研究目的
To understand the effects of an intensive training schedule on adaptation to artificial sight using simulations of thalamic visual prostheses, and to assess performance changes longitudinally in reading tasks.
研究成果
Daily training with simulated artificial vision significantly improves reading accuracy and speed, equivalent to doubling phosphene count. Training effects are robust but sensitive to gaps, suggesting post-implant rehabilitation should be frequent. The findings support the development of thalamic visual prostheses and inform rehabilitation strategies.
研究不足
The study used simulations with normal, sighted subjects rather than actual implant recipients, which may not fully replicate the experience of blind patients. The font size range was limited, affecting acuity measurement accuracy for easier conditions. System latency in the simulation could be improved. The sample size was small (six subjects completed), and the training regimen was fixed, not personalized.
1:Experimental Design and Method Selection:
The study used a longitudinal design with normal, sighted subjects performing a reading task under simulated artificial vision conditions. The simulation mimicked thalamic visual prostheses with gaze-contingent presentation.
2:Sample Selection and Data Sources:
Eight subjects were recruited, six completed 40 sessions. Subjects had normal vision, were seated 60 cm from a monitor, and read MNREAD-style sentences.
3:List of Experimental Equipment and Materials:
Equipment included an SR Research EyeLink 1000+ gaze tracker, a Lenovo M700 PC with custom AVR4 software, a Dell E2013H monitor, and a Snellen chart for vision screening.
4:Experimental Procedures and Operational Workflow:
Subjects underwent calibration, then read 40 sentences per session with varying font sizes and phosphene patterns. Performance was scored for accuracy and speed.
5:Data Analysis Methods:
Data were analyzed using logistic curve fitting for acuity, exponential decay models for learning rates, and statistical tests like Wilcoxon rank sum and Student's t-test.
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