Dynamic Random-dot Stereograms Research Articles

Temporal mechanisms in frontoparallel stereomotion revealed by individual differences analysis.

Masking experiments, using vertical and horizontal sinusoidal depth corrugations, have suggested the existence of more than two spatial-frequency disparity mechanisms. This result was confirmed through an individual differences approach. Here, using factor analytic techniques, we want to investigate the existence of independent temporal mechanisms in frontoparallel stereoscopic (cyclopean) motion. To construct stereomotion, we used sinusoidal depth corrugations obtained with dynamic random-dot stereograms. Thus, no luminance motion was present monocularly. We measured disparity thresholds for drifting vertical (up-down) and horizontal (left-right) sinusoidal corrugations of 0.4 cyc/deg at 0.25, 0.5, 1, 2, 4, 6, and 8Hz. In total, we tested 34 participants. Results showed a small orientation anisotropy with lower thresholds for horizontal corrugations. Disparity thresholds as a function of temporal frequency were almost constant from 0.25 up to 1Hz, and then they increased monotonically. Principal component analysis uncovered two significant factors for vertical and two for horizontal corrugations. Varimax rotation showed that one factor loaded from 0.25 to 1-2Hz and a second factor from 2 to 4 to 8Hz. Direct Oblimin rotation indicated a moderate intercorrelation of both factors. Our results suggest the possible existence of two somewhat interdependent temporal mechanisms involved in frontoparallel stereomotion.

Two Disparity Channels in Human Visual Cortex With Different Contrast and Blur Sensitivity.

Our goal is to describe the contrast and blur sensitivity of multiple horizontal disparity subsystems and to relate them to the contrast and spatial sensitivities of their monocular inputs. Steady-state visual evoked potential (SSVEP) amplitudes were recorded in response to dynamic random dot stereograms (DRDSs) alternating at 2 Hz between zero disparity and varying magnitudes of crossed disparity for disparity plane and disparity grating stimuli. Half-image contrasts ranged between 2.5% and 80% and over a range of Gaussian blurs from 1.4 to 12 arcmin. Separate experiments measured contrast and blur sensitivity for the monocular half-images. The first and second harmonics disparity responses were maximal for disparity gratings and for the disparity plane condition, respectively. The first harmonic of the disparity grating response was more affected by both contrast and blur than was the second harmonic of the disparity plane response, which had higher contrast sensitivity than the first harmonic. The corrugation frequency, contrast, and blur tuning of the first harmonic suggest that it reflects activity of neurons tuned to higher luminance spatial frequencies that are selective for relative disparity, whereas the second harmonic reflects the activity of neurons sensitive to absolute disparity that are driven by low monocular spatial frequencies. SSVEPs to DRDSs provide two objective neural measures of disparity processing, the first harmonic-whose stimulus preferences are similar to those of behavioral stereoacuity-and the second harmonic that represents an independent disparity-specific but not necessarily stereoscopic mechanism.

Artificial intelligence-based screening for amblyopia and its risk factors: comparison with four classic stereovision tests.

