A hybrid BMI-based exoskeleton for paresis: EMG control for assisting arm movements
暂无分享,去创建一个
[1] Robert E. Kearney,et al. Identification of nonlinearities in the neuromuscular system , 1988, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[2] P. Komi,et al. Electromechanical delay in skeletal muscle under normal movement conditions. , 1979, Acta physiologica Scandinavica.
[3] Ping Yu,et al. Classification of Surface EMG Signal Based on Energy Spectra Change , 2008, 2008 International Conference on BioMedical Engineering and Informatics.
[4] Changmok Choi,et al. Synergy matrices to estimate fluid wrist movements by surface electromyography. , 2011, Medical engineering & physics.
[5] Gary Kamen,et al. Essentials of Electromyography , 2009 .
[6] Panagiotis K. Artemiadis,et al. Learning efficient control of robots using myoelectric interfaces , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[7] Yoshiaki Hayashi,et al. Towards Hybrid EEG-EMG-Based Control Approaches to be Used in Bio-robotics Applications: Current Status, Challenges and Future Directions , 2013, Paladyn J. Behav. Robotics.
[8] Volkan Patoglu,et al. Tele-impedance control of a variable stiffness prosthetic hand , 2012, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO).
[9] D. Gravel,et al. Normality and stationarity of EMG signals of elbow flexor muscles during ramp and step isometric contractions. , 1997, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[10] Richard R Neptune,et al. Merging of healthy motor modules predicts reduced locomotor performance and muscle coordination complexity post-stroke. , 2010, Journal of neurophysiology.
[11] Ferat Sahin,et al. Pattern recognition with surface EMG signal based wavelet transformation , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
[12] D. Farina,et al. Linear and Nonlinear Regression Techniques for Simultaneous and Proportional Myoelectric Control , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[13] Yoshiyuki Sankai,et al. Control method of robot suit HAL working as operator's muscle using biological and dynamical information , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[14] U. Baspinar,et al. Classification of hand movements by using artificial neural network , 2012, 2012 International Symposium on Innovations in Intelligent Systems and Applications.
[15] Wynne A. Lee,et al. Neuromotor synergies as a basis for coordinated intentional action. , 1984, Journal of motor behavior.
[16] Marie-Françoise Lucas,et al. Multi-channel surface EMG classification using support vector machines and signal-based wavelet optimization , 2008, Biomed. Signal Process. Control..
[17] E. Bizzi,et al. The construction of movement by the spinal cord , 1999, Nature Neuroscience.
[18] Andrew Jackson,et al. Learning a Novel Myoelectric-Controlled Interface Task , 2008, Journal of neurophysiology.
[19] Catherine Marque,et al. Classification of multichannel uterine EMG signals by using unsupervised competitive learning , 2011, 2011 IEEE Workshop on Signal Processing Systems (SiPS).
[20] Othman Omran Khalifa,et al. VHDL Modelling of Fixed-point DWT for the Purpose of EMG Signal Denoising , 2011, 2011 Third International Conference on Computational Intelligence, Communication Systems and Networks.
[21] Francisco J. Valero Cuevas,et al. Challenges and New Approaches to Proving the Existence of Muscle Synergies of Neural Origin , 2012, PLoS Comput. Biol..
[22] Gea Drost,et al. Clinical applications of high-density surface EMG: a systematic review. , 2006, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[23] Jaime Valls Miró,et al. Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features , 2014, Neural Networks.
[24] Laura A. Miller,et al. Summary and Recommendations of the Academy's State of the Science Conference on Upper Limb Prosthetic Outcome Measures , 2009 .
[25] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[26] Fan Zhang,et al. Reduction of the effect of arm position variation on real-time performance of motion classification , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[27] Panagiotis K. Artemiadis,et al. EMG-based teleoperation of a robot arm in planar catching movements using ARMAX model and trajectory monitoring techniques , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..
[28] Changmok Choi,et al. A Real-time EMG-based Assistive Computer Interface for the Upper Limb Disabled , 2007, 2007 IEEE 10th International Conference on Rehabilitation Robotics.
[29] G. Pfurtscheller,et al. Self-Paced Operation of an SSVEP-Based Orthosis With and Without an Imagery-Based “Brain Switch:” A Feasibility Study Towards a Hybrid BCI , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[30] Rajesh P. N. Rao,et al. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. 1 Online Electromyographic Control of a Robotic , 2022 .
[31] Khalil Ullah,et al. A mathematical model for mapping EMG signal to joint torque for the human elbow joint using nonlinear regression , 2000, 2009 4th International Conference on Autonomous Robots and Agents.
[32] Barbara Caputo,et al. Stable myoelectric control of a hand prosthesis using non-linear incremental learning , 2014, Front. Neurorobot..
[33] Mamun Bin Ibne Reaz,et al. Surface Electromyography Signal Processing and Classification Techniques , 2013, Sensors.
[34] Bruce C. Wheeler,et al. EMG feature evaluation for movement control of upper extremity prostheses , 1995 .
[35] Elsa Andrea Kirchner,et al. Exoskeleton Technology in Rehabilitation: Towards an EMG-Based Orthosis System for Upper Limb Neuromotor Rehabilitation , 2013, J. Robotics.
