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Nature Inspired Engineering: Biomimetic Sensors (2nd Edition)
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Nature Inspired Engineering: Biomimetic Sensors (2nd Edition)

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 20 September 2026 | Viewed by 11458

Special Issue Editors

Dr. Xiao Wu

E-Mail Website
Guest Editor
Department of Information Electronics, Faculty of Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-Higashi, Higashi-ku, Fukuoka 811-0295, Japan
Interests: electronic tongue; electronic nose; gas sensors; multi-array sensors; food analysis; data processing; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Kiyoshi Toko

E-Mail Website
Guest Editor
Division of Taste Sensor, Research and Development Center for Five-Sense Devices, Kyushu University, Fukuoka 819-0395, Japan
Interests: taste sensors; electronic tongues; electronic noses; biosensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Nature provides a huge source of inspiration for sensor design. Among them, electronic tongue and electronic nose are analytical devices based on a series of partially selective chemical sensors or biosensors and multivariate data processing tools. Since their design concepts are inspired by biological sensing systems, they are called biomimetic sensors. Over the past three decades, these sensors have been employed in a wide range of applications, including the classification of samples by purpose, taste quantification, and flavor assessment. Biomimetic sensors simulate the human perception system, detect various external stimuli, and surpass the level of human senses in terms of sensitivity, selectivity, and accuracy, helping people to understand the unknown world and facilitating daily life.

In this Special Issue, we will focus on the latest research on biomimetic sensors, from basic theory to application. We welcome both review articles and original research papers on, though not limited to, the following areas:

  • Biomimetic sensing materials;
  • Bioinspired sensors;
  • Electronic tongue;
  • Bioelectronic tongue;
  • Electronic nose;
  • Taste sensor;
  • Odor-sensing arrays;
  • Olfaction proteins;
  • Cell sensors;
  • Biomedical sensors;
  • Data analysis;
  • MEMS;
  • Environmental analysis;
  • Biomedical applications;
  • Gas Sensors;
  • Multi-Array Sensors;
  • Machine Learning;
  • AI (Artificial Intelligence);
  • Food Sensors;
  • Image Sensors;
  • Wearable Sensors.

Dr. Xiao Wu
Prof. Dr. Kiyoshi Toko
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomimetic sensors/sensing
  • bioinspired sensors/sensing
  • artificial intelligence (AI)

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Related Special Issue

Published Papers (9 papers)