The development of costs-effective and sensitive screening solutions to prevent amblyopia and identify its risk factors (strabismus, refractive problems or mixed) is a significant priority of pediatric ophthalmology. The main objective of our study was to compare the classification performance of various vision screening tests, including classic, stereoacuity-based tests (Lang II, TNO, Stereo Fly, and Frisby), and non-stereoacuity-based, low-density static, dynamic, and noisy anaglyphic random dot stereograms. We determined whether the combination of non-stereoacuity-based tests integrated in the simplest artificial intelligence (AI) model could be an alternative method for vision screening. Our study, conducted in Spain and Hungary, is a non-experimental, cross-sectional diagnostic test assessment focused on pediatric eye conditions. Using convenience sampling, we enrolled 423 children aged 3.6-14 years, diagnosed with amblyopia, strabismus, or refractive errors, and compared them to age-matched emmetropic controls. Comprehensive pediatric ophthalmologic examinations ascertained diagnoses. Participants used filter glasses for stereovision tests and red-green goggles for an AI-based test over their prescribed glasses. Sensitivity, specificity, and the area under the ROC curve (AUC) were our metrics, with sensitivity being the primary endpoint. AUCs were analyzed using DeLong's method, and binary classifications (pathologic vs. normal) were evaluated using McNemar's matched pair and Fisher's nonparametric tests. Four non-overlapping groups were studied: (1) amblyopia (n = 46), (2) amblyogenic (n = 55), (3) non-amblyogenic (n = 128), and (4) emmetropic (n = 194), and a fifth group that was a combination of the amblyopia and amblyogenic groups. Based on AUCs, the AI combination of non-stereoacuity-based tests showed significantly better performance 0.908, 95% CI: (0.829-0.958) for detecting amblyopia and its risk factors than most classical tests: Lang II: 0.704, (0.648-0.755), Stereo Fly: 0.780, (0.714-0.837), Frisby: 0.754 (0.688-0.812), p < 0.02, n = 91, DeLong's method). At the optimum ROC point, McNemar's test indicated significantly higher sensitivity in accord with AUCs. Moreover, the AI solution had significantly higher sensitivity than TNO (p = 0.046, N = 134, Fisher's test), as well, while the specificity did not differ. The combination of multiple tests utilizing anaglyphic random dot stereograms with varying parameters (density, noise, dynamism) in AI leads to the most advanced and sensitive screening test for identifying amblyopia and amblyogenic conditions compared to all the other tests studied.

Electroencephalography recognition based on encephalic region and temporal sequence transformer

Stereoscopic vision is the key to good motor control and accurate cognition, and its formation is closely related to brain control. The early methods of measuring stereoscopic vision rely on the subject’s judgment, which might be influenced by inadvertent misjudgments. To solve this problem, we collected the Electroencephalography (EEG) of subjects watching dynamic random dot stereogram for stereogram recognition. To analyze stereogram EEG signals, this paper proposed a transformer-based encephalic region temporal sequence analysis network. Inspired by the concept of brain regions, this network designs an encephalic region Transformer module to capture global spatial features in each brain region and among the whole brain regions. Based on the spatial features of electrodes in different brain regions, the global spatial dependence of all electrodes can be further obtained. Then, the temporal sequence Transformer module is adopted to learn the global temporal EEG features. Finally, we utilize the spatial-temporal multi-scale convolution module to extract advanced spatial and temporal fusion features for recognition. The simulation results on two public EEG datasets illustrate the excellent classification performance of the proposed model, which is better than 9 existing comparison models in EEG recognition.

The eRDS v6 Stereotest and the Vivid Vision Stereo Test: Two New Tests of Stereoscopic Vision

To describe two new stereoacuity tests: the eRDS v6 stereotest, a global dynamic random dot stereogram (dRDS) test, and the Vivid Vision Stereo Test version 2 (VV), a local or "contour" stereotest for virtual reality (VR) headsets; and to evaluate the tests' reliability, validity compared to a dRDS standard, and learning effects. Sixty-four subjects passed a battery of stereotests, including perceiving depth from RDS. Validity was evaluated relative to a tablet-based dRDS reference test, ASTEROID. Reliability and learning effects were assessed over six sessions. eRDS v6 was effective at measuring small thresholds (<10 arcsec) and had a moderate correlation (0.48) with ASTEROID. Across the six sessions, test-retest reliability was good, varying from 0.84 to 0.91, but learning occurred across the first three sessions. VV did not measure stereoacuities below 15 arcsec. It had a weak correlation with ASTEROID (0.27), and test-retest reliability was poor to moderate, varying from 0.35 to 0.74; however, no learning occurred between sessions. eRDS v6 is precise and reliable but shows learning effects. If repeated three times at baseline, this test is well suited as an outcome measure for testing interventions. VV is less precise, but it is easy and rapid and shows no learning. It may be useful for testing interventions in patients who have no global stereopsis. eRDS v6 is well suited as an outcome measure to evaluate treatments that improve adult stereodepth perception. VV can be considered for screening patient with compromised stereovision.

