Biosensors

25 pages, 843 KB

Open AccessReview

Nanocarbon as a Quantum Material for Biointerfaces and Magnetic Platforms in Theranostic Biomedicine in Oncology: A Critical Review

by Priscila M. Galdino, Barbara R. Geraldino, Nilséia A. Barbosa and Fernando M. Araújo-Moreira

Biosensors 2026, 16(9), 482; https://doi.org/10.3390/bios16090482 - 1 Sep 2026

Abstract

Nanostructured carbon materials are low-dimensional systems relevant to oncology biosensing, with their utility arising from an electronic structure coupled to defect and edge states, a charge-transfer behavior and optical response that report molecular binding, an interfacial chemistry governing contact with the analyte, and, [...] Read more.

Nanostructured carbon materials are low-dimensional systems relevant to oncology biosensing, with their utility arising from an electronic structure coupled to defect and edge states, a charge-transfer behavior and optical response that report molecular binding, an interfacial chemistry governing contact with the analyte, and, in selected cases, magnetic properties enabling manipulation and readout. In functional terms, these behaviors trace to specific quantum-relevant features—quantum confinement, edge and defect states, and the resulting size-dependent optical and charge-transfer responses—rather than to a generic quantum-material designation. This critical review treats nanocarbons as engineered biointerfaces whose performance is set by how the carbon surface behaves in biological fluid, how recognition chemistry is anchored, and how the binding event is transduced, with magnetic responsiveness, stability, reproducibility, and fabrication control as decisive constraints. The analysis separates three material classes—non-magnetic nanocarbon sensors, hybrid carbon–magnetic systems, and defect-associated or potentially metal-free magnetic carbons—while grading evidence as direct, adjacent, comparator-derived, or prospective. Directly, graphene, carbon nanotubes, carbon dots, graphene quantum dots, and magnetic carbon hybrids serve in electrochemical, optical and fluorescent, field-effect, and magnetic-assisted formats. Clinical translation, however, remains constrained by biofouling, protein-corona formation, matrix interference, unstable functionalization, batch variability, incomplete standardization, and scarce validation in real samples and patient cohorts. Metal-free or defect-associated magnetic carbons therefore warrant caution, remaining prospective platforms until the preservation of magnetic response, reproducible functionalization, matrix compatibility, safety, and measurable analytical advantage are directly demonstrated. Full article

(This article belongs to the Special Issue Nano-Carbons in Biosensors)

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15 pages, 6384 KB

Open AccessArticle

Interval-Level Validation of a Wearable Dry-Electrode ECG Biosensor Platform: A Proof-of-Concept Study

by Avshalom Shaffer, Daniel Possti, Yizhaq Shmayahu, Deganit Barak-Shinar, Roy Beigel, David Hochstein, Rona Haker, Yael Hanein, Hila Meiri, Oliana Vazhgovsky and Shai Tejman-Yarden

Biosensors 2026, 16(9), 481; https://doi.org/10.3390/bios16090481 - 1 Sep 2026

Abstract

Wearable dry-electrode electrocardiographic (ECG) systems may enable longer and more comfortable rhythm monitoring, but their interval-level measurement fidelity requires validation against reference acquisition systems. In this single-center proof-of-concept study, 20 participants (10 healthy volunteers and 10 cardiology patients) underwent simultaneous ECG recordings with [...] Read more.

Wearable dry-electrode electrocardiographic (ECG) systems may enable longer and more comfortable rhythm monitoring, but their interval-level measurement fidelity requires validation against reference acquisition systems. In this single-center proof-of-concept study, 20 participants (10 healthy volunteers and 10 cardiology patients) underwent simultaneous ECG recordings with a U.S. Food and Drug Administration (FDA)-cleared wearable dry-electrode platform (X-trodes System M) and a wired reference system (MP150 with ECG100C module, Biopac Systems). Three-minute paired segments were recorded and underwent temporal synchronization, bandpass filtering, baseline correction, automated discrete-wavelet peak detection in NeuroKit2 (version 0.2.10), and standardized manual adjudication. After predefined exclusions for temporal alignment and P-wave detection quality, agreement was assessed in nine cardiac and ten healthy participants for RR intervals and in seven cardiac and eight healthy participants for P-to-R peak intervals. RR interval agreement was excellent in the healthy and cardiac cohorts, with a mean bias of 0.4 ± 3.1 ms and 0.1 ± 4.6 ms and mean absolute error (MAE) of 0.97 ms and 1.28 ms, respectively. Intraclass correlation coefficient (ICC) was over 0.99 for both cohorts. P-to-R peak interval agreement was strong, with an MAE of 1.76 ms and 7.14 ms and ICC of 0.96 and 0.98, respectively. These findings provide preliminary evidence of interval-level agreement for the X-trodes wearable dry-electrode ECG biosensor platform under controlled, short-duration daytime conditions. Because the matched interval pairs were clustered within a small number of participants, the findings should be regarded as proof-of-concept evidence supporting larger ambulatory validation studies rather than as definitive clinical validation. Full article

(This article belongs to the Special Issue AI-Based Biosensors and Biomedical Imaging)

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23 pages, 3399 KB

Open AccessArticle

Behavioral Dynamics of Zebrafish Under Hydrodynamic Stimuli Induced by Magnetic Microactuator in Microfluidics

by Dineshkumar Loganathan, Pu-Hsiang Wang and Chia-Yuan Chen

Biosensors 2026, 16(9), 480; https://doi.org/10.3390/bios16090480 - 1 Sep 2026

Abstract

Behavioral investigation in zebrafish is essential for understanding adaptive responses, where learning represents a key process influenced by external stimuli. The applied stimulus plays a critical role in shaping such responses, therefore making physiologically relevant stimulation strategies important. Hydrodynamic stimuli represent one such [...] Read more.