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Research

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15 pages, 2551 KB  
Article
Headset-Type Biofluorometric Gas Sensor with CMOS for Transcutaneous Ethanol from the Ear Canal
by Geng Zhang, Di Huang, Kenta Ichikawa, Kenta Iitani, Yoshikazu Nakajima and Kohji Mitsubayashi
Sensors 2026, 26(9), 2817; https://doi.org/10.3390/s26092817 - 30 Apr 2026
Viewed by 588
Abstract
This study presents a headset-type biofluorometric gas sensor incorporating a CMOS camera for continuous, non-invasive monitoring of transcutaneous ethanol from the ear canal. The sensor employs alcohol dehydrogenase (ADH) to catalyze the NAD+-to-NADH conversion during ethanol oxidation, enabling quantitative measurement through [...] Read more.
This study presents a headset-type biofluorometric gas sensor incorporating a CMOS camera for continuous, non-invasive monitoring of transcutaneous ethanol from the ear canal. The sensor employs alcohol dehydrogenase (ADH) to catalyze the NAD+-to-NADH conversion during ethanol oxidation, enabling quantitative measurement through NADH fluorescence detection (λex = 340 nm, λem = 490 nm). The integrated system comprises a wireless CMOS camera, an ADH-immobilized cotton mesh enzyme membrane, UV-LED excitation source, optical bandpass filters, and a dual convex lens assembly housed in a 3D-printed headset powered by a lithium battery. Key improvements include a 3.5-fold enhancement in fluorescence collection efficiency achieved through optimized dual convex lens configuration. Systematic screening of seven cotton mesh materials identified Iwatsuki cotton mesh as the optimal enzyme immobilization substrate, exhibiting minimal autofluorescence and 14.2-fold higher water retention capacity compared to H-PTFE membranes. The glutaraldehyde-crosslinked ADH-immobilized cotton mesh maintained enzymatic activity for over 45 min with a 10-fold improvement in signal-to-noise ratio. The system demonstrated a dynamic detection range spanning 10 ppb to 10 ppm for gaseous ethanol and exhibited high selectivity against interfering volatile organic compounds in skin gas, including methanol, acetaldehyde, formaldehyde, and acetone. Human experiments validated the system’s practical performance. Following alcohol consumption, subjects wore the device for 50 min while real-time fluorescence monitoring captured dynamic ethanol concentration changes in the ear canal. The dose-dependent fluorescence response—approximately 2-fold higher at 0.4 g/kg versus 0.04 g/kg alcohol intake—correlated well with calibration data. This headset-type biofluorometric sensor enables unrestrained continuous monitoring of ear canal ethanol, providing a novel wearable platform for alcohol metabolism assessment with potential applications in health monitoring and clinical research. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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16 pages, 2349 KB  
Article
Effect of the Chemical Structure of Modifiers Used in the Receptive Membrane of an Umami Taste Sensor on Its Electrical Responses
by Kiyoshi Toko, Sota Otsuka, Mariko Koshi, Yuzuki Koga, Takeshi Onodera, Rui Yatabe and Toshiro Matsui
Sensors 2026, 26(6), 1787; https://doi.org/10.3390/s26061787 - 12 Mar 2026
Viewed by 394
Abstract
In our previous study, a taste sensor employing a lipid/polymer membrane modified with 2,6-dihydroxyterephthalic acid (2,6-DHTPA) enabled the detection of the umami substances monosodium glutamate (MSG) and inosinate monophosphate (IMP). The taste sensor was also able to evaluate the synergistic effect, an umami [...] Read more.
In our previous study, a taste sensor employing a lipid/polymer membrane modified with 2,6-dihydroxyterephthalic acid (2,6-DHTPA) enabled the detection of the umami substances monosodium glutamate (MSG) and inosinate monophosphate (IMP). The taste sensor was also able to evaluate the synergistic effect, an umami enhancement phenomenon that occurs between MSG and IMP. However, the structural requirements for modifiers capable of detecting IMP have not yet been clarified. In the present study, to elucidate these requirements, nine different modifiers were prepared, and taste sensor measurements for IMP were conducted in combination with 1H-NMR analysis. As a result, three distinct patterns were observed: (1) modifiers that exhibited chemical shift changes and generated a potential response in the positive direction (i.e., a positive potential response); (2) modifiers that showed chemical shift changes but produced either an almost zero or a negative potential response; and (3) modifiers that exhibited neither chemical shift changes nor any potential response. For receptor membranes that did not exhibit a positive response, the corresponding modifiers either lacked two carboxyl groups or did not possess intramolecular hydrogen bonding involving hydroxyl groups. From these results, it was clarified that the essential conditions for obtaining a positive potential response to IMP are that the modifier (1) contains two carboxyl groups and (2) possesses intramolecular hydrogen bonding. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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11 pages, 1389 KB  
Article
Evaluation of Viral Collection Efficiency with Antibody-Modified Magnetic Particles by Polymerase Chain Reaction Assay
by Masato Yasuura, Hiroki Ashiba and Ken-ichi Nomura
Sensors 2026, 26(3), 1019; https://doi.org/10.3390/s26031019 - 4 Feb 2026
Viewed by 407
Abstract