Electroencephalography Study of Frontal Lobe Evoked by Dynamic Random-Dot Stereogram.

PurposeThe purpose of this study was to investigate the cortical electrical activity and electroencephalography (EEG) features of the frontal lobe evoked by dynamic random dot stereogram (DRDS) and to probe the functional connectivity (FC) between the frontal lobe and occipital lobe when processing 3D perception based on the binocular disparity.MethodsThe EEG experiment involved 14 healthy adults with normal stereopsis (<60″) and normal corrected visual acuity (20/20). The Neuroscan system and 32-channel EEG cap were used to record EEG signals based on the DRDS stimuli. The maximum energies of 3 frequency bands (theta-/alpha- /beta-wave) from 13 interesting channels (FP1, FP2, F7, F3, FZ, F4, F8, FC3, FCZ, FC4, O1, OZ, and O2) located in the frontal and occipital lobes were calculated and analyzed. The FC between any two electrodes from the frontal and occipital lobes was calculated based on the Phase lag index (PLI).ResultsThe maximum powers of theta- and alpha-waves in most channels of the frontal and occipital lobes were significantly increased (P < 0.05) when the depth perception was evoked by DRDS above the threshold, compared with that without stereo vision. The changes in the maximum powers of both theta- and alpha-waves were significantly different among the 13 electrodes (P = 0.0004 and 0.0015, respectively). Tukey's multiple comparisons showed that the changes in the maximum powers of theta-wave were significantly different in F8 vs. O1, F8 vs. OZ, and F4 vs. O1 (P = 0.0186, 0.0444, and 0.0412, respectively). Moreover, the changes in the maximum powers of alpha-waves were significantly different in FP1 vs. O1 (P = 0.0182). The FCs of theta-waves between the frontal channels and the occipital channels were significantly enhanced when processing the depth perception, compared with those without stereopsis. There was no significant change in the FCs of the alpha-waves when having 3D perception except for FC between F8 and O1 and FC between F8 and OZ.ConclusionsThe cortical electrical activity in the frontal lobe and the functional connectivity between the frontal lobe and the occipital lobe increase when participating in the processing binocular disparity and obtaining 3D perception. Theta-waves in the frontal lobe may be crucial in the stereo vision.

Dynamics of absolute and relative disparity processing in human visual cortex

Cortical processing of binocular disparity is believed to begin in V1 where cells are sensitive to absolute disparity, followed by the extraction of relative disparity in higher visual areas. While much is known about the cortical distribution and spatial tuning of disparity-selective neurons, the relationship between their spatial and temporal properties is less well understood. Here, we use steady-state Visual Evoked Potentials and dynamic random dot stereograms to characterize the temporal dynamics of spatial mechanisms in human visual cortex that are primarily sensitive to either absolute or relative disparity. Stereograms alternated between disparate and non-disparate states at 2 Hz. By varying the disparity-defined spatial frequency content of the stereograms from a planar surface to corrugated ones, we biased responses towards absolute vs. relative disparities. Reliable Components Analysis was used to derive two dominant sources from the 128 channel EEG records. The first component (RC1) was maximal over the occipital pole. In RC1, first harmonic responses were sustained, tuned for corrugation frequency, and sensitive to the presence of disparity references, consistent with prior psychophysical sensitivity measurements. By contrast, the second harmonic, associated with transient processing, was not spatially tuned and was indifferent to references, consistent with it being generated by an absolute disparity mechanism. Thus, our results reveal a duplex coding strategy in the disparity domain, where relative disparities are computed via sustained mechanisms and absolute disparities are computed via transient mechanisms.

Multiscale Temporal Self-Attention and Dynamical Graph Convolution Hybrid Network for EEG-Based Stereogram Recognition.

