AI Medical Compendium Topic:
Movement

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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 ...

Bio-inspired multi-scale fusion.

Biological cybernetics
We reveal how implementing the homogeneous, multi-scale mapping frameworks observed in the mammalian brain's mapping systems radically improves the performance of a range of current robotic localization techniques. Roboticists have developed a range ...

Key components of mechanical work predict outcomes in robotic stroke therapy.

Journal of neuroengineering and rehabilitation
BACKGROUND: Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots...

Training of deep neural networks for the generation of dynamic movement primitives.

Neural networks : the official journal of the International Neural Network Society
Dynamic movement primitives (DMPs) have proven to be an effective movement representation for motor skill learning. In this paper, we propose a new approach for training deep neural networks to synthesize dynamic movement primitives. The distinguishi...

Identification of Upper-Limb Movements Based on Muscle Shape Change Signals for Human-Robot Interaction.

Computational and mathematical methods in medicine
Towards providing efficient human-robot interaction, surface electromyogram (EMG) signals have been widely adopted for the identification of different limb movement intentions. Since the available EMG signal sensors are highly susceptible to external...

High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks.

Scientific reports
Patients with advanced Parkinson's disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recordi...

The optimized algorithm based on machine learning for inverse kinematics of two painting robots with non-spherical wrist.

PloS one
This paper studies the inverse kinematics of two non-spherical wrist configurations of painting robot. The simplest analytical solution of orthogonal wrist configuration is deduced in this paper for the first time. For the oblique wrist configuration...

Automatic discovery of resource-restricted Convolutional Neural Network topologies for myoelectric pattern recognition.

Computers in biology and medicine
Convolutional Neural Networks (CNNs) have been subject to extensive attention in the pattern recognition literature due to unprecedented performance in tasks of information extraction from unstructured data. Whereas available methods for supervised t...

Deciphering anomalous heterogeneous intracellular transport with neural networks.

eLife
Intracellular transport is predominantly heterogeneous in both time and space, exhibiting varying non-Brownian behavior. Characterization of this movement through averaging methods over an ensemble of trajectories or over the course of a single traje...

Design and verification of a human-robot interaction system for upper limb exoskeleton rehabilitation.

Medical engineering & physics
This paper presents the design of a motion intent recognition system, based on an altitude signal sensor, to improve the human-robot interaction performance of upper limb exoskeleton robots during rehabilitation training. A modified adaptive Kalman f...