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Olfaction01:25

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The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
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Humans detect odors with the help of specialized cells located in the upper part of the nasal cavity, called olfactory receptor neurons (ORNs). ORNs possess hair-like structures called cilia, which are receptive to sensations from the inhaled air. When an odorant molecule binds to a specific receptor on the cell of the cilia, it leads to a series of events that ultimately cause the ORN to send electrical signals to the olfactory bulb in the brain through the olfactory nerves.
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The process of olfaction, also known as the sense of smell, is a sophisticated chemical response system. The specialized sensory neurons that facilitate this process, known as olfactory receptor neurons, are situated in an upper segment of the nasal cavity, known as the olfactory epithelium. Olfactory sensory neurons are bipolar, with their dendrites extending from the epithelium's apex into the mucus that lines the nasal cavity. Airborne molecules, when inhaled, traverse the olfactory...
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Artificial Olfactory Neuron for an In-Sensor Neuromorphic Nose.

Joon-Kyu Han1, Mingu Kang2, Jaeseok Jeong2

  • 1School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|April 15, 2022
PubMed
Summary

A novel neuromorphic electronic nose (E-nose) integrates gas sensors with transistor neurons, mimicking biological olfaction for efficient odor detection and analysis. This power-saving design is ideal for Internet of Things applications.

Keywords:
electronic nose (E-nose)electronic sommelierneuromorphic systemolfactory neuronspiking neural network (SNN)

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Area of Science:

  • Materials Science
  • Neuroscience
  • Computer Engineering

Background:

  • Conventional electronic noses (E-noses) require bulky conversion circuits, central processing units (CPUs), and memory, limiting their scalability and energy efficiency.
  • Mimicking biological olfactory systems offers a pathway to more efficient and compact sensory processing.
  • Spike-based communication in biological systems is key to reducing power consumption.

Purpose of the Study:

  • To demonstrate a neuromorphic module for an electronic nose (E-nose) by hybridizing chemoresistive gas sensors with transistor neurons.
  • To enable in-sensor neuromorphic functioning for simultaneous gas detection and spike signal encoding.
  • To develop a power-efficient and scalable E-nose for Internet of Things (IoT) applications.

Main Methods:

  • Hybridization of semiconductor metal oxide (SMO) chemoresistive gas sensors with single transistor neurons (1T-neurons) based on MOSFETs.
  • Utilizing a spiking neural network (SNN) to analyze complex mixed signals for odor source identification.
  • Implementing spike transmission inspired by biological olfactory systems for reduced power consumption.

Main Results:

  • Demonstrated a functional neuromorphic E-nose module capable of simultaneous gas detection and spike signal encoding.
  • Achieved odor identification by analyzing mixed signals using an SNN, eliminating the need for external conversion circuits, CPUs, and memory.
  • Realized significant power savings compared to conventional E-noses using deep neural networks (DNNs) due to spike transmission.

Conclusions:

  • The proposed neuromorphic E-nose offers a highly scalable and energy-efficient solution for gas sensing.
  • This technology bypasses the limitations of traditional E-nose architectures, paving the way for advanced IoT devices.
  • Successfully applied the neuromorphic E-nose as an electronic sommelier for wine classification, showcasing its practical utility.