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Graphene K‐Tape Meshes for Densely Distributed Human Motion Monitoring

Yunan Lin, Yingjun Zhao, Long Wang, Yujin Park, Yi‐Jui Yeh, Wei‐Hung Chiang, Kenneth J. Loh

2020Advanced Materials Technologies43 citationsDOIOpen Access PDF

Abstract

Abstract Wearable sensors that measure parameters associated with physical activity and bodily motions have been regarded as an indispensable tool for assessing personal wellness. Recent advances in nanocomposite strain sensors have been successfully used for monitoring skin strains and other strain‐derived physiological parameters. This study complements the existing body of work and presents a flexible, self‐adhering, fabric‐based wearable sensor for measuring skin strains and human motions. Graphene nanosheet thin films are directly spray‐coated onto kinesiology tape (K‐Tape) to obtain a self‐adhering strain sensor of high sensitivity and linearity. Their stable sensing performance and high repeatability are verified, while human subject tests confirm that they adequately capture muscle engagement during functional movements. In addition, densely distributed strain monitoring can be achieved using an electrical impedance tomography measurement approach and algorithm. Spatial strain sensing is successfully demonstrated using a single strip of piezoresistive K‐Tape, as well as when a K‐Tape network or mesh pattern is formed. The results show promise for using graphene K‐Tape meshes to measure how specific major muscle groups engage during different physical activities.

Topics & Concepts

Piezoresistive effectMaterials scienceGrapheneRepeatabilityWearable computerPolygon meshStrain gaugeNanosheetComputer scienceHuman motionLinearitySensitivity (control systems)NanotechnologyAcousticsBiomedical engineeringComposite materialMotion (physics)Electronic engineeringArtificial intelligenceEngineeringPhysicsChemistryEmbedded systemComputer graphics (images)ChromatographyAdvanced Sensor and Energy Harvesting MaterialsMuscle activation and electromyography studiesNon-Invasive Vital Sign Monitoring
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