Behavioral investigation in zebrafish is essential for understanding adaptive responses, where learning represents a key process influenced by external stimuli. The applied stimulus plays a critical role in shaping such responses, therefore making physiologically relevant stimulation strategies important. Hydrodynamic stimuli represent one such modality, providing a natural and non-invasive means of activating mechanosensory responses in aquatic organisms, thereby enabling behavioral manipulation in microfluidic environments. To address this, a microfluidic assay was developed to generate controlled hydrodynamic environments by employing multiple S-shaped magnetic microactuators (SMMAs). Further, motions of these SMMAs were independently controlled to produce spatiotemporally varying vortical flow fields, enabling flow-induced transportation of zebrafish larvae. Flow dynamics were characterized by employing micro-particle image velocimetry (µPIV). Compared to the control condition, transportation time under microactuator-assisted guidance was significantly reduced, with a maximum improvement of 94.3% observed for a representative target zone. Building on this validated transport capability, training-dependent behavioral adaptation was quantified using latency under repeated hydrodynamic-training, where a reduction of 82.7% was achieved. Post-training assessment further demonstrated short-term retention of the acquired behavioral response followed by progressive extinction. These findings demonstrate that the proposed paradigm serves as a foundational behavioral assay leveraging hydrodynamic cues for studying adaptive responses in microfluidics. Full article

(This article belongs to the Section Environmental, Agricultural, and Food Biosensors)

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25 pages, 5136 KB

Open AccessReview

Conducting Polymer–Nanomaterial Hybrids for Cancer Diagnostics

by Mingyu Bae and Jin-Ho Lee

Biosensors 2026, 16(9), 479; https://doi.org/10.3390/bios16090479 - 1 Sep 2026

Abstract

Cancer continues to pose a major global burden because of the high incidence and mortality, underscoring the urgent need for innovative and highly sensitive diagnostic technologies. Conducting polymer–nanomaterial (CP–NM) hybrid biosensors have become promising platforms for cancer biomarker detection, integrating the redox-active and [...] Read more.

Cancer continues to pose a major global burden because of the high incidence and mortality, underscoring the urgent need for innovative and highly sensitive diagnostic technologies. Conducting polymer–nanomaterial (CP–NM) hybrid biosensors have become promising platforms for cancer biomarker detection, integrating the redox-active and biocompatible nature of conducting polymers such as polyaniline (PANI), polypyrrole (PPy), and poly(3,4-ethylenedioxythiophene) (PEDOT) with the high surface area and charge transport properties of nanomaterials, including metallic nanoparticles, metal oxides, carbon-based nanostructures, and two-dimensional materials. The synergistic interfaces in these hybrids enable efficient electron transfer, signal amplification, and stable biomolecular immobilization, facilitating ultrasensitive and multiplexed detection of proteins, nucleic acids, and metabolites associated with tumor progression. This review highlights recent advances in CP–NM hybrid biosensors for cancer diagnostics, focusing on material design strategies, sensing mechanisms, and representative applications across electrochemical, optical, and mechanical modalities. Finally, key challenges and future perspectives are discussed, emphasizing the potential of CP–NM hybrid platforms to drive next-generation approaches for early cancer detection, therapeutic monitoring, and personalized healthcare. Full article

(This article belongs to the Special Issue Material-Based Biosensors and Biosensing Strategies)

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24 pages, 5730 KB

Open AccessArticle

A Low-Cost Wearable Multimodal Brain Signal Acquisition System Integrating EEG and fNIRS for Depression Detection

by Zihan Fei, Hao Li, Zhongyuan Ying, Xingxing Li, Yuezhou Zhang, Qizhi Zhao, Bin Lian, Weiming Cai, Jialin Cui, Tao Yu, Xianghong Zhao, Shuhao Lv, Zhengxiang Yu, Guanxiang Ding, Yuzhou Ying and Yuhang Zhu

Biosensors 2026, 16(9), 478; https://doi.org/10.3390/bios16090478 - 31 Aug 2026

Abstract

Wearable brain-imaging devices have been developed to meet the growing demand in the healthcare industry for long-term monitoring of brain signals in natural conditions, such as monitoring brain diseases and emotions. However, conventional EEG and fNIRS (functional near-infrared spectroscopy) devices are often expensive, [...] Read more.

