AIMC Topic: Hip Joint

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Fully automated radiological analysis of spinal disorders and deformities: a deep learning approach.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: We present an automated method for extracting anatomical parameters from biplanar radiographs of the spine, which is able to deal with a wide scenario of conditions, including sagittal and coronal deformities, degenerative phenomena as well ...

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...

Robotic hip joint testing: Development and experimental protocols.

Medical engineering & physics
The use of robotic systems combined with force sensing is emerging as the gold standard for in vitro biomechanical joint testing, due to the advantage of controlling all six degrees of freedom independently of one another. This paper describes a nove...

Mechanical Design and Control Strategy for Hip Joint Power Assisting.

Journal of healthcare engineering
The basic requirements for mechanical design and control strategy are adapting to human joint movements and building an interaction model between human and robot. In this paper, a 3-UPS parallel mechanism is adopted to realize that the instantaneous ...

Predicting net joint moments during a weightlifting exercise with a neural network model.

Journal of biomechanics
The purpose of this study was to develop and train a Neural Network (NN) that uses barbell mass and motions to predict hip, knee, and ankle Net Joint Moments (NJM) during a weightlifting exercise. Seven weightlifters performed two cleans at 85% of th...

Supervised learning techniques and their ability to classify a change of direction task strategy using kinematic and kinetic features.

Journal of biomechanics
This study examines the ability of commonly used supervised learning techniques to classify the execution of a maximum effort change of direction task into predefined movement pattern as well as the influence of fuzzy executions and the impact of sel...

A preliminary examination of the diagnostic value of deep learning in hip osteoarthritis.

PloS one
Hip Osteoarthritis (OA) is a common disease among the middle-aged and elderly people. Conventionally, hip OA is diagnosed by manually assessing X-ray images. This study took the hip joint as the object of observation and explored the diagnostic value...

Physical human-robot interaction of an active pelvis orthosis: toward ergonomic assessment of wearable robots.

Journal of neuroengineering and rehabilitation
BACKGROUND: In human-centered robotics, exoskeletons are becoming relevant for addressing needs in the healthcare and industrial domains. Owing to their close interaction with the user, the safety and ergonomics of these systems are critical design f...

Biomechanical Assessment of Hip Capsular Repair and Reconstruction Procedures Using a 6 Degrees of Freedom Robotic System.

The American journal of sports medicine
BACKGROUND: Although acetabular labral repair has been biomechanically validated to improve stability, capsular management of the hip remains a topic of growing interest and controversy.

Effect of body weight support variation on muscle activities during robot assisted gait: a dynamic simulation study.

Computer methods in biomechanics and biomedical engineering
BACKGROUND AND OBJECTIVES: While body weight support (BWS) intonation is vital during conventional gait training of neurologically challenged subjects, it is important to evaluate its effect during robot assisted gait training. In the present researc...