Wearable Sensors‐Enabled Human–Machine Interaction Systems: From Design to Application

Advanced Functional Materials, Journal Year: 2020, Volume and Issue: 31(11)

Published: Dec. 29, 2020

Abstract In comparison to traditional bulky and rigid electronic devices, the human–machine interaction (HMI) system with flexible wearable components is an inevitable future trend. To achieve effective, intuitive, seamless manipulation of high‐performance HMI systems, it important develop effective strategies for designing material microstructures on sensors electric devices excellent mechanical flexibility stretchability. The real‐time acquisition human physiology surrounding signals through accurate basis HMIs. Herein, construction a that utilizes sensors, communication modes, actuators reviewed. mechanisms various based different are analyzed discussed. functional mechanism, selection, novel design each part summarized in detail. modes interactive systems manufacturing technology soft machines also introduced. Additionally, most advanced applications intelligent identification security, controls robots, augmented reality, virtual reality have been highlighted. review concludes overview remaining key challenges several ideas regarding further improvement systems.

Language: Английский

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Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications

Nature Communications, Journal Year: 2020, Volume and Issue: 11(1)

Published: Oct. 23, 2020

Designing efficient sensors for soft robotics aiming at human machine interaction remains a challenge. Here, we report smart soft-robotic gripper system based on triboelectric nanogenerator to capture the continuous motion and tactile information gripper. With special distributed electrodes, sensor can perceive contact position area of external stimuli. The gear-based length with stretchable strip allows detection elongation via sequential each tooth. sensory collected during operation is further trained by support vector algorithm identify diverse objects an accuracy 98.1%. Demonstration digital twin applications, which show object identification duplicate robotic manipulation in virtual environment according real-time system, successfully created assembly lines unmanned warehouse applications.

Language: Английский

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The Triboelectric Nanogenerator as an Innovative Technology toward Intelligent Sports

Advanced Materials, Journal Year: 2021, Volume and Issue: 33(17)

Published: March 24, 2021

Abstract In the new era of Internet‐of‐Things, athletic big data collection and analysis based on widely distributed sensing networks are particularly important in development intelligent sports. Conventional sensors usually require an external power supply, with limitations such as limited lifetime high maintenance cost. As a newly developed mechanical energy harvesting self‐powered technology, triboelectric nanogenerator (TENG) shows great potential to overcome these limitations. Most importantly, TENGs can be fabricated using wood, paper, fibers, polymers, which most frequently used materials for Recent progress field sports is summarized. First, working mechanism TENG its association introduced. Subsequently, TENG‐based systems, including smart facilities wearable equipment highlighted. At last, remaining challenges open opportunities also discussed.

Language: Английский

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Machine Learning Glove Using Self‐Powered Conductive Superhydrophobic Triboelectric Textile for Gesture Recognition in VR/AR Applications

Advanced Science, Journal Year: 2020, Volume and Issue: 7(14)

Published: June 9, 2020

The rapid progress of Internet things (IoT) technology raises an imperative demand on human machine interfaces (HMIs) which provide a critical linkage between and machines. Using glove as intuitive low-cost HMI can expediently track the motions fingers, resulting in straightforward communication media human-machine interactions. When combining several triboelectric textile sensors proper learning technique, it has great potential to realize complex gesture recognition with minimalist-designed for comprehensive control both real virtual space. However, humidity or sweat may negatively affect output well itself. Hence, this work, facile carbon nanotubes/thermoplastic elastomer (CNTs/TPE) coating approach is investigated detail achieve superhydrophobicity performance improvement. With energy harvesting motion sensing capabilities, using superhydrophobic realizes self-powered interface recognition. By leveraging technology, various tasks are done time by gestures highly accurate reality/augmented reality (VR/AR) controls including gun shooting, baseball pitching, flower arrangement, minimized effect from during operation.