Wearable brain-imaging devices have been developed to meet the growing demand in the healthcare industry for long-term monitoring of brain signals in natural conditions, such as monitoring brain diseases and emotions. However, conventional EEG and fNIRS (functional near-infrared spectroscopy) devices are often expensive, bulky and difficult to operate, making it difficult to monitor patients for long periods in natural conditions. To address these issues, this article proposes a low-cost, portable and multimodal wearable brain signal acquisition scheme. It combines EEG (electroencephalography) and fNIRS to reflect brain activity from different perspectives. In order to make it more wearable, a conductive rubber material is used as the electrode for the EEG. In this study, the corresponding experiments were used to verify the performance of the device. The first is the measurement of internal system noise, which satisfies the data acquisition of EEG and fNIRS at different gain levels. The α-rhythm experiment and the SSVEP (steady-state visual evoked potentials) experiment were used to validate the performance of EEG data acquisition. The performance of the fNIRS was verified by measuring changes in cerebral blood oxygen during breath-hold and breathing. In addition, by decomposing the raw fNIRS data with the VMD (variational mode decomposition) algorithm and performing correlation analysis, heart rate information was separated from the data. The performance of the proposed device was validated in the above experiments, confirming the feasibility of the design for multimodal data acquisition and meeting the requirements for portability and wearability. Furthermore, the proposed device was tested with 31 subjects (15 depressive subjects) to detect depression. Experiments proved the effectiveness of the multimodal signals, which outperformed single modal and surpassed EEG by 8.4% and fNIRS by 23.5%. Full article

(This article belongs to the Special Issue Latest Wearable Biosensors—2nd Edition)

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38 pages, 6386 KB

Open AccessReview

Beyond Detection Limits: Integrated Biosensors for Molecular Diagnostics, Longitudinal Monitoring, and Clinical Translation

by Nilanjan Roy, Michael Powers, Minelly Gonzalez and Luca Cucullo

Biosensors 2026, 16(9), 477; https://doi.org/10.3390/bios16090477 - 31 Aug 2026

Abstract

Biosensors are evolving from isolated analytical detectors into integrated systems for molecular diagnosis, longitudinal monitoring, dynamic tissue assessment, and clinical or preclinical decision support. This critical narrative review synthesizes literature from 2018 through July 2026 on biorecognition, biointerface engineering, transduction, wearable and microneedle [...] Read more.

Biosensors are evolving from isolated analytical detectors into integrated systems for molecular diagnosis, longitudinal monitoring, dynamic tissue assessment, and clinical or preclinical decision support. This critical narrative review synthesizes literature from 2018 through July 2026 on biorecognition, biointerface engineering, transduction, wearable and microneedle architectures, CRISPR diagnostics, and sensor-integrated microphysiological systems. Unlike previous work that primarily classifies biosensors by analyte, recognition chemistry, or transduction modality, this review provides a unified translational framework that shifts evaluation from analytical sensitivity alone to the ability of systems to generate reliable, longitudinal, and clinically actionable information. A central distinction is made among snapshot assays, repeated discrete measurements, and genuine molecular trajectories, which require reversible recognition, controlled sampling, calibration, drift management, and temporal fidelity. Across applications, translational maturity depends on the measurement pathway. Continuous glucose monitoring remains the clearest benchmark because it combines durable chemistry, reproducible manufacture, workflow integration, and demonstrated clinical benefit. Other platforms have reached authentic-matrix testing, feasibility, prospective validation, or regulatory clearance but remain limited by fouling, matrix effects, calibration transfer, incomplete sample-to-answer operation, device variability, and insufficient manufacturing evidence. Future progress requires durable interfaces, claim-matched validation, reproducible scale-up, interoperable data systems, and measurements that remain trustworthy across time, users, devices, and settings. Full article

(This article belongs to the Special Issue Biosensors for Monitoring and Diagnostics, 2nd Edition)

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15 pages, 6411 KB

Open AccessArticle

Low-Cost Self-Driven Liquid Biosensor Based on Metamaterials for Glioblastoma-Related Sample Detection

by Kanglong Chen, Minghui Du, Peiyuan Sun, Pei Yang and Xiaojun Wu

Biosensors 2026, 16(9), 476; https://doi.org/10.3390/bios16090476 - 30 Aug 2026

Abstract

A self-driven terahertz metamaterial liquid biosensor composed of channel-structured metamaterials and a quartz microcavity is proposed for glioblastoma sample detection. The device transports liquid samples via capillary force. The permittivity (ε_eff) of liquid suspensions is comprehensively analyzed to provide theoretical [...] Read more.

A self-driven terahertz metamaterial liquid biosensor composed of channel-structured metamaterials and a quartz microcavity is proposed for glioblastoma sample detection. The device transports liquid samples via capillary force. The permittivity (ε_eff) of liquid suspensions is comprehensively analyzed to provide theoretical support for the detection. For suspensions with the same contents, ε_eff decreases with increasing concentration, while under the same concentration condition, ε_eff decreases as particle size grows. An electric dipole resonance is excited at ~1.54 THz with theoretical sensitivity ≥ 242 GHz/RIU (where RIU denotes refractive index unit). For the same type of cell discrimination, the frequencies of the biosensor’s feature peaks shift from ~1.14, ~1.18, and ~1.20 THz with the rise in cell concentration of glioblastoma stem cell (GSC) suspension from 4 × 10⁵, 6 × 10⁵ to 8 × 10⁵ cells/mL, respectively. In addition, the GSC, U87 and U251—whose average diameters increase in that order—tested at the same concentration of 4 × 10⁵ cells/mL lead to feature peak shifts from ~1.14, ~1.17, and ~1.20 THz. Clear THz differences exist between healthy and patient serum, with peaks at 1.18 and 1.19 THz. The sensor effectively distinguishes cell suspensions but has limited serum discrimination capacity. The sensor retains cell morphology, requires little pretreatment, and is low-cost and fast for rapid glioblastoma clinical screening. Full article

(This article belongs to the Special Issue Terahertz Biophotonics: Advancing Biosensing Technologies)

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18 pages, 2726 KB

Open AccessArticle

Development of a Horseradish Peroxidase-Based Electrochemical Biosensor for Melatonin Detection

by Andra-Georgiana Trifan and Constantin Apetrei

Biosensors 2026, 16(9), 475; https://doi.org/10.3390/bios16090475 - 29 Aug 2026

Abstract

A horseradish peroxidase (HRP)-based electrochemical biosensor was developed for melatonin (MLT) detection using a graphene-modified screen-printed electrode (G/SPE). HRP was immobilized at different temperatures (4 °C and 20 °C) and enzyme amounts (10 and 20 µL of 5 mg/mL HRP solution) to optimize [...] Read more.