Stereopsis is the ability of human beings to get the 3D perception on real scenarios. The conventional stereopsis measurement is based on subjective judgment for stereograms, leading to be easily affected by personal consciousness. To alleviate the issue, in this paper, the EEG signals evoked by dynamic random dot stereograms (DRDS) are collected for stereogram recognition, which can help the ophthalmologists diagnose strabismus patients even without real-time communication. To classify the collected Electroencephalography (EEG) signals, a novel multi-scale temporal self-attention and dynamical graph convolution hybrid network (MTS-DGCHN) is proposed, including multi-scale temporal self-attention module, dynamical graph convolution module and classification module. Firstly, the multi-scale temporal self-attention module is employed to learn time continuity information, where the temporal self-attention block is designed to highlight the global importance of each time segments in one EEG trial, and the multi-scale convolution block is developed to further extract advanced temporal features in multiple receptive fields. Meanwhile, the dynamical graph convolution module is utilized to capture spatial functional relationships between different EEG electrodes, in which the adjacency matrix of each GCN layer is adaptively tuned to explore the optimal intrinsic relationship. Finally, the temporal and spatial features are fed into the classification module to obtain prediction results. Extensive experiments are conducted on collected datasets i.e., SRDA and SRDB, and the results demonstrate the proposed MTS-DGCHN achieves outstanding classification performance compared with the other methods. The datasets are available at https://github.com/YANGeeg/TJU-SRD-datasets and the code is at https://github.com/YANGeeg/MTS-DGCHN.

(Invited) Understanding Dynamic RDS(on) in GaN Devices

In this article, we expand on the wide body of experimental and theoretical knowledge of charge trapping phenomena in eGaN devices that cause dynamic on-resistance shifting (dRDS(on)). In previous publications, we advanced a first-principles model to explain this effect, based on the physics of hot carrier scattering. The model led to a set of equations to predict dRDS(on) under different operating conditions of drain voltage, junction temperature, switching frequency and current. In addition, the model has led to iterative improvements in device design, culminating in the near elimination of dynamic on-resistance effects in eGaN devices when operated within datasheet limits.Several groups have studied RDS(on) shifts in GaN FETs that result from single switching waveforms such as in the double-pulse test. EPC’s approach has been to quantify RDS(on) over relatively long time intervals, ranging from billions to trillions of switching transitions. This long-term data is more relevant to practical applications. Furthermore, the resistance rise versus time can be fit to a physics-based model equation. Using these fits, dRDS(on) can be projected out to years of continuous operation, providing an invaluable tool for users to assess lifetime against their mission profile.An example of this kind of long-term data and model fits is provided in Figure 1. The data was taken on the EPC2045 (5th generation 100V eGaN FET). The graph on the left shows the evolution of resistance versus time at different switching voltages (all at a junction temperature of 75 °C). Note that for operation below (and including) the datasheet maximum, dRDS(on) is negligible, even when projected out to 10 years of continuous operation. When operated above datasheet VDSmax, RDS(on) growth is observed, and the evolution is in good agreement with the model. The graph on the right shows data at 150V and two different temperatures. The trapping phenomenon is seen to have a negative temperature activation, whereby on-resistance increases faster at lower temperature. This counter-intuitive result is consistent with the physics of hot carrier scattering, because an electron can travel further between scattering events at lower temperature and therefore gain greater kinetic energy in a given electric field. These highly energetic electrons scatter into unintended regions in the device, where they trap and degrade on-resistance.In this work, we expand on previous results with the following new data and analyses: Long-term dynamic RDS(on) data and model fits for 5th generation 100V and 200V eGaN FETs at various temperatures and voltages extending well beyond datasheet limits.High speed measurements of RDS(on) less than 100 ns after a switching transition, seeking out possible trap states that recover on short timescales but may nonetheless increase switching losses. To within our measurement resolution, we find that eGaN FETs switch to a low resistance state instantly, with no evidence for such “fast” dynamic RDS(on) A comparison of hard-switching versus soft-switching. In contrast to some other GaN technologies, we find that eGaN is essentially immune to dRDS(on) under soft-switching conditions, consistent with the underlying physics of hot carrier scattering.A comparison of inductive versus resistive hard-switching. Despite the different loci in current-voltage space traversed during these two types of switches, we find the impact on dRDS(on) to be minor. This result affirms that the simpler resistive hard-switching circuit is an equally valid method to characterize dRDS(on) in eGaN.Effect of switching speed, with transitions ranging from 1-50 ns.Effect of third quadrant operation. Some GaN technologies suffer from adverse trapping effects when operated in reverse conduction, as can occur during dead time or synchronous operation in a dc-dc converter. We see no evidence for these effects in eGaN. Figure 1

