Machine Learning Based Sensing System and Biomedical Motion Analysis for Digital Health
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: closed (30 January 2024) | Viewed by 1464
Special Issue Editors
Interests: deep learning; pattern recognition; image processing; classification
Special Issues, Collections and Topics in MDPI journals
Interests: fuzzy sets and systems; ordered fuzzy numbers; applications of artificial intelligence; linguistic modelling of data
Special Issues, Collections and Topics in MDPI journals
Interests: human–robot interaction; robot vision; service robot perception and cognition; activity and behavior analysis and modeling; safe and socially aware robot navigation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The last 20 years have seen unprecedented developments in machine learning systems. Not only new sensors have been developed, but also new analytical methods have been developed that together allow accurate, reliable and fast assessment of human movement. This is especially true for their use in natural rather than laboratory settings, including within telemedicine systems. This makes it possible to supplement knowledge of movement mechanisms, their specific or individual characteristics, related to health or disease, as well as for inference, prediction and the possibility of trend changes. Scientists, engineers and clinicians are still longing for breakthroughs in these areas that could change clinical practice.
This Special Issue “Machine Learning Based Sensing System and Biomedical Motion Analysis for Digital Health” will address but is not limited to the following topics:
- ML applications for every daily activities;
- ML applications for sport performance;
- ML applications for the evaluation of movement in clinical practice;
- Using ML for the evaluation of movement variability and postural control;
- Methodological aspects of human movement analysis using motion capture;
- New sensors for human movement applications, including wearable;
- Novel approaches to data processing in human movement analysis;
- AI-based reasoning, prediction, and trend analysis;
- Digital twins and novel tools for eHealth;
- Uncertainty in data or incompleteness etc. resolved by fuzzy logic.
Dr. Dariusz Mikołajewski
Prof. Dr. Piotr Prokopowicz
Dr. Dimitrios Giakoumis
Guest Editors
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Keywords
- artificial intelligence
- machine learning
- artificial neural networks
- deep learning
- convolutional neural networks
- motion capture
- clinical applications
- preventive medicine
- sport medicine
- physical activity
- physiotherapy
- rehabilitation
- neurogeneration
- exoskeletons
- robotic ortheses
- sensing systems
- second opinion systems
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