A horseradish peroxidase (HRP)-based electrochemical biosensor was developed for melatonin (MLT) detection using a graphene-modified screen-printed electrode (G/SPE). HRP was immobilized at different temperatures (4 °C and 20 °C) and enzyme amounts (10 and 20 µL of 5 mg/mL HRP solution) to optimize the performance of the biosensors. FTIR analysis confirmed successful enzyme immobilization, while differential pulse voltammetry (DPV) showed a clear oxidation peak of MLT at 1.1 V with enhanced current responses for HRP-modified electrodes. The optimal biosensor, prepared at 4 °C with 10 µL enzyme of 5 mg/mL HRP solution, exhibited the best analytical performance, with a linear range of 0.4–3.6 µM, and a detection limit of 1.02 µM. Kinetic studies confirmed strong enzyme-substrate affinity, while the biosensors demonstrated excellent repeatability and a good stability. The method was successfully validated on pharmaceutical products, proving to be a reliable and an accurate tool for MLT quantification in real samples. Full article

(This article belongs to the Special Issue Advanced Nanomaterial-Based Electrochemical Biosensors and Their Applications)

36 pages, 34395 KB

Open AccessReview

Research Advances and Future Perspectives of Point-of-Care Detection Technologies and Biosensors for Mosquito-Borne Viruses

by Erkang Bian, Ruohang Wang, Kun Yin and Xiong Ding

Biosensors 2026, 16(9), 474; https://doi.org/10.3390/bios16090474 - 29 Aug 2026

Abstract

Mosquito-borne viruses, including dengue, Zika and chikungunya viruses, place a substantial burden on diagnostic services, especially where molecular laboratories are inaccessible or slow to return results. Point-of-care biosensors could reduce turnaround times and bring testing closer to patients in primary care, outbreak response, [...] Read more.

Mosquito-borne viruses, including dengue, Zika and chikungunya viruses, place a substantial burden on diagnostic services, especially where molecular laboratories are inaccessible or slow to return results. Point-of-care biosensors could reduce turnaround times and bring testing closer to patients in primary care, outbreak response, and field settings. This review critically examines nucleic acid amplification, CRISPR-assisted assays, lateral-flow platforms, microfluidic systems, electrochemical and optical biosensors, paper-based devices, and smartphone-enabled readouts. These technologies are evaluated in terms of sample preparation, analytical sensitivity and specificity, matrix interference, multiplexing, workflow integration, cost, and clinical validation. Overall, nucleic-acid-amplification and CRISPR-assisted platforms often achieve low reported detection limits under controlled conditions; lateral-flow and paper-based devices offer relatively simple and minimally instrumented workflows; and microfluidic, electrochemical, and smartphone-enabled systems support increasing levels of workflow integration, quantitative readout, and connectivity. However, few platforms currently integrate these advantages into a fully integrated and clinically validated “sample-to-result” workflow. Due to sample heterogeneity, viral strains, reference methods, assay conditions, and disparities in reporting practices, conducting meaningful cross-study comparisons remains challenging. Limited comparisons and insufficient prospective clinical and field validation further restrict the assessment of practical diagnostic utility. Therefore, strong analytical performance alone should not be interpreted as evidence of clinical validity. Priority directions include unified definitions of performance and reporting units, standardized validation protocols and external quality assessment, prospective multi-site evaluation using representative populations and specimens, and earlier consideration of manufacturing scalability, reagent stability, quality systems, and applicable regulatory requirements. Future platforms should integrate simplified sample preparation, multiplex detection, objective digital or AI-assisted interpretation, and secure connectivity while demonstrating measurable benefits for patient management and outbreak surveillance. Full article

(This article belongs to the Special Issue Nanobiosensors for the Rapid Detection of Mosquito-Borne Viruses: Advances, Challenges, and Future Perspectives)

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45 pages, 49097 KB

Open AccessReview

Microfluidic Single-Cell Bioanalysis for Decoding Tumor Heterogeneity

by Xingyu Tao, Shuang Feng, Yi Luo, Zhenfei Yu, Ruiheng Wang and Ru-Jia Yu

Biosensors 2026, 16(9), 473; https://doi.org/10.3390/bios16090473 - 28 Aug 2026

Abstract

Tumor heterogeneity drives cancer progression, dissemination, therapeutic adaptation, and relapse, yet many clinically relevant cell states are rare, transient, context-dependent, and obscured by population-averaged analysis. This review examines how microfluidic platforms preserve biologically meaningful linkages among cell identity, molecular state, secreted output, functional [...] Read more.

