Detecting and Localizing Objects With Color-Contrast With a Second-Generation (44-Channel) Suprachoroidal Retinal...

To assess the detection of color contrast in retinal prosthesis users by evaluating a novel Detecting Objects with Color-Contrast (DOCC) vision processing algorithm.

Three participants monocularly implanted with a suprachoroidal retinal prosthesis (NCT03406416) were asked to locate and identify objects on a tabletop that were color-contrasted with their backgrounds using the DOCC algorithm, a control algorithm (Lanczos2 [L2]) and system off. The task involved two setups; (i) high-contrast white-on-black objects, and (ii) low-grayscale-contrast (color-only contrast) red-on-green objects. Participants were required to verbally localize (nine alternative forced choice), then touch the object, with the distance measured from their finger to the true object location.

For low- (color-only) contrast objects, DOCC (58.3% ± 43.0%) performed better than L2 (27.9% ± 42.5%) for verbally localizing objects (P < 0.0001) and both DOCC (P < 0.0001) and L2 (P = 0.0018) performed better than system off (9.1% ± 33.1%). Furthermore, DOCC (9.7 ± 10.6 cm) had a closer final proximity to the object than L2 (28.0 ± 24.7 cm; P < 0.0001) and system off (45.0 ± 23.9 cm; P < 0.0001). For high-contrast objects, DOCC (59.8% ± 47.8%) performed similarly to L2 (60.8% ± 48.3%) and system off (25.4% ± 41.8%) for verbally localizing objects (P = 0.32, three-condition). Likewise, for final object proximity, DOCC (8.0 ± 7.5 cm) also performed similarly to L2 (6.2 ± 8.4 cm, P = 0.43), whereas both DOCC (P = 0.0014) and L2 (P < 0.0001) performed better than system off (25.6 ± 22.3 cm).

Vision processing software can improve object detection and localization for objects of one color against a low-contrast background of another color.

A color-contrast algorithm may assist retinal prosthesis users with detecting and localizing objects that are color-contrasted to their background.