Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:6515-6518. doi: 10.1109/EMBC46164.2021.9630991.
Visual prostheses provide promising solution to the blind through partial restoration of their vision via electrical stimulation of the visual system. However, there are some challenges that hinder the ability of subjects implanted with visual prostheses to correctly identify an object. One of these challenges is electrode dropout; the malfunction of some electrodes resulting in consistently dark phosphenes. In this paper, we propose a dropout handling algorithm for better and faster identification of objects. In this algorithm, phosphenes representing the object are translated to another location within the same image that has the minimum number of dropouts. Using simulated prosthetic vision, experiments were conducted to test the efficacy of our proposed algorithm. Electrode dropout rates of 10%, 20% and 30% were examined. Our results demonstrate significant increase in the object recognition accuracy, reduction in the recognition time and increase in the recognition confidence level using the proposed approach compared to presenting the images without dropout handling.Clinical Relevance- These results demonstrate the utility of dropout handling in enhancing the perception of images in prosthetic vision.
视觉假体通过对视觉系统的电刺激为盲人提供了有希望的解决方案，从而部分恢复他们的视力。然而，一些挑战阻碍了植入视觉假体的受试者正确识别物体的能力。其中一个挑战是电极脱落；一些电极发生故障，导致持续出现暗幻视。在本文中，我们提出了一种处理脱落的算法，以更好、更快地识别物体。在该算法中，代表物体的幻视被转换到同一图像内具有最小脱落电极数的另一个位置。使用模拟假体视觉进行了实验，以测试我们提出的算法的效果。检查了 10%、20%和 30%的电极脱落率。与不使用脱落处理呈现图像相比，我们的结果表明，使用提出的方法可显著提高物体识别准确性、减少识别时间并提高识别置信度。临床相关性-这些结果表明，在增强假体视觉中图像的感知方面，脱落处理是有用的。
