Trial reportTranslational vision science & technology2026
Detecting and Localizing Objects With Color-Contrast With a Second-Generation (44-Channel) Suprachoroidal Retinal Prosthesis.
Trial report in Translational vision science & technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03406416 (Evaluation of a Suprachoroidal Retinal Prosthesis), which is not on this map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Evaluation of a Suprachoroidal Retinal Prosthesis: A 44 Channel Fully Implantable Study
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To assess the detection of color contrast in retinal prosthesis users by evaluating a novel Detecting Objects with Color-Contrast (DOCC) vision processing algorithm. Methods: 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. Results: 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). Conclusions: Vision processing software can improve object detection and localization for objects of one color against a low-contrast background of another color. Translational Relevance: A color-contrast algorithm may assist retinal prosthesis users with detecting and localizing objects that are color-contrasted to their background.
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