利用微型电子鼻高速感应气味

IF 11.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Nik Dennler, Damien Drix, Tom P. A. Warner, Shavika Rastogi, Cecilia Della Casa, Tobias Ackels, Andreas T. Schaefer, André van Schaik, Michael Schmuker
{"title":"利用微型电子鼻高速感应气味","authors":"Nik Dennler,&nbsp;Damien Drix,&nbsp;Tom P. A. Warner,&nbsp;Shavika Rastogi,&nbsp;Cecilia Della Casa,&nbsp;Tobias Ackels,&nbsp;Andreas T. Schaefer,&nbsp;André van Schaik,&nbsp;Michael Schmuker","doi":"10.1126/sciadv.adp1764","DOIUrl":null,"url":null,"abstract":"<div >Animals have evolved to rapidly detect and recognize brief and intermittent encounters with odor packages, exhibiting recognition capabilities within milliseconds. Artificial olfaction has faced challenges in achieving comparable results—existing solutions are either slow; or bulky, expensive, and power-intensive—limiting applicability in real-world scenarios for mobile robotics. Here, we introduce a miniaturized high-speed electronic nose, characterized by high-bandwidth sensor readouts, tightly controlled sensing parameters, and powerful algorithms. The system is evaluated on a high-fidelity odor delivery benchmark. We showcase successful classification of tens-of-millisecond odor pulses and demonstrate temporal pattern encoding of stimuli switching with up to 60 hertz. Those timescales are unprecedented in miniaturized low-power settings and demonstrably exceed the performance observed in mice. It is now possible to match the temporal resolution of animal olfaction in robotic systems. This will allow for addressing challenges in environmental and industrial monitoring, security, neuroscience, and beyond.</div>","PeriodicalId":21609,"journal":{"name":"Science Advances","volume":null,"pages":null},"PeriodicalIF":11.7000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.science.org/doi/reader/10.1126/sciadv.adp1764","citationCount":"0","resultStr":"{\"title\":\"High-speed odor sensing using miniaturized electronic nose\",\"authors\":\"Nik Dennler,&nbsp;Damien Drix,&nbsp;Tom P. A. Warner,&nbsp;Shavika Rastogi,&nbsp;Cecilia Della Casa,&nbsp;Tobias Ackels,&nbsp;Andreas T. Schaefer,&nbsp;André van Schaik,&nbsp;Michael Schmuker\",\"doi\":\"10.1126/sciadv.adp1764\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div >Animals have evolved to rapidly detect and recognize brief and intermittent encounters with odor packages, exhibiting recognition capabilities within milliseconds. Artificial olfaction has faced challenges in achieving comparable results—existing solutions are either slow; or bulky, expensive, and power-intensive—limiting applicability in real-world scenarios for mobile robotics. Here, we introduce a miniaturized high-speed electronic nose, characterized by high-bandwidth sensor readouts, tightly controlled sensing parameters, and powerful algorithms. The system is evaluated on a high-fidelity odor delivery benchmark. We showcase successful classification of tens-of-millisecond odor pulses and demonstrate temporal pattern encoding of stimuli switching with up to 60 hertz. Those timescales are unprecedented in miniaturized low-power settings and demonstrably exceed the performance observed in mice. It is now possible to match the temporal resolution of animal olfaction in robotic systems. This will allow for addressing challenges in environmental and industrial monitoring, security, neuroscience, and beyond.</div>\",\"PeriodicalId\":21609,\"journal\":{\"name\":\"Science Advances\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":11.7000,\"publicationDate\":\"2024-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.science.org/doi/reader/10.1126/sciadv.adp1764\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science Advances\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://www.science.org/doi/10.1126/sciadv.adp1764\",\"RegionNum\":1,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science Advances","FirstCategoryId":"103","ListUrlMain":"https://www.science.org/doi/10.1126/sciadv.adp1764","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

动物在进化过程中能够快速检测和识别短暂、间歇性接触的气味包,并在几毫秒内表现出识别能力。人工嗅觉在实现类似效果方面面临挑战--现有的解决方案要么速度缓慢,要么体积庞大、价格昂贵、耗电量大,限制了其在移动机器人实际应用场景中的适用性。在这里,我们介绍一种微型高速电子鼻,其特点是高带宽传感器读出、严格控制的传感参数和强大的算法。我们在高保真气味传递基准上对该系统进行了评估。我们展示了数十毫秒气味脉冲的成功分类,并演示了高达 60 赫兹的刺激切换时间模式编码。这些时间尺度在小型化低功耗设置中是前所未有的,而且明显超过了在小鼠身上观察到的性能。现在,机器人系统的时间分辨率可以与动物嗅觉相媲美。这将有助于应对环境和工业监测、安全、神经科学等领域的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-speed odor sensing using miniaturized electronic nose
Animals have evolved to rapidly detect and recognize brief and intermittent encounters with odor packages, exhibiting recognition capabilities within milliseconds. Artificial olfaction has faced challenges in achieving comparable results—existing solutions are either slow; or bulky, expensive, and power-intensive—limiting applicability in real-world scenarios for mobile robotics. Here, we introduce a miniaturized high-speed electronic nose, characterized by high-bandwidth sensor readouts, tightly controlled sensing parameters, and powerful algorithms. The system is evaluated on a high-fidelity odor delivery benchmark. We showcase successful classification of tens-of-millisecond odor pulses and demonstrate temporal pattern encoding of stimuli switching with up to 60 hertz. Those timescales are unprecedented in miniaturized low-power settings and demonstrably exceed the performance observed in mice. It is now possible to match the temporal resolution of animal olfaction in robotic systems. This will allow for addressing challenges in environmental and industrial monitoring, security, neuroscience, and beyond.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Science Advances
Science Advances 综合性期刊-综合性期刊
CiteScore
21.40
自引率
1.50%
发文量
1937
审稿时长
29 weeks
期刊介绍: Science Advances, an open-access journal by AAAS, publishes impactful research in diverse scientific areas. It aims for fair, fast, and expert peer review, providing freely accessible research to readers. Led by distinguished scientists, the journal supports AAAS's mission by extending Science magazine's capacity to identify and promote significant advances. Evolving digital publishing technologies play a crucial role in advancing AAAS's global mission for science communication and benefitting humankind.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信