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Biosensing Technologies: Current Achievements and Future Challenges

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

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 12775

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Special Issue Editor

Dr. Bruno Wacogne

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Guest Editor

1. FEMTO-ST Institute UMR CNRS 6174, University Bourgogne Franche-Comte, Besançon, France
2. Clinical Investigation Center, INSERM CIC 1431, Besançon University Hospital, Besançon, France
Interests: health technologies; translational sciences; medical devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The current pandemic is a constant reminder that our lifestyles, our health, and even our lives may be disrupted in unprecedented ways. The challenges posed by the improvements in the diagnosis, therapeutic monitoring, and in-depth study of living phenomen and personalized care, which require a combination of multidisciplinary expertise at the crossroads of engineering sciences and life sciences.

At the same time, at the dawn of the massive deployment of ultra-fast information technologies, we are moving towards more precise, personalized, and delocalized health systems. It is now more the hospital that comes to us than we go there. In this rapidly changing landscape, the issues of access to care, reduction in biomedical research costs, and data security are becoming crucial and constitute one of the major challenges of tomorrow's societies.

Already, major advances are appearing and paving the way for the diagnostic, therapy, monitoring, and personalized support solutions of tomorrow. The purpose of this Special Issue is precisely to give researchers in the field the opportunity to present their most recent work in all areas related to these questions. The work considered here can be disciplinary or transversal, fundamental, or translational, and can also include studies in the field of humanities and social sciences related to the development of medical technologies.

Thank you for your contributions!

Dr. Bruno Wacogne
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

biosensing
biomedical engineering
monitoring techniques
biological qualification
in vitro diagnosis
integrated devices
wearable devices
implantable devices
translational research

Published Papers (6 papers)

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Research

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17 pages, 2177 KiB

Open AccessArticle

A Deep Learning-Based Automated Framework for Subpeak Designation on Intracranial Pressure Signals

by Donatien Legé, Laurent Gergelé, Marion Prud’homme, Jean-Christophe Lapayre, Yoann Launey and Julien Henriet

Sensors 2023, 23(18), 7834; https://doi.org/10.3390/s23187834 - 12 Sep 2023

Viewed by 772

Abstract

The intracranial pressure (ICP) signal, as monitored on patients in intensive care units, contains pulses of cardiac origin, where P1 and P2 subpeaks can often be observed. When calculable, the ratio of their relative amplitudes is an indicator of the patient’s cerebral compliance. This characterization is particularly informative for the overall state of the cerebrospinal system. The aim of this study is to develop and assess the performances of a deep learning-based pipeline for P2/P1 ratio computation that only takes a raw ICP signal as an input. The output P2/P1 ratio signal can be discontinuous since P1 and P2 subpeaks are not always visible. The proposed pipeline performs four tasks, namely (i) heartbeat-induced pulse detection, (ii) pulse selection, (iii) P1 and P2 designation, and (iv) signal smoothing and outlier removal. For tasks (i) and (ii), the performance of a recurrent neural network is compared to that of a convolutional neural network. The final algorithm is evaluated on a 4344-pulse testing dataset sampled from 10 patient recordings. Pulse selection is achieved with an area under the curve of 0.90, whereas the subpeak designation algorithm identifies pulses with a P2/P1 ratio > 1 with 97.3% accuracy. Although it still needs to be evaluated on a larger number of labeled recordings, our automated P2/P1 ratio calculation framework appears to be a promising tool that can be easily embedded into bedside monitoring devices. Full article

(This article belongs to the Special Issue Biosensing Technologies: Current Achievements and Future Challenges)

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12 pages, 2928 KiB

Open AccessArticle

Wearable Technologies for Electrodermal and Cardiac Activity Measurements: A Comparison between Fitbit Sense, Empatica E4 and Shimmer GSR3+

by Vincenzo Ronca, Ana C. Martinez-Levy, Alessia Vozzi, Andrea Giorgi, Pietro Aricò, Rossella Capotorto, Gianluca Borghini, Fabio Babiloni and Gianluca Di Flumeri

Sensors 2023, 23(13), 5847; https://doi.org/10.3390/s23135847 - 23 Jun 2023

Cited by 6 | Viewed by 3688

Abstract

The capability of measuring specific neurophysiological and autonomic parameters plays a crucial role in the objective evaluation of a human’s mental and emotional states. These human aspects are commonly known in the scientific literature to be involved in a wide range of processes, such as stress and arousal. These aspects represent a relevant factor especially in real and operational environments. Neurophysiological autonomic parameters, such as Electrodermal Activity (EDA) and Photoplethysmographic data (PPG), have been usually investigated through research-graded devices, therefore resulting in a high degree of invasiveness, which could negatively interfere with the monitored user’s activity. For such a reason, in the last decade, recent consumer-grade wearable devices, usually designed for fitness-tracking purposes, are receiving increasing attention from the scientific community, and are characterized by a higher comfort, ease of use and, therefore, by a higher compatibility with daily-life environments. The present preliminary study was aimed at assessing the reliability of a consumer wearable device, i.e., the Fitbit Sense, with respect to a research-graded wearable, i.e., the Empatica E4 wristband, and a laboratory device, i.e., the Shimmer GSR3+. EDA and PPG data were collected among 12 participants while they performed multiple resting conditions. The results demonstrated that the EDA- and PPG-derived features computed through the wearable and research devices were positively and significantly correlated, while the reliability of the consumer device was significantly lower. Full article

(This article belongs to the Special Issue Biosensing Technologies: Current Achievements and Future Challenges)

