An Improved Processing Strategy for Head Pose Detection in Phosphene Vision

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2021-01-29

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en

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Cortical visual implants can elicit activity in the visual cortex via electrical impulses. Speci c stimulation patterns can partially restore vision in the form of phosphene images. However, because of the limited resolution of these images only a small part of the visual eld can be e ectively represented. Intelligent processing strategies can help with transforming the visual eld image into a meaningful phosphene representation. I propose a new processing strategy for head pose position in phosphene vision using the vertices of a 3D model and call it \vertex processing". Multiple variations of this processing strategy were implemented and compared to each other as well as to an edge detection algorithm, which is a commonly used processing strategy for cortical visual implants at the moment. Accuracy and reaction time data from participants in online experiments was compared. I found that there was a signi cant improvement in these metrics for the vertex processing strategy compared to the current edge detection strategy. The head pose directions that pro ted most from this new strategy were up, down, front and down right. I also found that the amount of vertices in the 3D model could be reduced to a certain extent without signi cant accuracy loss, but not without a signi cant increase in reaction time. These results indicate that the vertex processing strategy can create a more e ective representation of the visual eld and in this way can contribute to a more meaningful visual experience for cortical visual implant users.

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Faculteit der Sociale Wetenschappen