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Feature reduction and selection for EMG signal classification

Expert systems with applications, 2012-06, Vol.39 (8), p.7420-7431

2012

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EMG Pattern Recognition in the Era of Big Data and Deep Learning

Big data and cognitive computing, 2018-08, Vol.2 (3), p.21

2018

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Current Trends and Confounding Factors in Myoelectric Control: Limb Position and Contraction Intensity

Sensors (Basel, Switzerland), 2020-03, Vol.20 (6), p.1613

2020

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Feature Extraction and Selection for Myoelectric Control Based on Wearable EMG Sensors

Sensors (Basel, Switzerland), 2018-05, Vol.18 (5), p.1615

2018

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EMG feature evaluation for improving myoelectric pattern recognition robustness

Expert systems with applications, 2013-09, Vol.40 (12), p.4832-4840

2013

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Fractal Analysis of Human Gait Variability via Stride Interval Time Series

Frontiers in physiology, 2020-04, Vol.11, p.333-333

2020

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Deep Cross-User Models Reduce the Training Burden in Myoelectric Control

Frontiers in neuroscience, 2021-05, Vol.15, p.657958-657958

2021

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Feature Extraction and Selection for Pain Recognition Using Peripheral Physiological Signals

Frontiers in neuroscience, 2019-05, Vol.13, p.437-437

2019

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Fractal analysis features for weak and single-channel upper-limb EMG signals

Expert systems with applications, 2012-09, Vol.39 (12), p.11156-11163

2012

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Kinematic gait patterns in healthy runners: A hierarchical cluster analysis

Journal of biomechanics, 2015-11, Vol.48 (14), p.3897-3904

2015

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Probability Density Functions of Stationary Surface EMG Signals in Noisy Environments

IEEE transactions on instrumentation and measurement, 2016-07, Vol.65 (7), p.1547-1557

2016

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Analysis of Big Data in Gait Biomechanics: Current Trends and Future Directions

Journal of medical and biological engineering, 2018, Vol.38 (2), p.244-260

2018

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Navigating features: a topologically informed chart of electromyographic features space

Journal of the Royal Society interface, 2017-12, Vol.14 (137)

2017

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Feature extraction of the first difference of EMG time series for EMG pattern recognition

Computer methods and programs in biomedicine, 2014-11, Vol.117 (2), p.247-256

2014

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Underfoot Pressure-Based Left and Right Foot Classification Algorithms: The Impact of Footwear

IEEE access, 2023, Vol.11, p.137937-137947

2023

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Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features

Frontiers in bioengineering and biotechnology, 2020-03, Vol.8, p.158-158

2020

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Gender and age-related differences in bilateral lower extremity mechanics during treadmill running

PloS one, 2014-08, Vol.9 (8), p.e105246-e105246

2014

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Methods Used in Computer-Aided Diagnosis for Breast Cancer Detection Using Mammograms: A Review

Journal of healthcare engineering, 2020-03, Vol.2020, p.9162464-21

2020

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LibEMG: An Open Source Library to Facilitate the Exploration of Myoelectric Control

IEEE access, 2023, Vol.11, p.87380-87397

2023

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Kinematic Gait Patterns in Competitive and Recreational Runners

Journal of applied biomechanics, 2017-08, Vol.33 (4), p.268-276

2017

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Day-to-Day Stability of Wrist EMG for Wearable-Based Hand Gesture Recognition

IEEE access, 2022, Vol.10, p.125942-125954

2022

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Classification of higher- and lower-mileage runners based on running kinematics

Journal of sport and health science, 2019-05, Vol.8 (3), p.249-257

2019

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Unsupervised Domain Adversarial Self-Calibration for Electromyography-Based Gesture Recognition

IEEE access, 2020, Vol.8, p.177941-177955

2020

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Runners with patellofemoral pain demonstrate sub-groups of pelvic acceleration profiles using hierarchical cluster analysis: an exploratory cross-sectional study

BMC musculoskeletal disorders, 2018-04, Vol.19 (1), p.120-120, Article 120

2018

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Psychiatric Institutions and the Physical Environment: Combining Medical Architecture Methodologies and Architectural Morphology to Increase Our Understanding

Journal of healthcare engineering, 2019-01, Vol.2019, p.4076259-16

2019

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Feature reduction and selection for EMG signal classification

EMG Pattern Recognition in the Era of Big Data and Deep Learning

Current Trends and Confounding Factors in Myoelectric Control: Limb Position and Contraction Intensity

Feature Extraction and Selection for Myoelectric Control Based on Wearable EMG Sensors

EMG feature evaluation for improving myoelectric pattern recognition robustness

Fractal Analysis of Human Gait Variability via Stride Interval Time Series

Deep Cross-User Models Reduce the Training Burden in Myoelectric Control

Feature Extraction and Selection for Pain Recognition Using Peripheral Physiological Signals

Fractal analysis features for weak and single-channel upper-limb EMG signals

Kinematic gait patterns in healthy runners: A hierarchical cluster analysis

Probability Density Functions of Stationary Surface EMG Signals in Noisy Environments

Analysis of Big Data in Gait Biomechanics: Current Trends and Future Directions

Navigating features: a topologically informed chart of electromyographic features space

Feature extraction of the first difference of EMG time series for EMG pattern recognition

Underfoot Pressure-Based Left and Right Foot Classification Algorithms: The Impact of Footwear

Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features

Gender and age-related differences in bilateral lower extremity mechanics during treadmill running

Methods Used in Computer-Aided Diagnosis for Breast Cancer Detection Using Mammograms: A Review

LibEMG: An Open Source Library to Facilitate the Exploration of Myoelectric Control

Kinematic Gait Patterns in Competitive and Recreational Runners

Day-to-Day Stability of Wrist EMG for Wearable-Based Hand Gesture Recognition

Classification of higher- and lower-mileage runners based on running kinematics

Unsupervised Domain Adversarial Self-Calibration for Electromyography-Based Gesture Recognition

Runners with patellofemoral pain demonstrate sub-groups of pelvic acceleration profiles using hierarchical cluster analysis: an exploratory cross-sectional study

Psychiatric Institutions and the Physical Environment: Combining Medical Architecture Methodologies and Architectural Morphology to Increase Our Understanding

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