Search Results (7)

The aim of our study was to test the application of a new vision training device, the EYE ROLL, for home-based eye movement training in athletes. Sixty-seven participants were randomly divided into three groups: a control group (no training); an eye movement training group with no device; and a group using the new EYE ROLL device. The results of 51 participants were used for statistical analyses after a 4-week period. Before and after the 4-week period, participants underwent the same assessment procedures: a comprehensive vision examination and saccadic eye movement recording. Before training, for both 10° and 5° stimuli, all subjects showed statistically significantly larger and faster rightward saccades compared to leftward saccades. After four weeks, the control group showed increased horizontal saccadic asymmetry and a decrease in leftward saccade amplitude. However, both velocities showed asymmetry in both visits. There were larger changes in saccadic parameters for leftward saccades, but no clear changes in saccadic response asymmetry after training. There were no consistent differences between the training groups. The EYE ROLL is a novel device that may serve as a substitute training tool for saccadic enhancement and may improve the symmetry of horizontal saccadic movements after four weeks of home-based training. Full article

The detection of the human mental fatigue state holds immense significance due to its direct impact on work efficiency, specifically in system operation control. Numerous approaches have been proposed to address the challenge of fatigue detection, aiming to identify signs of fatigue and alert the individual. This paper introduces an approach to human mental fatigue assessment based on the application of machine learning techniques to the video of a working operator. For validation purposes, the approach was applied to a dataset, “Human Fatigue Assessment Based on Video Data” (HFAVD) integrating video data with features computed by using our computer vision deep learning models. The incorporated features encompass head movements represented by Euler angles (roll, pitch, and yaw), vital signs (blood pressure, heart rate, oxygen saturation, and respiratory rate), and eye and mouth states (blinking and yawning). The integration of these features eliminates the need for the manual calculation or detection of these parameters, and it obviates the requirement for sensors and external devices, which are commonly employed in existing datasets. The main objective of our work is to advance research in fatigue detection, particularly in work and academic settings. For this reason, we conducted a series of experiments by utilizing machine learning techniques to analyze the dataset and assess the fatigue state based on the features predicted by our models. The results reveal that the random forest technique consistently achieved the highest accuracy and F1-score across all experiments, predominantly exceeding 90%. These findings suggest that random forest is a highly promising technique for this task and prove the strong connection and association among the predicted features used to annotate the videos and the state of fatigue. Full article

This study aims to explore the potential of a novel EYE ROLL device designed to facilitate guided vision relaxation exercises in an open space. A prospective study was performed on 89 participants who perform screenwork for at least four hours daily. All participants were randomly divided into three groups: a Control group with no exercising, a Manual group undertook manual vision relax ation exercises, and an Eyeroll group engaged in EYE ROLL device-assisted vision relaxation exercises. Each participant underwent three evaluations (an initial baseline assessment, a 4-week follow-up, and an 8-week follow-up) with four assessment tools: a comprehensive vision examination, an in-depth questionnaire, saccadic eye movement recordings, and objective accommodation measurements. There was a statistically significant decrease (35% and above) in complaint scores at the 4-week follow-up in both training groups. Although statistically insignificant, complaints continued to decrease after an 8-week period. No significant changes were observed in clinical or objective accommodative parameters. Some variation of visual functions was observed in all groups due to repeated measures. Vision relaxation exercises combined with proper vision ergonomics and working habits can reduce asthenopic complaints. The EYE ROLL device presents a promising tool for integrating these exercises into the working environment. Full article

