Wearable Inertial Sensors for Gait Pattern Recognition/Biometrics
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 697
Special Issue Editors
Interests: postural control strategy; muscle activity; dual-task; older adult; translation perturbation
Interests: deep learning; image processing; computer vision; image compression; video editing
Special Issues, Collections and Topics in MDPI journals
Interests: sensor; nanophotonics; MEMS; energy harvesting; AIoT
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Gait is a walking movement, but most importantly, it represents a person's manner of walking and a behavioral trait. Wearable sensing or inertial sensors have become a common approach to capture gait information, and have significantly changed the limited applications of gait analysis. Extended gait analysis provides sufficient information to discriminate between age, gender, emotion, etc. Moreover, the role of sensing approaches or sensors will become more critical, as they will serve as a capture device along with algorithms in machine learning/deep learning to distinguish between individuals as biometrics.
This Special Issue addresses innovative approaches, sensing, and challenges related to gait biometrics. It seeks the latest findings from research and ongoing projects. Additionally, review articles that provide readers with current research trends and solutions are also welcome. Potential topics include, but are not limited to, the following:
- New emerging architectures for sensing and data processing in gait.
- Gait pattern recognition and classification.
- Data fusion for gait analysis.
- Software platforms and frameworks for gait analysis.
- Wearable data processing and analytics.
- Inertial sensing for gait analysis.
- Network architectures to classify gait pattern.
- Age, gender, and emotion classification via gait.
Prof. Dr. Yun-Ju Lee
Prof. Dr. Chih-Chung Hsu
Prof. Dr. Chengkuo Lee
Guest Editors
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Keywords
- gait analysis
- inertial measurement unit
- wearable sensing
- pattern recognition and classification
- gait biometrics and identification
- algorithms
- machine learning and deep learning
- data fusion
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