preceding spontaneous blinking. A BP precedes voluntary blinks but not spontaneous blinks. This is the first study evaluating the BP preceding spontaneous and voluntary eye blinks.

Excision of Ocular Artifacts from EEG Using NVFF-RLS Adaptive Algorithm

This paper presents a technique for the removal of ocular artifacts from electro-encephalogram (EEG) by using adaptive filtering. The major concern is electro-oculogram (EOG) signal present in a recorded EEG signal, which appears due to abrupt eye movements. In the presented method, we use separately recorded horizontal EOG (HEOG) and vertical EOG (VEOG) signals as two reference inputs, which are processed using finite impulse response (FIR) filters. The linear filter coefficients are adaptively updated using a numerical variable forgetting factor (NVFF) recursive least squares (RLS) algorithm, which tracks nonstationary EOG signals. Subsequently, the processed HEOG and VEOG signals are subtracted from recorded EEG signal to obtain an artifact-free EEG signal. Simulation is conducted using synthetic EEG signal corrupted by noise, synthetic HEOG and VEOG signals. The real-time recorded EEG signal (corrupted by EOG and noise) is also refined using the separately recorded reference EOG signals and FIR filtering technique. For synthetic and real-time signals, the simulation results are presented to demonstrate that linear NVFF-RLS algorithm-based artifact and noise excision technique outperforms conventional fixed forgetting factor RLS, fixed step-size NLMS and generalized variable step-size NLMS algorithms, in terms of the reduction in mean-squared error, under low as well as high signal-to-noise ratio conditions.

Removing the Interdependency between Horizontal and Vertical Eye-Movement Components in Electrooculograms.

This paper introduces a method to remove the unwanted interdependency between vertical and horizontal eye-movement components in electrooculograms (EOGs). EOGs have been widely used to estimate eye movements without a camera in a variety of human-computer interaction (HCI) applications using pairs of electrodes generally attached either above and below the eye (vertical EOG) or to the left and right of the eyes (horizontal EOG). It has been well documented that the vertical EOG component has less stability than the horizontal EOG one, making accurate estimation of the vertical location of the eyes difficult. To address this issue, an experiment was designed in which ten subjects participated. Visual inspection of the recorded EOG signals showed that the vertical EOG component is highly influenced by horizontal eye movements, whereas the horizontal EOG is rarely affected by vertical eye movements. Moreover, the results showed that this interdependency could be effectively removed by introducing an individual constant value. It is therefore expected that the proposed method can enhance the overall performance of practical EOG-based eye-tracking systems.

Dynamic mental number line in simple arithmetic.

Studies have found that spatial-numerical associations could extend to arithmetic. Addition leads to rightward shift in spatial attention while subtraction leads to leftward shift (e.g., Knops et al. 2009; McCrink et al. 2007; Pinhas & Fischer 2008), which is consistent with the hypothesis of static mental number line (MNL) for arithmetic. The current investigation tested the hypothesis of dynamic mental number line which was shaped by the relative magnitudes of two operands in simple arithmetic. Horizontal and vertical electrooculograms (HEOG and VEOG) during simple arithmetic were recorded. Results showed that the direction of eye movements was dependent on the relative magnitudes of two operands. Subtraction was associated with larger rightward eye movements than addition (Experiment 1), and smaller-operand-first addition (e.g., 2+9) was associated with larger rightward eye movement than larger-operand-first addition (e.g., 9+2) only when the difference of two operands was large (Experiment 2). The results suggest that the direction of the mental number line could be dynamic during simple arithmetic, and that the eyes move along the dynamic mental number line to search for solutions.

Development of an eyewear to measure eye and body movements.

