A Combination of Feature Extraction and Feedforward Neural Network to Estimate Muscle Activity in Human Gait
Author:
Affiliation:
1. School of Engineering, Monash University Malaysia,Bandar Sunway,Malaysia
2. Curtin University,Department of Electrical & Computer Engineering,Miri,Malaysia
3. Sunway Medical Centre,Bandar Sunway,Malaysia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10322307/10322308/10322402.pdf?arnumber=10322402
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1. Principal Characteristics of Affected and Unaffected Side Trunk Movement and Gait Event Parameters during Hemiplegic Stroke Gait with IMU Sensor
2. A principal component analysis (PCA) based assessment of the gait performance
3. A comparison of machine learning models’ accuracy in predicting lower-limb joints’ kinematics, kinetics, and muscle forces from wearable sensors
4. Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh – A Python package)
5. Dimensionality reduction on hyperspectral images: A comparative review based on artificial datas
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