Machine olfaction

Abstract: The human nose is still the primaryinstrument' used to assess the smell or flavour of various industrial products today, despite considerable and sustained attempts to develop new electronic instrumentation capable of mimicking its remarkable ability In this paper we review the research effort that has been carried out over the past 25 years or so to create an electronic nose Indoing so, we first provide a definition for the term electronic nose, and then discuss some of the technologies that have been explored in what is essentially an intelligent chemical array sensor systemwe summarize the applications of electronic noses to date and suggest where future applications may lie

Abstract: PART 1: INTRODUCTION TO OLFACTION: PERCEPTION, ANATOMY, PHYSIOLOGY AND MOLECULAR BIOLOGY.Introduction to Olfaction.Odor Classification Schemes Based on Adjective Descriptors.Odor Classification Based on Chemical Properties.Physiology and Anatomy of Olfaction.Molecular Biology of Olfaction.Taste.Final Comment.PART 2: CHEMICAL SENSING IN HUMANS AND MACHINES.Human Chemosensory Perception of Airborne Chemicals.Nasal Chemosensory Detection.Olfactory and Nasal Chemesthetic Detection of Mixtures of Chemicals.Physicochemical Determinants of Odor and Nasal Pungency.Human Chemical Sensing: Olfactometry.Instruments for Chemical Sensing: Gas Chromatography-Olfactometry.PART 3: ODOR HANDLING AND DELIVERY SYSTEMS.Introduction.Physics of Evaporation.Sample Flow System.Static System.Preconcentrator.Measurement of Sensor Directly Exposed to Ambient Vapor.Summary.PART 4: INTRODUCTION TO CHEMOSENSORS.Introduction.Survey and Classification of Chemosensors.Chemoresistors.Chemocapcitors.Potentiometric Odor Sensors.Gravimetric Odor Sensors.Optical Odor Sensors.Thermal (Calorimetric) Sensors.Amperometric Sensors.Summary of Chemical Sensors.PART 5: SIGNAL CONDITIONING AND PREPROCESSING.Introduction.Interface Circuits.Signal Conditioning.Signal Preprocessing.Noise in Sensors and Circuits.Outlook.Conclusions.Acknowledgements.PART 6: PATTERN ANALYSIS FOR ELECTRONIC NOSES.Introduction.Statistical Pattern Analysis Techniques.'Intelligent' Pattern Analysis Techniques.Outlook and Conclusions.PART 7: COMMERCIAL ELECTRONIC NOSE INSTRUMENTS.Introduction.Commercial Availability.Some Market Considerations.PART 8: OPTICAL ELECTRONIC NOSES.Introduction.Optical Vapor Sensing.The Tufts Artificial Nose.Conclusion.PART 9: HAND-HELD AND PALM-TOP MICROSENSOR SYSTEMS FOR GAS ANALYSIS.Introduction.Conventional Hand-Held Systems.Silicon-Based Microsensors.Summary and Outlook.PART 10: INTEGRATED ELECTRONIC NOSES AND MICROSYSTEMS FOR CHEMCIAL ANALYSIS.Introduction.Microcomponents for Fluid Handling.Integrated E-Nose Systems.Microsystems for Chemical Analysis.Future Outlook.PART 11: ELECTRONIC TONGUES AND COMBINATIONS OF ARTIFICIAL SENSES.Introduction.Electronic Tongues.The Combination or Fusion of Artificial Senses.Conclusions.PART 12: DYNAMIC PATTERN RECOGNITION METHODS AND SYSTEM IDENTIFICATION.Introduction.Dynamic Models and System Identification.Identifying a Model.Dynamic Models and Intelligent Sensor Systems.Outlook.PART 13: DRIFT COMPENSATION, STANDARDS, AND CALIBRATION METHODS.Physical Reasons for Drift and Sensor Poisoning.Examples of Sensor Drift.Comparison of Drift and Noise.Model Building Strategies.Calibration Transfer.Drift Compensation.Conclusions.PART 14: CHEMICAL SENSOR ARRAY OPTIMIZATION: GEOMETRIC AND INFORMATION THEORETIC APPROACHES.The Need for Array Performance Definition and Optimization.Historical Perspective.Geometric Interpretation.Noise Considerations.Non-linear Transformations.Array Performance as a Statistical Estimation Problem.Fisher Information Matrix and the Best Unbiased Estimator.Performance Optimization.Conclusions.PART 15: CORRELATING ELECTRONIC NOSE AND SENSORY PANEL DATA.Sensory Panel Methods.Applications of Electronic Noses for Correlating Sensory Data.Algorithms for Correlating Sensor Array Data with Sensory Panels.Correlations of Electronic Nose Data with Sensory Panel Data.Conclusions.PART 16: MACHINE OLFACTION FOR MOBILE ROBOTS.Introduction.Olfactory-Guided Behavior of Animals.Sensors and Signal Processing in Mobile Robots.Trail Following Robots.Plume Tracking Robots.Other Technologies in Developing Plume Tracking Systems.Concluding Remarks.PART 17: ENVIRONMENTAL MONITORING.Introduction.Special Considerations for Environmental Monitoring.Case Study 1: Livestock Odor Classification.Case Study 2: Swine Odor Detection Thresholds.Case Study 3: Biofilter Evaluation.Case Study 4: Mold Detection.Future Directions.PART 18: MEDICAL DIAGNOSTICS AND HEALTH MONITORING.Introduction.Special Considerations in Medical/Healthcare Applications.Monitoring Metabolic Defects in Humans Using a Conducting Polymer Sensor Array to Measure Odor.The Use of Electronic Nose for the Detection of Bacterial Vaginosis.Conclusion.PART 19: RECOGNITION OF NATURAL PRODUCTS.Introduction.Recent Literature Review.Sampling Techniques.Case-Study: The Rapid Detection of Natural Products as a Means of Identifying Plant Species.Case Study: Differentiation of Essential Oil-Bearing Plants.Conclusion and Future Outlook.PART 20: PROCESS MONITORING.Introduction.Previous Work.Special Considerations.Selected Process Monitoring Examples.Future ProspectsPART 21: FOOD AND BEVERAGE QUALITY ASSURANCE.Introduction.Literature Survey.Methodological Issues in Food Measurement with Electronic Nose.Selected Case.Conclusions.Future Outlook.PART 22: AUTOMOTIVE AND AEROSPACE APPLICATIONS.Introduction.Automotive Applications.Aerospace Applications.Polymer Composite Films.Electronic Nose Operation in Spacecraft.Method Development.Future Directions.Conclusion.PART 23: DETECTION OF EXPLOSIVES.Introduction.Previous Work.State-of-the-Art of Various Explosive Vapor Sensors.Case Study.Conclusions.Future Directions.PART 24: COSMETICS AND FRAGRANCES.Introduction.The Case for an Electronic Nose in Perfumery.Current Challenges and Limitations of Electronic Noses.Literature Review of Electronic Noses in Perfumery and Cosmetics.Special Considerations for using Electronic Noses to Classify and Judge Quality of Perfumes, PRMs, and Products.Case Study 1: Use in Classification of PRMs with Different Odor Character but of Similar Composition.Case Study 2: Use in Judging the Odor Quality of a Sunscreen Product.Conclusions.Future Directions.Index.

