Bioelectronic Artificial Nose Using Four-Channel Moth Antenna Biopotential Recordings

A. Myrick, T. Baker, K. Park, J. Hetling
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引用次数: 6

Abstract

The use of insect antennae as an odor sensor array was evaluated as a means to advance the current capabilities of " artificial nose" technology. A given species is highly sensitive to odors of survival interest (e.g. species-specific pheromones), but also to a broad range of other natural and anthropogenic compounds. The sensitivity of the antennae to some odors extends to the parts per billion range. In contrast, the best current artificial nose technology is able to detect compounds in the parts per million range. Here, a system designed to utilize four antenna biopotential signals suitable for field use and a computational analysis strategy which allows discrimination between specific odors, and between odor and background or unknown compounds, with high fidelity and in real time, is described. The automated analysis measures three parameters per odor response. Following a training period, a K nearest-neighbor (KNN) approach is used to classify an unknown odor, assuming equal prior probabilities. The algorithm can also declare an odor as "unknown". System responses to single filaments in an odor plume can be analyzed and classified in less than one second
利用四通道飞蛾天线生物电位记录的生物电子学人工鼻子
利用昆虫触角作为气味传感器阵列进行评估,以提高当前“人工鼻子”技术的能力。一个给定的物种对生存利益的气味高度敏感(例如,物种特有的信息素),但也对广泛的其他自然和人为化合物敏感。天线对某些气味的敏感度可以达到十亿分之一。相比之下,目前最好的人工鼻子技术能够检测到百万分之一范围内的化合物。本文描述了一个系统,该系统设计利用适合于现场使用的四个天线生物电位信号和计算分析策略,该策略允许对特定气味,气味与背景或未知化合物之间的区分,具有高保真度和实时性。自动分析测量每个气味反应的三个参数。经过一段训练后,假设相同的先验概率,使用K近邻(KNN)方法对未知气味进行分类。该算法还可以将气味声明为“未知”。系统对气味羽流中单个细丝的响应可以在不到一秒钟的时间内进行分析和分类
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