Psychophysical Validation of Gestalt-Inspired Encoding Strategies for Dynamic Action Recognition in Simulated Prosthetic Vision

Visual prostheses provide restricted visual information through phosphene-like percepts, making the organization of spatial and temporal cues important for dynamic action recognition. This study investigated human action recognition under four simulated prosthetic vision (SPV) encoding conditions—NO_EDGE, BASELINE, PCL, and PCO—selected from 11 computationally screened candidates. Twenty normally sighted participants completed open-response action-recognition tasks with nominal 32×32 SPV videos. Experiment 1 compared strategies under full, half, and quarter temporal-availability conditions. Experiment 2, by contrast, examined two complementary manipulations—frame-holding and background-suppression—prior to SPV generation. Responses were classified as Correct, Vague, Uncertain, or Wrong, and Correct identification was analyzed using binomial generalized linear mixed models. In Experiment 1, strategy, temporal availability, and their interaction were associated with correct recognition. PCO had the highest overall observed Correct rate (58.6%) and the lowest Uncertain rate (20.8%); BASELINE approached PCO in the Quarter condition, while PCL showed lower overall recognition. Reduced temporal availability decreased correct identification and increased uncertainty. In Experiment 2, frame holding generally reduced recognition, whereas background suppression did not produce a consistent improvement. Model-defined pathway characteristics helped select contrasting strategies, and the behavioral results revealed their distinct, condition-dependent recognition profiles. The findings provide a basis for task-oriented SPV encoding that considers target organization and temporal presentation together.