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

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