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Joints

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A Novel Method of Synovitis Stratification in Ultrasound Using Machine Learning Algorithms: Results From Clinical Validation of the MEDUSA Project.

Ultrasound in medicine & biology
Ultrasound is widely used in the diagnosis and follow-up of chronic arthritis. We present an evaluation of a novel automatic ultrasound diagnostic tool based on image recognition technology. Methods used in developing the algorithm are described else...

Artificial neural network simulation of lower limb joint angles in normal and impaired human gait.

Acta of bioengineering and biomechanics
PURPOSE: Simulating the complexities of lower limb motion can be useful for orthosis or rehabilitation planning. The aim of this study was to develop an artificial neural network (ANN) able to accurately simulate the changes in the angle of the ankle...

Control of a Robot Arm Using Decoded Joint Angles from Electrocorticograms in Primate.

Computational intelligence and neuroscience
Electrocorticogram (ECoG) is a well-known recording method for the less invasive brain machine interface (BMI). Our previous studies have succeeded in predicting muscle activities and arm trajectories from ECoG signals. Despite such successful studie...

Assessment of pose repeatability and specimen repositioning of a robotic joint testing platform.

Medical engineering & physics
This paper describes the quantitative assessment of a robotic testing platform, consisting of an industrial robot and a universal force-moment sensor, via the design of fixtures used to hold the tibia and femur of cadaveric knees. This platform was u...

Modifying upper-limb inter-joint coordination in healthy subjects by training with a robotic exoskeleton.

Journal of neuroengineering and rehabilitation
BACKGROUND: The possibility to modify the usually pathological patterns of coordination of the upper-limb in stroke survivors remains a central issue and an open question for neurorehabilitation. Despite robot-led physical training could potentially ...

Control of Redundant Kinematic Degrees of Freedom in a Closed-Loop Brain-Machine Interface.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brain-machine interface (BMI) systems use signals acquired from the brain to directly control the movement of an actuator, such as a computer cursor or a robotic arm, with the goal of restoring motor function lost due to injury or disease of the nerv...

Use of Robotic Manipulators to Study Diarthrodial Joint Function.

Journal of biomechanical engineering
Diarthrodial joint function is mediated by a complex interaction between bones, ligaments, capsules, articular cartilage, and muscles. To gain a better understanding of injury mechanisms and to improve surgical procedures, an improved understanding o...

Proprioceptive assessment in clinical settings: Evaluation of joint position sense in upper limb post-stroke using a robotic manipulator.

PloS one
Proprioception is a critical component for motor functions and directly affects motor learning after neurological injuries. Conventional methods for its assessment are generally ordinal in nature and hence lack sensitivity. Robotic devices designed t...

Evolution of Joint-Level Control for Quadrupedal Locomotion.

Artificial life
We investigate a hierarchical approach to robot control inspired by joint-level control in animals. The method combines a high-level controller, consisting of an artificial neural network (ANN), with joint-level controllers based on digital muscles. ...

Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?

Sensors (Basel, Switzerland)
Human movement analysis has become easier with the wide availability of motion capture systems. Inertial sensing has made it possible to capture human motion without external infrastructure, therefore allowing measurements in any environment. As high...