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Biomedical Infrared Imaging: From Sensors to Applications Ⅱ
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Biomedical Infrared Imaging: From Sensors to Applications Ⅱ

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

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 21807

Special Issue Editors

Prof. Dr. Arcangelo Merla

E-Mail Website
Guest Editor
Department of Engineering and Geology, University of G. d'Annunzio Chieti and Pescara, 65127 Pescara, Italy
Interests: infrared imaging; medical imaging; neuroimaging; psychophysiology; human–machine interaction
Special Issues, Collections and Topics in MDPI journals
Dr. Antonio Maria Chiarelli

E-Mail Website
Guest Editor
Infrared Imaging Lab, ITAB Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, 66100 Chieti, Italy
Interests: infrared imaging; diffuse optical imaging; neuroimaging; Bayesian statistics; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Daniela Cardone

E-Mail Website
Guest Editor
Department of Engineering and Geology, University of G. d'Annunzio Chieti and Pescara, 65127 Pescara, Italy
Interests: artificial intelligence methods; robotics and affective computing; human–machine interaction; processing methods and analysis of biomedical images and physiological signals; computer vision
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Technological advancement of infrared sensors is particularly important for biomedical research. This Special Issue aims to create a sharing opportunity between experts on infrared sensors development and scientists that apply such technology within the biomedical field through software, experimental procedures, or novel applications. Different innovative detectors, sensitive to different ranges of the infrared spectrum (from near- to far- infrared; e.g., Silicon Photomultipliers, Bolometers, Quantum Well Detectors, etc.), and application that relies on such sensors, with emphasis on, but not only, wireless or portable technologies, are suitable topics. Original papers that describe new research or innovative biomedical application are welcome. We look forward to, and welcome, your participation in this Special Issue.

Dr. Arcangelo Merla
Dr. Antonio Maria Chiarelli
Dr. Daniela Cardone
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 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

  • Infrared Detectors
  • Semiconductor
  • High Performance
  • Medical Imaging
  • Portable Technology
  • Cutaneous Temperature
  • Tissue Perfusion
  • Image Analysis

Published Papers (6 papers)