[36] Takayuki Koizumi,et al. Forearm motion discrimination technique using real-time EMG signals , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[37] Lauren H Smith,et al. A comparison of the real-time controllability of pattern recognition to conventional myoelectric control for discrete and simultaneous movements , 2012, Journal of NeuroEngineering and Rehabilitation.
[38] 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.
[39] 清田晴彦,et al. Power assist device , 2012 .
[40] S. Giszter,et al. Modular Premotor Drives and Unit Bursts as Primitives for Frog Motor Behaviors , 2004, The Journal of Neuroscience.
[41] K. Kiguchi,et al. A human forearm and wrist motion assist exoskeleton robot with EMG-based Fuzzy-neuro control , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.
[42] Erik Scheme,et al. Motion Normalized Proportional Control for Improved Pattern Recognition-Based Myoelectric Control , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[43] E. Bizzi,et al. Muscle synergies encoded within the spinal cord: evidence from focal intraspinal NMDA iontophoresis in the frog. , 2001, Journal of neurophysiology.
[44] Dario Farina,et al. Influence of amplitude cancellation on the accuracy of determining the onset of muscle activity from the surface electromyogram. , 2012, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[45] H. H. Sears,et al. PROPORTIONAL MYOELECTRIC HAND CONTROL: AN EVALUATION , 1991, American journal of physical medicine & rehabilitation.
[46] L. J. Hargrove,et al. A new hierarchical approach for simultaneous control of multi-joint powered prostheses , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).
[47] Hirokazu Seki,et al. Optimal mapping of torus self-organizing map for forearm motion discrimination based on EMG , 2010, Proceedings of SICE Annual Conference 2010.
[48] Andreas Daffertshofer,et al. Independent Component Analysis of High-Density Electromyography in Muscle Force Estimation , 2007, IEEE Transactions on Biomedical Engineering.
[49] Tania Hanekom,et al. Effect of spatial filtering on crosstalk reduction in surface EMG recordings. , 2009, Medical engineering & physics.
[50] Günter Hommel,et al. Predicting the intended motion with EMG signals for an exoskeleton orthosis controller , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[51] T. Kuiken,et al. Improved Myoelectric Prosthesis Control Using Targeted Reinnervation Surgery: A Case Series , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[52] Lena H Ting,et al. A limited set of muscle synergies for force control during a postural task. , 2005, Journal of neurophysiology.
[53] Huosheng Hu,et al. Support Vector Machine-Based Classification Scheme for Myoelectric Control Applied to Upper Limb , 2008, IEEE Transactions on Biomedical Engineering.
[54] Aidan D. Roche,et al. Prosthetic Myoelectric Control Strategies: A Clinical Perspective , 2014, Current Surgery Reports.
[55] Massimo Sartori,et al. A lower limb EMG-driven biomechanical model for applications in rehabilitation robotics , 2009, 2009 International Conference on Advanced Robotics.
[56] Xiao Hu,et al. Multivariate AR modeling of electromyography for the classification of upper arm movements , 2004, Clinical Neurophysiology.
[57] W. Rymer,et al. Endpoint force fluctuations reveal flexible rather than synergistic patterns of muscle cooperation. , 2008, Journal of neurophysiology.
[58] D. Guiraud,et al. FES-Induced Torque Prediction With Evoked EMG Sensing for Muscle Fatigue Tracking , 2011, IEEE/ASME Transactions on Mechatronics.
[59] Aymar de Rugy,et al. Are muscle synergies useful for neural control? , 2013, Front. Comput. Neurosci..
[60] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[61] Panagiotis Artemiadis,et al. User-Independent Hand Motion Classification With Electromyography , 2013 .
[62] Dario Farina,et al. Noninvasive, Accurate Assessment of the Behavior of Representative Populations of Motor Units in Targeted Reinnervated Muscles , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[63] Dario Farina,et al. Multichannel surface EMG based estimation of bilateral hand kinematics during movements at multiple degrees of freedom , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[64] G. Pfurtscheller,et al. Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.
[65] Rami N. Khushaba,et al. Correlation Analysis of Electromyogram Signals for Multiuser Myoelectric Interfaces , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[66] Huosheng Hu,et al. CES-513 Stages for Developing Control Systems using EMG and EEG Signals: A survey , 2011 .
[67] K. Englehart,et al. Resolving the Limb Position Effect in Myoelectric Pattern Recognition , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[68] Gea Drost,et al. Motor unit characteristics in healthy subjects and those with postpoliomyelitis syndrome: A high‐density surface EMG study , 2004, Muscle & nerve.
[69] Spencer Kellis,et al. Sensing millimeter-scale dynamics in cortical surface potentials for neural prosthetics , 2011, 2011 IEEE SENSORS Proceedings.
[70] Lena H Ting,et al. Neuromechanics of muscle synergies for posture and movement , 2007, Current Opinion in Neurobiology.
[71] Guanglin Li,et al. Principal Components Analysis Preprocessing for Improved Classification Accuracies in Pattern-Recognition-Based Myoelectric Control , 2009, IEEE Transactions on Biomedical Engineering.
[72] Andrea d'Avella,et al. Matrix factorization algorithms for the identification of muscle synergies: evaluation on simulated and experimental data sets. , 2006, Journal of neurophysiology.
[73] Stefano Panzeri,et al. Quantitative evaluation of muscle synergy models: a single-trial task decoding approach , 2013, Front. Comput. Neurosci..