To enable precise detection of mental and physical states of users in a daily life, we have been developing an eyewear to measure eye and body movement in a unrestricted way. The horizontal and vertical EOG (electrooculogram) signals are measured and amplified with three metal dry electrodes placed near nasion and both sides of rhinion, of which positions correspond to the bridge and nose pads of eyewear, respectively. The user's mental states like drowsiness, sleepiness, fatigue, or interest to objects can be identified by the movements and blinking of the eyes extracted from the measured EOG. And the six-axis motion sensor (three-axis accelerometer and three-axis gyroscope) mounted in the eyewear measures the body motion. As the sensor located near the head is on the body axis, this eyewear is suitable to measure user's movement or shift of center of gravity during physical exercise with a high precision. The measured signals are used to extract various events of eye and body movement by the mounted microcontroller chip, or can be transmitted to the external devices via Bluetooth communication. This device can enable you to look into "yourself", as well as outer scenes. In this presentation, the outline of the eyewear is introduced and some possible applications are shown.

Eye blink characterization from frontal EEG electrodes using source separation and pattern recognition algorithms

Due to its major safety applications, including safe driving, mental fatigue estimation is a rapidly growing research topic in the engineering field. Most current mental fatigue monitoring systems analyze brain activity through electro-encephalography (EEG). Yet eye blink analysis can also be added to help characterize fatigue states. It usually requires the use of additional devices, such as EOG electrodes, uncomfortable to wear, or more expensive eye trackers. However, in this article, a method is proposed to evaluate eye blink parameters using frontal EEG electrodes only. EEG signals, which are generally corrupted by ocular artifacts, are decomposed into sources by means of a source separation algorithm. Sources are then automatically classified into ocular or non-ocular sources using temporal, spatial and frequency features. The selected ocular source is back propagated in the signal space and used to localize blinks by means of an adaptive threshold, and then to characterize detected blinks. The method, validated on 11 different subjects, does not require any prior tuning when applied to a new subject, which makes it subject-independent. The vertical EOG signal was recorded during an experiment lasting 90min in which the participants’ mental fatigue increased. The blinks extracted from this signal were compared to those extracted using frontal EEG electrodes. Very good performances were obtained with a true detection rate of 89% and a false alarm rate of 3%. The correlation between the blink parameters extracted from both recording modalities was 0.81 in average.

Online Voluntary Eye Blink Detection using Electrooculogram

This paper describes the voluntary eye blink detection method using electrooculogram (EOG). There are still challenge problems to put brain-computer interfa ce (BCI) systems to real-life applications. In general BCI sys- tems, there is a possibility of incorrect and unintentional input because input is automatically selected even if the requirements are accidentally met. This study aims to pro- pose the voluntary eye blink detection method and apply it to the trigger switch of BCI systems. In the proposed method, normal blink, double blink, and wink can be de- tected from vertical and horizontal EOG signals. We em- ployed the positive peak of vertical and horizontal ampli- tude and maximum cross correlation coeffi cient between vertical EOG and template signal of double blink in feature extraction. Eye blinks were classified by support vector machine. As the result of simulations, an average accuracy of 97.28% was obtained using our method. In addition, the best accuracy for voluntary eye blinks was obtained for wink with accuracy of 97.69 %. This paper proof wink is suitable for trigger switch of BCI system, and online method for voluntary eye blink detection.

ONLINE REMOVAL OF EYE BLINK ARTIFACT FROM SCALP EEG USING CANONICAL CORRELATION ANALYSIS BASED METHOD

Eye blink artifact, the main contamination in electroencephalography (EEG), brings serious problems for the analysis of EEG data. In this paper, an online method for eye blink artifact removal is presented. Canonical correlation analysis (CCA) is used to decompose the recorded signals containing several-channel EEG and one-channel vertical electrooculography (EOG). The identification of the artifactual component is fully automatically implemented based on evaluating the similarity between the reference EOG and decomposed CCA components. This method was compared with an independent component analysis based technique on a synthetic data set and achieved comparable performance for removing eye blink artifact. Moreover, the CCA based method is less time-consuming. The proposed method was finally implemented with Labview for removing eye blink artifact in online test. The online experiment results show that the proposed method could fulfill the identification and suppression of eye blink artifact from contaminated EEG in real-time.

