Nano Energy, Journal Year: 2024, Volume and Issue: unknown, P. 110493 - 110493
Published: Nov. 1, 2024
Language: Английский
ACS Nano, Journal Year: 2024, Volume and Issue: 18(26), P. 17041 - 17052
Published: June 21, 2024
Flexible tactile sensors show promise for artificial intelligence applications due to their biological adaptability and rapid signal perception. Triboelectric enable active dynamic sensing, while integrating static pressure sensing real-time multichannel transmission is key further development. Here, we propose an integrated structure combining a capacitive sensor spatiotemporal mapping triboelectric recognition. A liquid metal-based flexible dual-mode triboelectric-capacitive-coupled (TCTS) array of 4 × pixels achieves spatial resolution 7 mm, exhibiting detection limit 0.8 Pa fast response 6 ms. Furthermore, neuromorphic computing using the MXene-based synaptic transistor 100% recognition accuracy handwritten numbers/letters within 90 epochs based on signals collected by TCTS array, cross-spatial information communication from perceived data realized in mixed reality space. The results illuminate considerable application possibilities technology human-machine interfaces advanced robotics.
Language: Английский
Citations
23
Materials Today, Journal Year: 2024, Volume and Issue: unknown
Published: Sept. 1, 2024
Language: Английский
Citations
23
EcoMat, Journal Year: 2024, Volume and Issue: 6(5)
Published: May 1, 2024
Abstract Sedentary, inadequate sleep and exercise can affect human health. Artificial intelligence (AI) Internet of Things (IoT) create the Intelligence (AIoT), providing possibility to solve these problems. This paper presents a novel approach monitor various behaviors for AIoT‐based health management using triboelectric nanogenerator (TENG) sensors. The insole with solely one TENG sensor, creating most simplified system that utilizes machine learning (ML) personalized motion monitoring, encompassing identity recognition gait classification. A cushion 12 sensors achieves real‐time sitting posture accuracy rates 98.86% 98.40%, respectively, effectively correcting sedentary behavior. Similarly, smart pillow, equipped 15 sensory channels, detects head movements during sleep, identifying 8 patterns 96.25% accuracy. Ultimately, constructing an analyze data, displaying status through human‐machine interfaces, offers potential help individuals maintain good image
Language: Английский
Citations
18
Advanced Functional Materials, Journal Year: 2024, Volume and Issue: 34(49)
Published: Aug. 8, 2024
Abstract Recent developments in robotics increasingly highlight the importance of sensing technology, especially tactile perception, enabling robots to effectively engage with their environment and interpret physical interactions. Due power efficiency low cost, triboelectric mechanism has been frequently studied for measuring pressure identifying materials enhance robot perception. Nevertheless, there limited exploration using effect detect curved surfaces, despite prevalence daily lives. Here, a multimodal sensor (TMTS) multilayered structural design is proposed recognize distinct materials, curvatures, simultaneously, thus decoupling different modalities enable more accurate detection. By attaching sensors robotic fingertips leveraging deep learning analytics, quantitative curvature measurement provides precise insights into an object's detailed geometric characteristics rather than merely assessing its overall shape, hence achieving automatic recognition 12 grasped objects 99.2% accuracy. The can be further used accurately softness under touch gestures hand, 94.1% accuracy, demonstrating significant potential wide‐ranging applications future robotic‐enabled intelligent society.
Language: Английский
Citations
17
Journal of Semiconductors, Journal Year: 2025, Volume and Issue: 46(1), P. 011610 - 011610
Published: Jan. 1, 2025
Abstract Multimodal sensor fusion can make full use of the advantages various sensors, up for shortcomings a single sensor, achieve information verification or security through redundancy, and improve reliability safety system. Artificial intelligence (AI), referring to simulation human in machines that are programmed think learn like humans, represents pivotal frontier modern scientific research. With continuous development promotion AI technology Sensor 4.0 age, multimodal is becoming more intelligent automated, expected go further future. this context, review article takes comprehensive look at recent progress on AI-enhanced sensors their integrated devices systems. Based concept principle technologies algorithms, theoretical underpinnings, technological breakthroughs, pragmatic applications fields such as robotics, healthcare, environmental monitoring highlighted. Through comparative study dual/tri-modal with without using (especially machine learning deep learning), highlight potential performance, data processing, decision-making capabilities. Furthermore, analyzes challenges opportunities afforded by offers prospective outlook forthcoming advancements.
