A review on EMG-based motor intention prediction of continuous human upper limb motion for human-robot collaboration
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[1] Lee E. Miller,et al. Continuous movement decoding using a target-dependent model with EMG inputs , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[2] Enzo Mastinu,et al. Evaluation of Computer-Based Target Achievement Tests for Myoelectric Control , 2017, IEEE Journal of Translational Engineering in Health and Medicine.
[3] Peternel Luka,et al. Towards multi-modal intention interfaces for human-robot co-manipulation , 2016 .
[4] Mikhail Kuznetsov,et al. Filtering the surface EMG signal: Movement artifact and baseline noise contamination. , 2010, Journal of biomechanics.
[5] Yuan-Ting Zhang,et al. A novel channel selection method for multiple motion classification using high-density electromyography , 2014, BioMedical Engineering OnLine.
[6] Jaap H van Dieën,et al. Methodological aspects of SEMG recordings for force estimation--a tutorial and review. , 2010, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[7] Angkoon Phinyomark,et al. EMG feature evaluation for improving myoelectric pattern recognition robustness , 2013, Expert Syst. Appl..
[8] Xu Zhang,et al. ECG artifact removal from EMG recordings using independent component analysis and adapted filter , 2013, 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER).
[9] T. Beck,et al. Comparison of methods for removing electromagnetic noise from electromyographic signals. , 2012, Physiological measurement.
[10] Chang-Kyu Park,et al. An EMG-based variable impedance control for elbow exercise: preliminary study , 2017, Adv. Robotics.
[11] Loredana Zollo,et al. Multimodal adaptive interfaces for 3D robot-mediated upper limb neuro-rehabilitation: An overview of bio-cooperative systems , 2016, Robotics Auton. Syst..
[12] Yunfen Wu,et al. Overview of the Application of EMG Recording in the Diagnosis and Approach of Neurological Disorders , 2013 .
[13] Guang-Zhong Yang,et al. Wearable Sensing for Solid Biomechanics: A Review , 2015, IEEE Sensors Journal.
[14] S. N. Sidek,et al. Estimation of continuous thumb angle and force using electromyogram classification , 2016 .
[15] Pu Liu,et al. Identification of Constant-Posture EMG–Torque Relationship About the Elbow Using Nonlinear Dynamic Models , 2012, IEEE Transactions on Biomedical Engineering.
[16] Nicola Vitiello,et al. Intention-Based EMG Control for Powered Exoskeletons , 2012, IEEE Transactions on Biomedical Engineering.
[17] Kerstin Dautenhahn,et al. Methodology & Themes of Human-Robot Interaction: A Growing Research Field , 2007 .
[18] Makoto Noshiro,et al. Development of a Compact Wireless Laplacian Electrode Module for Electromyograms and Its Human Interface Applications , 2013, Sensors.
[19] Jonathon W. Sensinger,et al. EMG Versus Torque Control of Human–Machine Systems: Equalizing Control Signal Variability Does not Equalize Error or Uncertainty , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[20] Kejun Zhang,et al. An Upper-Limb Power-Assist Exoskeleton Using Proportional Myoelectric Control , 2014, Sensors.
[21] Silvestro Micera,et al. Development and Quantitative Performance Evaluation of a Noninvasive EMG Computer Interface , 2009, IEEE Transactions on Biomedical Engineering.
[22] Joris M. Lambrecht,et al. Electromyogram-based neural network control of transhumeral prostheses. , 2011, Journal of rehabilitation research and development.
[23] Todd A. Kuiken,et al. The Effects of Electrode Size and Orientation on the Sensitivity of Myoelectric Pattern Recognition Systems to Electrode Shift , 2011, IEEE Transactions on Biomedical Engineering.
[24] Krishnan Chemmangat,et al. A novel pre-processing procedure for enhanced feature extraction and characterization of electromyogram signals , 2018, Biomed. Signal Process. Control..
[25] Ping Zhou,et al. Myoelectric Pattern Recognition Based on Muscle Synergies for Simultaneous Control of Dexterous Finger Movements , 2017, IEEE Transactions on Human-Machine Systems.
[26] Erik Scheme,et al. Signal whitening preprocessing for improved classification accuracies in myoelectric control , 2011, 2011 IEEE 37th Annual Northeast Bioengineering Conference (NEBEC).
[27] Asnor Juraiza Ishak,et al. Recommended surface EMG electrode position for wrist extension and flexion , 2015, 2015 IEEE Student Symposium in Biomedical Engineering & Sciences (ISSBES).