[74] Desney S. Tan,et al. Demonstrating the feasibility of using forearm electromyography for muscle-computer interfaces , 2008, CHI.
[75] A. Jackson,et al. Flexible Cortical Control of Task-Specific Muscle Synergies , 2012, The Journal of Neuroscience.
[76] Farbod Fahimi,et al. Online human training of a myoelectric prosthesis controller via actor-critic reinforcement learning , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.
[77] Giulio Sandini,et al. Fine detection of grasp force and posture by amputees via surface electromyography , 2009, Journal of Physiology-Paris.
[78] F. Lacquaniti,et al. An assessment of the existence of muscle synergies during load perturbations and intentional movements of the human arm , 2004, Experimental Brain Research.
[79] Dingguo Zhang,et al. A discriminant bispectrum feature for surface electromyogram signal classification. , 2010, Medical engineering & physics.
[80] Christian Cipriani,et al. Abstract and Proportional Myoelectric Control for Multi-Fingered Hand Prostheses , 2013, Annals of Biomedical Engineering.
[81] Huosheng Hu,et al. Myoelectric control systems - A survey , 2007, Biomed. Signal Process. Control..
[82] Ferdinando A Mussa-Ivaldi,et al. Remapping hand movements in a novel geometrical environment. , 2005, Journal of neurophysiology.
[83] N. Thakor,et al. A Training Strategy for Learning Pattern Recognition Control for Myoelectric Prostheses , 2013, Journal of prosthetics and orthotics : JPO.
[84] F. Lacquaniti,et al. Coordination of Locomotion with Voluntary Movements in Humans , 2005, The Journal of Neuroscience.
[85] Dario Farina,et al. Intuitive, Online, Simultaneous, and Proportional Myoelectric Control Over Two Degrees-of-Freedom in Upper Limb Amputees , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[86] E.M. El-Daydamony,et al. A computerized system for SEMG signals analysis and classifieation , 2008, 2008 National Radio Science Conference.
[87] Shiqian Wang,et al. Design and Control of the MINDWALKER Exoskeleton , 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[88] Blair A. Lock,et al. Determining the Optimal Window Length for Pattern Recognition-Based Myoelectric Control: Balancing the Competing Effects of Classification Error and Controller Delay , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[89] Dario Farina,et al. Identifying representative synergy matrices for describing muscular activation patterns during multidirectional reaching in the horizontal plane. , 2010, Journal of neurophysiology.
[90] Evelyn Morin. Identifying the EMG-force relationship , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.
[91] M. Tresch,et al. The case for and against muscle synergies , 2022 .
[92] Jose M. Carmena,et al. Learning in Closed-Loop Brain–Machine Interfaces: Modeling and Experimental Validation , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[93] Andrea d'Avella,et al. Effective force control by muscle synergies , 2014, Front. Comput. Neurosci..
[94] G. E. Loeb,et al. Functionally complex muscles of the cat hindlimb , 2004, Experimental Brain Research.
[95] Damjan Zazula,et al. An approach to surface EMG decomposition based on higher-order cumulants , 2005, Comput. Methods Programs Biomed..
[96] 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.
[97] Otr Joan C. Rogers,et al. Evaluation in occupational therapy , 2016 .
[98] Dennis C. Tkach,et al. Study of stability of time-domain features for electromyographic pattern recognition , 2010, Journal of NeuroEngineering and Rehabilitation.
[99] Qingshan She,et al. EMG signals based gait phases recognition using hidden Markov models , 2010, The 2010 IEEE International Conference on Information and Automation.
[100] Linan Zu,et al. Electromyogram signal analysis and movement recognition based on wavelet packet transform , 2009, 2009 International Conference on Information and Automation.
[101] Dario Farina,et al. Myoelectric Control of Artificial Limbs¿Is There a Need to Change Focus? [In the Spotlight] , 2012, IEEE Signal Process. Mag..
[102] Dick F. Stegeman,et al. T. Multi-channel surface EMG in clinical neurophysiology. , 2000 .
[103] Waixi Liu,et al. Feature Extraction of Surface EMG Signal Based on Wavelet Coefficient Entropy , 2008, 2008 2nd International Conference on Bioinformatics and Biomedical Engineering.
[104] A. M. Simon,et al. Patient Training for Functional Use of Pattern Recognition–Controlled Prostheses , 2012, Journal of prosthetics and orthotics : JPO.
[105] F. Mohd-Yasin,et al. Techniques of EMG signal analysis: detection, processing, classification and applications , 2006, Biological Procedures Online.
[106] Sébastien Marcel,et al. Inter-session variability modelling and joint factor analysis for face authentication , 2011, 2011 International Joint Conference on Biometrics (IJCB).
[107] Justin Bayer,et al. Continuous robot control using surface electromyography of atrophic muscles , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[108] Maura Casadio,et al. Reorganization of finger coordination patterns during adaptation to rotation and scaling of a newly learned sensorimotor transformation. , 2011, Journal of neurophysiology.
[109] Ning Jiang,et al. Extracting Simultaneous and Proportional Neural Control Information for Multiple-DOF Prostheses From the Surface Electromyographic Signal , 2009, IEEE Transactions on Biomedical Engineering.
[110] S. Meek,et al. Comparison of signal-to-noise ratio of myoelectric filters for prosthesis control. , 1992, Journal of rehabilitation research and development.
