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Movement

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Optimization of Choreography Teaching with Deep Learning and Neural Networks.

Computational intelligence and neuroscience
To improve the development level of intelligent dance education and choreography network technology, the research mainly focuses on the automatic formation system of continuous choreography by using the deep learning method. Firstly, it overcomes the...

Fitness Movement Types and Completeness Detection Using a Transfer-Learning-Based Deep Neural Network.

Sensors (Basel, Switzerland)
Fitness is important in people's lives. Good fitness habits can improve cardiopulmonary capacity, increase concentration, prevent obesity, and effectively reduce the risk of death. Home fitness does not require large equipment but uses dumbbells, yog...

Standardizing continuous data classifications in a virtual T-maze using two-layer feedforward networks.

Scientific reports
There continues to be difficulties when it comes to replication of studies in the field of Psychology. In part, this may be caused by insufficiently standardized analysis methods that may be subject to state dependent variations in performance. In th...

Estimating heading from optic flow: Comparing deep learning network and human performance.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) have made significant advances over the past decade with visual recognition, matching or exceeding human performance on certain tasks. Visual recognition is subserved by the ventral stream of the visual system, wh...

A novel sEMG data augmentation based on WGAN-GP.

Computer methods in biomechanics and biomedical engineering
The classification of sEMG signals is fundamental in applications that use mechanical prostheses, making it necessary to work with generalist databases that improve the accuracy of those classifications. Therefore, synthetic signal generation can be ...

Multiple Groups of Agents for Increased Movement Interference and Synchronization.

Sensors (Basel, Switzerland)
We examined the influence of groups of agents and the type of avatar on movement interference. In addition, we studied the synchronization of the subject with the agent. For that, we conducted experiments utilizing human subjects to examine the influ...

Comparative Analysis of Aesthetic Emotion of Dance Movement: A Deep Learning Based Approach.

Computational intelligence and neuroscience
Dance is a unique art with the human body movement as the main means, but dance is not limited to the human body movement itself. Like any art, dance is the product of human social behavior and a romantic behavior of human thoughts and emotions in th...

Explainable Deep Learning Model for EMG-Based Finger Angle Estimation Using Attention.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Electromyography (EMG) is one of the most common methods to detect muscle activities and intentions. However, it has been difficult to estimate accurate hand motions represented by the finger joint angles using EMG signals. We propose an encoder-deco...

Research on Multimodal Dance Movement Recognition Based on Artificial Intelligence Image Technology.

Computational intelligence and neuroscience
At present, most robot dances are precompiled. Changing music requires manual adjustment of relevant parameters and metamovements, which greatly reduces the fun and intelligence. In view of the above problems, this paper designed CNN system, studied ...

Impedance Variation and Learning Strategies in Human-Robot Interaction.

IEEE transactions on cybernetics
In this survey, various concepts and methodologies developed over the past two decades for varying and learning the impedance or admittance of robotic systems that physically interact with humans are explored. For this purpose, the assumptions and ma...