Tumor heterogeneity drives cancer progression, dissemination, therapeutic adaptation, and relapse, yet many clinically relevant cell states are rare, transient, context-dependent, and obscured by population-averaged analysis. This review examines how microfluidic platforms preserve biologically meaningful linkages among cell identity, molecular state, secreted output, functional phenotype, perturbation history, and microenvironmental context, which are frequently disrupted by conventional workflows. We first define analytical requirements imposed by tumor heterogeneity, then examine microwell- and microchamber-based systems, droplet microfluidic platforms, valve-assisted and other active manipulation or capture systems, and integrated multimodal workflows that preserve single-cell information while introducing distinct engineering trade-offs. We further discuss major readout modalities, including genomic and transcriptomic profiling, extracellular vesicle and secretome analysis, metabolic measurements, and proteomic readouts, and applications in circulating tumor-cell dissemination, tumor–microenvironment interactions, and therapy-response heterogeneity. Finally, we highlight bottlenecks in measurement fidelity, source attribution, reproducibility, benchmarking, biological representation, multimodal integration, and clinical validation. We propose that microfluidic single-cell oncology should advance from descriptive profiling toward decision-oriented systems that preserve cell-resolved states, source-attributed outputs, perturbation histories, and longitudinal responses within reproducible workflows and connect them to clinically actionable information. Full article

(This article belongs to the Special Issue Biosensing of Cell Heterogeneity and Circulating Biomarker Dynamics)

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25 pages, 15848 KB

Open AccessArticle

NIRSLINK: A Modular Cascaded Wearable Near-Infrared Spectroscopy System for High-Speed Multi-Site Hemodynamic Monitoring

by Shuo Zhang, Kangkang Xu, Nan Zeng, Jiansong Sun, Qianrui Yang, Qianke Zeng, Zheng Ding, Yanyu Lu, Jian Zhao, Mohamad Sawan, Shan Fu, Guoxing Wang and Cheng Chen

Biosensors 2026, 16(9), 472; https://doi.org/10.3390/bios16090472 - 28 Aug 2026

Abstract

Wearable near-infrared spectroscopy (NIRS) enables non-invasive hemodynamic monitoring, yet conventional CW-NIRS systems suffer from limited temporal resolution, scalp-only measurement, and mandatory manual tuning to compensate for optical heterogeneity across subjects and sites. This work develops NIRSLINK, a modular cascaded wearable NIRS system for [...] Read more.

Wearable near-infrared spectroscopy (NIRS) enables non-invasive hemodynamic monitoring, yet conventional CW-NIRS systems suffer from limited temporal resolution, scalp-only measurement, and mandatory manual tuning to compensate for optical heterogeneity across subjects and sites. This work develops NIRSLINK, a modular cascaded wearable NIRS system for high-speed multi-site hemodynamic acquisition. Its flexible probes adopt spring-floating optics with a standardized 30 mm optode separation, integrating dual 735/850 nm LEDs, silicon photodiodes, and a two-stage closed-loop tuning algorithm. A single probe achieves a peak sampling rate of 3 kHz, and up to eight cascaded probes form 52 valid channels, with a signal-to-noise ratio (SNR) of 78.61 ± 7.03 dB and an optical dynamic range (DR) of 101.32 ± 12.41 dB. Phantom experiments verify its millisecond temporal resolution and high sensitivity to blood flow and hemoglobin variations. In vivo trials, including the Valsalva maneuver, forearm occlusion, and two-back cognitive tasks, demonstrate simultaneous recording of hemoglobin concentration shifts, pulse waveforms, and beat-to-beat pulse transit times (PTTs). NIRSLINK supports hemodynamic measurements across multiple anatomical locations, including the forehead, forearm, upper arm, and thigh, covering both cranial and peripheral body regions. The embedded auto-tuning module stabilizes signals from the forehead, forearm, and other regions within the optimal ADC range without manual adjustment, preventing signal saturation and SNR degradation. This scalable adaptive platform overcomes critical drawbacks of traditional wearable NIRS, applicable to cognitive neuroscience, non-invasive cardiovascular assessment, and ambulatory physiological monitoring, and provides design references for multi-site optical sensors. Full article

(This article belongs to the Special Issue Wearable Sensors and Biosensors for Physiological Signals Measurement)

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20 pages, 4569 KB

Open AccessArticle

Skin Calorimetry of the Vastus Lateralis During Incremental Exercise: Thermal Analysis and Modeling

by Pedro Jesús Rodríguez de Rivera, Miriam Rodríguez de Rivera, Fabiola Socorro, Eduardo Garcia-Gonzalez, Elisabetta De Nigris, Jose A. L. Calbet and Manuel Rodríguez de Rivera

Biosensors 2026, 16(9), 471; https://doi.org/10.3390/bios16090471 - 27 Aug 2026

Abstract

In this study, we examined the thermal response of the vastus lateralis muscle using a skin calorimeter designed for localized measurements. Five healthy young male participants (20–23 years old) performed an incremental test on a cycle ergometer at 20 W·min⁻¹ until exhaustion. [...] Read more.

