Human gait contains plentiful information on kinematics, kinetics, psychology, and physiology. Healthy and normal gait is the highly coordinated activities of the nervous system, musculoskeletal system, and sensory system, dysfunction of any part of them will lead to abnormal gaits.
Gait analysis is considered to be an effective way for abnormal gait detection. Existing machine vision-based gait analysis methods have been widely studied for clinical diagnosis of various kinds of gait abnormalities. However, due to the limitation of monitoring time and fixed experimental site, the machine vision-based method can’t achieve long-term continuous monitoring of gait variability and early detection of gait abnormalities. With the increasing application of various kinds of wearable sensors and the fast development of AI technology, wearable gait analysis technologies are emerging and are considered to have significant importance for the early detection of gait abnormalities.
The goal of this topic is to provide the most recent advances in wearable gait monitoring technology and corresponding signal processing and analysis methods. Especially, with the fast development of various kinds of AI algorithms, more and more intelligent wearable gait analysis technologies are emerging and being studied. Therefore, this research topic also aims at providing a platform to share the recent advances in the usage of new AI technology in wearable gait analysis. With the development of wearable gait analysis technology, emerging applications, including prosthetic control, biped robot gait programming, assisted rehabilitation, and professional running posture analysis, are also to be covered in this Research Topic.
We would like researchers to contribute review and research papers to provide the latest research on wearable gait monitoring sensors and systems, AI-assisted gait analysis algorithms, and applications of wearable gait analysis. Relevant research areas covered in this Research Topic include, but are not limited to:
- Wearable gait monitoring sensors and systems
- Multi-sensor information fusion methods for wearable gait analysis
- Lightweight AI algorithms for wearable gait analysis
- Gait phase detection methods and spatiotemporal parameter calculation methods
- Gait kinematics and Kinetics modeling methods
- Quantitative assessment of gait quality methods
- Gait pattern recognition and abnormalities detection
- Gait variability analysis, risk warning, and early detection of abnormal gait based on long-term wearable gait monitoring data
- Gait based identity authentication and recognition for wearable devices
- Applications of wearable gait analysis technologies
Human gait contains plentiful information on kinematics, kinetics, psychology, and physiology. Healthy and normal gait is the highly coordinated activities of the nervous system, musculoskeletal system, and sensory system, dysfunction of any part of them will lead to abnormal gaits.
Gait analysis is considered to be an effective way for abnormal gait detection. Existing machine vision-based gait analysis methods have been widely studied for clinical diagnosis of various kinds of gait abnormalities. However, due to the limitation of monitoring time and fixed experimental site, the machine vision-based method can’t achieve long-term continuous monitoring of gait variability and early detection of gait abnormalities. With the increasing application of various kinds of wearable sensors and the fast development of AI technology, wearable gait analysis technologies are emerging and are considered to have significant importance for the early detection of gait abnormalities.
The goal of this topic is to provide the most recent advances in wearable gait monitoring technology and corresponding signal processing and analysis methods. Especially, with the fast development of various kinds of AI algorithms, more and more intelligent wearable gait analysis technologies are emerging and being studied. Therefore, this research topic also aims at providing a platform to share the recent advances in the usage of new AI technology in wearable gait analysis. With the development of wearable gait analysis technology, emerging applications, including prosthetic control, biped robot gait programming, assisted rehabilitation, and professional running posture analysis, are also to be covered in this Research Topic.
We would like researchers to contribute review and research papers to provide the latest research on wearable gait monitoring sensors and systems, AI-assisted gait analysis algorithms, and applications of wearable gait analysis. Relevant research areas covered in this Research Topic include, but are not limited to:
- Wearable gait monitoring sensors and systems
- Multi-sensor information fusion methods for wearable gait analysis
- Lightweight AI algorithms for wearable gait analysis
- Gait phase detection methods and spatiotemporal parameter calculation methods
- Gait kinematics and Kinetics modeling methods
- Quantitative assessment of gait quality methods
- Gait pattern recognition and abnormalities detection
- Gait variability analysis, risk warning, and early detection of abnormal gait based on long-term wearable gait monitoring data
- Gait based identity authentication and recognition for wearable devices
- Applications of wearable gait analysis technologies
