Combining Machine Learning and Sensors in Human Movement Biomechanics: 2nd Edition
A Special Issue of Sensors (ISSN 1424-8220) belonging to the section "Wearables".
Deadline for manuscript submissions: 20 December 2026 | Viewed by 1487
Editors
Interests: neurology; clinical biomechanics; machine learning; movement disorders
Special Issues, Collections and Topics in MDPI journals
Interests: movement analysis; surface electromyography; ergonomics; biomechanical risk; manual handling activities; rehabilitation; neurorehabilitation; wearable monitoring devices; robotics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Over the last few years, miniature and wearable human body sensors have attracted increasing attention due to their appealing applications. Wearable devices allow for a wireless, low-power-consumption, and real-time quantification of motor functions and abilities, pathological conditions, compensatory motor strategies, and improvements following pharmacological or non-pharmacological (e.g., rehabilitation) treatments and ergonomic interventions. The ongoing joint use of specific algorithms and sensors leads to an intelligent, accurate, and precise characterization of human motion.
Machine learning provides systems with the ability to automatically learn and improve from data and experience without human intervention or assistance, without being explicitly programmed to act as or better than humans. Machine learning is driven by the computational challenges of building statistical models from massive data sets and is located at the intersection of statistics, trying to find relationships based on data and computer science and create efficient computing algorithms.
Many branches of medicine, as well as robotics, ergonomics, and sports, can benefit from the use of machine learning approaches and sensors.
This Special Issue aims to collect the best scientific contributions capable of determining significant improvements on the above-described topic.
Potential topics include but are not limited to the following:
- Human movement analysis and machine learning categorization;
- Machine learning-based diagnostic algorithms of human movement disorders;
- Machine learning- and movement analysis-based clinical decision in human movement disorders;
- Machine learning for biomechanical risk classification in manual handling activities in the workplace;
- Wearable wireless devices for movement analysis and machine learning procedures;
- Computational models in machine learning and sensors for movement analysis;
- Wearable wireless and machine learning communication systems in human movement biomechanics.
Dr. Mariano Serrao
Dr. Alberto Ranavolo
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.
Keywords
- machine learning
- neural network
- biomechanics
- human movement
- wearable devices
- movement disorders
- movement analysis
- motor function
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