Language: Английский

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AI enabled sign language recognition and VR space bidirectional communication using triboelectric smart glove

Nature Communications, Journal Year: 2021, Volume and Issue: 12(1)

Published: Sept. 10, 2021

Sign language recognition, especially the sentence is of great significance for lowering communication barrier between hearing/speech impaired and non-signers. The general glove solutions, which are employed to detect motions our dexterous hands, only achieve recognizing discrete single gestures (i.e., numbers, letters, or words) instead sentences, far from satisfying meet signers' daily communication. Here, we propose an artificial intelligence enabled sign recognition system comprising sensing gloves, deep learning block, virtual reality interface. Non-segmentation segmentation assisted model achieves 50 words 20 sentences. Significantly, approach splits entire signals into word units. Then recognizes all elements reversely reconstructs Furthermore, new/never-seen sentences created by new-order recombination can be recognized with average correct rate 86.67%. Finally, results projected space translated text audio, allowing remote bidirectional signers

Language: Английский

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Augmented tactile-perception and haptic-feedback rings as human-machine interfaces aiming for immersive interactions

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Sept. 5, 2022

Abstract Advancements of virtual reality technology pave the way for developing wearable devices to enable somatosensory sensation, which can bring more comprehensive perception and feedback in metaverse-based society. Here, we propose augmented tactile-perception haptic-feedback rings with multimodal sensing capabilities. This highly integrated ring consists triboelectric pyroelectric sensors tactile temperature perception, vibrators nichrome heaters vibro- thermo-haptic feedback. All these components on be directly driven by a custom wireless platform low power consumption wearable/portable scenarios. With voltage integration processing, high-resolution continuous finger motion tracking is achieved via sensor, also contributes superior performance gesture/object recognition artificial intelligence analysis. By fusing functions, an interactive metaverse cross-space capability successfully achieved, giving people face-to-face like immersive social experience.

Language: Английский

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Artificial Intelligence‐Enabled Sensing Technologies in the 5G/Internet of Things Era: From Virtual Reality/Augmented Reality to the Digital Twin

Advanced Intelligent Systems, Journal Year: 2022, Volume and Issue: 4(7)

Published: March 29, 2022

With the development of 5G and Internet Things (IoT), era big data‐driven product design is booming. In addition, artificial intelligence (AI) also emerging evolving by recent breakthroughs in computing power software architectures. this regard, digital twin, analyzing various sensor data with help AI algorithms, has become a cutting‐edge technology that connects physical virtual worlds, which sensors are highly desirable to collect environmental information. However, although existing technologies, including cameras, microphones, inertial measurement units, etc., widely used as sensing elements for applications, high‐power consumption battery replacement them still problem. Triboelectric nanogenerators (TENGs) self‐powered supply feasible platform realizing self‐sustainable low‐power systems. Herein, progress on TENG‐based intelligent systems, is, wearable electronics, robot‐related smart homes, followed prospective future enabled fusion technology, focused on. Finally, how apply systems IoT discussed.

Language: Английский

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Portable and wearable self-powered systems based on emerging energy harvesting technology

Microsystems & Nanoengineering, Journal Year: 2021, Volume and Issue: 7(1)

Published: March 17, 2021

A self-powered system based on energy harvesting technology can be a potential candidate for solving the problem of supplying power to electronic devices. In this review, we focus portable and wearable systems, starting with typical technology, introduce systems sensing functions. addition, demonstrate in actuation functions development toward intelligent under support information processing artificial intelligence technologies.

Language: Английский

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Promoting smart cities into the 5G era with multi-field Internet of Things (IoT) applications powered with advanced mechanical energy harvesters

Nano Energy, Journal Year: 2021, Volume and Issue: 88, P. 106304 - 106304

Published: July 4, 2021

Language: Английский

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Wearable Triboelectric Sensors Enabled Gait Analysis and Waist Motion Capture for IoT‐Based Smart Healthcare Applications

Advanced Science, Journal Year: 2021, Volume and Issue: 9(4)

Published: Nov. 19, 2021

Gait and waist motions always contain massive personnel information it is feasible to extract these data via wearable electronics for identification healthcare based on the Internet of Things (IoT). There also remains a demand develop cost-effective human-machine interface enhance immersion during long-term rehabilitation. Meanwhile, triboelectric nanogenerator (TENG) revealing its merits in both IoT tends be possible solution. Herein, authors present TENG-based devices gait analysis motion capture intelligence performance lower-limb Four sensors are equidistantly sewed onto fabric belt recognize motion, enabling real-time robotic manipulation virtual game immersion-enhanced training. The insole equipped with two TENG designed walking status detection 98.4% accuracy five different humans aiming at rehabilitation plan selection achieved by leveraging machine learning technology further analyze signals. Through robot, demonstrate that sensory system performs well user recognition, monitoring, as robot gaming-aided training, showing potential IoT-based smart applications.

Language: Английский

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