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Movement

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Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson's Disease Mobility Assessments.

Sensors (Basel, Switzerland)
Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson's disease (PD) on motor control, balance, and cognitive function. We assess the test-retest reliability o...

A parallel CNN architecture for sport activity recognition based on minimal movement data.

Scientific reports
Novel Human Activity Recognition (HAR) methodologies, which are built upon learning algorithms and employ ubiquitous sensors, have achieved remarkable precision in the identification of sports activities. Such progress benefits all age groups of huma...

Human motion similarity evaluation based on deep metric learning.

Scientific reports
In order to eliminate the impact of camera viewpoint factors and human skeleton differences on the action similarity evaluation and to address the issue of human action similarity evaluation under different viewpoints, a method based on deep metric l...

Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person.

Scientific reports
Recently, social demands for a good quality of life have increased among the elderly and disabled people. So, biomedical engineers and robotic researchers aimed to fuse these techniques in a novel rehabilitation system. Moreover, these models utilize...

Squat Motion of a Humanoid Robot Using Three-Particle Model Predictive Control and Whole-Body Control.

Sensors (Basel, Switzerland)
Squatting is a fundamental and crucial movement, often employed as a basic test during robot commissioning, and it plays a significant role in some service industries and in cases when robots perform high-dynamic movements like jumping. Therefore, ac...

Surmounting the ceiling effect of motor expertise by novel sensory experience with a hand exoskeleton.

Science robotics
For trained individuals such as athletes and musicians, learning often plateaus after extensive training, known as the "ceiling effect." One bottleneck to overcome it is having no prior physical experience with the skill to be learned. Here, we chall...

A hybrid CNN model for classification of motor tasks obtained from hybrid BCI system.

Scientific reports
The Hybrid-Brain Computer Interface (BCI) has shown improved performance, especially in classifying multi-class data. Two non-invasive BCI modules are combined to achieve an improved classification which are Electroencephalogram (EEG) and functional ...

Explainable quality assessment of effective aligned skeletal representations for martial arts movements by multi-machine learning decisions.

Scientific reports
How to utilize modern technological means to provide both accurate scoring and objective feedback for martial arts movements has become an issue that needs to be addressed in the field of physical education. This study proposes an intelligent scoring...

Research on the movement pattern and kinematic model of the hindlegs of the water boatman.

Bioinspiration & biomimetics
The special hindleg structure and swimming setae of a water boatman give it a high degree of maneuverability, which plays an important role in swimming. This paper used a high-speed photography platform to extract key points from videos, obtaining th...