Navigational outcomes with a depth-based vision processing algorithm in a second-generation suprachoroidal retinal prosthesis.

Abstract

Objective.To evaluate the effectiveness of a novel depth-based vision processing (VP) method, local background enclosure (LBE), in comparison to the comprehensive VP method, Lanczos2 (L2), in suprachoroidal retinal prosthesis implant recipients during navigational tasks in laboratory and real-world settings.Approach.Four participants were acclimatized to both VP methods. Participants were asked to detect and navigate past five of eight possible obstacles in a white corridor across 20-30 trials. Randomized obstacles included black or white mannequins, black or white overhanging boxes, black or white bins and black or white stationary boxes. The same four participants underwent trials at three different real-word urban locations using both VP methods (randomized order). They were tasked with navigating a complex, dynamic pre-determined scene while detecting, verbally identifying, and avoiding obstacles in their path.Main results.The indoor obstacle course showed that the LBE method (63.6 ± 10.7%, mean ± SD) performed significantly better than L2 (48.5 ± 11.2%), for detection of obstacles (p< 0.001, Mack-Skillings). The real-world assessment showed that of the objects detected, 50.2% (138/275) were correctly identified using LBE and 41.7% (138/331) using L2, corresponding to a risk difference of 8 percentage points,p= 0.081).Significance.Real world outcomes can be improved using an enhanced VP algorithm, providing depth-based visual cues (#NCT05158049).