AIMC Topic: Gait Analysis

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Identification and interpretation of gait analysis features and foot conditions by explainable AI.

Scientific reports
Clinical gait analysis is a crucial step for identifying foot disorders and planning surgery. Automating this process is essential for efficiently assessing the substantial amount of gait data. In this study, we explored the potential of state-of-the...

Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Elderly patients often have more than one disease that affects walking behavior. An objective tool to identify which disease is the main cause of functional limitations may aid clinical decision making. Therefore, we investigated whether gait pattern...

Quantitative gait analysis and prediction using artificial intelligence for patients with gait disorders.

Scientific reports
Quantitative Gait Analysis (QGA) is considered as an objective measure of gait performance. In this study, we aim at designing an artificial intelligence that can efficiently predict the progression of gait quality using kinematic data obtained from ...

Depth-aware pose estimation using deep learning for exoskeleton gait analysis.

Scientific reports
In rehabilitation medicine, real-time analysis of the gait for human wearing lower-limb exoskeleton rehabilitation robot during walking can effectively prevent patients from experiencing excessive and asymmetric gait during rehabilitation training, t...

Validity of AI-Based Gait Analysis for Simultaneous Measurement of Bilateral Lower Limb Kinematics Using a Single Video Camera.

Sensors (Basel, Switzerland)
Accuracy validation of gait analysis using pose estimation with artificial intelligence (AI) remains inadequate, particularly in objective assessments of absolute error and similarity of waveform patterns. This study aimed to clarify objective measur...

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: The relationship between physical function, musculoskeletal disorders and sarcopenia is intricate. Current physical function tests, such as the gait speed test and the chair stand test, have limitations in eliminating subjective influence...

A Systematic Review of Gait Analysis in the Context of Multimodal Sensing Fusion and AI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
BACKGROUND: Neurological diseases are a leading cause of disability and mortality. Gait, or human walking, is a significant predictor of quality of life, morbidity, and mortality. Gait patterns and other kinematic, kinetic, and balance gait features ...

Visual Gait Analysis Based on UE4.

Sensors (Basel, Switzerland)
With the development of artificial intelligence technology, virtual reality technology has been widely used in the medical and entertainment fields, as well as other fields. This study is supported by the 3D modeling platform in UE4 platform technolo...

Automated Implementation of the Edinburgh Visual Gait Score (EVGS) Using OpenPose and Handheld Smartphone Video.

Sensors (Basel, Switzerland)
Recent advancements in computing and artificial intelligence (AI) make it possible to quantitatively evaluate human movement using digital video, thereby opening the possibility of more accessible gait analysis. The Edinburgh Visual Gait Score (EVGS)...

Intelligent Gait Analysis and Evaluation System Based on Cane Robot.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Gait analysis and evaluation are vital for disease diagnosis and rehabilitation. Current gait analysis technologies require wearable devices or high-resolution vision systems within a limited usage space. To facilitate gait analysis and quantitative ...