Innovative Technologies of Acquiring, Processing, Modeling, or Utilizing Biomedical and Physiological Signals from Biosensing

Dear Colleagues,

In recent years, the continuous increases in accessible biosignal acquisition and processing technology have contributed to a significant amount of available data. Continuous data collection through internal (e.g., wearable) or external (e.g., video and audio) biosensors in mobile phones, smartwatches, hearables, wristbands, video cameras, as well as other non-invasive and invasive sensors, has provided a valuable volume of information, which needs to be curated, prepared, processed, and modeled to serve various AI application scenarios, including healthcare, sports, smart homes, edutainment, and security, among others.

This Special Issue focuses on biomedical and physiological signals obtained from traditional and innovative sensors, the types of which include, but are not limited to, electric, magnetic, mechanical/kinetic, thermal, chemical, optical, and acoustic, among others. The research objects can be single-modal or multi-modal signals.

We welcome findings, studies, and reviews on innovative technologies for acquiring, processing, modeling, and utilizing biosignals, such as devices, data collection, validation, digitalization, signal processing, segmentation and annotation, feature engineering, time-series analysis, data mining, non-deep and deep learning, software development, interface and interaction, as well as wide applications in various fields.

We cherish every new piece of work from our peer scientists and value information from all areas. We look forward to sharing this academic feast and making friends with world-wide authors on this platform through the compact, professional, but comfortable editing process that we ensure.

The main topics for this Special Issue include (but are not limited to) the following:

• Biosignal/biomedical signal/physiological signal: IMU, ACC, Gyro, MAG, BARO, MEMS, Gonio/EGM, FSR/Force, PPG, ABP, HRV, PWV, RISP, PCG, ECG, EMG, EOG, EGG, EVG, EHG, EEG, ECoG, fNIRS, EDA, GSR, EDR, SCR, SCL, SSR, TMP, PZT, audio, video, among others.
• (Wearable) body sensor network (BSN/WBSN).
• Ubiquitous computation and pervasive computation.
• Artificial intelligence (AI), machine learning (ML), and deep learning (DL).
• Human activity/behavior recognition (HAR/HBR) and action unit recognition (AUR).
• Big data mining (BDM), information retrieval (IR), and outlier detection (OD).
• Time-series processing and analysis.
• Feature engineering: feature extraction, feature selection, feature dimensionality study, feature stacking, feature space reduction, and high-level feature design.
• New sensing technologies for biomedical engineering, e.g., Wi-Fi, RFID, seismic, and environmental, among others.
• Human–computer interaction (HCI), real-time system (RTS), and metaverse (VR/AR/MR/XR).

Dr. Hui Liu
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. 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.

• biosignal/biomedical signal/physilogical signal
• (wearable) body sensor network
• artificial intelligence
• machine learning
• deep learning
• human activity/behavior recognition
• action unit recognition
• new sensing technologies for biomedical engineering