2022
DOI: 10.3390/mi13091429
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Liquid Metal-Based Flexible and Wearable Sensor for Functional Human–Machine Interface

Abstract: Rigid sensors are a mature type of sensor, but their poor deformation and flexibility limit their application range. The appearance and development of flexible sensors provide an opportunity to solve this problem. In this paper, a resistive flexible sensor utilizes gallium−based liquid metal (eutectic gallium indium alloy, EGaIn) and poly(dimethylsiloxane) (PDMS) and is fabricated using an injecting thin−line patterning technique based on soft lithography. Combining the scalable fabrication process and unique … Show more

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Cited by 7 publications
(2 citation statements)
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“…For one thing, using liquid metal as a conductor and combining flexible circuits with traditional electronic chips can be used to prepare wearable electronic devices, such as various physiological electrical signal detection circuits [15]- [17]. For another, the combination of liquid metal and robots can be used for human-machine interaction, robot sensors, and other devices [18], [19].…”
Section: Introductionmentioning
confidence: 99%
“…For one thing, using liquid metal as a conductor and combining flexible circuits with traditional electronic chips can be used to prepare wearable electronic devices, such as various physiological electrical signal detection circuits [15]- [17]. For another, the combination of liquid metal and robots can be used for human-machine interaction, robot sensors, and other devices [18], [19].…”
Section: Introductionmentioning
confidence: 99%
“…In addition, piezoelectric sensors are self-powered, exhibit reduced system complexity, and can operate over a wide temperature range. [20][21][22][23][24] Strain sensors and triboelectric sensors are usually used for motion monitoring, but strain sensors usually require additional power supply [25] and triboelectric sensors can exhibit nonlinearity. [26] In previous studies, surface electromyography and inertial acceleration sensors were often used to recognizing sarcopenia by measuring surface electromyography signals and gait parameters, respectively.…”
Section: Introductionmentioning
confidence: 99%