(Invited) Understanding Dynamic RDS(on) in GaN Devices

In this article, we expand on the wide body of experimental and theoretical knowledge of charge trapping phenomena in eGaN devices that cause dynamic on-resistance shifting. We describe in detail a flexible test circuit used to measure RDS(on) in real time as devices are switched in different modes. Using an ultra-fast synchronized clipper FET, we obtain accurate measurements as soon as ~25 ns after the turn-on transition, showing that eGaN FETs switch to a low resistance state immediately without any lingering de-trapping effects that are observed in other GaN technologies. Comparing hard-switching of resistive versus inductive loads, we find very low dynamic RDS(on) shifting in either case when parts are operated at or below datasheet VDSmax. For parts operated well above datasheet limits, we measure long-term RDS(on) growth for 100V and 200V devices, and find the data is in good agreement with our hot carrier trapping model.

ASTEROID stereotest v1.0: lower stereo thresholds using smaller, denser and faster dots.

In 2019, we described ASTEROID, a new stereotest run on a 3D tablet computer which involves a four-alternative disparity detection task on a dynamic random-dot stereogram. Stereo thresholds measured with ASTEROID were well correlated with, but systematically higher than (by a factor of around 1.5), thresholds measured with previous laboratory stereotests or the Randot Preschool clinical stereotest. We speculated that this might be due to the relatively large, sparse dots used in ASTEROID v0.9. Here, we introduce and test the stereo thresholds and test-repeatability of the new ASTEROID v1.0, which uses precomputed images to allow stereograms made up of much smaller, denser dots. Stereo thresholds and test/retest repeatability were tested and compared between the old and new versions of ASTEROID (n=75) and the Randot Circles (n=31) stereotest, in healthy young adults. Thresholds on ASTEROID v1.0 are lower (better) than on ASTEROID v0.9 by a factor of 1.4, and do not differ significantly from thresholds on the Randot Circles. Thresholds were roughly log-normally distributed with a mean of 1.54 log10 arcsec (35 arcsec) on ASTEROID v1.0 compared to 1.70 log10 arcsec (50 arcsec) on ASTEROID v0.9. The standard deviation between observers was the same for both versions, 0.32 log10 arcsec, corresponding to a factor of 2 above and below the mean. There was no difference between the versions in their test/retest repeatability, with 95% coefficient of repeatability=0.46 log10 arcsec (a factor of 2.9 or 1.5 octaves) and a Pearson correlation of 0.8 (comparable to other clinical stereotests). The poorer stereo thresholds previously reported with ASTEROID v0.9 appear to have been due to the relatively large, coarse dots and low density used, rather than to some other aspect of the technology. Employing the small dots and high density used in ASTEROID v1.0, thresholds and test/retest repeatability are similar to other clinical stereotests.

