用类脑组织识别盲文，单个组织准确率61%，三组结合达83%。
Encoding Tactile Stimuli for Braille Recognition with Organoids
- 将触觉信号转为电刺激，让类脑组织处理盲文输入。
- 单组织识别准确率61%，三组织集成提升至83%。
- 系统对噪声有抗性，适合未来生物混合计算架构。
本研究提出一种可迁移的编码策略，将触觉传感器数据映射为电刺激模式，使神经类器官完成开环人工触觉盲文分类任务。在低密度微电极阵列（MEA）上培养的人类前脑类器官被系统性刺激，以刻画电刺激参数（脉冲数、相位幅值、相位持续时间、触发延迟）与类器官响应（尖峰活动和活动中心空间位移）的关系。该系统基于来自Evetac传感器的事件驱动触觉输入实现，单个类器官平均盲文字母分类准确率达61%，当整合三个类器官响应时，准确率显著提升至83%。此外，多类器官配置对多种人为引入的噪声表现出更强鲁棒性。本研究展示了类器官作为低功耗、自适应生物混合计算单元的潜力，并为未来可扩展的生物混合计算架构提供了基础编码框架。
原文摘要 · Abstract (English)
This study proposes a transferable encoding strategy that maps tactile sensor data to electrical stimulation patterns, enabling neural organoids to perform an open-loop artificial tactile Braille classification task. Human forebrain organoids cultured on a low-density microelectrode array (MEA) are systematically stimulated to characterize the relationship between electrical stimulation parameters (number of pulse, phase amplitude, phase duration, and trigger delay) and organoid responses, measured as spike activity and spatial displacement of the center of activity. Implemented on event-based tactile inputs recorded from the Evetac sensor, our system achieved an average Braille letter classification accuracy of 61% with a single organoid, which increased significantly to 83% when responses from a three-organoid ensemble were combined. Additionally, the multi-organoid configuration demonstrated enhanced robustness against various types of artificially introduced noise. This research demonstrates the potential of organoids as low-power, adaptive bio-hybrid computational elements and provides a foundational encoding framework for future scalable bio-hybrid computing architectures.
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