Machine Learning Based Sensing System and Biomedical Motion Analysis for Digital Health

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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