Direction of selective attention modulates direct current (DC) brain potentials

Event Abstract Back to Event Direction of selective attention modulates direct current (DC) brain potentials Michael Trimmel1*, Julia Hintermayr1 and Karin Trimmel1 1 Medical University Vienna, Austria Facilitation of relevant information and inhibition of non-relevant stimuli are basic mechanisms of selective attention. They were investigated by the manipulation of the direction of attention by means of externally (intake of information) versus internally (rejection of environmental stimuli) directed attention. This study investigated effects of intake and of rejection tasks on brain direct current (DC) potential shifts, which are discussed as a sign of cortical activation/inhibition. It was hypothesized that rejection tasks are associated with more positive DC potential changes compared to intake tasks as an expression of cortical inhibition. Attention tasks consisted of a figural and a verbal task to take into account modality effects. Based on a 2 (Direction of Attention; intake vs. rejection)  2 (Modality; figural vs. verbal)  9 (Recording Location)  3 (Time on Task; 30-s blocks) repeated measures ANOVA design, DC potential shifts were analyzed at frontal (F3, Fz, F4), central (C3, Cz, C4), and parietal (P3, Pz, P4) locations. Forty-eight test persons performed 4 attention tasks: Intake figural (viewing and memorizing pictures), Intake verbal (Listening to and memorizing a text), Reject figural (completing figures in mind), and Reject verbal (creating words), all of a duration of 90 sec with a balanced order across test persons. Additionally, vertical EOG and skin potential were recorded to control for confounding factors. Rejection tasks were associated with more positive DC potential changes compared to intake tasks, this effect was independent of modality and recording location. Positive DC potential shifts during the rejection tasks, which are discussed as a sign of cortical inhibition, are suggested to be related to filtering out non task-relevant information. Keywords: Cognition, DC brain potentials Conference: XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011. Presentation Type: Poster Presentation Topic: Poster Sessions: Neurophysiology of Cognition and Attention Citation: Trimmel M, Hintermayr J and Trimmel K (2011). Direction of selective attention modulates direct current (DC) brain potentials. Conference Abstract: XI International Conference on Cognitive Neuroscience (ICON XI). doi: 10.3389/conf.fnhum.2011.207.00436 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 24 Nov 2011; Published Online: 28 Nov 2011. * Correspondence: Dr. Michael Trimmel, Medical University Vienna, Vienna, Austria, michael.trimmel@univie.ac.at Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Michael Trimmel Julia Hintermayr Karin Trimmel Google Michael Trimmel Julia Hintermayr Karin Trimmel Google Scholar Michael Trimmel Julia Hintermayr Karin Trimmel PubMed Michael Trimmel Julia Hintermayr Karin Trimmel Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Design of a Novel Efficient Human–Computer Interface: An Electrooculagram Based Virtual Keyboard

The aim of this paper is to present the design and application of an electrooculogram (EOG) based on an efficient human-computer interface (HCI). Establishing an alternative channel without speaking and hand movements is important in increasing the quality of life for the handicapped. EOG-based systems are more efficient than electroencephalogram (EEG)-based systems in some cases. By using a realized virtual keyboard, it is possible to notify in writing the needs of the patient in a relatively short time. Considering the biopotential measurement pitfalls, the novel EOG-based HCI system allows people to successfully communicate with their environment by using only eye movements. Classifying horizontal and vertical EOG channel signals in an efficient interface is realized in this study. The new system is microcontroller based, with a common-mode rejection ratio of 88 dB, an electronic noise of 0.6 μV (p-p), and a sampling rate of 176 Hz. The nearest neighborhood algorithm is used to classify the signals, and the classification performance is 95%. The novel EOG-based HCI system allows people to successfully and economically communicate with their environment by using only eye movements.

