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Advanced Non-Invasive Sensors: Methods and Applications—2nd Edition
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Advanced Non-Invasive Sensors: Methods and Applications—2nd Edition

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

Deadline for manuscript submissions: 20 January 2026 | Viewed by 2598

Special Issue Editor

Prof. Dr. Janusz Kulon

E-Mail Website
Guest Editor
Faculty of Computing, Engineering and Science, University of South Wales, Pontypridd CF37 1DL, UK
Interests: biomedical engineering and computing; design of medical instrumentation; non-invasive sensor applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The field of sensor technology is witnessing transformative change with the advent of non-invasive sensing methods. This non-invasive approach, preserving the integrity of the observed system or process, ensures a wide range of applications, from personal health monitoring to industrial automation, agriculture, and environmental sensing. Advancements in methodologies, ranging from design and fabrication to the processing algorithms, play a pivotal role in enhancing the efficiency and effectiveness of non-invasive sensors.

How can we advance non-invasive sensor technology to deliver higher performance and broader applicability? How can we leverage these advancements to innovate applications across various domains? We eagerly await innovative research papers that address these questions and illuminate the path forward for non-invasive sensing.

This Special Issue, entitled “Advanced Non-Invasive Sensors: Methods and Applications—2nd Edition”, welcomes contributions that delve into every facet of non-invasive sensor technology.

Relevant topics include, but are not limited to, the following:

  • Advanced design and fabrication of non-invasive sensors;
  • Innovative sensor applications in health monitoring, agriculture, industry, and environment;
  • Integration of AI and non-invasive sensors;
  • Non-invasive sensor networks;
  • Data analysis and processing for non-invasive sensor signals;
  • Wearable non-invasive devices;
  • Sensor-captured imaging and non-invasive techniques.

Let us collaborate to shed light on the exciting frontier of non-invasive sensor technology, its potential, and practical applications across diverse domains. We look forward to your valuable contributions.

Prof. Dr. Janusz Kulon
Guest Editor

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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • non-invasive sensors
  • smartphones
  • non-invasive sensor networks
  • wearable non-invasive devices
  • data analysis
  • sensor design

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Related Special Issue

Published Papers (3 papers)

