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Shi Y, Shen G. Haptic Sensing and Feedback Techniques toward Virtual Reality. RESEARCH (WASHINGTON, D.C.) 2024; 7:0333. [PMID: 38533183 PMCID: PMC10964227 DOI: 10.34133/research.0333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 02/10/2024] [Indexed: 03/28/2024]
Abstract
Haptic interactions between human and machines are essential for information acquisition and object manipulation. In virtual reality (VR) system, the haptic sensing device can gather information to construct virtual elements, while the haptic feedback part can transfer feedbacks to human with virtual tactile sensation. Therefore, exploring high-performance haptic sensing and feedback interface imparts closed-loop haptic interaction to VR system. This review summarizes state-of-the-art VR-related haptic sensing and feedback techniques based on the hardware parts. For the haptic sensor, we focus on mechanism scope (piezoresistive, capacitive, piezoelectric, and triboelectric) and introduce force sensor, gesture translation, and touch identification in the functional view. In terms of the haptic feedbacks, methodologies including mechanical, electrical, and elastic actuators are surveyed. In addition, the interactive application of virtual control, immersive entertainment, and medical rehabilitation is also summarized. The challenges of virtual haptic interactions are given including the accuracy, durability, and technical conflicts of the sensing devices, bottlenecks of various feedbacks, as well as the closed-loop interaction system. Besides, the prospects are outlined in artificial intelligence of things, wise information technology of medicine, and multimedia VR areas.
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Affiliation(s)
- Yuxiang Shi
- School of Integrated Circuits and Electronics,
Beijing Institute of Technology, Beijing 100081, China
- Institute of Flexible Electronics,
Beijing Institute of Technology, Beijing 102488, China
| | - Guozhen Shen
- School of Integrated Circuits and Electronics,
Beijing Institute of Technology, Beijing 100081, China
- Institute of Flexible Electronics,
Beijing Institute of Technology, Beijing 102488, China
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Xi J, Yang H, Li X, Wei R, Zhang T, Dong L, Yang Z, Yuan Z, Sun J, Hua Q. Recent Advances in Tactile Sensory Systems: Mechanisms, Fabrication, and Applications. NANOMATERIALS (BASEL, SWITZERLAND) 2024; 14:465. [PMID: 38470794 DOI: 10.3390/nano14050465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 02/07/2024] [Accepted: 02/19/2024] [Indexed: 03/14/2024]
Abstract
Flexible electronics is a cutting-edge field that has paved the way for artificial tactile systems that mimic biological functions of sensing mechanical stimuli. These systems have an immense potential to enhance human-machine interactions (HMIs). However, tactile sensing still faces formidable challenges in delivering precise and nuanced feedback, such as achieving a high sensitivity to emulate human touch, coping with environmental variability, and devising algorithms that can effectively interpret tactile data for meaningful interactions in diverse contexts. In this review, we summarize the recent advances of tactile sensory systems, such as piezoresistive, capacitive, piezoelectric, and triboelectric tactile sensors. We also review the state-of-the-art fabrication techniques for artificial tactile sensors. Next, we focus on the potential applications of HMIs, such as intelligent robotics, wearable devices, prosthetics, and medical healthcare. Finally, we conclude with the challenges and future development trends of tactile sensors.