[111] Maura Casadio,et al. Sensory motor remapping of space in human-machine interfaces. , 2011, Progress in brain research.
[112] Hillel J. Chiel,et al. The Brain in Its Body: Motor Control and Sensing in a Biomechanical Context , 2009, The Journal of Neuroscience.
[113] Stephane Cotin,et al. Constraint-Based Haptic Rendering of Multirate Compliant Mechanisms , 2011, IEEE Transactions on Haptics.
[114] Milos Manic,et al. Fuzzy Force-Feedback Augmentation for Manual Control of Multirobot System , 2011, IEEE Transactions on Industrial Electronics.
[115] Sue Francis,et al. Physiological measurements using ultra-high field fMRI: a review , 2014, Physiological measurement.
[116] B. Hudgins,et al. REAL-TIME MYOELECTRIC CONTROL IN A VIRTUAL ENVIRONMENT TO RELATE USABILITY VS. ACCURACY , 2005 .
[117] Dario Farina,et al. Influence of the training set on the accuracy of surface EMG classification in dynamic contractions for the control of multifunction prostheses , 2011, Journal of NeuroEngineering and Rehabilitation.
[118] Levi J. Hargrove,et al. A Comparison of Surface and Intramuscular Myoelectric Signal Classification , 2007, IEEE Transactions on Biomedical Engineering.
[119] L. E. Peppard,et al. Feature-based classification of myoelectric signals using artificial neural networks , 1998, Medical and Biological Engineering and Computing.
[120] Dario Farina,et al. Interpretation of the Surface Electromyogram in Dynamic Contractions , 2006, Exercise and sport sciences reviews.
[121] D. Atkins,et al. Epidemiologic Overview of Individuals with Upper-Limb Loss and Their Reported Research Priorities , 1996 .
[122] R. Enoka,et al. Influence of amplitude cancellation on the simulated surface electromyogram. , 2005, Journal of applied physiology.
[123] Rahman Khorsandi,et al. Estimation of Muscle Force with EMG Signals Using Hammerstein-Wiener Model , 2011 .
[124] Keitaro Naruse,et al. Study for control of a power assist device. Development of an EMG based controller considering a human model , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).
[125] Robert E. Kass,et al. 2009 Special Issue: Bias, optimal linear estimation, and the differences between open-loop simulation and closed-loop performance of spiking-based brain-computer interface algorithms , 2009 .
[126] 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.
[127] K. Nazarpour,et al. Negentropy analysis of surface electromyogram signal , 2005, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005.
[128] A.D.C. Chan,et al. Examining the adverse effects of limb position on pattern recognition based myoelectric control , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[129] Andreas Daffertshofer,et al. Removing ECG contamination from EMG recordings: a comparison of ICA-based and other filtering procedures. , 2012, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[130] Fei Xu,et al. SEMG feature extraction methods for pattern recognition of upper limbs , 2011, The 2011 International Conference on Advanced Mechatronic Systems.
[131] G.F. Inbar,et al. Classification of finger activation for use in a robotic prosthesis arm , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[132] Dennis J. McFarland,et al. Brain–computer interfaces for communication and control , 2002, Clinical Neurophysiology.
[133] Robert N. Scott. MYOELECTRIC CONTROL OF PROSTHESES AND ORTHOSES , 2009 .
[134] François Hug,et al. Can muscle coordination be precisely studied by surface electromyography? , 2011, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[135] Levi J. Hargrove,et al. Classification of Simultaneous Movements Using Surface EMG Pattern Recognition , 2013, IEEE Transactions on Biomedical Engineering.
[136] Dingguo Zhang,et al. Spatio-spectral filters for low-density surface electromyographic signal classification , 2012, Medical & Biological Engineering & Computing.
[137] Christopher Assad,et al. BioSleeve: A natural EMG-based interface for HRI , 2013, 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[138] Carlo Menon,et al. Surface EMG pattern recognition for real-time control of a wrist exoskeleton , 2010, Biomedical engineering online.
[139] Adrian D. C. Chan,et al. A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses , 2005, IEEE Transactions on Biomedical Engineering.
[140] Jin Zhong,et al. Recognition of hand motions via surface EMG signal with rough entropy , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[141] 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.
[142] A. Hudspeth,et al. The physics of hearing: fluid mechanics and the active process of the inner ear , 2014, Reports on progress in physics. Physical Society.
[143] Lena H Ting,et al. Muscle synergy organization is robust across a variety of postural perturbations. , 2006, Journal of neurophysiology.
[144] 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.
[145] Etem Koklukaya,et al. Classification of EMG signals using wavelet based autoregressive models and neural networks to control prothesis-bionic hand , 2009, 2009 14th National Biomedical Engineering Meeting.
[146] Adrian D. C. Chan,et al. Continuous myoelectric control for powered prostheses using hidden Markov models , 2005, IEEE Transactions on Biomedical Engineering.
[147] H. M. Toussaint,et al. The electro-mechanical delay of the erector spinae muscle: influence of rate of force development, fatigue and electrode location , 2004, European Journal of Applied Physiology and Occupational Physiology.
[148] Ann M. Simon,et al. Pattern recognition control outperforms conventional myoelectric control in upper limb patients with targeted muscle reinnervation , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[149] Martha Flanders,et al. Muscular and postural synergies of the human hand. , 2004, Journal of neurophysiology.