Polymerase chain reaction (PCR) is the primary method for virus detection; however, its complex preprocessing has prompted research into simpler immunoassay-based approaches. Among these, techniques using antibody-modified magnetic particles, exemplified by digital ELISA, provide ultra-high sensitivity comparable to PCR by efficiently capturing trace [...] Read more.
Polymerase chain reaction (PCR) is the primary method for virus detection; however, its complex preprocessing has prompted research into simpler immunoassay-based approaches. Among these, techniques using antibody-modified magnetic particles, exemplified by digital ELISA, provide ultra-high sensitivity comparable to PCR by efficiently capturing trace viruses and enabling concentration, washing, and transfer to microreactors. In this study, we evaluated the virus capture efficiency of antibody-modified magnetic particles based on quantitative PCR (qPCR). Influenza A virus (H1N1/A/Puerto Rico/8/1934) was tested with 1 μm magnetic beads modified with HA1 antibodies. As quantification becomes unreliable and difficult in an extremely low-concentration range near the detection limit of qPCR, low-concentration viral suspensions (105 copies/mL) were mixed with particle dispersions (up to 5 × 108 particles/mL) for 10 min, followed by magnetic separation and washing, and the remaining virus in each fraction was analyzed by qPCR. At the highest particle concentration, capture rates exceeded 80% relative to the initial suspension, indicating near-complete capturing when considering free nucleic acids. Time-course analysis showed that the capture rate reached saturation within 2 min, with approximately 90% of the saturation at 1 min. Furthermore, kinetic modeling of magnetic bead–virus binding reproduced experimental data. These findings demonstrate that short mixing times with high particle concentrations enable efficient virus capture, contributing to the development of rapid and highly sensitive immunoassay systems. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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17 pages, 3806 KB  
Article
Multivariate Gas Sensor E-Nose System with PARAFAC and Machine Learning Modeling for Quantifying and Classifying the Impact of Fishing Gears
by Vinie Lee Silva-Alvarado and Jaime Lloret
Sensors 2026, 26(1), 6; https://doi.org/10.3390/s26010006 - 19 Dec 2025
Cited by 1 | Viewed by 865
Abstract
The quality of seafood is intrinsically linked to the accumulated history of stress, feeding, handling, and physical damage imposed by the fishing gear employed. This study proposes an innovative methodology using an E-nose sensor. The study species was Sparus aurata. Eight fishing [...] Read more.
The quality of seafood is intrinsically linked to the accumulated history of stress, feeding, handling, and physical damage imposed by the fishing gear employed. This study proposes an innovative methodology using an E-nose sensor. The study species was Sparus aurata. Eight fishing gears were studied. The methodology integrates Parallel Factor Analysis (PARAFAC) for impact quantification and Machine Learning (ML) for classifying the fishing gear of origin. Longline was established as the method with the lowest deviation. The impact hierarchy, from highest to lowest deviation, is as follows: Aquaculture 50.61% (95% CI: 34%, 68%), Purse seine 37.92% (95% CI: 22%, 54%), Trawl 35.92% (95% CI: 21%, 51%), Gillnet (three panels) 27.69% (95% CI: 14%, 41%), Gillnet (single panel) 24.63% (95% CI: 9%, 40%), Gillnet (two panels) 18.12% (95% CI: 4%, 31%) and Hook and line 1.36% (95% CI: −10%, 13%). For the classification task, 33 ML models were evaluated. Subspace KNN model yielded the best results with an accuracy of 97.14% in the validation and 98.08% in the testing, using 35 variables. Using 10, 15, 20, 25, and 30 variables, an accuracy higher than 85% was achieved. These results demonstrate the high precision in fish traceability by exploiting the sensor response profile left by each fishing gear. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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22 pages, 4258 KB  
Article
A Few-Shot SE-Relation Net-Based Electronic Nose for Discriminating COPD
by Zhuoheng Xie, Yao Tian and Pengfei Jia
Sensors 2025, 25(15), 4780; https://doi.org/10.3390/s25154780 - 3 Aug 2025
Cited by 2 | Viewed by 1268
Abstract
We propose an advanced electronic nose based on SE-RelationNet for COPD diagnosis with limited breath samples. The model integrates residual blocks, BiGRU layers, and squeeze–excitation attention mechanisms to enhance feature-extraction efficiency. Experimental results demonstrate exceptional performance with minimal samples: in 4-way 1-shot tasks, [...] Read more.
We propose an advanced electronic nose based on SE-RelationNet for COPD diagnosis with limited breath samples. The model integrates residual blocks, BiGRU layers, and squeeze–excitation attention mechanisms to enhance feature-extraction efficiency. Experimental results demonstrate exceptional performance with minimal samples: in 4-way 1-shot tasks, the model achieves 85.8% mean accuracy (F1-score = 0.852), scaling to 93.3% accuracy (F1-score = 0.931) with four samples per class. Ablation studies confirm that the 5-layer residual structure and single-hidden-layer BiGRU optimize stability (h_F1-score ≤ 0.011). Compared to SiameseNet and ProtoNet, SE-RelationNet shows superior accuracy (>15% improvement in 1-shot tasks). This technology enables COPD detection with as few as one breath sample, facilitating early intervention to mitigate lung cancer risks in COPD patients. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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Review