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Affiliation(s)
- Jianguo Xi
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
| | - Huaiwen Yang
- School of Integrated Circuit Science and Engineering, Beihang University, Beijing 100191, China
| | - Xinyu Li
- School of Integrated Circuit Science and Engineering, Beihang University, Beijing 100191, China
| | - Ruilai Wei
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
- Institute of Flexible Electronics, Beijing Institute of Technology, Beijing 102488, China
| | - Taiping Zhang
- Tianfu Xinglong Lake Laboratory, Chengdu 610299, China
| | - Lin Dong
- Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, Key Laboratory of Materials Physics, Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
| | - Zhenjun Yang
- Hefei Hospital Affiliated to Anhui Medical University (The Second People's Hospital of Hefei), Hefei 230011, China
| | - Zuqing Yuan
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
- Institute of Flexible Electronics, Beijing Institute of Technology, Beijing 102488, China
| | - Junlu Sun
- Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, Key Laboratory of Materials Physics, Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
| | - Qilin Hua
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
- Institute of Flexible Electronics, Beijing Institute of Technology, Beijing 102488, China
- Guangxi Key Laboratory of Brain-Inspired Computing and Intelligent Chips, Guangxi Normal University, Guilin 541004, China
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Zhang T, Zhao M, Zhai M, Wang L, Ma X, Liao S, Wang X, Liu Y, Chen D. Improving the Resolution of Flexible Large-Area Tactile Sensors through Machine-Learning Perception. ACS APPLIED MATERIALS & INTERFACES 2024; 16:11013-11025. [PMID: 38353218 DOI: 10.1021/acsami.3c17880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/01/2024]
Abstract
Industrial robots are the main piece of equipment of intelligent manufacturing, and array-type tactile sensors are considered to be the core devices for their active sensing and understanding of the production environment. A great challenge for existing array-type tactile sensors is the wiring of sensing units in a limited area, the contradiction between a small number of sensing units and high resolution, and the deviation of the overall output pattern due to the difference in the performance of each sensing unit itself. Inspired by the human somatosensory processing hierarchy, we combine tactile sensors with artificial intelligence algorithms to simplify the sensor architecture while achieving tactile resolution capabilities far greater than the number of signal channels. The prepared 8-electrode carbon-based conductive network achieves high-precision identification of 32 regions with 97% classification accuracy assisted by a quadratic discriminant analysis algorithm. Notably, the output of the sensor remains unchanged after 13,000 cycles at 60 kPa, indicating its excellent durability performance. Moreover, the large-area skin-like continuous conductive network is simple to fabricate, cost-effective, and can be easily scaled up/down depending on the application. This work may address the increasing need for simple fabrication, rapid integration, and adaptable geometry tactile sensors for use in industrial robots.
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Affiliation(s)
- Tong Zhang
- College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China
| | - Minghui Zhao
- College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China
| | - Mingxuan Zhai
- College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China
| | - Lisha Wang
- Laser Institute, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, Shandong 266000, China
| | - Xingyu Ma
- College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China
| | - Shengmei Liao
- College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China
| | - Xiaona Wang
- College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China
| | - Yijian Liu
- College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China
| | - Da Chen
- College of Electronic and Information Engineering, Shandong University of Science and Technology, 266590 Qingdao, China
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Tu X, Fang L, Zhang H, Wang Z, Chen C, Wang L, He W, Liu H, Wang P. Performance-Enhanced Flexible Self-Powered Tactile Sensor Arrays Based on Lotus Root-Derived Porous Carbon for Real-Time Human-Machine Interaction of the Robotic Snake. ACS APPLIED MATERIALS & INTERFACES 2024; 16:9333-9342. [PMID: 38345015 DOI: 10.1021/acsami.3c18714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Flexible tactile sensors play an important role in the development of wearable electronics and human-machine interaction (HMI) systems. However, poor sensing abilities, an indispensable external energy supply, and limited material selection have significantly constrained their advancement. Herein, a self-powered flexible triboelectric sensor (TES) is proposed by integrating lotus-root-derived porous carbon (PC) into polydimethylsiloxane (PDMS). Owing to the superior charge capturing capability of PC, the PDMS/PC (PPC)-based TES exhibits an open-circuit voltage (Voc) of 22.8 V when it is periodically patted by skin at the pressure of 2 N and the frequency of 1 Hz, which is 5 times higher than that of a pristine PDMS-based TES. Furthermore, the as-prepared self-powered TES exhibits a high sensitivity of 3.24 V kPa-1 below 15 kPa for detecting human motion signals, such as finger clicks, joint bends, etc. Last but not the least, after the assembly of a PPC-based TES array and construction of an HMI system, the robotic snake can be controlled remotely by recognizing finger touching signals. This work shows broad potential applications for the self-powered TES in the fields of intelligent robotics, flexible electronics, disaster relief, and intelligence spying.