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Research

14 pages, 10764 KiB  
Article
A Motion Artifact Correction Procedure for fNIRS Signals Based on Wavelet Transform and Infrared Thermography Video Tracking
by David Perpetuini, Daniela Cardone, Chiara Filippini, Antonio Maria Chiarelli and Arcangelo Merla
Sensors 2021, 21(15), 5117; https://doi.org/10.3390/s21155117 - 28 Jul 2021
Cited by 17 | Viewed by 2818
Abstract
Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly [...] Read more.
Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly indicative of the underlying biological process. A novel procedure for motion artifact correction for fNIRS signals based on wavelet transform and video tracking developed for infrared thermography (IRT) is presented. In detail, fNIRS and IRT were concurrently recorded and the optodes’ movement was estimated employing a video tracking procedure developed for IRT recordings. The wavelet transform of the fNIRS signal and of the optodes’ movement, together with their wavelet coherence, were computed. Then, the inverse wavelet transform was evaluated for the fNIRS signal excluding the frequency content corresponding to the optdes’ movement and to the coherence in the epochs where they were higher with respect to an established threshold. The method was tested using simulated functional hemodynamic responses added to real resting-state fNIRS recordings corrupted by movement artifacts. The results demonstrated the effectiveness of the procedure in eliminating noise, producing results with higher signal to noise ratio with respect to another validated method. Full article
(This article belongs to the Special Issue Biomedical Infrared Imaging: From Sensors to Applications Ⅱ)
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12 pages, 7045 KiB  
Communication
Over 1000 nm Near-Infrared Multispectral Imaging System for Laparoscopic In Vivo Imaging
by Toshihiro Takamatsu, Yuichi Kitagawa, Kohei Akimoto, Ren Iwanami, Yuto Endo, Kenji Takashima, Kyohei Okubo, Masakazu Umezawa, Takeshi Kuwata, Daiki Sato, Tomohiro Kadota, Tomohiro Mitsui, Hiroaki Ikematsu, Hideo Yokota, Kohei Soga and Hiroshi Takemura
Sensors 2021, 21(8), 2649; https://doi.org/10.3390/s21082649 - 09 Apr 2021
Cited by 9 | Viewed by 4406
Abstract
In this study, a laparoscopic imaging device and a light source able to select wavelengths by bandpass filters were developed to perform multispectral imaging (MSI) using over 1000 nm near-infrared (OTN-NIR) on regions under a laparoscope. Subsequently, MSI (wavelengths: 1000–1400 nm) was performed [...] Read more.
In this study, a laparoscopic imaging device and a light source able to select wavelengths by bandpass filters were developed to perform multispectral imaging (MSI) using over 1000 nm near-infrared (OTN-NIR) on regions under a laparoscope. Subsequently, MSI (wavelengths: 1000–1400 nm) was performed using the built device on nine live mice before and after tumor implantation. The normal and tumor pixels captured within the mice were used as teaching data sets, and the tumor-implanted mice data were classified using a neural network applied following a leave-one-out cross-validation procedure. The system provided a specificity of 89.5%, a sensitivity of 53.5%, and an accuracy of 87.8% for subcutaneous tumor discrimination. Aggregated true-positive (TP) pixels were confirmed in all tumor-implanted mice, which indicated that the laparoscopic OTN-NIR MSI could potentially be applied in vivo for classifying target lesions such as cancer in deep tissues. Full article
(This article belongs to the Special Issue Biomedical Infrared Imaging: From Sensors to Applications Ⅱ)
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19 pages, 6315 KiB  
Article
Smart Sensor Based on Biofeedback to Measure Child Relaxation in Out-of-Home Care
by Daniel Jaramillo-Quintanar, Irving A. Cruz-Albarran, Veronica M. Guzman-Sandoval and Luis A. Morales-Hernandez
Sensors 2020, 20(15), 4194; https://doi.org/10.3390/s20154194 - 28 Jul 2020
Cited by 5 | Viewed by 2905
Abstract
Children from out-of-home care are a vulnerable population that faces high stress and anxiety levels due to stressful experiences, such as being abused, being raped, and violence. This problem could have negative effects on their bio-psycho-social well-being if they are not provided with [...] Read more.
Children from out-of-home care are a vulnerable population that faces high stress and anxiety levels due to stressful experiences, such as being abused, being raped, and violence. This problem could have negative effects on their bio-psycho-social well-being if they are not provided with comprehensive psychological treatment. Numerous methods have been developed to help them relax, but there are no current approaches for assessing the relaxation level they reach. Based on this, a novel smart sensor that can evaluate the level of relaxation a child experiences is developed in this paper. It evaluates changes in thermal biomarkers (forehead, right and left cheek, chin, and maxillary) and heart rate (HR). Then, through a k-nearest neighbors (K-NN) intelligent classifier, four possible levels of relaxation can be obtained: no-relax, low-relax, relax, and very-relax. Additionally, an application (called i-CARE) for anxiety management, which is based on biofeedback diaphragmatic breathing, guided imagery, and video games, is evaluated. After testing the developed smart sensor, an 89.7% accuracy is obtained. The smart sensor used provides a reliable measurement of relaxation levels and the i-CARE application is effective for anxiety management, both of which are focused on children exposed to out-of-home care conditions. Full article
(This article belongs to the Special Issue Biomedical Infrared Imaging: From Sensors to Applications Ⅱ)
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21 pages, 3686 KiB  
Article
A Computational Method to Assist the Diagnosis of Breast Disease Using Dynamic Thermography
