ReviewBiomedical engineering online2026
Operational mechanisms and application advances in artificial olfactory systems.
Review in Biomedical engineering online, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Artificial olfactory systems represent biomimetic platforms that emulate biological olfaction for volatile compound detection and discrimination. Biological olfaction achieves efficient perception through the specific binding of volatile molecules to olfactory receptors (OR), odorant-binding proteins (OBPs), and associated chemosensory proteins, followed by neural encoding, providing a theoretical foundation for artificial olfactory system design. This review synthesizes the current literature sourced from Web of Science, PubMed, and Scopus databases, with selection criteria emphasizing sensing mechanisms, device architectures, and translational applications. Bioelectronic nose platforms utilizing ORs, OBPs, and synthetic peptides are critically evaluated alongside nonbioreceptor-based sensing approaches, specifically colorimetric arrays employing chemo-responsive dyes and metal oxide semiconductor (MOS) sensors, which rely on synthetic rather than biological recognition elements. Four principal application domains constitute the thematic framework: medical diagnosis through breath volatile biomarker detection, food safety assessment via freshness monitoring, environmental surveillance of air and water quality, and public safety applications in hazardous substance detection. Signal processing methodologies encompassing feature extraction and machine learning-based pattern recognition are examined. Critical translational challenges including limited long-term stability of biological recognition elements, sensor drift, and environmental interference are addressed. The comparative analysis indicates that bioreceptor-based platforms achieve superior sensitivity suitable for trace biomarker detection, whereas nonbioreceptor-based sensors offer enhanced operational stability for continuous monitoring, and hybrid architectures integrating biological selectivity with robust synthetic transduction mechanisms represent a promising direction for next-generation devices.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.