Encoding tactile stimuli for Braille recognition with organoids
- 1School of Engineering Mathematics and Technology, University of Bristol , ,
Abstract
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 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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BibTeX
@article{liu2026encoding,
title = {{Encoding tactile stimuli for Braille recognition with organoids}},
author = {Tianyi Liu and Hemma Philamore and Benjamin Ward-Cherrier},
journal = {Frontiers in artificial intelligence},
year = {2026},
month = oct,
doi = {10.3389/frai.2026.1800219},
url = {https://europepmc.org/article/PMC/PMC13719542},
note = {CC BY},
}
RIS
TY - JOUR
TI - Encoding tactile stimuli for Braille recognition with organoids
AU - Tianyi Liu
AU - Hemma Philamore
AU - Benjamin Ward-Cherrier
PY - 2026
DA - 2026/10/16
JO - Frontiers in artificial intelligence
DO - 10.3389/frai.2026.1800219
UR - https://europepmc.org/article/PMC/PMC13719542
AB - 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 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.
SN - 2624-8212
ER -