[28] Ping Zhou,et al. Automatic Implementation of Progressive FastICA Peel-Off for High Density Surface EMG Decomposition , 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[29] Suncheol Kwon,et al. Real-Time Upper Limb Motion Estimation From Surface Electromyography and Joint Angular Velocities Using an Artificial Neural Network for Human–Machine Cooperation , 2011, IEEE Transactions on Information Technology in Biomedicine.
[30] E. Clancy,et al. Using the Electromyogram to Anticipate Torques About the Elbow , 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[31] Huosheng Hu,et al. Human motion tracking for rehabilitation - A survey , 2008, Biomed. Signal Process. Control..
[32] Peter J. Kyberd,et al. EMG signal filtering based on Empirical Mode Decomposition , 2006, Biomed. Signal Process. Control..
[33] Gerald Seet,et al. An Implementation of Seamless Human-Robot Interaction for Telerobotics , 2008 .
[34] Jean-Sébastien Blouin,et al. Rectification is required to extract oscillatory envelope modulation from surface electromyographic signals. , 2014, Journal of neurophysiology.
[35] Mamun Bin Ibne Reaz,et al. Surface Electromyography Signal Processing and Classification Techniques , 2013, Sensors.
[36] Ruifeng Li,et al. Interface Design of a Physical Human–Robot Interaction System for Human Impedance Adaptive Skill Transfer , 2018, IEEE Transactions on Automation Science and Engineering.
[37] S. Leonhardt,et al. A survey on robotic devices for upper limb rehabilitation , 2014, Journal of NeuroEngineering and Rehabilitation.
[38] D. Donoval,et al. Biomedical signal amplifier for EMG wireless sensor system , 2010, The Eighth International Conference on Advanced Semiconductor Devices and Microsystems.
[39] Hasan Sözen,et al. Surface Electromyography in Sports and Exercise , 2013 .
[40] David L. Akin,et al. Space Telerobotics: Unique Challenges to Human–Robot Collaboration in Space , 2013 .
[41] B. Rajaratnam,et al. A Comparison of EMG Signals from Surface and Fine-Wire Electrodes During Shoulder Abduction , 2014 .
[42] Jianda Han,et al. Hierarchical projection regression for online estimation of elbow joint angle using EMG signals , 2013, Neural Computing and Applications.
[43] Dmitry Berenson,et al. Human-robot collaborative manipulation planning using early prediction of human motion , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[44] Javier Ruiz-del-Solar,et al. EMG Signal Filtering Based on Independent Component Analysis and Empirical Mode Decomposition for Estimation of Motor Activation Patterns , 2017 .
[45] Winnie Jensen,et al. Simultaneous and Proportional Force Estimation in Multiple Degrees of Freedom From Intramuscular EMG , 2012, IEEE Transactions on Biomedical Engineering.
[46] Rui Liu,et al. Fuzzy context-specific intention inference for robotic caregiving , 2016 .
[47] Carlos Martínez,et al. Human-robot collaboration in manufacturing: Quantitative evaluation of predictable, convergent joint action , 2013, IEEE ISR 2013.
[48] Etienne Burdet,et al. Slaves no longer: review on role assignment for human–robot joint motor action , 2014, Adapt. Behav..
[49] Parvin Mousavi,et al. EMG-force modeling using parallel cascade identification. , 2012, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[50] Panagiotis Artemiadis,et al. EMG-based Robot Control Interfaces: Past, Present and Future , 2012, ICRA 2012.
[51] Kenneth Sundaraj,et al. Design and development of a low cost EMG signal acquisition system using surface EMG electrode , 2010, 2010 IEEE Asia Pacific Conference on Circuits and Systems.
[52] Fuchun Sun,et al. sEMG-Based Joint Force Control for an Upper-Limb Power-Assist Exoskeleton Robot , 2014, IEEE Journal of Biomedical and Health Informatics.
[53] Jack P Callaghan,et al. Effects of minimum sampling rate and signal reconstruction on surface electromyographic signals. , 2005, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[54] Qin Zhang,et al. Human joint motion estimation for electromyography (EMG)-based dynamic motion control , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[55] Yiannis Demiris,et al. Collaborative Control for a Robotic Wheelchair: Evaluation of Performance, Attention, and Workload , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[56] Chandramouli Krishnan,et al. Modeling nonlinear errors in surface electromyography due to baseline noise: a new methodology. , 2011, Journal of biomechanics.