Power Loss Characterization and Modeling for GaN-Based Hard-Switching Half-Bridges Considering Dynamic on-State Resistance

Gallium nitride enhancement-mode high electron mobility transistors (GaN E-HEMTs) can achieve high frequency and high efficiency due to its excellent switching performance compared with conventional Si transistors. Nevertheless, GaN HEMTs exhibit a more pronounced dynamic ON-state resistance R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DS(ON)</sub> than silicon transistors. The variation of R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DS(ON)</sub> is caused by both the static R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DS(ON)</sub> due to junction temperature rise and the dynamic RDS(ON) due to the electron trapping. Without a careful decoupling analysis, it is difficult to calculate and model the dynamic R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DS(ON)</sub> portion. This article introduces a comprehensive approach of dynamic R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DS(ON)</sub> evaluation comprising four techniques: 1) a clamping circuit for both the hard-switching (HS) device and synchronous rectification (SR) device; 2) a junction temperature monitoring technique; 3) control of both the pulse test and soak time; and 4) continuous operation of device under test. Based on the dynamic RDS(ON) test results, a new model of the RDS(ON) variation is developed where two coefficients k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Tj</sub> and k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dR</sub> are defined to model the contribution of the heating effect and the impact of the trapping effect, respectively. The RDS(ON) model is validated by the comparison between the calculated and measured junction temperatures of a 650-V/30-A GaN-based half-bridge. Furthermore, a detailed loss breakdown analysis is conducted for the GaN-based HS half-bridge. The results show that the switching losses, E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</sub> and E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OFF</sub> , are the dominant loss factors with high switching frequency. At last, the possible efficiency improvements are also discussed in detail.

Calibration of random dot stereograms and correlograms free of monocular cues.

Dynamic random dot stereograms (DRDSs) and correlograms (DRDCs) are cyclopean stimuli containing binocular depth cues that are ideally, invisible by one eye alone. Thus, they are important tools in assessing stereoscopic function in experimental or ophthalmological diagnostic settings. However, widely used filter-based three-dimensional display technologies often cannot guarantee complete separation of the images intended for the two eyes. Without proper calibration, this may result in unwanted monocular cues in DRDSs and DRDCs, which may bias scientific or diagnostic results. Here, we use a simple mathematical model describing the relationship of digital video values and average luminance and dot contrast in the two eyes. We present an optimization algorithm that provides the set of digital video values that achieve minimal crosstalk at user-defined average luminance and dot contrast for both eyes based on photometric characteristics of a given display. We demonstrated in a psychophysical experiment with color normal participants that this solution is optimal because monocular cues were not detectable at either the calculated or the experimentally measured optima. We also explored the error by which a range of luminance and contrast combinations can be implemented. Although we used a specific monitor and red-green glasses as an example, our method can be easily applied for other filter based three-dimensional systems. This approach is useful for designing psychophysical experiments using cyclopean stimuli for a specific display.

Analysis and classification of hybrid EEG features based on the depth DRDS videos

BackgroundStereo vision cognition is a crucial advanced function of human beings, and stereoscopic acuity is an important index to detect stereo vision. Electroencephalograph (EEG) is an effective method of detection. Therefore, it has great significance to research the relationship between stereoscopic acuity and EEG signals for the development of 3D technology. New methodThis paper proposes a multi-channel selection sparse time window common spatial group (MCS-STWCSG) multi-classification method. Firstly, a channel selection method based on improved common spatial pattern- (CSP-) rank is applied to select optimal channels to reduce redundant signal. Secondly, based on the one vs. one (OVO) computational model, we extend traditional CSP to the common spatial group (CSG) to implement three-classification. Finally, this paper optimizes time-frequency characteristics and hybrid signal features by sparse regression and utilizes a support vector machine (SVM) with radial basis function (RBF) kernel to identify depth dynamic random dot stereogram (DRDS) video tasks. ResultsThe selected channels are all located in and near the occipital region and time-frequency characteristics can acquire better classification results compared with frequency characteristics. The highest classification result can reach 94.67%. Comparison with existing methodsThe MCS-STWCSG multi-classification method optimizes features from multiple aspects and its performance is obviously better than other methods for hybrid EEG signals of depth DRDS. ConclusionsChannel selection and time-frequency segmentation for feature extraction and classification algorithm of EEG signals can increase the classification accuracy. It proves the feasibility and accuracy of the proposed method.

