Person:

Luo, Gang

Aims. Increasing evidence shows that imbalanced suppressive drive prior to binocular combination may be the key factor in amblyopia. We described a novel binocular approach, interocular shift of visual attention (ISVA), for treatment of amblyopia in adult patients. Methods. Visual stimuli were presented anaglyphically on a computer screen. A square target resembling Landolt C had 2 openings, one in red and one in cyan color. Through blue-red goggles, each eye could only see one of the two openings. The patient was required to report the location of the opening presented to the amblyopic eye. It started at an opening size of 800 sec of arc, went up and down in 160 sec of arc step, and stopped when reaching the 5th reversals. Ten patients with anisometropic amblyopia older than age 14 (average age: 26.7) were recruited and received ISVA treatment for 6 weeks, with 2 training sessions per day. Results. Both Titmus stereopsis (z = −2.809, P = 0.005) and Random-dot stereopsis (z = −2.317, P = 0.018) were significantly improved. Average improvement in best corrected visual acuity (BCVA) was 0.74 line (t = 5.842, P < 0.001). Conclusions. The ISVA treatment may be effective in treating amblyopia and restoring stereoscopic function.

Most gaze tracking techniques estimate gaze points on screens, on scene images, or in confined spaces. Tracking of gaze in open-world coordinates, especially in walking situations, has rarely been addressed. We use a head-mounted eye tracker combined with two inertial measurement units (IMU) to track gaze orientation relative to the heading direction in outdoor walking. Head movements relative to the body are measured by the difference in output between the IMUs on the head and body trunk. The use of the IMU pair reduces the impact of environmental interference on each sensor. The system was tested in busy urban areas and allowed drift compensation for long (up to 18 min) gaze recording. Comparison with ground truth revealed an average error of 3.3° while walking straight segments. The range of gaze scanning in walking is frequently larger than the estimation error by about one order of magnitude. Our proposed method was also tested with real cases of natural walking and it was found to be suitable for the evaluation of gaze behaviors in outdoor environments.

Purpose Speed estimation of drivers’ own vehicles and other vehicles on the road is an important task for drivers and is also crucial to the roadway safety. The objective of the study was to examine the effects of multiple factors such as image scale, speed, road type, driving experience, and gender on the speed perception of drivers’ own vehicles. Methods: Thirty participants consisted of 17 males and 13 females, including 13 without driving experience. All participants estimated the driving speed of 192 5-second video clips, which were selected from naturalistic driving recordings. The recorded driving speeds were evenly distributed across the entire range from 5mph to 65mph. Half of the selected video clips were recorded on wide roads and another half were recorded on comparatively narrow roads. Video clips were played on a large screen, with each clip shown in one of 4 image scales (100%, 75%, 50%, and 38% of the actual field of view in the real world). Results: Speed estimates were most accurate for the smallest image size (38% of the actual field of view). As the image size increased, the driving speed was increasingly underestimated. Participants with driving experience accurately estimated the driving speed on both wide and narrow roads whereas those without driving experience had greater underestimates on wider roads. Speeds were most accurately estimated within the range 25-35mph, but the speeds slower than the range tend to be overestimated and the speeds faster than the range are more likely to be underestimated. While males and females showed the same pattern across speed groups, females have greater estimation errors at the highest and lowest speed groups. Participants without driving experience showed increasing underestimation of speed as driving speed increased whereas participants with driving experience primarily underestimated the highest speeds. Conclusions: The present study shows the effect of multidimensional influential factors on perceived vehicle speed from drivers’ perspective. The results also have implications for driving simulation scenario design, driving simulator setup, and the assessment of speed control in simulated and naturalistic environments.

Analyzing naturalistic driving behavior recorded with in-car cameras is an ecologically valid method for measuring driving errors, but it is time intensive and not easily applied on a large scale. This study validated a semi-automated, computerized method using archival naturalistic driving data collected for drivers with mild Alzheimer’s disease (AD; n = 44) and age-matched healthy controls (HC; n = 16). The computerized method flagged driving situations where safety concerns are most likely to occur (i.e., rapid stops, lane deviations, turns, and intersections). These driving epochs were manually reviewed and rated for error type and severity, if present. Ratings were made with a standardized scoring system adapted from DriveCam®. The top eight error types were applied as features to train a logistic model tree classifier to predict diagnostic group. The sensitivity and specificity were compared among the event-based method, on-road test, and composite ratings of two weeks of recorded driving. The logistic model derived from the event-based method had the best overall accuracy (91.7%) and sensitivity (97.7%) and high specificity (75.0%) compared to the other methods. Review of driving situations where risk is highest appears to be a sensitive data reduction method for detecting cognitive impairment associated driving behaviors and may be a more cost-effective method for analyzing large volumes of naturalistic data.

Gaze-contingent displays have been widely used in vision research and virtual reality applications. Due to data transmission, image processing, and display preparation, the time delay between the eye tracker and the monitor update may lead to a misalignment between the eye position and the image manipulation during eye movements. We propose a method to reduce the misalignment using a Taylor series to predict the saccadic eye movement. The proposed method was evaluated using two large datasets including 219,335 human saccades (collected with an EyeLink 1000 system, 95% range from 1° to 32°) and 21,844 monkey saccades (collected with a scleral search coil, 95% range from 1° to 9°). When assuming a 10-ms time delay, the prediction of saccade movements using the proposed method could reduce the misalignment greater than the state-of-the-art methods. The average error was about 0.93° for human saccades and 0.26° for monkey saccades. Our results suggest that this proposed saccade prediction method will create more accurate gaze-contingent displays.