2026-10-12T20:44:02Z https://www.scidb.cn/oai

10.57760/sciencedb.27606 2026-06-30T17:07:37Z

2026-06-30 High-Throughput Biopotential-Driven Dual-Mode Epidermal Sensors for Ultrastretchable Human-Machine Interfacing Bracelets doi:10.57760/sciencedb.27606 en Developing multimode flexible sensors is highly desirable for human-machine interaction (HMI), yet the challenge of acquiring crosstalk-free multimodal physiological signals using a single material and compact device persists. Here, an epidermal biopotential driven integrated Electromyogram (EMG)-Forcemyography (FMG) dual-mode sensor (IEFDS) is designed to simultaneously capture these two signals without crosstalk. This sensor utilizes the coupling effect of bimodal signals within a single-layer organohydrogel tailored for skin impedance matching. Muscle movements generate distinct EMG and FMG signals, which the IEFDS quantifies as potential differences within unique frequency bands, and the designed decoupling algorithm ensures high-fidelity extraction of these signals. Subsequent decoding by artificial intelligence algorithms interprets motion intentions accurately (95.8%). Furthermore, a high-throughput 128-channel sensor array is monolithically integrated onto a continuous organohydrogel film with superior self-adhesive and mechanical properties. This allows the fabrication of an integrated HMI bracelet with impressive stretchability (100% strain) and adaptability to different individuals and body parts. The wireless bracelet is finally leveraged for the remote and accurate control of various execution terminals. human-machine interaction; Electromyogram (EMG)-Forcemyography (FMG) dual-mode sensor; Hydrogel Hao Wang Yubin Zhou Yubin Luo Wenxiong Shi Jianye Li Mingxuan Xiao Ruijie Xie Binghua Zou Huizhi Chen Yan Wang Shaowu Pan Daohui Zhang Kai Tao Fei Liu Fengwei Huo Jin Wu PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset Science Data Bank