[150] Panagiotis Artemiadis,et al. Embedded Human Control of Robots Using Myoelectric Interfaces , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[151] Adel Al-Jumaily,et al. Orthogonal Fuzzy Neighborhood Discriminant Analysis for Multifunction Myoelectric Hand Control , 2010, IEEE Transactions on Biomedical Engineering.
[152] D T Hutchinson,et al. Continuous Detection and Decoding of Dexterous Finger Flexions With Implantable MyoElectric Sensors , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[153] Ahmad R. Sharafat,et al. Application of Higher Order Statistics to Surface Electromyogram Signal Classification , 2007, IEEE Transactions on Biomedical Engineering.
[154] H. Flor,et al. A spelling device for the paralysed , 1999, Nature.
[155] Ernest Nlandu Kamavuako,et al. Combined surface and intramuscular EMG for improved real-time myoelectric control performance , 2014, Biomed. Signal Process. Control..
[156] Panagiotis K. Artemiadis,et al. EMG-Based Position and Force Estimates in Coupled Human-Robot Systems: Towards EMG-Controlled Exoskeletons , 2008, ISER.
[157] Panagiotis K. Artemiadis,et al. Learning human reach-to-grasp strategies: Towards EMG-based control of robotic arm-hand systems , 2012, 2012 IEEE International Conference on Robotics and Automation.
[158] W. Kargo,et al. Early Skill Learning Is Expressed through Selection and Tuning of Cortically Represented Muscle Synergies , 2003, The Journal of Neuroscience.
[159] Nikolaos G. Tsagarakis,et al. Teleimpedance control of a synergy-driven anthropomorphic hand , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[160] K.B. Englehart,et al. Multiple Binary Classifications via Linear Discriminant Analysis for Improved Controllability of a Powered Prosthesis , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[161] D. Stegeman,et al. Multichannel surface EMG: Basic aspects and clinical utility , 2003, Muscle & nerve.
[162] 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.
[163] Dario Farina,et al. Self-Correcting Pattern Recognition System of Surface EMG Signals for Upper Limb Prosthesis Control , 2014, IEEE Transactions on Biomedical Engineering.
[164] K. Englehart,et al. Classification of the myoelectric signal using time-frequency based representations. , 1999, Medical engineering & physics.
[165] Y. Kobayashi,et al. Tremor frequency based filter to extract voluntary movement of patients with essential tremor , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).
[166] Finley Fr,et al. Myocoder studies of multiple myopotential response. , 1967 .
[167] L GILLIS. Recent advances in the treatment of arm amputations, kineplastic surgery and arm prostheses. , 1948, Annals of the Royal College of Surgeons of England.
[168] Vladimir M. Zatsiorsky,et al. Muscle synergies during shifts of the center of pressure by standing persons , 2003, Experimental Brain Research.
[169] Allison M. Okamura,et al. Task-dependent impedance and implications for upper-limb prosthesis control , 2014, Int. J. Robotics Res..
[170] Imteyaz Ahmad,et al. A Review of EMG recording technique , 2012 .
[171] Nikolaos G. Tsagarakis,et al. Tele-impedance: Teleoperation with impedance regulation using a body–machine interface , 2012, Int. J. Robotics Res..
[172] Jun Yu,et al. Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study , 2000, IEEE Transactions on Biomedical Engineering.
[173] S. Chatterji,et al. Trends and Challenges in EMG Based Control Scheme of Exoskeleton Robots- A Review , 2012 .
[174] R. Atkins,et al. The Lower Limb , 1991 .
[175] Richard R Neptune,et al. Modular control of human walking: a simulation study. , 2009, Journal of biomechanics.
[176] Shin-Ki Kim,et al. Control of multifunction myoelectric hand using a real-time EMG pattern recognition , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[177] Toshio Tsuji,et al. A human-assisting manipulator teleoperated by EMG signals and arm motions , 2003, IEEE Trans. Robotics Autom..
[178] Kevin B. Englehart,et al. A wavelet-based continuous classification scheme for multifunction myoelectric control , 2001, IEEE Transactions on Biomedical Engineering.
[179] T. Kuiken,et al. Quantifying Pattern Recognition—Based Myoelectric Control of Multifunctional Transradial Prostheses , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[180] Patrick van der Smagt,et al. EMG-based teleoperation and manipulation with the DLR LWR-III , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[181] Sijiang Du,et al. Temporal vs. spectral approach to feature extraction from prehensile EMG signals , 2004, Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, 2004. IRI 2004..
[182] Jun Morimoto,et al. Bilinear Modeling of EMG Signals to Extract User-Independent Features for Multiuser Myoelectric Interface , 2013, IEEE Transactions on Biomedical Engineering.
[183] Xiaolin Liu,et al. Contributions of online visual feedback to the learning and generalization of novel finger coordination patterns. , 2008, Journal of neurophysiology.
[184] Levi J. Hargrove,et al. A real time performance assessment of simultaneous pattern recognition control for multi-functional upper limb prostheses , 2013, 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER).
[185] Patrick van der Smagt,et al. Learning EMG control of a robotic hand: towards active prostheses , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..
[186] D. Farina,et al. The linear electrode array: a useful tool with many applications. , 2003, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[187] Jose M. Carmena,et al. Creating new functional circuits for action via brain-machine interfaces , 2013, Front. Comput. Neurosci..
