Biocomputation Group, University of Hertfordshire, Hatfield AL10 9AB, UK.
International Centre for Neuromorphic Systems, Western Sydney University, Kingswood, 2747 NSW, Australia.
Sci Adv. 2024 Nov 8;10(45):eadp1764. doi: 10.1126/sciadv.adp1764. Epub 2024 Nov 6.
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.
动物已经进化到能够快速检测和识别短暂且间歇性的气味包,在几毫秒内表现出识别能力。人工嗅觉在实现可比结果方面面临挑战——现有解决方案要么速度慢;要么体积大、昂贵且耗电高,限制了其在移动机器人的实际场景中的适用性。在这里,我们引入了一种小型化高速电子鼻,其特点是具有高带宽传感器读数、严格控制的传感参数和强大的算法。该系统在高保真度气味输送基准上进行了评估。我们成功地对数十毫秒的气味脉冲进行了分类,并展示了高达 60 赫兹的刺激切换的时间模式编码。在小型化低功耗设置中,这些时间尺度是前所未有的,明显超过了在老鼠身上观察到的性能。现在可以在机器人系统中匹配动物嗅觉的时间分辨率。这将能够解决环境和工业监测、安全、神经科学等领域的挑战。