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Integrated Sensors for Biomedical Applications

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

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 4283

Special Issue Editors


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Guest Editor
Department of Information Engineering - DII, Università Politecnica delle Marche, Via Brecce Bianche 12, I-60131 Ancona, Italy
Interests: microelectronics; analog and mixed-signal integrated circuits; electronic device modeling; statistical IC design; machine learning signal processing; pattern recognition; bio-signal analysis and classification; system identification; neural networks; stochastic processes
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, AN, Italy
Interests: statistical integrated circuit design and device modeling; mixed-signal and RF circuit design; nanoelectronics and nanodevices; biomedical circuits and systems; bio-signal analysis and classification; signal processing; neural networks; system identification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

nowadays telemonitoring is becoming of paramount importance in the medicine, healthcare and sport research and development fields. Monitoring persons is an important component of the personalized medicine and healthcare activities and protocols where health providers and sport trainers can obtain precise information to improve diagnose and therapy, and to modify and supervise exercises sessions, respectively.

Telemonitoring is based on mobile and wearable devices capable of noninvasively acquiring biological and inertial signals that give information about health status and body position. To this end the accurate hardware design of integrated wireless wearable sensors (along with skin electrodes) and the signal processing and transmission of acquired data (that are inherently affected by motion artifacts) represent two key issues in biomedical and healthcare applications.

The aim of this Special Issue is to publish original research articles that cover recent advances in the theory and applications of integrated sensors in the biomedical and healthcare fields.

Potential topics include, but are not limited to:

  • Wearable Wireless Sensors for ExG Signals Acquisition
  • Integrated Wireless Sensors for Biological and Inertial Signals Acquisition
  • Wearable Integrated Sensor Platforms for ExG, Motion Capture & Eye Tracking
  • Healthcare and Medical Applications of Pattern Recognition Based on Wearable Sensor Data;
  • Special Skin Electrodes for Biosignal Acquisition (Theory and Methods);
  • ECG, EEG, sEMG, PPG, and Inertial Signal Based Recognition Systems;
  • Motion Artifact Removal for Wearable Sensors;
  • Multi-Sensor Health Monitoring Systems;
  • Data Fusion and Compressing Sensing Techniques for Low Power Integrated Sensors;
  • Biosignal Processing and Analysis;
  • Special Hardware Architectures;
Prof. Turchetti Claudio
Prof. Dr. Paolo Crippa
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

  • Wearable Sensors
  • Electromyography (sEMG)
  • Electrocardiography (ECG)
  • Photoplethysmography (PPG)
  • Hardware
  • Embedded Systems
  • Integrated Circuits
  • Inertial Signals
  • Healthcare
  • Human Activity Recognition
  • Biosignal Processing

Published Papers (1 paper)

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Research

19 pages, 1519 KiB  
Article
Energy and Performance Analysis of Lossless Compression Algorithms for Wireless EMG Sensors
by Giorgio Biagetti, Paolo Crippa, Laura Falaschetti, Ali Mansour and Claudio Turchetti
Sensors 2021, 21(15), 5160; https://doi.org/10.3390/s21155160 - 30 Jul 2021
Cited by 10 | Viewed by 2901
Abstract
Electromyography (EMG) sensors produce a stream of data at rates that can easily saturate a low-energy wireless link such as Bluetooth Low Energy (BLE), especially if more than a few EMG channels are being transmitted simultaneously. Compressing data can thus be seen as [...] Read more.
Electromyography (EMG) sensors produce a stream of data at rates that can easily saturate a low-energy wireless link such as Bluetooth Low Energy (BLE), especially if more than a few EMG channels are being transmitted simultaneously. Compressing data can thus be seen as a nice feature that could allow both longer battery life and more simultaneous channels at the same time. A lot of research has been done in lossy compression algorithms for EMG data, but being lossy, artifacts are inevitably introduced in the signal. Some artifacts can usually be tolerable for current applications. Nevertheless, for some research purposes and to enable future research on the collected data, that might need to exploit various and currently unforseen features that had been discarded by lossy algorithms, lossless compression of data may be very important, as it guarantees no extra artifacts are introduced on the digitized signal. The present paper aims at demonstrating the effectiveness of such approaches, investigating the performance of several algorithms and their implementation on a real EMG BLE wireless sensor node. It is demonstrated that the required bandwidth can be more than halved, even reduced to 1/4 on an average case, and if the complexity of the compressor is kept low, it also ensures significant power savings. Full article
(This article belongs to the Special Issue Integrated Sensors for Biomedical Applications)
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