[188] A B Ajiboye,et al. Muscle synergies as a predictive framework for the EMG patterns of new hand postures , 2009, Journal of neural engineering.
[189] B. Hudgins,et al. The effect of electrode displacements on pattern recognition based myoelectric control , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.
[190] Patrick van der Smagt,et al. Evidence of muscle synergies during human grasping , 2013, Biological Cybernetics.
[191] Stefano Panzeri,et al. A methodology for assessing the effect of correlations among muscle synergy activations on task-discriminating information , 2013, Front. Comput. Neurosci..
[192] Christopher L. Vaughan,et al. Fundamental patterns of bilateral muscle activity in human locomotion , 1995, Biological Cybernetics.
[193] 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.
[194] T. Kuiken,et al. Neural Interfaces for Control of Upper Limb Prostheses: The State of the Art and Future Possibilities , 2011, PM & R : the journal of injury, function, and rehabilitation.
[195] Ferat Sahin,et al. Camera control with EMG signals using Principal Component Analysis and support vector machines , 2011, 2011 IEEE International Systems Conference.
[196] M. Swiontkowski. Targeted Muscle Reinnervation for Real-time Myoelectric Control of Multifunction Artificial Arms , 2010 .
[197] Jianda Han,et al. A Novel Motion Estimate Method of Human Joint with EMG-Driven Model , 2011, 2011 5th International Conference on Bioinformatics and Biomedical Engineering.
[198] Thomas J. Burkholder,et al. Practical limits on muscle synergy identification by non-negative matrix factorization in systems with mechanical constraints , 2012, Medical & Biological Engineering & Computing.
[199] Dario Farina,et al. EMG-based simultaneous and proportional estimation of wrist/hand kinematics in uni-lateral trans-radial amputees , 2011, Journal of NeuroEngineering and Rehabilitation.
[200] S Micera,et al. A hybrid approach to EMG pattern analysis for classification of arm movements using statistical and fuzzy techniques. , 1999, Medical engineering & physics.
[201] Jonathan R Wolpaw,et al. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[202] Andrew Y. Ng,et al. A low-cost compliant 7-DOF robotic manipulator , 2011, 2011 IEEE International Conference on Robotics and Automation.
[203] Dario Farina,et al. Surface EMG crosstalk between knee extensor muscles: Experimental and model results , 2002, Muscle & nerve.
[204] Panagiotis K. Artemiadis,et al. A Switching Regime Model for the EMG-Based Control of a Robot Arm , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[205] Mark R. Cutkosky,et al. Selectively compliant underactuated hand for mobile manipulation , 2012, 2012 IEEE International Conference on Robotics and Automation.
[206] Francesco Lacquaniti,et al. Control of Fast-Reaching Movements by Muscle Synergy Combinations , 2006, The Journal of Neuroscience.
[207] J. Ushiba,et al. Effects of neurofeedback training with an electroencephalogram-based brain-computer interface for hand paralysis in patients with chronic stroke: a preliminary case series study. , 2011, Journal of rehabilitation medicine.
[208] E L Morin,et al. Sampling, noise-reduction and amplitude estimation issues in surface electromyography. , 2002, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[209] Catherine Disselhorst-Klug,et al. Simulation analysis of the ability of different types of multi-electrodes to increase selectivity of detection and to reduce cross-talk. , 2003, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[210] P. Cavanagh,et al. Electromechanical delay in human skeletal muscle under concentric and eccentric contractions , 1979, European Journal of Applied Physiology and Occupational Physiology.
[211] Erik Scheme,et al. Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. , 2011, Journal of rehabilitation research and development.
[212] Joel C. Perry,et al. Real-Time Myoprocessors for a Neural Controlled Powered Exoskeleton Arm , 2006, IEEE Transactions on Biomedical Engineering.
[213] Panagiotis K. Artemiadis,et al. Proportional Myoelectric Control of Robots: Muscle Synergy Development Drives Performance Enhancement, Retainment, and Generalization , 2015, IEEE Transactions on Robotics.
[214] Giulio Sandini,et al. Multi-subject/daily-life activity EMG-based control of mechanical hands , 2009, Journal of NeuroEngineering and Rehabilitation.
[215] L. Ting,et al. Muscle synergies characterizing human postural responses. , 2007, Journal of neurophysiology.
[216] F. Zajac. Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. , 1989, Critical reviews in biomedical engineering.
[217] Aymar de Rugy,et al. Muscle Coordination Is Habitual Rather than Optimal , 2012, The Journal of Neuroscience.
[218] Anthony Jarc,et al. Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics , 2009, Proceedings of the National Academy of Sciences.
[219] Ding Liu,et al. Multi-class surface EMG classification using support vector machines and wavelet transform , 2010, 2010 8th World Congress on Intelligent Control and Automation.
[220] Todd A. Kuiken,et al. The Effect of ECG Interference on Pattern-Recognition-Based Myoelectric Control for Targeted Muscle Reinnervated Patients , 2009, IEEE Transactions on Biomedical Engineering.
[221] Levi J. Hargrove,et al. Real-time comparison of conventional direct control and pattern recognition myoelectric control in a two-dimensional Fitts' law style test , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[222] Dingguo Zhang,et al. Application of a self-enhancing classification method to electromyography pattern recognition for multifunctional prosthesis control , 2013, Journal of NeuroEngineering and Rehabilitation.
