Intelligent wearable olfactory interface for latency-free mixed reality and fast olfactory enhancement
Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay i...
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| Vydané v: | Nature Communications Ročník 15; číslo 1; s. 4474 - 15 |
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| Hlavní autori: | , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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London
Springer Science and Business Media LLC
25.05.2024
Nature Publishing Group UK Nature Publishing Group Nature Portfolio |
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| ISSN: | 2041-1723, 2041-1723 |
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| Abstract | Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces.
Liu et al. developed AI-driven, wearable olfactory interfaces with odor generators for realizing latency-free mixed-reality and fast olfaction recovery. This technology enables personalized olfactory feedback and enhanced virtual environments for various applications including education, and clinical treatment. |
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| AbstractList | Abstract Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces. Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces. Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces.Liu et al. developed AI-driven, wearable olfactory interfaces with odor generators for realizing latency-free mixed-reality and fast olfaction recovery. This technology enables personalized olfactory feedback and enhanced virtual environments for various applications including education, and clinical treatment. Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces.Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces. Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces. Liu et al. developed AI-driven, wearable olfactory interfaces with odor generators for realizing latency-free mixed-reality and fast olfaction recovery. This technology enables personalized olfactory feedback and enhanced virtual environments for various applications including education, and clinical treatment. |
| ArticleNumber | 4474 |
| Author | Hongting Chen Shengxin Jia Xingcan Huang Yiming Liu Xinge Yu Weike Song Wenyang Li Yuhang Li Yuyu Gao Wooyoung Park Chun Ki Yiu Zhenlin Chen Jin Nan Tomoyuki Yokota Takao Someya Zhao Zhao |
| Author_xml | – sequence: 1 givenname: Yiming orcidid: 0000-0003-0134-1934 surname: Liu fullname: Liu, Yiming organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong, Department of Electrical Engineering and Information systems, The University of Tokyo – sequence: 2 givenname: Shengxin orcidid: 0000-0002-6998-3872 surname: Jia fullname: Jia, Shengxin organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong, Hong Kong Center for Cerebra-Cardiovascular Health Engineering, Hong Kong Science Park, New Territories – sequence: 3 givenname: Chun Ki surname: Yiu fullname: Yiu, Chun Ki organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong, Hong Kong Center for Cerebra-Cardiovascular Health Engineering, Hong Kong Science Park, New Territories – sequence: 4 givenname: Wooyoung orcidid: 0000-0003-2250-3613 surname: Park fullname: Park, Wooyoung organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong – sequence: 5 givenname: Zhenlin surname: Chen fullname: Chen, Zhenlin organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong, Hong Kong Center for Cerebra-Cardiovascular Health Engineering, Hong Kong Science Park, New Territories – sequence: 6 givenname: Jin surname: Nan fullname: Nan, Jin organization: Institute of Solid Mechanics, Beihang University – sequence: 7 givenname: Xingcan orcidid: 0000-0003-4210-2470 surname: Huang fullname: Huang, Xingcan organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong – sequence: 8 givenname: Hongting surname: Chen fullname: Chen, Hongting organization: Department of Electrical Engineering and Information systems, The University of Tokyo – sequence: 9 givenname: Wenyang surname: Li fullname: Li, Wenyang organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong – sequence: 10 givenname: Yuyu surname: Gao fullname: Gao, Yuyu organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong – sequence: 11 givenname: Weike surname: Song fullname: Song, Weike organization: China Special Equipment Inspection and Research Institute – sequence: 12 givenname: Tomoyuki orcidid: 0000-0003-1546-8864 surname: Yokota fullname: Yokota, Tomoyuki organization: Department of Electrical Engineering and Information systems, The University of Tokyo, Institution of Engineering Innovation, The University of Tokyo – sequence: 13 givenname: Takao orcidid: 0000-0003-3051-1138 surname: Someya fullname: Someya, Takao email: someya@ee.t.u-tokyo.ac.jp organization: Department of Electrical Engineering and Information systems, The University of Tokyo, RIKEN Center for Emergent Matter Science (CEMS), Thin-film Device Laboratory, RIKEN – sequence: 14 givenname: Zhao orcidid: 0009-0005-3045-688X surname: Zhao fullname: Zhao, Zhao email: zhaozhao@csei.org.cn organization: China Special Equipment Inspection and Research Institute – sequence: 15 givenname: Yuhang orcidid: 0000-0001-9865-5221 surname: Li fullname: Li, Yuhang email: liyuhang@buaa.edu.cn organization: Institute of Solid Mechanics, Beihang University, Tianmushan Laboratory, NA, Aircraft and Propulsion Laboratory, Ningbo Institute of Technology Beihang University (BUAA), Liaoning Academy of Materials, NA – sequence: 16 givenname: Xinge orcidid: 0000-0003-0522-1171 surname: Yu fullname: Yu, Xinge email: xingeyu@cityu.edu.hk organization: Department of Biomedical Engineering, City University of Hong Kong, Kowloong Tong, Hong Kong Center for Cerebra-Cardiovascular Health Engineering, Hong Kong Science Park, New Territories, Hong Kong Institute for Clean Energy (HKICE), City University of Hong Kong |
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| Title | Intelligent wearable olfactory interface for latency-free mixed reality and fast olfactory enhancement |
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