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Affiliation(s)
- Xinbo Tu
- School of Materials Science and Engineering, Energy Materials and Devices Key Lab of Anhui Province for Photoelectric Conversion, Anhui University, Hefei, Anhui 230601, China
| | - Lin Fang
- School of Materials Science and Engineering, Energy Materials and Devices Key Lab of Anhui Province for Photoelectric Conversion, Anhui University, Hefei, Anhui 230601, China
| | - Haonan Zhang
- School of Materials Science and Engineering, Energy Materials and Devices Key Lab of Anhui Province for Photoelectric Conversion, Anhui University, Hefei, Anhui 230601, China
| | - Zixun Wang
- School of Materials Science and Engineering, Energy Materials and Devices Key Lab of Anhui Province for Photoelectric Conversion, Anhui University, Hefei, Anhui 230601, China
| | - Chen Chen
- School of Materials Science and Engineering, Energy Materials and Devices Key Lab of Anhui Province for Photoelectric Conversion, Anhui University, Hefei, Anhui 230601, China
| | - Longsen Wang
- School of Materials Science and Engineering, Energy Materials and Devices Key Lab of Anhui Province for Photoelectric Conversion, Anhui University, Hefei, Anhui 230601, China
| | - Wen He
- School of Materials Science and Engineering, Energy Materials and Devices Key Lab of Anhui Province for Photoelectric Conversion, Anhui University, Hefei, Anhui 230601, China
| | - Huawang Liu
- College of Artificial Intelligence, Nankai University, Tianjin 300071, China
| | - Peihong Wang
- School of Materials Science and Engineering, Energy Materials and Devices Key Lab of Anhui Province for Photoelectric Conversion, Anhui University, Hefei, Anhui 230601, China
- Hubei Key Laboratory of Electric Manufacturing and Packaging Integration (Wuhan University), Wuhan University, Wuhan, Hubei 430072, China
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Li R, Wei D, Wang Z. Synergizing Machine Learning Algorithm with Triboelectric Nanogenerators for Advanced Self-Powered Sensing Systems. NANOMATERIALS (BASEL, SWITZERLAND) 2024; 14:165. [PMID: 38251130 PMCID: PMC10819602 DOI: 10.3390/nano14020165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 12/25/2023] [Accepted: 01/07/2024] [Indexed: 01/23/2024]
Abstract
The advancement of the Internet of Things (IoT) has increased the demand for large-scale intelligent sensing systems. The periodic replacement of power sources for ubiquitous sensing systems leads to significant resource waste and environmental pollution. Human staffing costs associated with replacement also increase the economic burden. The triboelectric nanogenerators (TENGs) provide both an energy harvesting scheme and the possibility of self-powered sensing. Based on contact electrification from different materials, TENGs provide a rich material selection to collect complex and diverse data. As the data collected by TENGs become increasingly numerous and complex, different approaches to machine learning (ML) and deep learning (DL) algorithms have been proposed to efficiently process output signals. In this paper, the latest advances in ML algorithms assisting solid-solid TENG and liquid-solid TENG sensors are reviewed based on the sample size and complexity of the data. The pros and cons of various algorithms are analyzed and application scenarios of various TENG sensing systems are presented. The prospects of synergizing hardware (TENG sensors) with software (ML algorithms) in a complex environment and their main challenges for future developments are discussed.
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Affiliation(s)
- Roujuan Li
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China;
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Di Wei
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China;
| | - Zhonglin Wang
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China;
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0245, USA
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Chen X, Li H, Xu Z, Lu L, Pan Z, Mao Y. Electrospun Nanofiber-Based Bioinspired Artificial Skins for Healthcare Monitoring and Human-Machine Interaction. Biomimetics (Basel) 2023; 8:223. [PMID: 37366818 DOI: 10.3390/biomimetics8020223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/28/2023] Open
Abstract
Artificial skin, also known as bioinspired electronic skin (e-skin), refers to intelligent wearable electronics that imitate the tactile sensory function of human skin and identify the detected changes in external information through different electrical signals. Flexible e-skin can achieve a wide range of functions such as accurate detection and identification of pressure, strain, and temperature, which has greatly extended their application potential in the field of healthcare monitoring and human-machine interaction (HMI). During recent years, the exploration and development of the design, construction, and performance of artificial skin has received extensive attention from researchers. With the advantages of high permeability, great ratio surface of area, and easy functional modification, electrospun nanofibers are suitable for the construction of electronic skin and further demonstrate broad application prospects in the fields of medical monitoring and HMI. Therefore, the critical review is provided to comprehensively summarize the recent advances in substrate materials, optimized fabrication techniques, response mechanisms, and related applications of the flexible electrospun nanofiber-based bio-inspired artificial skin. Finally, some current challenges and future prospects are outlined and discussed, and we hope that this review will help researchers to better understand the whole field and take it to the next level.
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Affiliation(s)
- Xingwei Chen
- Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
| | - Han Li
- Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
| | - Ziteng Xu
- Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
| | - Lijun Lu
- Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
| | - Zhifeng Pan
- Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
| | - Yanchao Mao
- Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450001, China
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