Biosignal and Motion Measurements
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: 10 August 2025 | Viewed by 746
Special Issue Editors
Interests: behavioural science; biosignals; emotion recognition; affective computing
Interests: data acquisition; signal processing; embedded systems
Interests: electrophysiology; animal behaviour; biosignals
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Biosignal and motion measurements involve the acquisition, analysis, and interpretation of physiological and movement-related data taken from the human body. These measurements are essential in applications such as diagnostics, rehabilitation, sports science, and human–computer interactions, offering real-time data that aid in understanding, monitoring, and enhancing physical health and performance.
Biosignals include electrical activity from organs (heart, brain, muscles, skin) measured through techniques like ECG (electrocardiography) EEG (electroencephalography), electromyography (EMG), and EDA (electrodermal activity) assessment, while motion measurements capture body movement patterns through accelerometers, gyroscopes, Inertial Measurement Units (IMUs), or other motion capture systems.
In this Special Issue, we aim to collect the latest advanced research achievements in biosignal processing and motion analysis to address a wide range of application scenarios, which include, but are not limited to, the following:
- Physiological monitoring;
- Human motion analysis (gait, hand gesture, etc.);
- Wearable sensors;
- Emotion detection and classification;
- Healthcare monitoring (computer-aided diagnostics, remote health system, etc.);
- Multimodal feature extraction and integration;
- Biosignal processing (ECG, EMG, EEG, PCG, PPG, BCG, etc.).
Dr. Livia Petrescu
Dr. Catalin Petrescu
Dr. Beatrice Mihaela Radu
Guest Editors
Manuscript Submission Information
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Keywords
- physiological monitoring
- wearable sensors
- signal processing
- biomechanics
- motion analysis
- emotion recognition
- healthcare
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