[57] Dario Farina,et al. Effect of arm position on the prediction of kinematics from EMG in amputees , 2012, Medical & Biological Engineering & Computing.
[58] Kaspar Althoefer,et al. Analysis of comfort and ergonomics for clinical work environments , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[59] Frédéric Lerasle,et al. A multi-modal perception based assistive robotic system for the elderly , 2016, Comput. Vis. Image Underst..
[60] June Sic Kim,et al. Estimation of the velocity and trajectory of three-dimensional reaching movements from non-invasive magnetoencephalography signals , 2013, Journal of neural engineering.
[61] Caihua Xiong,et al. Simultaneous and Continuous Estimation of Shoulder and Elbow Kinematics from Surface EMG Signals , 2017, Frontiers in neuroscience.
[62] Andrew J. Pullan,et al. Neuromuscular Interfacing: Establishing an EMG-Driven Model for the Human Elbow Joint , 2012, IEEE Transactions on Biomedical Engineering.
[63] Hamid R. Marateb,et al. Muscle Activity Map Reconstruction from High Density Surface EMG Signals With Missing Channels Using Image Inpainting and Surface Reconstruction Methods , 2017, IEEE Transactions on Biomedical Engineering.
[64] Pornchai Phukpattaranont,et al. Feature reduction and selection for EMG signal classification , 2012, Expert Syst. Appl..
[65] T. Kuiken,et al. The effect of subcutaneous fat on myoelectric signal amplitude and cross-talk , 2003, Prosthetics and orthotics international.
[66] Nurhazimah Nazmi,et al. A Review of Classification Techniques of EMG Signals during Isotonic and Isometric Contractions , 2016, Sensors.
[67] Nikolaos G. Tsagarakis,et al. Tele-impedance: Teleoperation with impedance regulation using a body–machine interface , 2012, Int. J. Robotics Res..
[68] Timothy Bretl,et al. Estimation of distal arm joint angles from EMG and shoulder orientation for transhumeral prostheses. , 2017, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[69] E. Clancy,et al. Two degrees of freedom quasi-static EMG-force at the wrist using a minimum number of electrodes. , 2017, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[70] Gordon Cheng,et al. Understanding the intention of human activities through semantic perception: observation, understanding and execution on a humanoid robot , 2015, Adv. Robotics.
[71] Jianda Han,et al. A novel EMG-driven state space model for the estimation of continuous joint movements , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.
[72] Giorgio Biagetti,et al. Homomorphic Deconvolution for MUAP Estimation From Surface EMG Signals , 2017, IEEE Journal of Biomedical and Health Informatics.
[73] Shan Xu,et al. A Research and Design on Surface EMG Amplifier , 2010, 2010 International Conference on Measuring Technology and Mechatronics Automation.
[74] Winnie Jensen,et al. Influence of the feature space on the estimation of hand grasping force from intramuscular EMG , 2013, Biomed. Signal Process. Control..
[75] Roberto Merletti,et al. Technology and instrumentation for detection and conditioning of the surface electromyographic signal: state of the art. , 2009, Clinical biomechanics.
[76] R Merletti,et al. Surface EMG: the issue of electrode location. , 2009, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[77] Jianda Han,et al. A State-Space EMG Model for the Estimation of Continuous Joint Movements , 2015, IEEE Transactions on Industrial Electronics.
[78] Wenwei Yu,et al. Classification of Upper Limb Motions from Around-Shoulder Muscle Activities: Hand Biofeedback , 2010, The open medical informatics journal.
[79] Sonia Duprey,et al. Kinematic models of the upper limb joints for multibody kinematics optimisation: An overview. , 2017, Journal of biomechanics.
[80] Chu Yih Bing,et al. Electromyography (EMG) and Human Locomotion , 2012 .
[81] K. S. Sivanandan,et al. Real Time Identification of Human Forearm Kinematics from Surface EMG Signal Using Artificial Neural Network Models , 2016 .
[82] Yee Mon Aung,et al. Estimation of Upper Limb Joint Angle Using Surface EMG Signal , 2013 .
[83] I. Kingma,et al. Towards optimal multi-channel EMG electrode configurations in muscle force estimation: a high density EMG study. , 2005, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[84] Jun Morimoto,et al. Human Movement Modeling to Detect Biosignal Sensor Failures for Myoelectric Assistive Robot Control , 2017, IEEE Transactions on Robotics.
[85] Ernest Nlandu Kamavuako,et al. Combined surface and intramuscular EMG for improved real-time myoelectric control performance , 2014, Biomed. Signal Process. Control..