[223] Todd A Kuiken,et al. Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses. , 2011, Journal of rehabilitation research and development.
[224] 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.
[225] Günter Hommel,et al. A Human--Exoskeleton Interface Utilizing Electromyography , 2008, IEEE Transactions on Robotics.
[226] J. Carmena. Advances in Neuroprosthetic Learning and Control , 2013, PLoS biology.
[227] Blair A. Lock,et al. Adaptive Pattern Recognition of Myoelectric Signals: Exploration of Conceptual Framework and Practical Algorithms , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[228] Editedby Eleanor Criswell,et al. Cram's Introduction to Surface Electromyography , 2010 .
[229] Junuk Chu,et al. Wearable EMG-based HCI for Electric-Powered Wheelchair Users with Motor Disabilities , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.
[230] F. Finley,et al. Myocoder studies of multiple myopotential response. , 1967, Archives of physical medicine and rehabilitation.
[231] Edward D Lemaire,et al. A novel approach to surface electromyography: an exploratory study of electrode-pair selection based on signal characteristics , 2012, Journal of NeuroEngineering and Rehabilitation.
[232] Manfredo Atzori,et al. Building the Ninapro database: A resource for the biorobotics community , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).
[233] Jacques Duchateau,et al. The relative lengthening of the myotendinous structures in the medial gastrocnemius during passive stretching differs among individuals. , 2009, Journal of applied physiology.
[234] Kongqiao Wang,et al. Automatic recognition of sign language subwords based on portable accelerometer and EMG sensors , 2010, ICMI-MLMI '10.
[235] Erik J. Scheme,et al. Selective Classification for Improved Robustness of Myoelectric Control Under Nonideal Conditions , 2011, IEEE Transactions on Biomedical Engineering.
[236] R Merletti,et al. Innervation zone of the vastus medialis muscle: position and effect on surface EMG variables , 2013, Physiological measurement.
[237] Anish Sebastian,et al. An adaptive multi sensor data fusion with hybrid nonlinear ARX and Wiener-Hammerstein models for skeletal muscle force estimation , 2010 .
[238] Stacie A. Chvatal,et al. Decomposing Muscle Activity in Motor TasksMethods and Interpretation , 2010 .
[239] C. Disselhorst-Klug,et al. Principles of high-spatial-resolution surface EMG (HSR-EMG): single motor unit detection and application in the diagnosis of neuromuscular disorders. , 1997, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[240] R. Merletti,et al. Methods for estimating muscle fibre conduction velocity from surface electromyographic signals , 2004, Medical and Biological Engineering and Computing.
[241] M. Osman Tokhi,et al. A fuzzy clustering neural network architecture for multifunction upper-limb prosthesis , 2003, IEEE Transactions on Biomedical Engineering.
[242] S H Park,et al. EMG pattern recognition based on artificial intelligence techniques. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[243] Pu Liu,et al. Identification of Constant-Posture EMG–Torque Relationship About the Elbow Using Nonlinear Dynamic Models , 2012, IEEE Transactions on Biomedical Engineering.
[244] Panagiotis K. Artemiadis,et al. EMG-Based Control of a Robot Arm Using Low-Dimensional Embeddings , 2010, IEEE Transactions on Robotics.
[245] Dario Farina,et al. Simultaneous and Proportional Force Estimation for Multifunction Myoelectric Prostheses Using Mirrored Bilateral Training , 2011, IEEE Transactions on Biomedical Engineering.
[246] Ganesh R. Naik,et al. Twin SVM for Gesture Classification Using the Surface Electromyogram , 2010, IEEE Transactions on Information Technology in Biomedicine.
[247] D F Stegeman,et al. Multi-channel surface EMG in clinical neurophysiology. , 2000, Supplements to Clinical neurophysiology.
[248] K. Sundaraj,et al. A study of back-propagation and radial basis neural network on EMG signal classification , 2009, 2009 6th International Symposium on Mechatronics and its Applications.
[249] 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.
[250] Panagiotis Artemiadis,et al. Beyond User-Specificity for EMG Decoding Using Multiresolution Muscle Synergy Analysis , 2013 .
[251] Emanuel Todorov,et al. Structured variability of muscle activations supports the minimal intervention principle of motor control. , 2009, Journal of neurophysiology.
[252] José del R. Millán,et al. Brain-Computer Interfaces , 2020, Handbook of Clinical Neurology.
[253] 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.
[254] Panagiotis K. Artemiadis,et al. A biomimetic approach to inverse kinematics for a redundant robot arm , 2010, Auton. Robots.
[255] Todd A. Kuiken,et al. A Decision-Based Velocity Ramp for Minimizing the Effect of Misclassifications During Real-Time Pattern Recognition Control , 2011, IEEE Transactions on Biomedical Engineering.
[256] D. Yatsenko,et al. Simultaneous, Proportional, Multi-axis Prosthesis Control using Multichannel Surface EMG , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[257] Robert W. Mann,et al. Myoelectric Signal Processing: Optimal Estimation Applied to Electromyography - Part I: Derivation of the Optimal Myoprocessor , 1980, IEEE Transactions on Biomedical Engineering.
[258] K. Krysztoforski,et al. RECOGNITION OF PALM FINGER MOVEMENTS ON THE BASIS OF EMG SIGNALS WITH THE APPLICATION OF WAVELETS , 2004 .