In this study, we examined the thermal response of the vastus lateralis muscle using a skin calorimeter designed for localized measurements. Five healthy young male participants (20–23 years old) performed an incremental test on a cycle ergometer at 20 W·min⁻¹ until exhaustion. The calorimeter’s thermostat was maintained at 30 °C. Ambient temperature was 23 ± 1 °C, and relative humidity ranged from 55% to 60%. The measured heat flow was modeled using functions relating mechanical power output to the thermal response. The model included the exercise phase, recovery, and sweat evaporation. The proposed model accurately reproduced the experimental data and supported a physiological interpretation of the main thermal effects. Two major contributions were identified and physiologically interpreted as muscle warming due to increased metabolic activity and a cooling effect likely linked to changes in blood perfusion. For an area of 2 × 2 cm² and an incremental exercise of 20 W·min⁻¹, the following values were obtained: (1) a resting heat loss of 150 ± 20 mW; (2) an exponential increase due to exercise of 0.4 ± 0.1 mW·W⁻¹, with a time constant of 1.0 ± 0.3 min; and (3) a negative blood-flow contribution described by a function that, in the steady state, has an amplitude of −20 ± 9 mW. Since only five participants were included, correlations with anthropometric variables were treated as exploratory consistency checks. These results demonstrate the usefulness of the calorimeter for decomposing and quantifying muscle thermal dynamics during exercise. Full article

(This article belongs to the Special Issue Portable, Wearable and Wireless Biosensing Technologies)

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65 pages, 21130 KB

Open AccessReview

Artificial Intelligence in Electrochemical Sensing: A Network Evidence Map of Translational Barriers and Pathways to Point-of-Care Deployment

by Muhammad Saqib, Elena I. Korotkova, Kunquan Li, Neda Firoz, Mrinal Vashisth, Amrit L. Hui, Olga I. Lipskikh and Pradip Kumar Kar

Biosensors 2026, 16(9), 470; https://doi.org/10.3390/bios16090470 - 27 Aug 2026

Abstract

The integration of artificial intelligence (AI) and machine learning (ML) with electrochemical sensing has revolutionized analytical diagnostics by overcoming traditional limitations such as signal drift, peak overlapping, and matrix interference. However, despite the exponential growth of this field, a unified framework evaluating translational [...] Read more.

The integration of artificial intelligence (AI) and machine learning (ML) with electrochemical sensing has revolutionized analytical diagnostics by overcoming traditional limitations such as signal drift, peak overlapping, and matrix interference. However, despite the exponential growth of this field, a unified framework evaluating translational feasibility remains absent. This review critically analyzes AI/ML architectures applied to electrochemical sensors and biosensors from 2016 to 2025. To the best of our knowledge, this work introduces the first coded Network Evidence Map to quantitatively map the co-occurrence of methodological strengths, weaknesses, and translational barriers across the examined literature. The analysis reveals that while deep learning and ensemble models excel in signal deconvolution and multiplexing, the field is severely constrained by systemic bottlenecks. Network pathways demonstrate that over 83% of studies lack uncertainty quantification, and data scarcity coupled with restricted data-sharing policies critically undermines model reproducibility. Furthermore, batch-to-batch hardware variability measurably co-occurs with the opacity of black-box algorithms, hindering regulatory approval. We conclude that advancing from laboratory proof-of-concept to real-world point-of-care deployment necessitates a paradigm shift toward open-source electrochemical repositories, explainable AI (XAI), physics-informed machine learning, and hardware-software co-design. Full article

(This article belongs to the Special Issue Electrochemical Biosensors for Environmental and Food Safety)

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24 pages, 10814 KB

Open AccessArticle

A Spiking Neural Network for Non-Invasive Glucose Estimation on Wearable Bioimpedance Biosensors, with a Multiplication-Free Neuromorphic Path

by Matheus Willian Sprotte and Pedro Bertemes Filho

Biosensors 2026, 16(9), 469; https://doi.org/10.3390/bios16090469 - 27 Aug 2026

Abstract

Wearable glucose monitoring demands low-power local processing, but conventional neural networks rely on energy-intensive multiply–accumulate (MAC) operations that limit battery life. This study shows that a Spiking Neural Network (SNN), built on a regression-adapted Leaky Integrate-and-Fire (LIF) neuron, can estimate blood glucose from [...] Read more.

Wearable glucose monitoring demands low-power local processing, but conventional neural networks rely on energy-intensive multiply–accumulate (MAC) operations that limit battery life. This study shows that a Spiking Neural Network (SNN), built on a regression-adapted Leaky Integrate-and-Fire (LIF) neuron, can estimate blood glucose from multi-frequency bioimpedance and auxiliary biosignals with clinically auditable accuracy at low computational and memory cost. Using data from 98 patients (717 measurements, eGluco3 device, Azambuja Hospital, Brusque, Brazil) evaluated by 5-fold walk-forward cross-validation under ISO 15197:2013, three main findings emerge. First, a new calibration method—the Patient Fingerprint, built from each patient’s first K sensor readings—outperforms conventional one-hot patient encoding (14.2 ± 2.6 mg/dL vs. 15.4 ± 3.3 mg/dL mean absolute error) and, unlike one-hot, requires only these K readings rather than the patient’s presence in the training set; a leave-patients-out analysis confirms that the fingerprint captures individual physiology and that unseen-patient accuracy improves with calibration depth but remains clinically insufficient (MAE

94.8 \to 65.9

mg/dL from

K = 3

to

K = 5

), positioning clinical-grade cross-patient generalization on a larger cohort as the primary scaling axis. Second, the direct-injection fingerprint model reaches 100% of the samples within Consensus Error Grid Zones A+B across all validation folds (the rate-coding variant reaches 98.8%, just below the 99% Criterion B threshold), without requiring any demographic or clinical metadata; sensor history alone renders such records redundant; and Criterion A, however, stays below the 95% normative threshold, so the results support clinical safety rather than formal certification. Third, replacing the analog input encoding with a multiplication-free rate-coding scheme removes all first-layer MAC operations at a cost of 2.7 mg/dL additional error; because the additional microticks raise the total operation count, this defines a design lever whose energy payoff is specific to neuromorphic hardware rather than a net saving on conventional microcontrollers. Together, these results demonstrate that SNNs offer a clinically auditable, self-calibrating, and memory-efficient path to continuous glucose estimation on embedded wearable devices. Full article

