AIMC Topic: Motor Skills
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Importance of anthropometric features to predict physical performance in elite youth soccer: a machine learning approach.
Research in sports medicine (Print)
Aug 23, 2020
The present study aimed to determine the contribution of soccer players' anthropometric features to predict their physical performance. Sixteen players, from a professional youth soccer academy, were recruited. Several anthropometric features such as...
Complementing subjective with objective data in analysing expertise: A machine-learning approach applied to badminton.
Journal of sports sciences
Jun 17, 2020
This study aimed to assess which combination of subjective and empirical data might help to identify the expertise level. A group of 10 expert coaches classified 40 participants in 5 different expertise groups based on the video footage of the rallie...
Phase portraits as movement primitives for fast humanoid robot control.
Neural networks : the official journal of the International Neural Network Society
Apr 21, 2020
Currently, usual approaches for fast robot control are largely reliant on solving online optimal control problems. Such methods are known to be computationally intensive and sensitive to model accuracy. On the other hand, animals plan complex motor a...
Training of deep neural networks for the generation of dynamic movement primitives.
Neural networks : the official journal of the International Neural Network Society
Apr 16, 2020
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...
Quantitative Assessment of Motor Function for Patients with a Stroke by an End-Effector Upper Limb Rehabilitation Robot.
BioMed research international
Apr 8, 2020
With the popularization of rehabilitation robots, it is necessary to develop quantitative motor function assessment methods for patients with a stroke. To make the assessment equipment easier to use in clinics and combine the assessment methods with ...
Machine learning-based motor assessment of Parkinson's disease using postural sway, gait and lifestyle features on crowdsourced smartphone data.
Biomedical physics & engineering express
Mar 4, 2020
OBJECTIVES: Remote assessment of gait in patients' homes has become a valuable tool for monitoring the progression of Parkinson's disease (PD). However, these measurements are often not as accurate or reliable as clinical evaluations because it is ch...
Remote Sensing Technology
Walking
Gait
Pattern Recognition, Automated
Posture
Parkinson Disease
Area Under Curve
Postural Balance
Tremor
Accelerometry
Life Style
Motor Skills
Crowdsourcing
Reproducibility of Results
Aged
Male
Middle Aged
Disease Progression
Diagnosis, Computer-Assisted
Wearable Electronic Devices
Smartphone
Humans
Machine Learning
Female
Auto detecting deliveries in elite cricket fast bowlers using microsensors and machine learning.
Journal of sports sciences
Feb 26, 2020
Cricket fast bowlers are at a high risk of injury occurrence, which has previously been shown to be correlated to bowling workloads. This study aimed to develop and test an algorithm that can automatically, reliably and accurately detect bowling deli...
Assessing various sensorimotor and cognitive functions in people with epilepsy is feasible with robotics.
Epilepsy & behavior : E&B
Jan 7, 2020
BACKGROUND: Epilepsy is a common neurological disorder characterized by recurrent seizures, along with comorbid cognitive and psychosocial impairment. Current gold standards of assessment can quantify cognitive and motor performance, but may not capt...
Data-driven analyses of motor impairments in animal models of neurological disorders.
PLoS biology
Nov 21, 2019
Behavior provides important insights into neuronal processes. For example, analysis of reaching movements can give a reliable indication of the degree of impairment in neurological disorders such as stroke, Parkinson disease, or Huntington disease. T...
A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis.
Journal of sports sciences
Oct 28, 2019
The purpose of this study was to develop an automated method for identifying and classifying change of direction (COD) movements in professional tennis using tracking data. Three sport science and strength and conditioning experts coded match-play fo...
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