Electrode Dropout Compensation in Visual Prostheses: An Optimal Object Placement Approach

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.