Abstract: Pattern analysis constitutes a critical building block in the development of gas sensor array instruments capable of detecting, identifying, and measuring volatile compounds, a technology that has been proposed as an artificial substitute for the human olfactory system. The successful design of a pattern analysis system for machine olfaction requires a careful consideration of the various issues involved in processing multivariate data: signal-preprocessing, feature extraction, feature selection, classification, regression, clustering, and validation. A considerable number of methods from statistical pattern recognition, neural networks, chemometrics, machine learning, and biological cybernetics have been used to process electronic nose data. The objective of this review paper is to provide a summary and guidelines for using the most widely used pattern analysis techniques, as well as to identify research directions that are at the frontier of sensor-based machine olfaction.

Abstract: Odors are sensations that occur when compounds (called odorants) stimulate receptors located in the olfactory epithelium at the roof of the nasal cavity. Odorants are hydrophobic, volatile compounds with a molecular weight of less than 300 daltons. Humans can recognize and distinguish up to 10 000 different substances on the basis of their odor quality. Odorant receptors (ORs) in the nasal cavity detect and discriminate among these thousands of diverse chemical ligands. An individual odorant can bind to multiple receptor types, and structurally different odorants can bind to a single receptor. Specific patterns of activation generate signals that allow us to discriminate between the vast number of distinct smells. The physicochemical attributes of odorants that induce specific odor sensations are not well understood. The genes that code for ORs have been cloned, and results from cloning studies indicate that ORs are members of a superfamily of hundreds of different G-protein-coupled receptors that possess seven transmembrane domains. A complete knowledge of structureodor relationships in olfaction awaits the three-dimensional analysis of this large family of ORs. Ultimately, simultaneous knowledge of the three-dimensional structure of ORs as well as odorants will allow us to develop a pattern recognition paradigm that can predict odor quality.