EEG based dynamic RDS recognition with frequency domain selection and bispectrum feature optimization

BackgroundStereopsis plays a vital role in many aspects of human daily life. Random-dot stereogram (RDS) is often used to detect stereoacuity and perform research on visual cognition. Electroencephalogram (EEG) is one of the commonly adopted visual cognition techniques due to its noninvasive collection. New methodIn this study, a methodology named WPT-BED based on wavelet packet transform (WPT) and bispectral eigenvalues of differential signals (BED) is proposed, which can classify the three-pattern EEG signals evoked by dynamic RDS (DRDS). Specifically, the signals are decomposed into different frequency bands by WPT. The appropriate sub-bands are selected for reconstruction. Finally, the optimized bispectrum features are extracted for classification to achieve higher accuracy. ResultsThe classification performance of the proposed method in different periods of signal processing are investigated. The method WPT-BED has the highest classification accuracy 84.38%, and the average classification accuracy is 73.98%. The active channels with higher accuracy are focused on the visual pathway in the human cerebral cortex. Comparison with existing methodsComparison with other methods for EEG signals classification is performed to identify the effectiveness of the proposed methodology. ConclusionsThe proposed methodology can effectively distinguish the EEG signals evoked by DRDS. It demonstrates the feasibility of DRDS recognition based on EEG.

ASTEROID: A New Clinical Stereotest on an Autostereo 3D Tablet.

PurposeTo describe a new stereotest in the form of a game on an autostereoscopic tablet computer designed to be suitable for use in the eye clinic and present data on its reliability and the distribution of stereo thresholds in adults.MethodsTest stimuli were four dynamic random-dot stereograms, one of which contained a disparate target. Feedback was given after each trial presentation. A Bayesian adaptive staircase adjusted target disparity. Threshold was estimated from the mean of the posterior distribution after 20 responses. Viewing distance was monitored via a forehead sticker viewed by the tablet's front camera, and screen parallax was adjusted dynamically so as to achieve the desired retinal disparity.ResultsThe tablet must be viewed at a distance of greater than ∼35 cm to produce a good depth percept. Log thresholds were roughly normally distributed with a mean of 1.75 log10 arcsec = 56 arcsec and SD of 0.34 log10 arcsec = a factor of 2.2. The standard deviation agrees with previous studies, but ASTEROID thresholds are approximately 1.5 times higher than a similar stereotest on stereoscopic 3D TV or on Randot Preschool stereotests. Pearson correlation between successive tests in same observer was 0.80. Bland-Altman 95% limits of reliability were ±0.64 log10 arcsec = a factor of 4.3, corresponding to an SD of 0.32 log10 arcsec on individual threshold estimates. This is similar to other stereotests and close to the statistical limit for 20 responses.ConclusionsASTEROID is reliable, easy, and portable and thus well-suited for clinical stereoacuity measurements.Translational RelevanceNew 3D digital technology means that research-quality psychophysical measurement of stereoacuity is now feasible in the clinic.

Infants perceive two-dimensional shape from horizontal disparity

Previous studies observed that responsiveness to horizontal disparity as such emerges at approximately 2 months of age. Moreover, 3- to 4-month-old infants utilize stereoscopic information to perceive object variations in depth. The present study investigated infants’ ability to respond to crossed horizontal disparity information that defines two-dimensional shape. Infants 4 and 5 months of age were habituated to either a cross or the outline of a square. During the posthabituation period, they were presented with both shapes. The stimuli were dynamic random dot stereograms shown on an autostereoscopic monitor. The participants 5 but not 4 months of age displayed significant novelty preferences for the unfamiliar shape during the posthabituation period. Five-month-old infants are hence sensitive to horizontal disparity information that specifies shape.