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Research

17 pages, 3129 KB  
Article
A Framework to Evaluate Feasibility, Safety, and Accuracy of Wireless Sensors in the Neonatal Intensive Care Unit: Oxygen Saturation Monitoring
by Eva Senechal, Daniel Radeschi, Emily Jeanne, Ana Saveedra Ruiz, Brittany Dulmage, Wissam Shalish, Robert E. Kearney and Guilherme Sant’Anna
Sensors 2025, 25(18), 5647; https://doi.org/10.3390/s25185647 - 10 Sep 2025
Viewed by 412
Abstract
Monitoring vital signs in the Neonatal Intensive Care Unit (NICU) typically relies on wired skin sensors, which can limit mobility, cause skin issues, and interfere with parent–infant bonding. Wireless sensors offer promising alternatives, but evaluations to date often emphasize accuracy alone, lack NICU-specific [...] Read more.
Monitoring vital signs in the Neonatal Intensive Care Unit (NICU) typically relies on wired skin sensors, which can limit mobility, cause skin issues, and interfere with parent–infant bonding. Wireless sensors offer promising alternatives, but evaluations to date often emphasize accuracy alone, lack NICU-specific validation, and rarely use standardized frameworks. Our objective was to develop and apply a comprehensive framework for evaluating the feasibility, safety, and accuracy of wireless monitoring technologies using a wireless pulse oximeter, the Anne limb (Sibel Health, USA), in real-world NICU conditions. A prospective study was conducted on a diverse NICU population. A custom system enabled synchronized data recordings from both standard and wireless devices. Feasibility was assessed as signal coverage across a variety of daily care activities and during routine procedures. Safety was evaluated through skin assessments after extended wear. Accuracy was examined sample-by-sample and interpreted using the Clarke Error Grid for clinical relevance. The wireless oximeter device showed high feasibility with reliable Bluetooth connection across a range of patients and activities (median wireless PPG coverage = 100%, IQR: 99.85–100%). Skin assessments showed no significant adverse effects. Accuracy was strong overall (median bias 1.34%, 95% LoA −3.63 to 6.41), with most data points within clinically acceptable Clarke error grid zones A and B, though performance declined for infants on supplemental oxygen. This study presents a robust, multidimensional framework for evaluating wireless monitoring devices in NICUs and offers recommendations for future research design and reporting. Full article
(This article belongs to the Special Issue Advanced Non-Invasive Sensors: Methods and Applications—2nd Edition)
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24 pages, 6133 KB  
Article
A Smart System for Continuous Sitting Posture Monitoring, Assessment, and Personalized Feedback
by David Faith Odesola, Janusz Kulon, Shiny Verghese, Adam Partlow and Colin Gibson
Sensors 2025, 25(18), 5610; https://doi.org/10.3390/s25185610 - 9 Sep 2025
Viewed by 926
Abstract
Prolonged sitting and the adoption of unhealthy sitting postures have been a common issue generally seen among many adults and the working population in recent years. This alone has contributed to the alarming rise of various health issues, such as musculoskeletal disorders and [...] Read more.
Prolonged sitting and the adoption of unhealthy sitting postures have been a common issue generally seen among many adults and the working population in recent years. This alone has contributed to the alarming rise of various health issues, such as musculoskeletal disorders and a range of long-term health conditions. Hence, this study proposes the development of a novel smart-sensing chair system designed to analyze and provide actionable insights to help encourage better postural habits and promote well-being. The proposed system was equipped with two 32 × 32 pressure sensor mats, which were integrated into an office chair to facilitate the collection of postural data. Unlike traditional approaches that rely on generalized datasets collected from multiple healthy participants to train machine learning models, this study adopts a user-tailored methodology—collecting data from a single individual to account for their unique physiological characteristics and musculoskeletal conditions. The dataset was trained using five different machine learning models—Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Convolutional Neural Networks (CNN)—to classify 19 distinct sitting postures. Overall, CNN achieved the highest accuracy, with 98.29%. To facilitate user engagement and support long-term behavior change, we developed SitWell—an intelligent postural feedback platform comprising both mobile and web applications. The platform’s core features include sitting posture classification, posture duration analytics, and sitting quality assessment. Additionally, the platform integrates OpenAI’s GPT-4o Large Language Model (LLM) to deliver personalized insights and recommendations based on users’ historical posture data. Full article
(This article belongs to the Special Issue Advanced Non-Invasive Sensors: Methods and Applications—2nd Edition)
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10 pages, 1071 KB  
Article
Noninvasive Analysis of Biological Components Using Simplified Mid-Infrared Photothermal Deflection Spectroscopy
by Hiroto Ito, Saiko Kino and Yuji Matsuura
Sensors 2025, 25(14), 4368; https://doi.org/10.3390/s25144368 - 12 Jul 2025
Viewed by 452
Abstract
We developed a photothermal deflection spectroscopy (PTDS) system for the noninvasive analysis of biological tissue. This system detects heat induced by irradiation with pulse-modulated mid-infrared light as the deflection of a probe laser. The probe light is incident on the sensing element horizontal [...] Read more.
We developed a photothermal deflection spectroscopy (PTDS) system for the noninvasive analysis of biological tissue. This system detects heat induced by irradiation with pulse-modulated mid-infrared light as the deflection of a probe laser. The probe light is incident on the sensing element horizontal with respect to its contact surface with the sample. This setup simplifies the optical alignment compared to conventional systems, which require the probe laser to be totally reflected at the prism contact surface and aligned with the point of mid-infrared light irradiation. In this study, we measured the PTDS spectra of biological samples to determine the characteristic features of their infrared absorption. We also compared the measurement reproducibility of two configurations: a horizontal optical path and a total reflection optical path. The horizontal optical path showed greater measurement reproducibility than the total reflection optical path when performing intermittent measurements on the wrist. Full article
(This article belongs to the Special Issue Advanced Non-Invasive Sensors: Methods and Applications—2nd Edition)
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