Visualization of activated muscle area based on sEMG

[1]  Chi-Woong Mun,et al.  Comparison of k-nearest neighbor, quadratic discriminant and linear discriminant analysis in classification of electromyogram signals based on the wrist-motion directions , 2011 .

[2]  Ying Sun,et al.  Surface EMG hand gesture recognition system based on PCA and GRNN , 2019, Neural Computing and Applications.

[3]  Bo Tao,et al.  Probability analysis for grasp planning facing the field of medical robotics , 2019, Measurement.

[4]  Bo Tao,et al.  Intelligent Human-Computer Interaction Based on Surface EMG Gesture Recognition , 2019, IEEE Access.

[5]  Gongfa Li,et al.  Human Lesion Detection Method Based on Image Information and Brain Signal , 2019, IEEE Access.

[6]  Andrew G. Ewing,et al.  Using imaging ToF‐SIMS data to determine the cell wall thickness of fibers in wood , 2014 .

[7]  Alireza Akbarzadeh,et al.  Toward a bio-inspired rehabilitation aid: sEMG-CPG approach for online generation of jaw trajectories for a chewing robot , 2019, Biomed. Signal Process. Control..

[8]  William Z Rymer,et al.  Changes in motor unit behavior following isometric fatigue of the first dorsal interosseous muscle. , 2015, Journal of neurophysiology.

[9]  Ahmed Farouk,et al.  Robust general N user authentication scheme in a centralized quantum communication network via generalized GHZ states , 2017, Frontiers of Physics.

[10]  G. Brostow,et al.  HILC: Domain-Independent PbD System Via Computer Vision and Follow-Up Questions , 2019, ACM Trans. Interact. Intell. Syst..

[11]  Ahmed Farouk,et al.  Red-Green-Blue multi-channel quantum representation of digital images , 2017 .

[12]  Jarmo T. Alander,et al.  Integer-based accurate conversion between RGB and HSV color spaces , 2015, Comput. Electr. Eng..

[13]  Yinfeng Fang,et al.  Interface Prostheses With Classifier-Feedback-Based User Training , 2017, IEEE Transactions on Biomedical Engineering.

[14]  Honghai Liu,et al.  Optimal grasp planning of multi-fingered robotic hands:a review , 2015 .

[15]  Honghai Liu,et al.  Hand gesture recognition based on convolution neural network , 2017, Cluster Computing.

[16]  Dingguo Zhang,et al.  sEMG Bias-Driven Functional Electrical Stimulation System for Upper-Limb Stroke Rehabilitation , 2018, IEEE Sensors Journal.

[17]  Ahmed Farouk,et al.  A New Quantum Watermarking Based on Quantum Wavelet Transforms , 2017 .

[18]  Munish Kumar,et al.  Fusion of RGB and HSV colour space for foggy image quality enhancement , 2018, Multimedia Tools and Applications.

[19]  Jung Kim,et al.  Recognition of walking environments and gait period by surface electromyography , 2019, Frontiers of Information Technology & Electronic Engineering.

[20]  Gordon Cheng,et al.  Gumpy: a Python toolbox suitable for hybrid brain–computer interfaces , 2018, Journal of neural engineering.

[21]  Angkoon Phinyomark,et al.  EMG feature evaluation for improving myoelectric pattern recognition robustness , 2013, Expert Syst. Appl..

[22]  M. Osman Tokhi,et al.  A fuzzy clustering neural network architecture for multifunction upper-limb prosthesis , 2003, IEEE Transactions on Biomedical Engineering.

[23]  Beth Jelfs,et al.  Self-Recalibrating Surface EMG Pattern Recognition for Neuroprosthesis Control Based on Convolutional Neural Network , 2017, Front. Neurosci..

[24]  Honghai Liu,et al.  Surface EMG data aggregation processing for intelligent prosthetic action recognition , 2018, Neural Computing and Applications.

[25]  Hao Wu,et al.  Dynamic Gesture Recognition in the Internet of Things , 2019, IEEE Access.

[26]  Lorenz Kahl,et al.  Comparison of algorithms to quantify muscle fatigue in upper limb muscles based on sEMG signals. , 2016, Medical engineering & physics.

[27]  Honghai Liu,et al.  Jointly network: a network based on CNN and RBM for gesture recognition , 2018, Neural Computing and Applications.

[28]  Jatin P. Ambegaonkar,et al.  Changing filtering parameters affects lower extremity pre-landing muscle activation onset times , 2010 .

[29]  Yinfeng Fang,et al.  Facilitate sEMG-Based Human-Machine Interaction Through Channel Optimization , 2019, Int. J. Humanoid Robotics.

[30]  Zhizeng Luo,et al.  Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors , 2017, Sensors.