(This article belongs to the Special Issue Bioimpedance-Based Biosensors)

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21 pages, 3978 KB

Open AccessArticle

An Optically Silent Epoxysilane Chemistry for Paper-Based ABO Blood Typing

by Chinnawut Pipatpanukul, Komkrisd Wongtimnoi, Laurent Mezeix and Santi Phosri

Biosensors 2026, 16(9), 468; https://doi.org/10.3390/bios16090468 - 27 Aug 2026

Abstract

Safe transfusion depends on rapid, accurate ABO typing, yet reference methods require centrifuges and instrumentation unavailable at the point of need. Here, a paper-based ABO-RhD typing device built on a covalent, optically silent surface chemistry is reported. Aminosilane (APTES) and epoxysilane (GPTMS) functionalisation [...] Read more.

Safe transfusion depends on rapid, accurate ABO typing, yet reference methods require centrifuges and instrumentation unavailable at the point of need. Here, a paper-based ABO-RhD typing device built on a covalent, optically silent surface chemistry is reported. Aminosilane (APTES) and epoxysilane (GPTMS) functionalisation of Whatman cellulose was compared by water contact angle, energy-dispersive X-ray spectroscopy (SEM-EDS) and infrared spectroscopy (FT-IR) across two paper grades, three silane concentrations (5, 10 and 20% v/v) and three reaction times (1–6 h). APTES produced a strongly hydrophobic layer that impeded aqueous wicking, and its glutaraldehyde activation generated a red-brick chromophore incompatible with a red-channel readout. GPTMS coupled antibodies in a single mild step, without a crosslinker or visible chromophore, while preserving wicking. GPTMS (10% v/v, 3 h, Whatman No. 4) with a six-cycle 100 µL saline wash was selected; antibodies were immobilised in a four-zone layout (anti-A, anti-B, anti-D and control) within a 3D-printed two-compartment housing that traps agglutinated cells while free cells wash through. On 80 EDTA clinical blood samples (20 each of groups A, B, AB and O) the device classified every sample correctly (accuracy 100%; 95% confidence interval 95.4–100%), with visual and instrumented reads in full agreement. All samples were RhD-positive, so the anti-D channel is validated here for the positive call. Full article

(This article belongs to the Section Biosensor Materials)

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16 pages, 2666 KB

Open AccessFeature PaperArticle

Systematic Benchmarking of a Dry Electrode EEG Prototype Against Wet Electrode EEG Systems in Electrophysiological/Cognitive Scenarios

by Boli Pan, Shuo Ding, Yingbo Geng, Jiacheng Liang, Fali Li, Gang Wang, Xirong Li, Yanbin Dong and Rihui Li

Biosensors 2026, 16(9), 467; https://doi.org/10.3390/bios16090467 - 27 Aug 2026

Abstract

Objective: Recent advances in dry electrode EEG have enabled rapid setup and recording in unconventional scenarios. However, past developments were primarily driven by brain–computer interfaces (BCI), leaving their comparability to wet electrodes in clinical and daily life applications an open question. Here, we [...] Read more.

Objective: Recent advances in dry electrode EEG have enabled rapid setup and recording in unconventional scenarios. However, past developments were primarily driven by brain–computer interfaces (BCI), leaving their comparability to wet electrodes in clinical and daily life applications an open question. Here, we developed a new dry EEG system and systematically benchmarked its performance against a commercial wet EEG system across various tasks. Methods: Participants (n = 19) underwent simultaneous recording using both devices. We first collected resting-state EEG under both eyes-closed and eyes-open conditions, followed by a steady-state visual evoked potential (SSVEP) task at different flicker frequencies and a motor imagery (MI) task. System performance was evaluated using power spectral density (PSD), signal to noise ratio (SNR), event-related spectral perturbation (ERSP), and single-trial classification accuracy. Results: The two systems performed similarly across different tasks. During the resting state, no statistically significant differences were observed between the two systems in the PSD of the five frequency bands (p > 0.05 in all cases). Similarly, SNR in the SSVEP task showed no significant differences at 8 Hz, 10 Hz, and 12 Hz after correction. For cognitive tasks, classification accuracies were comparable (SSVEP: dry 80.08% ± 7.1% vs. wet 81.10% ± 6.5%; MI: dry 72.46% ± 3.89% vs. wet 70.7% ± 2.37%). Conclusions: The developed dry EEG system can effectively record electrophysiological measurements commonly employed in research and clinical settings, with quality comparable to that of traditional wet EEG systems. Full article

(This article belongs to the Special Issue Biosensors for Physiological Signal Monitoring)

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20 pages, 5480 KB

Open AccessArticle

A Dual-Mode Neural Amplifier Array for Biopotential and FSCV-Based Neurochemical Measurements

by Matthew A. Crocker, Kevin A. White, Mahdieh Darroudi, Vishnu Saket S. Bapanapalli, Charles S. Lipscomb, Benjamin S. John and Brian N. Kim

Biosensors 2026, 16(9), 466; https://doi.org/10.3390/bios16090466 - 26 Aug 2026

Abstract

The simultaneous measurement of biopotential and neurochemical signals provides a comprehensive view of the brain. Yet, most neural interfaces record solely biopotential or neurochemical activity. This work presents a complementary metal-oxide-semiconductor (CMOS) analog front-end (AFE) chip that integrates 32 biopotential amplifiers and 32 [...] Read more.

