Advanced Wearable Sensors for Human Gait Analysis
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 220
Special Issue Editors
Interests: gait biomechanics; musculoskeletal modeling and simulation; wearable sensors; assistive robotics
Interests: biomechanical system design; energy harvesting; wearable sensors; gait analysis; load carriage
Interests: wearable sensors; human motion analysis; rehabilitation robot
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid development of wearable sensors has revolutionized how we monitor and analyze human movement, particularly in the field of gait analysis. Understanding and assessing human gait is essential for a variety of applications, including rehabilitation, clinical diagnostics, sport performance, and injury prevention. The integration of wearable sensor technologies offers the potential for real-time, personalized, and unobtrusive monitoring of gait, providing valuable insights into both healthy and pathological movement patterns.
This Special Issue seeks to highlight the latest research, innovations, and applications in the field of wearable sensors for human gait analysis. We invite original research articles, reviews, and case studies that explore the development, application, and impact of wearable technologies for capturing and analyzing human gait.
We are particularly interested in contributions that address the following areas:
- Advancements in wearable sensor technologies;
- Data processing and machine learning approaches;
- Clinical applications and rehabilitation;
- Wearable sensors in sports and performance optimization;
- Real-time feedback systems for users during training and recovery;
- User-centric design and implementation challenges.
Dr. Tong Li
Prof. Dr. Qingguo Li
Dr. Bingfei Fan
Guest Editors
Manuscript Submission Information
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Keywords
- wearable sensors
- human movement analysis
- rehabilitation
- sport science
- sensor fusion
- machine learning
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