Biohybrid Robots with Embedded Conductive Fibers for Actuation, Sensing, and Closed-loop Control

Living organisms achieve adaptive actuation through the seamless integration of neural motor control circuitry and proprioceptive feedback. While biohybrid robotics aims to replicate these capabilities by merging engineered muscle with synthetic scaffolds, the field remains limited by interfaces that lack the efficiency and closed-loop regulation of natural neuromuscular systems. Here, we introduce a biohybrid muscle actuator system featuring a bioelectronic interface based on soft poly(3,4-ethylenedioxythiophene) (PEDOT) fibers for stimulation and sensing. These fibers conformally couple to muscle tissues, eliciting robust contractions at voltages as low as 1 V-requiring ultra-low power (0.376 ± 0.034 mW) and preserving long-term tissue viability. By leveraging the independent addressability of these fibers, we demonstrate selective actuation of individual muscle units to achieve precise spatiotemporal control of a two-muscle-powered walking biohybrid robot, reaching a locomotion speed of 5.43 ± 0.79 mm/min. When configured as strain sensors, the fibers exhibit a high gauge factor of 155.45 ± 6.59 and resolve contractile displacements within tens of micrometers. We demonstrate that this sensing modality can be integrated into a closed-loop controller to autonomously modulate stimulation based on real-time feedback, significantly mitigating muscle fatigue (p = 0.038) during continuous operation. This work establishes a versatile platform for efficient actuation and intrinsic feedback sensing, providing a blueprint for efficient, autonomous, and adaptive biohybrid machines.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-04-06
DOI
https://doi.org/10.64898/2026.04.01.715915
Primary Topic
Advanced Materials and Mechanics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Biohybrid Robots with Embedded Conductive Fibers for Actuation, Sensing, and Closed-loop Control

Josiah D. Hester, Rachel E. Daso, Michael J. Bennington, Jonathan Rivnay et al.
bioRxiv (Cold Spring Harbor Laboratory)
Advanced Materials and Mechanics
article

Biohybrid Robots with Embedded Conductive Fibers for Actuation, Sensing, and Closed-loop Control

Josiah D. Hester, Rachel E. Daso, Michael J. Bennington, Jonathan Rivnay, Yuhui Zhao, Abhijith Surendran, Tingyu Cheng, Xinran Xie, Junyi Liu, Wenjia Xu, Victoria A Webster-Wood, Ruiheng Wu
article en

Abstract

Living organisms achieve adaptive actuation through the seamless integration of neural motor control circuitry and proprioceptive feedback. While biohybrid robotics aims to replicate these capabilities by merging engineered muscle with synthetic scaffolds, the field remains limited by interfaces that lack the efficiency and closed-loop regulation of natural neuromuscular systems. Here, we introduce a biohybrid muscle actuator system featuring a bioelectronic interface based on soft poly(3,4-ethylenedioxythiophene) (PEDOT) fibers for stimulation and sensing. These fibers conformally couple to muscle tissues, eliciting robust contractions at voltages as low as 1 V-requiring ultra-low power (0.376 ± 0.034 mW) and preserving long-term tissue viability. By leveraging the independent addressability of these fibers, we demonstrate selective actuation of individual muscle units to achieve precise spatiotemporal control of a two-muscle-powered walking biohybrid robot, reaching a locomotion speed of 5.43 ± 0.79 mm/min. When configured as strain sensors, the fibers exhibit a high gauge factor of 155.45 ± 6.59 and resolve contractile displacements within tens of micrometers. We demonstrate that this sensing modality can be integrated into a closed-loop controller to autonomously modulate stimulation based on real-time feedback, significantly mitigating muscle fatigue (p = 0.038) during continuous operation. This work establishes a versatile platform for efficient actuation and intrinsic feedback sensing, providing a blueprint for efficient, autonomous, and adaptive biohybrid machines.

bioRxiv (Cold Spring Harbor Laboratory)
University of Notre Dame (US), Northwestern University (US), Georgia Institute of Technology (US), Carnegie Mellon University (US)
National Science Foundation, Northwestern University, National Cancer Institute, Army Research Office, National Science Foundation Graduate Research Fellowship Program
Openalex Percentile: Top 31%
Advanced Materials and Mechanics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.