Regarding the characteristics of VPL, there are three most prominent features: (1) ubiquity, (2) long-term persistence, and (3) lack of generalization (or transfer). Over the last three decades, VPL has been widely studied, and research has primarily focused on characteristics, cortical sites of occurrence, and manifestation of VPL. Repetitive practice on visual tasks can improve our ability to process visual sensory information and even in adults, this neural process is termed visual perceptual learning. This principle is also applicable in sensory information processing. Therefore, in this review, we will focus on the current research progress of visual function enhancement by combing VPL and tES techniques in healthy adults as well as patients with neuro-ophthalmological disorders in other words, VPL-induced vision enhancement further augmented by tES techniques. Since some methods which can induce neuroplasticity share similar principles (e.g., both VPL and tES are assumed to be able to induce long-term potentiation (LTP)-like plasticity, applying multiple methods simultaneously to induce greater plasticity becomes feasible in practice. To date, there are multiple methods that can induce visual plasticity, such as rapid visual stimulation, visual deprivation, action video game, visual perceptual learning (VPL), and transcranial electrical stimulation (tES) techniques.
Our review provides a guide for future research and application of vision enhancement and restoration by combining VPL and tES.įor both healthy and clinical populations, the visual system preserves a high capacity for plasticity even after maturity. In this review, we firstly introduced the basic concept and possible mechanisms of VPL and tES then we reviewed the current research progress of visual enhancement using the combination of two methods in both general and clinical population finally, we discussed the limitations and future directions in this field. Vision enhancement by combining these two methods concurrently is both theoretically and practically significant. Theoretically, visual function could be further improved in a shorter time frame by combining tES and VPL than by solely using tES or VPL. By contrast, VPL can lead to a substantial and long-lasting improvement in visual function, but extensive training is typically required. TES can change visual function rapidly, but its modulation effect is short-lived and unstable. Our visual function can be enhanced through many ways, such as transcranial electrical stimulation (tES) and visual perceptual learning (VPL). Finally, the information of image analysis and processing is transmitted back to the AR device, so the prompts of target text and voice are given for intelligent auxiliary decision-making in time.The visual system remains highly malleable even after its maturity or impairment. And stable target tracking is achieved by time sequence state filtering. Then, the method of deep learning and feature matching is adopted to carry out facial consistency analysis, which improves the robustness of target detection. First, small, remote and wireless cameras are used to obtain image data, which need to be uploaded to a cloud. To overcome these shortcomings, we designed a visual enhancement system that integrates cloud computing, AR technology and deep learning.
However, the existing visual enhancement equipment has single function, limited processing capacity and poor interaction. Vision-based augmented reality is a new kind of visual application technology, which transfers synthetic sensory information into a user's perception of a real environment.
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