by Thiago Alves Elias da Silva, Lincoln Faria da Silva, Débora Christina Muchaluat-Saade and Aura Conci
Sensors 2020, 20(14), 3866; https://doi.org/10.3390/s20143866 - 10 Jul 2020
Cited by 24 | Viewed by 2920
Abstract
Breast cancer has been the second leading cause of cancer death among women. New techniques to enhance early diagnosis are very important to improve cure rates. This paper proposes and evaluates an image analysis method to automatically detect patients with breast benign and [...] Read more.
Breast cancer has been the second leading cause of cancer death among women. New techniques to enhance early diagnosis are very important to improve cure rates. This paper proposes and evaluates an image analysis method to automatically detect patients with breast benign and malignant changes (tumors). Such method explores the difference of Dynamic Infrared Thermography (DIT) patterns observed in patients’ skin. After obtaining the sequential DIT images of each patient, their temperature arrays are computed and new images in gray scale are generated. Then the regions of interest (ROIs) of those images are segmented and, from them, arrays of the ROI temperature are computed. Features are extracted from the arrays, such as the ones based on statistical, clustering, histogram comparison, fractal geometry, diversity indices and spatial statistics. Time series that are broken down into subsets of different cardinalities are generated from such features. Automatic feature selection methods are applied and used in the Support Vector Machine (SVM) classifier. In our tests, using a dataset of 68 images, 100% accuracy was achieved. Full article
(This article belongs to the Special Issue Biomedical Infrared Imaging: From Sensors to Applications Ⅱ)
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13 pages, 1751 KiB  
Article
Near-Infrared Spectroscopy for Monitoring Sternocleidomastoid Muscular Oxygenation during Isometric Flexion for Patients with Mild Nonspecific Neck Pain: A Pilot Study
by Chia-Chi Yang, Po-Ching Yang, Jia-Jin J. Chen, Yi-Horng Lai, Chia-Han Hu, Yung Chang, Shihfan Jack Tu and Lan-Yuen Guo
Sensors 2020, 20(8), 2197; https://doi.org/10.3390/s20082197 - 13 Apr 2020
Cited by 2 | Viewed by 2934
Abstract
Since there is merit in noninvasive monitoring of muscular oxidative metabolism for near-infrared spectroscopy in a wide range of clinical scenarios, the present study attempted to evaluate the clinical usability for featuring the modulatory strategies of sternocleidomastoid muscular oxygenation using near-infrared spectroscopy in [...] Read more.
Since there is merit in noninvasive monitoring of muscular oxidative metabolism for near-infrared spectroscopy in a wide range of clinical scenarios, the present study attempted to evaluate the clinical usability for featuring the modulatory strategies of sternocleidomastoid muscular oxygenation using near-infrared spectroscopy in mild nonspecific neck pain patients. The muscular oxygenation variables of the dominant or affected sternocleidomastoid muscles of interest were extracted at 25% of the maximum voluntary isometric contraction from ten patients (5 males and 5 females, 23.6 ± 4.2 years) and asymptomatic individuals (6 males and 4 females, 24.0 ± 5.1 years) using near-infrared spectroscopy. Only a shorter half-deoxygenation time of oxygen saturation during a sternocleidomastoid isometric contraction was noted in patients compared to asymptomatic individuals (10.43 ± 1.79 s vs. 13.82 ± 1.42 s, p < 0.001). Even though the lack of statically significant differences in most of the muscular oxygenation variables failed to refine the definite pathogenic mechanisms underlying nonspecific neck pain, the findings of modulatory strategies of faster deoxygenation implied that near-infrared spectroscopy appears to have practical potential to provide relevant physiological information regarding muscular oxidative metabolism and constituted convincing preliminary evidences of the adaptive manipulations rather than pathological responses of oxidative metabolism capacity of sternocleidomastoid muscles in nonspecific neck patients with mild disability. Full article
(This article belongs to the Special Issue Biomedical Infrared Imaging: From Sensors to Applications Ⅱ)
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16 pages, 2647 KiB  
Article
Performance Assessment of Low-Cost Thermal Cameras for Medical Applications
by Enrique Villa, Natalia Arteaga-Marrero and Juan Ruiz-Alzola
Sensors 2020, 20(5), 1321; https://doi.org/10.3390/s20051321 - 28 Feb 2020
Cited by 31 | Viewed by 4924
Abstract
Thermal imaging is a promising technology in the medical field. Recent developments in low-cost infrared (IR) sensors, compatible with smartphones, provide competitive advantages for home-monitoring applications. However, these sensors present reduced capabilities compared to more expensive high-end devices. In this work, the characterization [...] Read more.
Thermal imaging is a promising technology in the medical field. Recent developments in low-cost infrared (IR) sensors, compatible with smartphones, provide competitive advantages for home-monitoring applications. However, these sensors present reduced capabilities compared to more expensive high-end devices. In this work, the characterization of thermal cameras is described and carried out. This characterization includes non-uniformity (NU) effects and correction as well as the thermal cameras’ dependence on room temperature, noise-equivalent temperature difference (NETD), and response curve stability with temperature. Results show that low-cost thermal cameras offer good performance, especially when used in temperature-controlled environments, providing evidence of the suitability of such sensors for medical applications, particularly in the assessment of diabetic foot ulcers on which we focused this study. Full article
(This article belongs to the Special Issue Biomedical Infrared Imaging: From Sensors to Applications Ⅱ)
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