Eye-tracking with MEG

Event Abstract Back to Event Eye-tracking with MEG Markus Bauer1*, Gareth Barnes1, Christian Kluge2 and Jon Driver3 1 University College London, United Kingdom 2 Otto-von-Guericke University, Department of Neurology, Germany 3 University College London, Wellcome Trust Centre for Neuroimaging, Institute of Neurology, United Kingdom We compared optical and electrophysiological measures for estimating eye-position and saccade-direction and -extent from simultaneous measurement of magnetoencephalography (MEG), bipolar electrooculogram (EOG) and optical (infrared) eye-tracking. A standard saccade-/gaze-calibration task was used to evaluate the absolute and comparative precision of each measure. In the constrained MEG environment, EOG and especially MEG itself were usually superior for estimating horizontal saccade-extent compared to the optical eyetracker. For vertical saccades EOG was worst while MEG often performed comparably to the optical eyetracker. For static gaze position (rather than deviations from this), the optical eyetracker proved essential due to drift in all other signals. In conclusion, saccade-direction and saccade-extent can reliably be measured from MEG and/or EOG datasets without an optical eyetracker, provided a standard gaze-calibration procedure is implemented. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: Instrumentation and Multi-modal Integrations: MEG, Low-field MRI,EEG, fMRI,TMS,NIRS Citation: Bauer M, Barnes G, Kluge C and Driver J (2010). Eye-tracking with MEG. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00438 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 12 Apr 2010; Published Online: 12 Apr 2010. * Correspondence: Markus Bauer, University College London, London, United Kingdom, markus.bauer@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Markus Bauer Gareth Barnes Christian Kluge Jon Driver Google Markus Bauer Gareth Barnes Christian Kluge Jon Driver Google Scholar Markus Bauer Gareth Barnes Christian Kluge Jon Driver PubMed Markus Bauer Gareth Barnes Christian Kluge Jon Driver Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Real-time estimation system of the gaze position based on an electrooculogram

This article describes an online eye-tracking method based on an electrooculogram (EOG) to estimate gaze position. The objective is to use a biomedical signal EOG as the input of a human-machine interface for both disabled and healthy people. In this study, features of horizontal and vertical EOG signals were extracted to estimate the gaze position. Compensation for time-shift and nonlinearity were applied to improve the performance of the estimation. The estimated locus of the moving eye was compared with the locus of the target, and the deviation was about 3 cm. The results can be applied in some raw tracking fields, such as online communication, EOG-based pointers, and so on.

Diurnal variation of spontaneous eye blink rate in the elderly and its relationships with sleepiness and arousal

Sleep-wake rhythms in the elderly are deeply modified compared to young subjects, irrespective of physical or mental illnesses. However, still controversial are the results about age-related circadian variations of sleepiness levels. The objective of this study is to investigate the profile of diurnal sleepiness in healthy elderly subjects through subjective scales and by measuring spontaneous eye-blink rate (BR). In fact, we have previously found that BR, a reliable and non-invasive peripheral measure of central dopamine activity, increases in the young at times when subjective sleepiness is increased. Twelve healthy elderly volunteers (F=9, M=3, age range 64–79) participated in the experiment. At four times during the day (10a.m., 1.30p.m., 5p.m., 8.30p.m.), Karolinska sleepiness scale and a visual analogue scale for mood were administered to the subjects and BR was measured through vertical EOG. Alpha EEG power was used as objective measure of sleepiness. Sleepiness significantly changes across the day; according to post hoc contrasts, this is due to more sleepiness at 5p.m. Future research should be aimed at clarifying whether this peak is related to phase-advanced core body temperature in elderly people. Differently from the young, no significant differences were found in BR across the day, suggesting that an age-related modification of dopaminergic arousal mechanisms counteracting the rising sleep drive should be further explored.

Method of Menu Selection by Gaze Movement Using AC EOG Signals

A method to detect the direction and the distance of voluntary eye gaze movement from EOG (electrooculogram) signals was proposed and tested. In this method, AC-amplified vertical and horizontal transient EOG signals were classified into 8-class directions and 2-class distances of voluntary eye gaze movements. A horizontal and a vertical EOGs during eye gaze movement at each sampling time were treated as a two-dimensional vector, and the center of gravity of the sample vectors whose norms were more than 80% of the maximum norm was used as a feature vector to be classified. By the classification using the k-nearest neighbor algorithm, it was shown that the averaged correct detection rates on each subject were 98.9%, 98.7%, 94.4%, respectively. This method can avoid strict EOG-based eye tracking which requires DC amplification of very small signal. It would be useful to develop robust human interfacing systems based on menu selection for severely paralyzed patients.