[86] Siddhartha S. Srinivasa,et al. Human-robot mutual adaptation in collaborative tasks: Models and experiments , 2017, Int. J. Robotics Res..
[87] Lucas C. Parra,et al. Concurrent Adaptation of Human and Machine Improves Simultaneous and Proportional Myoelectric Control , 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[88] O. Stavdahl,et al. Control of Upper Limb Prostheses: Terminology and Proportional Myoelectric Control—A Review , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[89] Hande Türker,et al. Chapter 9 Surface Electromyography in Sports and Exercise , 2013 .
[90] Sanem Sariel,et al. Cognition-Enabled Robot Manipulation in Human Environments: Requirements, Recent Work, and Open Problems , 2017, IEEE Robotics & Automation Magazine.
[91] G. Schalk,et al. Brain-Computer Interfaces Using Electrocorticographic Signals , 2011, IEEE Reviews in Biomedical Engineering.
[92] J. F. Alonso,et al. Identification of isometric contractions based on High Density EMG maps. , 2013, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[93] Antonio Frisoli,et al. An EMG-based approach for on-line predicted torque control in robotic-assisted rehabilitation , 2014, 2014 IEEE Haptics Symposium (HAPTICS).
[94] Andrew J. Harrison,et al. An exploration of eliminating cross-talk in surface electromyography using independent component analysis , 2015, 2015 26th Irish Signals and Systems Conference (ISSC).
[95] Yoshiaki Hayashi,et al. Task estimation of upper-limb using EEG and EMG signals , 2014, 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.
[96] Robert Tibold,et al. Prediction of muscle activity during loaded movements of the upper limb , 2014, Journal of NeuroEngineering and Rehabilitation.
[97] Carlo J De Luca,et al. Inter-electrode spacing of surface EMG sensors: reduction of crosstalk contamination during voluntary contractions. , 2012, Journal of biomechanics.
[98] Hiroshi Yokoi,et al. Development of myoelectric hand that determines hand posture and estimates grip force simultaneously , 2017, Biomed. Signal Process. Control..
[99] F. Mohd-Yasin,et al. Techniques of EMG signal analysis: detection, processing, classification and applications , 2006, Biological Procedures Online.
[100] Xinjun Sheng,et al. Continuous estimation of finger joint angles under different static wrist motions from surface EMG signals , 2014, Biomed. Signal Process. Control..
[101] Maryam Shojaei Baghini,et al. A novel low-noise fully differential CMOS instrumentation amplifier with 1.88 noise efficiency factor for biomedical and sensor applications , 2016, Microelectron. J..
[102] M. Latash. Fundamentals of Motor Control , 2012 .
[103] Mohsen Naji,et al. The application of Empirical Mode Decomposition in elimination of ECG contamination from EMG signals , 2011, 2011 18th Iranian Conference of Biomedical Engineering (ICBME).
[104] Ilse Jonkers,et al. Three-dimensional reaching tasks: effect of reaching height and width on upper limb kinematics and muscle activity. , 2010, Gait & posture.
[105] Fumitoshi Matsuno,et al. Hand and Wrist Movement Control of Myoelectric Prosthesis Based on Synergy , 2015, IEEE Transactions on Human-Machine Systems.
[106] Dario Farina,et al. High-density EMG E-Textile systems for the control of active prostheses , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[107] Shuxiang Guo,et al. Electromyography-Based Quantitative Representation Method for Upper-Limb Elbow Joint Angle in Sagittal Plane , 2015, Journal of medical and biological engineering.
[108] Chenguang Yang,et al. Guest Editorial An Overview of Biomedical Robotics and Bio-Mechatronics Systems and Applications , 2016, IEEE Trans. Syst. Man Cybern. Syst..
[109] E. Clancy,et al. Influence of Joint Angle on EMG-Torque Model During Constant-Posture, Torque-Varying Contractions , 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[110] J. Geoffrey Chase,et al. Human-Robot Collaboration: A Literature Review and Augmented Reality Approach in Design , 2008 .
[111] Luca Benini,et al. Digitally controlled feedback for DC offset cancellation in a wearable multichannel EMG platform , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[112] Edward A. Clancy,et al. Electromyogram Bandwidth Requirements When the Signal is Whitened , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[113] H. Huang,et al. Lumped-parameter electromyogram-driven musculoskeletal hand model: A potential platform for real-time prosthesis control. , 2016, Journal of biomechanics.
[114] Cagatay Basdogan,et al. The role of roles: Physical cooperation between humans and robots , 2012, Int. J. Robotics Res..
