Osteoarthritis is a degenerative joint disease, which causes the degradation of articular cartilage and subchondral bone. The disease may result in mechanical abnormalities of the joints, including weight bearing joints such as the knees and hips. In this work, we analyze gait biomechanical data using neural network models to predict the level of joint deterioration and the level of pain in participants suffering from knee osteoarthritis. The results of the analyses demonstrate strong correlation between gait kinetics and joint deterioration and level of pain in osteoarthritic individuals. © 2011 IEEE
A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine o...
Deep learning models developed to predict knee joint kinematics are usually trained on inertial meas...
Joint moment measurements represent an objective biomechemical parameter in joint health assessment....
There is a growing interest in non-surgical gait rehabilitation treatments to reduce the loading in ...
In this study neural networks were applied to perform automated diagnosis of gait patterns. The thre...
Gait alterations in those with mild unilateral knee pain during walking may provide clues to modifia...
Joint angles are one of the fundamental parameters to control the exoskeleton robotic leg. This rese...
Gait measures have received increasing attention in the evaluation of patients with knee osteoarthri...
Osteoarthritis (OA) is the second leading cause of pain and disability, affecting more than 250 mill...
Due to recent heart attacks on humans, it is necessary to predict heart graphs of humans during runn...
Application of an artificial neural network (ANN) for the prediction of a rehabilitation progress af...
PurposeTo couple quantitative compositional MRI, gait analysis, and machine learning multidimensiona...
SummaryObjectiveTo describe a novel classification method for knee osteoarthritis (OA) based on spat...
Gait analysis can be defined as the numerical and graphical representation of the mechanical measure...
Osteopenia and sarcopenia can cause various senile diseases and are key factors related to the quali...
A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine o...
Deep learning models developed to predict knee joint kinematics are usually trained on inertial meas...
Joint moment measurements represent an objective biomechemical parameter in joint health assessment....
There is a growing interest in non-surgical gait rehabilitation treatments to reduce the loading in ...
In this study neural networks were applied to perform automated diagnosis of gait patterns. The thre...
Gait alterations in those with mild unilateral knee pain during walking may provide clues to modifia...
Joint angles are one of the fundamental parameters to control the exoskeleton robotic leg. This rese...
Gait measures have received increasing attention in the evaluation of patients with knee osteoarthri...
Osteoarthritis (OA) is the second leading cause of pain and disability, affecting more than 250 mill...
Due to recent heart attacks on humans, it is necessary to predict heart graphs of humans during runn...
Application of an artificial neural network (ANN) for the prediction of a rehabilitation progress af...
PurposeTo couple quantitative compositional MRI, gait analysis, and machine learning multidimensiona...
SummaryObjectiveTo describe a novel classification method for knee osteoarthritis (OA) based on spat...
Gait analysis can be defined as the numerical and graphical representation of the mechanical measure...
Osteopenia and sarcopenia can cause various senile diseases and are key factors related to the quali...
A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine o...
Deep learning models developed to predict knee joint kinematics are usually trained on inertial meas...
Joint moment measurements represent an objective biomechemical parameter in joint health assessment....