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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Triboelectric Nanogenerator Enabled Wearable Sensors and Electronics for Sustainable Internet of Things Integrated Green Earth

Advanced Energy Materials, Journal Year: 2022, Volume and Issue: 13(1)

Published: Nov. 18, 2022

Abstract The advancement of the Internet Things/5G infrastructure requires a low‐cost ubiquitous sensory network to realize an autonomous system for information collection and processing, aiming at diversified applications ranging from healthcare, smart home, industry 4.0 environmental monitoring. triboelectric nanogenerator (TENG) is considered most promising technology due its self‐powered, cost‐effective, highly customizable advantages. Through use wearable electronic devices, advanced TENG developed as core enabling self‐powered sensors, power supplies, data communications aforementioned applications. In this review, advancements TENG‐based electronics regarding materials, material/device hybridization, systems integration, convergence, in environment monitoring, transportation, homes toward future green earth are reported.

Language: Английский

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An Open‐Environment Tactile Sensing System: Toward Simple and Efficient Material Identification

Advanced Materials, Journal Year: 2022, Volume and Issue: 34(29)

Published: May 17, 2022

Robotic perception can have simple and effective sensing functions that are unreachable for humans using only the isolated tactile method, with assistance of a triboelectric nanogenerator (TENG). However, reliability sensors remains major challenge due to inherent environmental limitations. Here, an intelligent system combines TENG deep-learning technology is proposed. Using triple sensor array, typical characteristics each testing material be maintained stably even under different contact conditions (touch external conditions) by extracting features from three independent electrical signals as well normalized output signals. Furthermore, convolutional neural network model integrated, high accuracy 96.62% achieved in identification task. The exhibited open environment real-time demonstration. Compared complex process must integrate multiple (touching viewing) accomplish perception, proposed shows huge advantage cognitive learning visually impaired, biomimetic prosthetics, virtual spaces construction.

Language: Английский

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Deep‐Learning‐Assisted Noncontact Gesture‐Recognition System for Touchless Human‐Machine Interfaces

Advanced Functional Materials, Journal Year: 2022, Volume and Issue: 32(49)

Published: Sept. 30, 2022

Abstract Human‐machine interfaces (HMIs) play important role in the communication between humans and robots. Touchless HMIs with high hand dexterity hygiene hold great promise medical applications, especially during pandemic of coronavirus disease 2019 (COVID‐19) to reduce spread virus. However, current touchless are mainly restricted by limited types gesture recognition, requirement wearing accessories, complex sensing platforms, light conditions, low recognition accuracy, obstructing their practical applications. Here, an intelligent noncontact gesture‐recognition system is presented through integration a triboelectric sensor (TTS) deep learning technology. Combined deep‐learning‐based multilayer perceptron neural network, TTS can recognize 16 different gestures average accuracy 96.5%. The further applied control robot for collecting throat swabs mode. Compared present HMIs, proposed diverse utilizing charges naturally carried on human fingers without need complicated device structures, adequate achieves accuracy. This could provide exciting opportunities develop new generation equipment, as well public facilities, smart robots, virtual reality, metaverse, etc.

Language: Английский

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A Self‐Powered Body Motion Sensing Network Integrated with Multiple Triboelectric Fabrics for Biometric Gait Recognition and Auxiliary Rehabilitation Training

Advanced Functional Materials, Journal Year: 2023, Volume and Issue: 33(35)

Published: May 7, 2023

Abstract Gait analysis provides a convenient strategy for the diagnosis and rehabilitation assessment of diseases skeletal, muscular, neurological systems. However, challenges remain in current gait recognition methods due to drawbacks complex systems, high cost, affecting natural gait, one‐size‐fits‐all model. Here, highly integrated system composed self‐powered multi‐point body motion sensing network (SMN) based on full textile structure is demonstrated. By combining newly developed energy harvesting technology triboelectric nanogenerator (TENG) traditional manufacturing process, SMN not only ensures pressure response sensitivity up 1.5 V kPa −1 , but also endowed with several good properties, such as flexibility, excellent breathability (165 mm s ), moisture permeability (318 g m −2 h ). using machine learning analyze periodic signals dynamic parameters limbs swing, exhibits accuracy 96.7% five pathological gaits. In addition, customizable auxiliary exercise that monitors extent patient's observe condition instruct timely recovery training. The learning‐assisted can provide feasible solution disease personalized patients.