[115] D. Farina,et al. Simultaneous and Proportional Estimation of Hand Kinematics From EMG During Mirrored Movements at Multiple Degrees-of-Freedom , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[116] Keith S. Jones,et al. Human-Robot Interaction Toward Usable Personal Service Robots , 2011 .
[117] Dario Farina,et al. The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[118] Huosheng Hu,et al. Bio-signal based control in assistive robots: a survey , 2015, Digit. Commun. Networks.
[119] Yasuharu Koike,et al. Estimation of dynamic joint torques and trajectory formation from surface electromyography signals using a neural network model , 1995, Biological Cybernetics.
[120] Kristin E. Schaefer,et al. Relinquishing Manual Control: Collaboration Requires the Capability to Understand Robot Intent , 2016, 2016 International Conference on Collaboration Technologies and Systems (CTS).
[121] Youngjin Choi,et al. EMG-Based Continuous Control Scheme With Simple Classifier for Electric-Powered Wheelchair , 2016, IEEE Transactions on Industrial Electronics.
[122] Fabio Babiloni,et al. On the Use of Electrooculogram for Efficient Human Computer Interfaces , 2009, Comput. Intell. Neurosci..
[123] Guanglin Li,et al. Conditioning and Sampling Issues of EMG Signals in Motion Recognition of Multifunctional Myoelectric Prostheses , 2011, Annals of Biomedical Engineering.
[124] Dario Farina,et al. Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation , 2017, Nature Biomedical Engineering.
[125] Constantinos Gavriel,et al. Gaussian Process Autoregression for Simultaneous Proportional Multi-Modal Prosthetic Control With Natural Hand Kinematics , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[126] Yupeng Ren,et al. EMG-Based Continuous and Simultaneous Estimation of Arm Kinematics in Able-Bodied Individuals and Stroke Survivors , 2017, Front. Neurosci..
[127] Levi J. Hargrove,et al. Comparison of surface and intramuscular EMG pattern recognition for simultaneous wrist/hand motion classification , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[128] G R Johnson,et al. A framework for the definition of standardized protocols for measuring upper-extremity kinematics. , 2009, Clinical biomechanics.
[129] Dario Farina,et al. Extracting Signals Robust to Electrode Number and Shift for Online Simultaneous and Proportional Myoelectric Control by Factorization Algorithms , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[130] Dario Farina,et al. Bayesian Filtering of Surface EMG for Accurate Simultaneous and Proportional Prosthetic Control , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[131] Norman I. Badler,et al. Defining Next-Generation Multi-Modal Communication in Human Robot Interaction , 2011 .
[132] Sridhar Krishnan,et al. Biosignal monitoring using wearables: Observations and opportunities , 2017, Biomed. Signal Process. Control..
[133] Panagiotis K. Artemiadis,et al. Estimating arm motion and force using EMG signals: On the control of exoskeletons , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[134] Chang-Soo Han,et al. Estimation of desired motion intention using extreme learning machine for upper limb assist exoskeleton , 2016, 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).
[135] Allison M. Okamura,et al. Toward human-robot collaboration in surgery: Performance assessment of human and robotic agents in an inclusion segmentation task , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[136] Péter Szolgay,et al. Real-time inverse kinematics for the upper limb: a model-based algorithm using segment orientations , 2017, Biomedical engineering online.
[137] Lin Wang,et al. Prediction of joint moments using a neural network model of muscle activations from EMG signals , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[138] Yee Mon Aung,et al. SEMG based ANN for shoulder angle prediction , 2012 .
[139] David G. Lloyd,et al. Neural Data-Driven Musculoskeletal Modeling for Personalized Neurorehabilitation Technologies , 2016, IEEE Transactions on Biomedical Engineering.
[140] Minoru Asada,et al. Efficient human-robot collaboration: When should a robot take initiative? , 2017, Int. J. Robotics Res..
[141] Séverin Lemaignan,et al. Artificial cognition for social human-robot interaction: An implementation , 2017, Artif. Intell..
[142] Yoshiaki Hayashi,et al. An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[143] Panagiotis Kosmas,et al. An Embedded, 8-Channel, Noise Canceling, Wireless, Wearable sEMG Data Acquisition System with Adaptive Muscle Contraction Detection , 2017 .
[144] K. K. Ray,et al. EMG based man-machine interaction - A pattern recognition research platform , 2014, Robotics Auton. Syst..