[259] Roberto Merletti,et al. Uneven spatial distribution of surface EMG: what does it mean? , 2012, European Journal of Applied Physiology.
[260] Matthew C. Tresch,et al. The number and choice of muscles impact the results of muscle synergy analyses , 2013, Front. Comput. Neurosci..
[261] Roberto Merletti,et al. Biophysics of the Generation of EMG Signals , 2004 .
[262] Terence D Sanger,et al. Bayesian filtering of myoelectric signals. , 2007, Journal of neurophysiology.
[263] Panagiotis K. Artemiadis,et al. Teleoperation of a robot manipulator using EMG signals and a position tracker , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[264] Daniel Graupe,et al. Functional Separation of EMG Signals via ARMA Identification Methods for Prosthesis Control Purposes , 1975, IEEE Transactions on Systems, Man, and Cybernetics.
[265] Hiroshi Yokoi,et al. Real-time Learning Method for Adaptable Motion-Discrimination using Surface EMG Signal , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[266] M M Ash,et al. Power spectral analysis of the surface electromyogram of human jaw muscles during fatigue. , 1981, Archives of oral biology.
[267] R.N. Scott,et al. A new strategy for multifunction myoelectric control , 1993, IEEE Transactions on Biomedical Engineering.
[268] Giulio Sandini,et al. Model adaptation with least-squares SVM for adaptive hand prosthetics , 2009, 2009 IEEE International Conference on Robotics and Automation.
[269] R.Fff. Weir,et al. A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[270] Bernd Freisleben,et al. HaWCoS: the "hands-free" wheelchair control system , 2002, ASSETS.
[271] R.F. Kirsch,et al. Evaluation of Head Orientation and Neck Muscle EMG Signals as Command Inputs to a Human–Computer Interface for Individuals With High Tetraplegia , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[272] Erik J. Scheme,et al. Validation of a Selective Ensemble-Based Classification Scheme for Myoelectric Control Using a Three-Dimensional Fitts' Law Test , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[273] E. Bizzi,et al. Muscle synergy patterns as physiological markers of motor cortical damage , 2012, Proceedings of the National Academy of Sciences.
[274] Hong Liu,et al. Levenberg-Marquardt Based Neural Network Control for a Five-fingered Prosthetic Hand , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.
[275] Christian Kothe,et al. Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general , 2011, Journal of neural engineering.
[276] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[277] D. Lloyd,et al. An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. , 2003, Journal of biomechanics.
[278] Ricardo Chavarriaga,et al. A hybrid brain–computer interface based on the fusion of electroencephalographic and electromyographic activities , 2011, Journal of neural engineering.
[279] Francesco Lacquaniti,et al. Motor Control Programs and Walking , 2006, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.
[280] Wenwei Yu,et al. EMG prosthetic hand controller using real-time learning method , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).
[281] Jacob Rosen,et al. Performances of Hill-Type and Neural Network Muscle Models - Toward a Myosignal-Based Exoskeleton , 1999, Comput. Biomed. Res..
[282] Adriano de Oliveira Andrade,et al. On the relationship between features extracted from EMG and force for constant and dynamic protocols , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[283] Ann M. Simon,et al. A comparison of proportional control methods for pattern recognition control , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[284] D. Reinkensmeyer,et al. Review of control strategies for robotic movement training after neurologic injury , 2009, Journal of NeuroEngineering and Rehabilitation.
[285] Dario Farina,et al. Amplitude cancellation reduces the size of motor unit potentials averaged from the surface EMG. , 2006, Journal of applied physiology.
[286] Marimuthu Palaniswami,et al. Multi run ICA and surface EMG based signal processing system for recognising hand gestures , 2008, 2008 8th IEEE International Conference on Computer and Information Technology.
[287] R Merletti,et al. Comparison of algorithms for estimation of EMG variables during voluntary isometric contractions. , 2000, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[288] Marco Platzner,et al. Development Of A Pattern Recognition-Based Myoelectric Transhumeral Prosthesis With Multifunctional Simultaneous Control Using A Model-Driven Approach For Mechatronic Systems , 2011 .
[289] Kazuo Kiguchi,et al. Muscle-model-oriented EMG-based control of an upper-limb power-assist exoskeleton with a neuro-fuzzy modifier , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).
[290] B Hudgins,et al. Myoelectric signal processing for control of powered limb prostheses. , 2006, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[291] Stefano Stramigioli,et al. Myoelectric forearm prostheses: state of the art from a user-centered perspective. , 2011, Journal of rehabilitation research and development.
[292] P. Dario,et al. Control of multifunctional prosthetic hands by processing the electromyographic signal. , 2002, Critical reviews in biomedical engineering.
[293] Ernest Nlandu Kamavuako,et al. Real-Time, Simultaneous Myoelectric Control Using Force and Position-Based Training Paradigms , 2014, IEEE Transactions on Biomedical Engineering.
[294] Winnie Jensen,et al. Introduction to Neural Engineering for Motor Rehabilitation , 2013 .
[295] N. Hogan. An organizing principle for a class of voluntary movements , 1984, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[296] Emilio Bizzi,et al. Shared and specific muscle synergies in natural motor behaviors. , 2005, Proceedings of the National Academy of Sciences of the United States of America.