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24 pages, 3992 KB  
Review
Overview of AI-Based Scent Creation
by Takamichi Nakamoto and Manuel Aleixandre
Sensors 2026, 26(8), 2568; https://doi.org/10.3390/s26082568 - 21 Apr 2026
Viewed by 844
Abstract
Although odor classification and odor quantification by e-nose have been studied for a long time, the next stage is to express a detected scent using language. The methods used to map molecular structure parameters, mass spectra, and sensor responses onto language expression are [...] Read more.
Although odor classification and odor quantification by e-nose have been studied for a long time, the next stage is to express a detected scent using language. The methods used to map molecular structure parameters, mass spectra, and sensor responses onto language expression are reviewed first. NLP (Natural Language Processing) is useful for that purpose. Conversely, the linguistic expression of the scent can be transformed into sensing data. The odor mixture can be generated so that the measured response pattern can be identical to that of the scent to be created. Two methods, optimization-based and generative AI-based ones, to search for the recipe of the created scent, are explained. Finally, the intended odor is generated using an olfactory display. We provide the latest information on the emerging technology of scent creation. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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29 pages, 24525 KB  
Review
From Biomarkers to Biosensors: Transforming Comorbidity Management in Dialysis Care
by Ali Fardoost, Koosha Karimi, Aratrika Bhattacharya, Viresh Patel, Matthew Lucien Saintyl, Samanthia Grace Welsh and Mehdi Javanmard
Sensors 2026, 26(6), 1929; https://doi.org/10.3390/s26061929 - 19 Mar 2026
Viewed by 606
Abstract
Patients receiving dialysis treatments suffer from a high rate of systemic comorbid conditions, including cardiovascular disease, mineral and bone disorders, chronic inflammation, amyloidosis, and recurring infections, leading to increased morbidity and mortality rates despite the progress made in the field of renal replacement [...] Read more.
Patients receiving dialysis treatments suffer from a high rate of systemic comorbid conditions, including cardiovascular disease, mineral and bone disorders, chronic inflammation, amyloidosis, and recurring infections, leading to increased morbidity and mortality rates despite the progress made in the field of renal replacement therapies. The aforementioned conditions result from the continued dysregulation and overproduction of molecular biomarkers, which cannot be adequately monitored by traditional, intermittent laboratory tests. This review critically assesses the newly developed biosensor technologies for the detection of major dialysis biomarkers, including potassium, phosphorus, parathyroid hormone (PTH), β2-microglobulin, creatinine, and cystatin C, with special emphasis on biosensors based on electrochemistry, optics, impedimetry, nanophotonics, and biological engineering techniques. These recent biosensors have been evaluated based on their analytical performance, the biofluids used in the studies, and their suitability for measuring relevant concentrations of these biomarkers. Special attention is given to biosensors capable of continuous operation or minimally invasive sampling, as well as to newly developed biofluid sampling techniques, including microneedle-, microtube-, and micropillar-based systems, for the long-term monitoring of the biomarkers in the serum of patients receiving dialysis treatments. The biosensing techniques for measuring infection biomarkers have also been discussed, given the high risk of bloodstream and access infections among patients receiving dialysis. The limitations of these biosensors include biofouling, calibration drift, and their integration into the dialysis treatment workflow. Finally, the future prospects of the recent biosensors offer the possibility of the proactive management of the high rate of comorbid conditions in this high-risk population of patients receiving dialysis treatments. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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37 pages, 4139 KB  
Review
Recent Advances in Metal–Organic Frameworks for Gas Sensors: Design Strategies and Sensing Applications
by Aviraj M. Teli, Sagar M. Mane, Sonali A. Beknalkar, Rajneesh Kumar Mishra, Wookhee Jeon and Jae Cheol Shin
Sensors 2026, 26(3), 956; https://doi.org/10.3390/s26030956 - 2 Feb 2026
Cited by 1 | Viewed by 1174
Abstract
