Special Issues
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Advances in Computational Approaches to Action and Movement Analysis

Submission Deadline: 31 January 2026 (closed) View: 757 Submit to Journal

Guest Editors

Prof. Dr. Vitor Filipe

Email: vfilipe@utad.pt

Affiliation: 1. Department of Engineering, School of Science and Technology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal 

2. INESC TEC – Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal

Homepage:

Research Interests: computer vision and machine learning

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Prof. Dr. Hugo Paredes

Email: hparedes@utad.pt

Affiliation: 1. Department of Engineering, School of Science and Technology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal 

2. Center for Human-Centered Computing and Information Science (HumanISE), Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal

Homepage:

Research Interests: human-centered artificial intelligence

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Summary

The study of human movement has long been a fundamental area of research across multiple disciplines, with high impact in fields such as healthcare, sports, robotics, and artificial intelligence. With recent advancements in sensor technology, artificial intelligence, and computational modeling, new approaches for precise and efficient movement analysis can be explored by researchers to detect, recognize and interpret motion dynamics and action in a variety of scenarios. These innovations enable breakthroughs in real-time motion tracking, predictive modeling, and automated recognition of complex movement behaviors.


This Special Issue seeks to bring together researchers from diverse backgrounds to share new knowledge, insights, methodologies, and applications that drive the field forward. Researchers and academics are invited to submit original research papers, review articles, and case studies on, but not limited to, the following topics:
· Machine learning and deep learning approaches for movement analysis
· Gesture recognition for human-computer interaction
· Robotics and assistive technologies for movement assessment
· Human action recognition and behavior understanding
· Applications of movement analysis in healthcare and ergonomics
· Movement analysis in sports science and performance enhancement
· Gait analysis and rehabilitation applications
· Biomechanical modeling and simulation


Keywords

Movement Analysis, Gesture Recognition, Human Motion, Human Activity Recognition, Posture Recognition

Published Papers


  • Open Access

    ARTICLE

    Efficient Gait Phase Estimation and Trajectory Prediction in Wearable Devices Using a Dual-Stage Approach

    Sihan Wang, Luyao Liu, Xingjun Wang, Yifan Liu
    CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077791
    (This article belongs to the Special Issue: Advances in Computational Approaches to Action and Movement Analysis)
    Abstract This paper presents a novel dual-stage approach for efficient gait phase recognition and trajectory prediction, tailored for the operation of wearable devices such as exoskeletons. By leveraging dynamic template matching techniques and addressing their computational challenges, we propose an innovative algorithm that significantly enhances both prediction accuracy and computational efficiency. The approach integrates Dynamic Time Warping-KMeans (DTW-KM) template selection in the offline phase and a Soft Constraint Weighted (SCW) template matching technique in the online phase. In the offline stage, the DTW-KM method extracts diverse and generalizable gait patterns from a database, establishing a robust More >

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