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25 pages, 8429 KiB

Open AccessArticle

Absorption/Attenuation Spectral Description of ESKAPEE Bacteria: Application to Seeder-Free Culture Monitoring, Mammalian T-Cell and Bacteria Mixture Analysis and Contamination Description

by Bruno Wacogne, Marine Belinger Podevin, Naïs Vaccari, Claudia Koubevi, Céline Codjiová, Emilie Gutierrez, Pauline Bourgeois, Lucie Davoine, Marjorie Robert-Nicoud, Alain Rouleau and Annie Frelet-Barrand

Sensors 2023, 23(9), 4325; https://doi.org/10.3390/s23094325 - 27 Apr 2023

Viewed by 1211

Abstract

Despite numerous innovations, measuring bacteria concentrations on a routine basis is still time consuming and ensuring accurate measurements requires careful handling. Furthermore, it often requires sampling small volumes of bacteria suspensions which might be poorly representative of the real bacteria concentration. In this paper, we propose a spectroscopy measurement method based on a description of the absorption/attenuation spectra of ESKAPEE bacteria. Concentrations were measured with accuracies less than 2%. In addition, mixing the mathematical description of the absorption/attenuation spectra of mammalian T-cells and bacteria allows for the simultaneous measurements of both species’ concentrations. This method allows real-time, sampling-free and seeder-free measurement and can be easily integrated into a closed-system environment. Full article

(This article belongs to the Special Issue Biosensing Technologies: Current Achievements and Future Challenges)

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Review

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17 pages, 1673 KiB

Open AccessReview

Acoustic Lung Imaging Utilized in Continual Assessment of Patients with Obstructed Airway: A Systematic Review

by Chang-Sheng Lee, Minghui Li, Yaolong Lou, Qammer H. Abbasi and Muhammad Ali Imran

Sensors 2023, 23(13), 6222; https://doi.org/10.3390/s23136222 - 7 Jul 2023

Cited by 3 | Viewed by 1082

Abstract

Smart respiratory therapy is enabled by continual assessment of lung functions. This systematic review provides an overview of the suitability of equipment-to-patient acoustic imaging in continual assessment of lung conditions. The literature search was conducted using Scopus, PubMed, ScienceDirect, Web of Science, SciELO Preprints, and Google Scholar. Fifteen studies remained for additional examination after the screening process. Two imaging modalities, lung ultrasound (LUS) and vibration imaging response (VRI), were identified. The most common outcome obtained from eleven studies was positive observations of changes to the geographical lung area, sound energy, or both, while positive observation of lung consolidation was reported in the remaining four studies. Two different modalities of lung assessment were used in eight studies, with one study comparing VRI against chest X-ray, one study comparing VRI with LUS, two studies comparing LUS to chest X-ray, and four studies comparing LUS in contrast to computed tomography. Our findings indicate that the acoustic imaging approach could assess and provide regional information on lung function. No technology has been shown to be better than another for measuring obstructed airways; hence, more research is required on acoustic imaging in detecting obstructed airways regionally in the application of enabling smart therapy. Full article

(This article belongs to the Special Issue Biosensing Technologies: Current Achievements and Future Challenges)

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21 pages, 2780 KiB

Open AccessReview

Biomagnetism: The First Sixty Years

by Bradley J. Roth

Sensors 2023, 23(9), 4218; https://doi.org/10.3390/s23094218 - 23 Apr 2023

Cited by 8 | Viewed by 3108

Abstract

Biomagnetism is the measurement of the weak magnetic fields produced by nerves and muscle. The magnetic field of the heart—the magnetocardiogram (MCG)—is the largest biomagnetic signal generated by the body and was the first measured. Magnetic fields have been detected from isolated tissue, such as a peripheral nerve or cardiac muscle, and these studies have provided insights into the fundamental properties of biomagnetism. The magnetic field of the brain—the magnetoencephalogram (MEG)—has generated much interest and has potential clinical applications to epilepsy, migraine, and psychiatric disorders. The biomagnetic inverse problem, calculating the electrical sources inside the brain from magnetic field recordings made outside the head, is difficult, but several techniques have been introduced to solve it. Traditionally, biomagnetic fields are recorded using superconducting quantum interference device (SQUID) magnetometers, but recently, new sensors have been developed that allow magnetic measurements without the cryogenic technology required for SQUIDs. Full article

(This article belongs to the Special Issue Biosensing Technologies: Current Achievements and Future Challenges)

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18 pages, 1832 KiB

Open AccessReview

Multi-Sensing Techniques with Ultrasound for Musculoskeletal Assessment: A Review

by Jonathan de Oliveira, Mauren Abreu de Souza, Amauri Amorin Assef and Joaquim Miguel Maia

Sensors 2022, 22(23), 9232; https://doi.org/10.3390/s22239232 - 27 Nov 2022

Cited by 1 | Viewed by 2320

Abstract

The study of muscle contractions generated by the muscle-tendon unit (MTU) plays a critical role in medical diagnoses, monitoring, rehabilitation, and functional assessments, including the potential for movement prediction modeling used for prosthetic control. Over the last decade, the use of combined traditional techniques to quantify information about the muscle condition that is correlated to neuromuscular electrical activation and the generation of muscle force and vibration has grown. The purpose of this review is to guide the reader to relevant works in different applications of ultrasound imaging in combination with other techniques for the characterization of biological signals. Several research groups have been using multi-sensing systems to carry out specific studies in the health area. We can divide these studies into two categories: human–machine interface (HMI), in which sensors are used to capture critical information to control computerized prostheses and/or robotic actuators, and physiological study, where sensors are used to investigate a hypothesis and/or a clinical diagnosis. In addition, the relevance, challenges, and expectations for future work are discussed. Full article

(This article belongs to the Special Issue Biosensing Technologies: Current Achievements and Future Challenges)

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