AIMC Topic: Motor Skills
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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...
Humans
Machine Learning
Female
Tremor
Accelerometry
Life Style
Motor Skills
Posture
Crowdsourcing
Parkinson Disease
Area Under Curve
Postural Balance
Remote Sensing Technology
Walking
Gait
Pattern Recognition, Automated
Reproducibility of Results
Disease Progression
Aged
Diagnosis, Computer-Assisted
Male
Wearable Electronic Devices
Middle Aged
Smartphone
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...
Long-Dose Intensive Therapy Is Necessary for Strong, Clinically Significant, Upper Limb Functional Gains and Retained Gains in Severe/Moderate Chronic Stroke.
Neurorehabilitation and neural repair
May 25, 2019
. Effective treatment methods are needed for moderate/severely impairment chronic stroke. . The questions were the following: (1) Is there need for long-dose therapy or is there a mid-treatment plateau? (2) Are the observed gains from the prior-studi...
Using Surgeon Hand Motions to Predict Surgical Maneuvers.
Human factors
Apr 23, 2019
OBJECTIVE: This study explores how common machine learning techniques can predict surgical maneuvers from a continuous video record of surgical benchtop simulations.
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