On-State Voltage Measurement of Fast Switching Power Semiconductors

The on-state resistance R ds,on is a key characteristic of unipolar power semiconductors and its value depends on the operating conditions, e.g. junction temperature, conducted current and applied gate voltage. Hence, the exact determination of the R ds,on value cannot rely on datasheet information and requires the measurement of current and on-state voltage during operation. Besides the determination of the conduction losses, the on-state voltage measurement enables dynamic R ds,on analysis, device temperature estimation, condition monitoring and consequently time-to-failure prediction. However, in contrast to a switch current measurement, several challenges arise in the design of an on-state voltage measurement circuit (OVMC), i.e. high measurement accuracy (mV-range) during on-state, high blocking voltage capability (kV-range) during off-state and fast dynamic response (ns-range) during switching transitions are demanded. Different OVMC concepts are known from IGBT applications, however, the more severe requirements introduced from the high switching frequency and low OV characterizing the operation of fast switching power semiconductors, prevent their usage. Off-the-shelf products hardly satisfy the mentioned specifications, whereas the performance of state-of-the-art OVM research prototypes require further investigations and/or improvements. With this aim, an innovative OVMC concept is designed, analyzed, calibrated and tested in this paper. Furthermore, the conduction losses of different power semiconductors are measured as function of their operating conditions to validate the performance and highlight the potential of the proposed OVMC.

Simple reaction times to cyclopean stimuli reveal that the binocular system is tuned to react faster to near than to far objects.

Binocular depth perception is an important mechanism to segregate the visual scene for mapping relevant objects in our environment. Convergent evidence from psychophysical and neurophysiological studies have revealed asymmetries between the processing of near (crossed) and far (uncrossed) binocular disparities. The aim of the present study was to test if near or far objects are processed faster and with higher contrast sensitivity in the visual system. We therefore measured the relationship between binocular disparity and simple reaction time (RT) as well as contrast gain based on the contrast-RT function in young healthy adults. RTs were measured to suddenly appearing cyclopean target stimuli, which were checkerboard patterns encoded by depth in dynamic random dot stereograms (DRDS). The DRDS technique allowed us to selectively study the stereoscopic processing system by eliminating all monocular cues. The results showed that disparity and contrast had significant effects on RTs. RTs as a function of disparity followed a U-shaped tuning curve indicating an optimum at around 15 arc min, where RTs were minimal. Surprisingly, the disparity tuning of RT was much less pronounced for far disparities. At the optimal disparity, we measured advantages of about 80 ms and 30 ms for near disparities at low (10%) and high (90%) contrasts, respectively. High contrast always reduced RTs as well as the disparity dependent differences. Furthermore, RT-based contrast gains were higher for near disparities in the range of disparities where RTs were the shortest. These results show that the sensitivity of the human visual system is biased for near versus far disparities and near stimuli can result in faster motor responses, probably because they bear higher biological relevance.

Assessment of Cyclofusion Capabilities of Normal Subjects with 3D Dynamic Random-Dot Stereograms

Evaluation of a new method for cyclofusion measurement. The maximal incyclofusion and excyclofusion tolerated of 20 normal subjects (15 females, mean age 36 ± 9.9 years) were measured by computer-generated dynamic random-dot stereograms (DRDS). Subjects had to detect the orientation of only binocularly visible Landolt C stimuli randomly presented with a 3-D monitor. Both eyes were separately stimulated with shutter glasses. The DRDS-pattern projected to the left and right eye were rotated in the opposite direction in 0.5° steps. In 10 subjects, cyclofusion measurements were repeated. Incylofusional amplitudes were between 2.5° and 6°, excyclofusional amplitudes measured between 3° and 5.5°. Mean incyclofusion was 3.71° (SD 0.82) and mean excyclofusion measured 4.24° (SD 0.73). Repeated measurements of incyclofusion and excyclofusion in the same subject demonstrated a difference of about 0.5° (0.55° for incyclofusion, 0.45° for excyclofusion). The DRDS Landolt C method provided a reliable assessment with good reproducibility of cyclofusion in healthy subjects with only binocularly perceivable objects. Our cyclofusional capabilities were slightly higher than those received with dissociating 2D measurements.