[31]  Matthew J. Kyan,et al.  Visualization of Trunk Muscle Synergies During Sitting Perturbations Using Self-Organizing Maps (SOM) , 2012, IEEE Transactions on Biomedical Engineering.

[32]  Bernard J. Martin,et al.  Keyboard Reaction Force and Finger Flexor Electromyograms during Computer Keyboard Work , 1996, Hum. Factors.

[33]  J. Batle,et al.  Equilibrium and uniform charge distribution of a classical two-dimensional system of point charges with hard-wall confinement , 2017 .

[34]  Bo Tao,et al.  Gesture recognition based on skeletonization algorithm and CNN with ASL database , 2018, Multimedia Tools and Applications.

[35]  M. Hepp-Reymond,et al.  EMG activation patterns during force production in precision grip , 2004, Experimental Brain Research.

[36]  Yinfeng Fang,et al.  Surface electromyography feature extraction via convolutional neural network , 2020, Int. J. Mach. Learn. Cybern..

[37]  Honghai Liu,et al.  Gesture Recognition Based on Kinect and sEMG Signal Fusion , 2018, Mobile Networks and Applications.

[38]  Gongfa Li,et al.  Grip strength forecast and rehabilitative guidance based on adaptive neural fuzzy inference system using sEMG , 2019, Personal and Ubiquitous Computing.

[39]  J. Batle,et al.  Shareability of correlations in multiqubit states: Optimization of nonlocal monogamy inequalities , 2017 .

[40]  Angela E. Kedgley,et al.  The effects of wrist motion and hand orientation on muscle forces: A physiologic wrist simulator study , 2017, Journal of biomechanics.

[41]  Youngjin Na,et al.  Dynamic Elbow Flexion Force Estimation Through a Muscle Twitch Model and sEMG in a Fatigue Condition , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[42]  Davide Ballabio,et al.  A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure , 2015 .

[43]  Guohai Liu,et al.  Novel hybrid soft computing pattern recognition system SVM–GAPSO for classification of eight different hand motions , 2015 .

[44]  Ying Sun,et al.  Towards the sEMG hand: internet of things sensors and haptic feedback application , 2018, Multimedia Tools and Applications.

[45]  C. Kinnaird,et al.  Medial Gastrocnemius Myoelectric Control of a Robotic Ankle Exoskeleton , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[46]  Changmok Choi,et al.  Real-time pinch force estimation by surface electromyography using an artificial neural network. , 2010, Medical engineering & physics.

[47]  Sung Wook Baik,et al.  Image steganography using uncorrelated color space and its application for security of visual contents in online social networks , 2016, Future Gener. Comput. Syst..

[48]  Honghai Liu,et al.  Ultrasound-Based Sensing Models for Finger Motion Classification , 2018, IEEE Journal of Biomedical and Health Informatics.

[49]  Gongfa Li,et al.  Decomposition algorithm for depth image of human health posture based on brain health , 2019, Neural Computing and Applications.

[50]  Gongfa Li,et al.  A novel feature extraction method for machine learning based on surface electromyography from healthy brain , 2019, Neural Computing and Applications.

[51]  Jiang Hua,et al.  An Optimized Selection Method of Channel Numbers and Electrode Layouts for Hand Motion Recognition , 2019, Int. J. Humanoid Robotics.

[52]  Ahmed Farouk,et al.  A scheme for secure quantum communication network with authentication using GHZ-like states and cluster states controlled teleportation , 2015, Quantum Information Processing.

[53]  Ahmed Farouk,et al.  A new secure quantum watermarking scheme , 2017 .

[54]  Ahmed Farouk,et al.  A generalized architecture of quantum secure direct communication for N disjointed users with authentication , 2015, Scientific Reports.

[55]  Honghai Liu,et al.  Research on gesture recognition of smart data fusion features in the IoT , 2019, Neural Computing and Applications.

[56]  Gongfa Li,et al.  Hand medical monitoring system based on machine learning and optimal EMG feature set , 2019, Personal and Ubiquitous Computing.

[57]  Gongfa Li,et al.  CNN-Based Facial Expression Recognition from Annotated RGB-D Images for Human-Robot Interaction , 2019, Int. J. Humanoid Robotics.

[58]  Pornchai Phukpattaranont,et al.  Feature reduction and selection for EMG signal classification , 2012, Expert Syst. Appl..

[59]  Tanu Sharma,et al.  A novel feature extraction for robust EMG pattern recognition , 2016, Journal of medical engineering & technology.

[60]  Eduardo Gamaliel Hernández-Martínez,et al.  Multi-robot formation control using distance and orientation , 2016, Adv. Robotics.

[61]  Madasu Hanmandlu,et al.  High dynamic range optimal fuzzy color image enhancement using Artificial Ant Colony System , 2012, Appl. Soft Comput..