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Gait Analysis

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Leaving hip rotation out of a conventional 3D gait model improves discrimination of pathological gait in cerebral palsy: A novel neural network analysis.

Gait & posture
BACKGROUND: Complex clinical gait analysis results can be expressed as single number gait deviations by applying multivariate processing methods. The original Movement Deviation Profile (MDP) quantifies the deviation of abnormal gait using the most t...

The Treadport: Natural Gait on a Treadmill.

Human factors
OBJECTIVE: To evaluate the differences between walking on an advanced robotic locomotion interface called the Treadport and walking overground with healthy subjects.

Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach.

IEEE journal of biomedical and health informatics
Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Particularly, difficulties to start/stop movements have been observed in patients. From a technical/diagnostic point of view, these movement changes can...

Gait Estimation from Anatomical Foot Parameters Measured by a Foot Feature Measurement System using a Deep Neural Network Model.

Scientific reports
An accurate and credible measurement of human gait is essential in multiple areas of medical science and rehabilitation. Yet, the methods currently available are not only arduous but also costly. Researchers who investigated the relationship between ...

Tensor Decomposition of Gait Dynamics in Parkinson's Disease.

IEEE transactions on bio-medical engineering
OBJECTIVE: The study of gait in Parkinson's disease is important because it can provide insights into the complex neural system and physiological behaviors of the disease, of which understanding can help improve treatment and lead to effective develo...

A Machine Learning Approach to Automated Gait Analysis for the Noldus Catwalk System.

IEEE transactions on bio-medical engineering
OBJECTIVE: Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Nold...

Applying Machine Learning to Gait Analysis Data for Hip Osteoarthritis Diagnosis.

Studies in health technology and informatics
BACKGROUND: Hip osteoarthritis (OA) is a degenerative joint disease that affects approximately 25% of individuals over their lifetime, with prevalence expected to rise due to population aging. Gait analysis is recognized as a valuable tool for unders...

[Early gait analysis after total knee arthroplasty based on artificial intelligence dynamic image recognition].

Zhongguo gu shang = China journal of orthopaedics and traumatology
OBJECTIVE: To explore early postoperative gait characteristics and clinical outcomes after total knee arthroplasty (TKA).

Classification of Abnormal Gaits with Machine Learning Algorithms using Sensor-Inherited Insoles.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The digital health industry's interest in gait analysis has driven research into sensor-enabled insoles for practical, everyday gait monitoring. Traditional methods, such as 3D motion capture systems, are costly and time-consuming. To address this, w...

Unsupervised Gait Assessments of Stroke Patients Using a Smartphone and Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Home-based rehabilitation is a trend of post-stroke lower limb rehabilitation, aimed at a long-term and higher dose of therapy. Unsupervised gait assessments can help therapists to track patients' recovery progress and timely adjust rehabilitation in...