Background: Mobile phones, laptops, and computers have become an indispensable part of our lives in recent years. Workers may have an incorrect posture when using a computer for a prolonged period of time. Using these products with an incorrect posture can lead to neck pain. However, there are limited data on postures in real-life situations. Methods: In this study, we used a common camera to record images of subjects carrying out three different tasks (a typing task, a gaming task, and a video-watching task) on a computer. Different artificial intelligence (AI)-based pose estimation approaches were applied to analyze the head’s yaw, pitch, and roll and coordinate information of the eyes, nose, neck, and shoulders in the images. We used machine learning models such as random forest, XGBoost, logistic regression, and ensemble learning to build a model to predict whether a subject had neck pain by analyzing their posture when using the computer. Results: After feature selection and adjustment of the predictive models, nested cross-validation was applied to evaluate the models and fine-tune the hyperparameters. Finally, the ensemble learning approach was utilized to construct a model via bagging, which achieved a performance with 87% accuracy, 92% precision, 80.3% recall, 95.5% specificity, and an AUROC of 0.878. Conclusions: We developed a predictive model for the identification of non-specific neck pain using 2D video images without the need for costly devices, advanced environment settings, or extra sensors. This method could provide an effective way for clinically evaluating poor posture during real-world computer usage scenarios. Full article

Rapid detection of pathogenic bacteria is extremely important for public health and safety. Here, we describe for the first time an integrated origami paper-based analytical device (PAD) incorporating cell lysis, molecular recognition, amplification and visual detection of Escherichia coli (E. coli). The device features three components: paper for its ability to extract protein molecules nonspecifically from cells, DNA superstructures for their ability to immobilize RNA-cleaving DNAzymes (RCDs) but undergo target-induced RNA cleavage on paper, and isothermal rolling circle amplification (RCA) for its ability to amplify each cleavage event into repetitive sequence units that can be detected by naked eye. This device can achieve detection of E. coli K12 with a detection limit of as low as 10³ CFU·mL⁻¹ in a total turnaround time of 35 min. Furthermore, this device allowed the sensitive detection of E. coli in complex sample matrices such as juice and milk. Given that more specific RCDs can be evolved for diverse bacteria, the integrated PAD holds great potential for rapid, sensitive and highly selective detection of pathogenic bacteria in resource-limited settings. Full article

The most accurate remote Point of Gaze (PoG) estimation methods that allow free head movements use infrared light sources and cameras together with gaze estimation models. Current gaze estimation models were developed for desktop eye-tracking systems and assume that the relative roll between the system and the subjects’ eyes (the ’R-Roll’) is roughly constant during use. This assumption is not true for hand-held mobile-device-based eye-tracking systems. We present an analysis that shows the accuracy of estimating the PoG on screens of hand-held mobile devices depends on the magnitude of the R-Roll angle and the angular offset between the visual and optical axes of the individual viewer. We also describe a new method to determine the PoG which compensates for the effects of R-Roll on the accuracy of the POG. Experimental results on a prototype infrared smartphone show that for an R-Roll angle of ${90}^{°}$ , the new method achieves accuracy of approximately $1^{°}$ , while a gaze estimation method that assumes that the R-Roll angle remains constant achieves an accuracy of ${3.5}^{°}$ . The manner in which the experimental PoG estimation errors increase with the increase in the R-Roll angle was consistent with the analysis. The method presented in this paper can improve significantly the performance of eye-tracking systems on hand-held mobile-devices. Full article

To investigate the temporary tamponade effects of an ophthalmic viscosurgical device (OVD) for experimental retinal tears, we performed vitrectomy in four rabbit eyes and created a posterior vitreous detachment and artificial retinal tear to produce retinal detachment. The retina was flattened with liquid perfluorocarbon (PFC), the area peripheral to the tear was photocoagulated, an OVD was applied to the retinal tear surface below the PFC and the PFC was removed by aspiration. In the control group, PFC was removed without application of OVD. At one, three and seven days postoperatively, funduscopy and optical coherence tomography (OCT) were performed to examine the sealing process of the retinal tear. In OVD-treated eyes, the OVD remained on the retinal surface, and the retinal tear was patched for ≥ 3 days postoperatively. By seven days postoperatively, the OVD on the retinal surface had disappeared, and the retina was reattached. In control eyes, the edge of the retinal tear was rolled, and retinal detachment persisted. In OVD-treated eyes, the border of the retinal tear was indistinct, and the defect area was significantly decreased. These results show that application of an OVD effectively seals retinal tears and eliminates retinal detachments. Full article