Language: Английский
Citations
2
Nano Energy, Journal Year: 2024, Volume and Issue: 125, P. 109567 - 109567
Published: April 2, 2024
Language: Английский
Citations
9
Langmuir, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 2, 2025
Triboelectric nanogenerators (TENGs) offer a convenient means to convert mechanical energy from human movement into electricity, exhibiting the application prospects in behavior monitoring. Nevertheless, present methods improve device monitoring effect are limited design of triboelectric material level (control electron gain and loss ability). As compared with reported work, we TENG-based tactile sensors by optimizing structure electrode/triboelectric interface multiple strains mechanism. Cu@Ni double-clad waste woven fabrics used as electrodes, which characterized large number pores formed between fibers, greatly increasing specific surface area electrode generating dynamic strain under differentiated stress fields because their different elastic modulus. To be exact, resin layer undergoes deformation 0.64-4.47 kPa external new generates at induced slip 4.47-63.84 stress, resulting accumulation charges on PDMS surface. The establishment further facilitates generation distinct signal waveforms that easily distinguishable its amplitude peak form. Besides, combined deep machine learning effect, an open setting, identification accuracy five behaviors approaches 100%. This provides pathway for enhancing sensor.
Language: Английский
Citations
1
Materials Today Physics, Journal Year: 2024, Volume and Issue: 46, P. 101496 - 101496
Published: July 2, 2024
Language: Английский
Citations
6
Advanced Functional Materials, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 8, 2024
Abstract The combination of fluidity and metallic conductivity has attracted considerable attention to liquid metal (LM), but its development remains challenging due enormous surface tension. Here, vinyl‐terminated silicone oil platinum catalyst are added LM reduce tension, which develops a special type liquid‐metal‐silicone (LMS) ink with diffusion effect. Combined an embedded three‐dimentional (3D) printing method, the LMS is printed on support matrix, diffuses outward along print path cure around it, directly constructing self‐encapsulated conductive composites excellent flexible tactile sensors based triboelectric nanogenerator (TENG). sensor exhibits sensitivity (0.308 V kPa −1 ), high linearity (≈0.99), good durability (over 10 000 cycles). Furthermore, when used in wearable electronics, demonstrates performance accuracy ≈96% classifying different human postures using convolutional neural network. Finally, through 3D ink, somatosensory soft robotic gripper complex cavity structures designed manufactured one step, achieving all‐in‐one integration actuators. This study shows great application potential electronics systems.
Language: Английский
Citations
6
Advanced Functional Materials, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 14, 2024
Abstract Electronic skins (E‐skins) are poised to revolutionize human interaction not only with one another but also machines, electronics, and surrounding environment. However, the wearable E‐skin that simultaneously offers multiple sensing capabilities, high sensitivity, broad ranges remains a great challenge. Here, drawing inspiration from haptic perception, multimodal, ultrasensitive, biomimetic (MES) founded on micro‐frustum ionogel is developed based iontronic capacitive triboelectric effects for imaginary keyboard multifunctional cognition. Leveraging as layer layer, MES enables human‐dermis perception performances of sensitivity (357.56 kPa −1 ), low limit detection (0.47 Pa), linear range (0–500 kPa). Moreover, finger joint movements can be precisely monitored by attached transferred into accurate typed letter information an keyboard. More importantly, harnessing signal acquisition/processing circuits machine learning, real‐time cognition different materials, surface roughness, contact pressure achieved MES, which endows advancement between next‐generation intelligent robot physical Consequently, proposed demonstrates impressive potentials in fields human–machine (HMI), Artificial Intelligence (AI).
Language: Английский
Citations
6