Language: Английский

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Incorporating Wireless Strategies to Wearable Devices Enabled by a Photocurable Hydrogel for Monitoring Pressure Information

Advanced Materials, Journal Year: 2023, Volume and Issue: 35(29)

Published: March 31, 2023

Advances in emerging technologies for wireless collection and the timely analysis of various information captured by wearable devices are growing interest. Herein, a crosslinked ionic hydrogel prepared facile photocuring process is proposed, which allows to be further incorporated into two integrated systems pressure monitoring applications. The device exhibits simplified structure effectively sharing functional layers, rather than conventional separate combinations, offering salient performance iontronic sensing electrochromic properties simultaneously quantify visualize pressure. developed smart patch system demonstrated monitor physiological signals real-time utilizing user interface remote portable equipment with Bluetooth protocol on-site displays. Moreover, passive based on magnetic coupling effect designed, can operate free from battery acquire multiple information. It envisioned that strategies would hold enormous potential flexible electronics, versatile platforms, on-body networks.

Language: Английский

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Artificial intelligence enhanced sensors - enabling technologies to next-generation healthcare and biomedical platform

Bioelectronic Medicine, Journal Year: 2023, Volume and Issue: 9(1)

Published: Aug. 2, 2023

The fourth industrial revolution has led to the development and application of health monitoring sensors that are characterized by digitalization intelligence. These have extensive applications in medical care, personal management, elderly sports, other fields, providing people with more convenient real-time services. However, these face limitations such as noise drift, difficulty extracting useful information from large amounts data, lack feedback or control signals. artificial intelligence provided powerful tools algorithms for data processing analysis, enabling intelligent monitoring, achieving high-precision predictions decisions. By integrating Internet Things, intelligence, sensors, it becomes possible realize a closed-loop system functions collection, online diagnosis, treatment recommendations. This review focuses on healthcare enhanced technologies aspects materials, device structure, integration, scenarios. Specifically, this first introduces great advances wearable respiration rate, heart pulse, sweat, tears; implantable cardiovascular nerve signal acquisition, neurotransmitter monitoring; soft electronics precise therapy. Then, recent volatile organic compound detection highlighted. Next, current developments human-machine interfaces, AI-enhanced multimode self-sustainable systems reviewed. Last, perspective future directions further research is also provided. In summary, fusion will provide intelligent, convenient, secure services next-generation biomedical applications.

Language: Английский

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Scalable spinning, winding, and knitting graphene textile TENG for energy harvesting and human motion recognition

Nano Energy, Journal Year: 2022, Volume and Issue: 107, P. 108137 - 108137

Published: Dec. 27, 2022

Language: Английский

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Soft Robotic Perception System with Ultrasonic Auto-Positioning and Multimodal Sensory Intelligence

ACS Nano, Journal Year: 2023, Volume and Issue: 17(5), P. 4985 - 4998

Published: March 3, 2023

Flexible electronics such as tactile cognitive sensors have been broadly adopted in soft robotic manipulators to enable human-skin-mimetic perception. To achieve appropriate positioning for randomly distributed objects, an integrated guiding system is inevitable. Yet the conventional based on cameras or optical exhibits limited environment adaptability, high data complexity, and low cost effectiveness. Herein, a perception with remote object multimodal cognition capability developed by integrating ultrasonic sensor flexible triboelectric sensors. The able detect shape distance reflected ultrasound. Thereby manipulator can be positioned position perform grasping, during which capture sensory information top profile, size, shape, hardness, material, etc. These are then fused deep-learning analytics, leading highly enhanced accuracy identification (∼100%). proposed presents facile, low-cost, effective methodology integrate intelligence robotics, significantly expanding functionalities adaptabilities of current systems industrial, commercial, consumer applications.

Language: Английский

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