AIMC Topic: Gait Analysis

Clear Filters Showing 101 to 110 of 146 articles

Fully Automated Leg Tracking in Freely Moving Insects using Feature Learning Leg Segmentation and Tracking (FLLIT).

Journal of visualized experiments : JoVE
The Drosophila model has been invaluable for the study of neurological function and for understanding the molecular and cellular mechanisms that underlie neurodegeneration. While fly techniques for the manipulation and study of neuronal subsets have ...

Discriminating progressive supranuclear palsy from Parkinson's disease using wearable technology and machine learning.

Gait & posture
BACKGROUND: Progressive supranuclear palsy (PSP), a neurodegenerative conditions may be difficult to discriminate clinically from idiopathic Parkinson's disease (PD). It is critical that we are able to do this accurately and as early as possible in o...

Adaptive predictive systems applied to gait analysis: A systematic review.

Gait & posture
BACKGROUND: Due to the high susceptivity of the walking pattern to be affected by several disorders, accurate analysis methods are necessary. Given the complexity and relevance of such assessment, the utilization of methods to facilitate it plays a s...

Automatic classification of gait patterns in children with cerebral palsy using fuzzy clustering method.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Subjective classification of gait pattern in children with cerebral palsy depends on the assessor's experience, while mathematical methods produce virtual groups with no clinical interpretation.

Deep Learning for Fall Risk Assessment With Inertial Sensors: Utilizing Domain Knowledge in Spatio-Temporal Gait Parameters.

IEEE journal of biomedical and health informatics
Fall risk assessment is essential to predict and prevent falls in geriatric populations, especially patients with life-long conditions like neurological disorders. Inertial sensor-based pervasive gait analysis systems have become viable means to faci...

Input representations and classification strategies for automated human gait analysis.

Gait & posture
BACKGROUND: Quantitative gait analysis produces a vast amount of data, which can be difficult to analyze. Automated gait classification based on machine learning techniques bear the potential to support clinicians in comprehending these complex data....

A new deep learning-based method for the detection of gait events in children with gait disorders: Proof-of-concept and concurrent validity.

Journal of biomechanics
The stance and swing phases of the gait cycle are defined by foot strike (FS) and foot off (FO). Accurate determination of these events is thus an essential component of 3D motion recordings processing. Several methods have been developed for the aut...

A probabilistic method to estimate gait kinetics in the absence of ground reaction force measurements.

Journal of biomechanics
Human joint torques during gait are usually computed using inverse dynamics. This method requires a skeletal model, kinematics and measured ground reaction forces and moments (GRFM). Measuring GRFM is however only possible in a controlled environment...

Estimation of Vertical Ground Reaction Force Using Low-Cost Insole With Force Plate-Free Learning From Single Leg Stance and Walking.

IEEE journal of biomedical and health informatics
For the evaluation of pathological gait, a machine learning-based estimation of the vertical ground reaction force (vGRF) using a low-cost insole is proposed as an alternative to costly force plates. However, learning a model for estimation still rel...