Gas sensors are essential in areas such as environmental monitoring, industrial safety, and healthcare, where the accurate detection of hazardous and volatile gases is crucial for ensuring safety and well-being. Metal–organic frameworks (MOFs), which are crystalline porous materials composed of metal nodes and [...] Read more.
Gas sensors are essential in areas such as environmental monitoring, industrial safety, and healthcare, where the accurate detection of hazardous and volatile gases is crucial for ensuring safety and well-being. Metal–organic frameworks (MOFs), which are crystalline porous materials composed of metal nodes and organic linkers, have recently emerged as a versatile platform for gas sensing due to their adjustable porosity, high surface area, and diverse chemical functionality. This review provides a detailed overview of MOF-based gas sensors, beginning with the fundamental sensing mechanisms of physisorption, chemisorption, and charge transfer interactions with gas molecules. We explore design strategies, including functionalization and the use of composites, which improve sensitivity, selectivity, response speed, and durability. Particular attention is given to the influence of MOF morphology, pore size engineering, and framework flexibility on adsorption behavior. Recent developments are showcased across various applications, including the detection of volatile organic compounds (VOCs), greenhouse gases, toxic industrial chemicals, and biomedical markers. Finally, we address practical challenges such as humidity interference, scalability, and integration into portable platforms, while outlining future opportunities for real-world deployment of MOF-based sensors in environmental, industrial, and medical fields. This review highlights the potential of MOFs to transform next-generation gas sensing technology by integrating foundational material design with real-world applications. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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37 pages, 2180 KB  
Review
Recent Advances and Unaddressed Challenges in Biomimetic Olfactory- and Taste-Based Biosensors: Moving Towards Integrated, AI-Powered, and Market-Ready Sensing Systems
by Zunaira Khalid, Yuqi Chen, Xinyi Liu, Beenish Noureen, Yating Chen, Miaomiao Wang, Yao Ma, Liping Du and Chunsheng Wu
Sensors 2025, 25(22), 7000; https://doi.org/10.3390/s25227000 - 16 Nov 2025
Cited by 2 | Viewed by 2502
Abstract
Biomimetic olfactory and taste biosensors replicate human sensory functions by coupling selective biological recognition elements (such as receptors, binding proteins, or synthetic mimics) with highly sensitive transducers (including electrochemical, transistor, optical, and mechanical types). This review summarizes recent progress in olfactory and taste [...] Read more.
Biomimetic olfactory and taste biosensors replicate human sensory functions by coupling selective biological recognition elements (such as receptors, binding proteins, or synthetic mimics) with highly sensitive transducers (including electrochemical, transistor, optical, and mechanical types). This review summarizes recent progress in olfactory and taste biosensors focusing on three key areas: (i) materials and device design, (ii) artificial intelligence (AI) and data fusion for real-time decision-making, and (iii) pathways for practical application, including hybrid platforms, Internet of Things (IoT) connectivity, and regulatory considerations. We provide a comparative analysis of smell and taste sensing methods, emphasizing cases where integrating both modalities enhances sensitivity, selectivity, detection limits, and reliability in complex environments like food, environmental monitoring, healthcare, and security. Ongoing challenges are addressed with emerging solutions such as antifouling/self-healing interfaces, modular cartridges, machine learning (ML)-assisted calibration, and manufacturing-friendly approaches using scalable microfabrication and sustainable materials. The review concludes with a practical roadmap advocating for the joint development of receptors, materials, and algorithms; establishment of open standards for long-term stability; implementation of explainable/edge AI with privacy-focused analytics; and proactive collaboration with regulatory bodies. Collectively, these strategies aim to advance biomimetic smell and taste biosensors from experimental prototypes to dependable, commercially viable tools for continuous chemical sensing in real-world applications. Full article
(This article belongs to the Special Issue Nature Inspired Engineering: Biomimetic Sensors (2nd Edition))
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