[145] Xinjun Sheng,et al. Toward an Enhanced Human–Machine Interface for Upper-Limb Prosthesis Control With Combined EMG and NIRS Signals , 2017, IEEE Transactions on Human-Machine Systems.
[146] Huosheng Hu,et al. Myoelectric control systems - A survey , 2007, Biomed. Signal Process. Control..
[147] Jun Morimoto,et al. EMG-Based Model Predictive Control for Physical Human–Robot Interaction: Application for Assist-As-Needed Control , 2018, IEEE Robotics and Automation Letters.
[148] Alois Knoll,et al. Mechanisms and capabilities for human robot collaboration , 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.
[149] Maarouf Saad,et al. EMG based control of a robotic exoskeleton for shoulder and elbow motion assist , 2015 .
[150] Francesco Nori,et al. Evidence for Composite Cost Functions in Arm Movement Planning: An Inverse Optimal Control Approach , 2011, PLoS Comput. Biol..
[151] Kaspar Althoefer,et al. Embroidered Electromyography: A Systematic Design Guide , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[152] Youngjin Choi,et al. Human elbow joint angle estimation using electromyogram signal processing , 2011 .
[153] Yili Liu,et al. EEG-Based Brain-Controlled Mobile Robots: A Survey , 2013, IEEE Transactions on Human-Machine Systems.
[154] Panagiotis K. Artemiadis,et al. An EMG-Based Robot Control Scheme Robust to Time-Varying EMG Signal Features , 2010, IEEE Transactions on Information Technology in Biomedicine.
[155] M. Noshiro,et al. A Capacitive Sensor System for Measuring Laplacian Electromyogram through Cloth: A Pilot Study , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[156] Rainer Bader,et al. The Effect of the Weight of Equipment on Muscle Activity of the Lower Extremity in Soldiers , 2012, TheScientificWorldJournal.
[157] Othman Omran Khalifa,et al. EMG signal classification for human computer interaction: a review , 2009 .
[158] F Stegeman Dick,et al. High-density Surface EMG: Techniques and Applications at a Motor Unit Level , 2012 .
[159] Arto Visala,et al. urrent state of digital signal processing in myoelectric interfaces and elated applications , 2015 .
[160] Dario Farina,et al. Decomposition of Multi-Channel Intramuscular EMG Signals by Cyclostationary-Based Blind Source Separation , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[161] Yan Wu,et al. Human-robot partnership: A study on collaborative storytelling , 2016, 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[162] J. Ives,et al. Sampling rate effects on surface EMG timing and amplitude measures. , 2003, Clinical biomechanics.
[163] Jun Morimoto,et al. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation , 2016, PloS one.
[164] Toshio Tsuji,et al. A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution , 2017, IEEE Transactions on Biomedical Engineering.
[165] B. Freriks,et al. Development of recommendations for SEMG sensors and sensor placement procedures. , 2000, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[166] Dario Farina,et al. Decoding Motor Unit Activity From Forearm Muscles: Perspectives for Myoelectric Control , 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[167] David A Gabriel,et al. Effects of monopolar and bipolar electrode configurations on surface EMG spike analysis. , 2011, Medical engineering & physics.
[168] Erik J Scheme,et al. On the usability of intramuscular EMG for prosthetic control: a Fitts' Law approach. , 2014, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[169] Panagiotis K. Artemiadis,et al. Proportional Myoelectric Control of Robots: Muscle Synergy Development Drives Performance Enhancement, Retainment, and Generalization , 2015, IEEE Transactions on Robotics.
[170] Amedeo Cesta,et al. Psychophysiological Methods to Evaluate User's Response in Human Robot Interaction: A Review and Feasibility Study , 2013, Robotics.
[171] Panagiotis K. Artemiadis,et al. EMG-Based Control of a Robot Arm Using Low-Dimensional Embeddings , 2010, IEEE Transactions on Robotics.
[172] Dario Farina,et al. Simultaneous and Proportional Force Estimation for Multifunction Myoelectric Prostheses Using Mirrored Bilateral Training , 2011, IEEE Transactions on Biomedical Engineering.
[173] Dario Farina,et al. Is Accurate Mapping of EMG Signals on Kinematics Needed for Precise Online Myoelectric Control? , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[174] Danica Kragic,et al. Motion intention recognition in robot assisted applications , 2008, Robotics Auton. Syst..
[175] Gert-Åke Hansson,et al. Modeling nonlinear errors in surface electromyography due to baseline noise: a new methodology. , 2011, Journal of biomechanics.