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Biosensors
Special Issues
Advances in Biometrics and Biosensors Technologies and Applications
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Advances in Biometrics and Biosensors Technologies and Applications

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensors and Healthcare".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 4441

Special Issue Editors

Prof. Dr. Tsu-Wang Shen

E-Mail Website
Guest Editor
Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan
Interests: biometrics; smart sensors; biomimetic algorithm; photoacoustic imaging and biomedical signal processing
Dr. Feng-Cheng Lin

E-Mail Website
Guest Editor
Department of Information Engineering and Computer Science, Feng Chia University, Taichung, Taiwan
Interests: artificial intelligence; data analysis; algorithm; cloud computing applications; image processing; deep learning

Special Issue Information

Dear Colleagues,

Biometrics use identification methods based on unique physical attributes, such as a fingerprint, iris, gait, electrocardiogram, image or voice patterns to prevent privacy and property loss. Nevertheless, due to the COVID-19 pandemic and metaverse applications, the demand for robust, contact-free, biometrics-on-the-move, and advanced encryption systems has become essential in real world applications. Biosensors and data fusion technologies combined with biometric systems involve signal/image processing and artificial intelligence techniques to provide the possibilities to analyze human biological conditions and behaviors at the same time. Therefore, this Special Issue on “Biometrics and Biosensors” focuses on recent advances in the production of biometrics and biosensor technologies and their applications in the detection of human biomarkers. We invite submissions of research that help to advance the state of the art in methodologies and perspectives on future developments and applications. The Special Issue will not include articles which focus only on algorithm. Please always emphasize biosensors and the biosensing aspect in your paper. The topics of interest within the scope of this Special Issue include (but are not limited to) the following:

  • Fingerprint
  • Iris
  • Gait recognition
  • ECG biometrics
  • DNA/RNA biometrics
  • Robust biometrics system
  • Biometrics encryption
  • Contact-free biosensors
  • Biometrics-on-the-move
  • Data or sensor fusion
  • Artificial Intelligence
  • Deep learning

With best regards,

Prof. Dr. Tsu-Wang Shen
Dr. Feng-Cheng Lin
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. Biosensors is an international peer-reviewed open access monthly 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 2700 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.

 

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Published Papers (1 paper)

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Research

34 pages, 13006 KiB  
Article
Feature-Based Information Retrieval of Multimodal Biosignals with a Self-Similarity Matrix: Focus on Automatic Segmentation
by João Rodrigues, Hui Liu, Duarte Folgado, David Belo, Tanja Schultz and Hugo Gamboa
Biosensors 2022, 12(12), 1182; https://doi.org/10.3390/bios12121182 - 19 Dec 2022
Cited by 28 | Viewed by 3186
Abstract
Biosignal-based technology has been increasingly available in our daily life, being a critical information source. Wearable biosensors have been widely applied in, among others, biometrics, sports, health care, rehabilitation assistance, and edutainment. Continuous data collection from biodevices provides a valuable volume of information, [...] Read more.
Biosignal-based technology has been increasingly available in our daily life, being a critical information source. Wearable biosensors have been widely applied in, among others, biometrics, sports, health care, rehabilitation assistance, and edutainment. Continuous data collection from biodevices provides a valuable volume of information, which needs to be curated and prepared before serving machine learning applications. One of the universal preparation steps is data segmentation and labelling/annotation. This work proposes a practical and manageable way to automatically segment and label single-channel or multimodal biosignal data using a self-similarity matrix (SSM) computed with signals’ feature-based representation. Applied to public biosignal datasets and a benchmark for change point detection, the proposed approach delivered lucid visual support in interpreting the biosignals with the SSM while performing accurate automatic segmentation of biosignals with the help of the novelty function and associating the segments grounded on their similarity measures with the similarity profiles. The proposed method performed superior to other algorithms in most cases of a series of automatic biosignal segmentation tasks; of equal appeal is that it provides an intuitive visualization for information retrieval of multimodal biosignals. Full article
(This article belongs to the Special Issue Advances in Biometrics and Biosensors Technologies and Applications)
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