The simultaneous measurement of biopotential and neurochemical signals provides a comprehensive view of the brain. Yet, most neural interfaces record solely biopotential or neurochemical activity. This work presents a complementary metal-oxide-semiconductor (CMOS) analog front-end (AFE) chip that integrates 32 biopotential amplifiers and 32 neurochemical amplifiers for parallel recording from 64 electrodes. The biopotential amplifier is a two-stage design providing a gain of 57.1 dB, a bandwidth of 0.4 Hz–6.2 kHz, and 6.7 µV_RMS input-referred noise (20 kHz sampling rate). The neurochemical amplifier is a rail-to-rail folded-cascode operational amplifier with selectable transimpedance gain (91.9 kΩ to 851.9 kΩ), a dynamic range of ±15 μA to ±2 μA, respectively, a bandwidth of 12.6 kHz, and input-referred noise as low as 46.3 pA_RMS (20 kHz sampling rate). The neurochemical amplifiers are designed for fast-scan cyclic voltammetry (FSCV) measurements. I/O complexity is minimized using a time-division multiplexing scheme for readout, enabling straightforward scalability. The chip is fabricated using a 0.35-µm CMOS process and occupies a 3.0 × 8.3 mm² area. In vitro recordings of catecholamines and neural spikes validate the chip’s function. The chip enables scalable, low-noise, bimodal neural recording, supporting investigations into the dynamics between neuronal biopotential activity and neurochemical signaling. Full article

(This article belongs to the Special Issue Nano-Biosensors and Their Applications for In Vivo/Vitro Diagnosis—3rd Edition)

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12 pages, 2102 KB

Open AccessArticle

Yes/No Quantitative Analysis of Single-Stranded Oligonucleotides with Lateral Flow Assays

by Niusha Hassandoost, Leslie Munoz, Kerrigan Kotecki and Irina V. Nesterova

Biosensors 2026, 16(9), 465; https://doi.org/10.3390/bios16090465 - 26 Aug 2026

Abstract

Accessible molecular diagnostics is fundamental to effective healthcare. While most current point-of-care devices detect only the presence of a molecular biomarker(s), biomarker quantification can be equally important for decision-making on disease treatment and containment. Here, we present a diagnostic platform that enables the [...] Read more.

Accessible molecular diagnostics is fundamental to effective healthcare. While most current point-of-care devices detect only the presence of a molecular biomarker(s), biomarker quantification can be equally important for decision-making on disease treatment and containment. Here, we present a diagnostic platform that enables the equipment-free quantification of molecular biomarkers with the simplicity of a binary (yes/no) readout. This capability is achieved by integrating a stoichiometric quantitative approach with widely available and easy-to-use lateral flow dipsticks. To implement the approach, we engineer negative cooperativity into target–probe binding interactions for oligonucleotide targets as a model system. The resulting threshold-based semi-quantitative assay with lateral flow dipsticks quantifies targets in the low-nanomolar range and operates reliably in complex biological backgrounds. A key advantage of this platform is its potential adaptability to new and emerging targets: repurposing will require only reagent redesign, without the need for additional fabrication. Full article

(This article belongs to the Section Biosensors and Healthcare)

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30 pages, 10709 KB

Open AccessReview

Advances in Extracellular Vesicle-Based Surface-Enhanced Raman Spectroscopy for Cancer Diagnosis

by Shuyuan Zhao, Wen Lei, Juan Li and Jingjing Xia

Biosensors 2026, 16(9), 464; https://doi.org/10.3390/bios16090464 - 26 Aug 2026

Abstract

As a noninvasive liquid biopsy approach, extracellular vesicle (EV)-based detection offers significant advantages in reflecting real-time tumor dynamis and overcoming the limitations of conventional tissue biopsy. EVs, nanoscale vesicles secreted by cells, carry diverse biomolecules such as proteins and nucleic acids, playing key [...] Read more.

As a noninvasive liquid biopsy approach, extracellular vesicle (EV)-based detection offers significant advantages in reflecting real-time tumor dynamis and overcoming the limitations of conventional tissue biopsy. EVs, nanoscale vesicles secreted by cells, carry diverse biomolecules such as proteins and nucleic acids, playing key roles in tumor progression, metastasis, and immune evasion, and have emerged as promising biomarkers for cancer liquid biopsy. Surface-enhanced Raman spectroscopy (SERS), characterized by high sensitivity, resistance to photobleaching, minimal sample consumption, and multiplexing capability, has shown great potential in EV analysis. This review systematically summarizes current methods for EV isolation, characterization, and storage, with a focus on label-free and label-based SERS detection strategies for early cancer diagnosis, treatment response monitoring, and prognosis evaluation. Furthermore, the integration of SERS with machine learning and deep learning algorithms has substantially improved diagnostic accuracy and cancer subtyping. Despite remaining challenges, such as optimization of SERS substrate performance, intelligent processing of Raman spectral fingerprints, and clinical translation, EV-based SERS technology holds great promise for precision oncology. Full article

(This article belongs to the Special Issue Surface-Enhanced Raman Spectroscopy in Biosensing)

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