A Review of Sensory Feedback in Upper-Limb Prostheses From the Perspective of Human Motor Control
暂无分享,去创建一个
[1] P. Fitts. The information capacity of the human motor system in controlling the amplitude of movement. , 1954, Journal of experimental psychology.
[2] A. Gale,et al. MUSCLE TRAINING FOR BICEPS CINEPLASTY , 1957 .
[3] A. H. Bottomley. MYO-ELECTRIC CONTROL OF POWERED PROSTHESES. , 1965, The Journal of bone and joint surgery. British volume.
[4] J. C. Bliss,et al. Compensatory Tracking with Visual and Tactile Displays , 1966 .
[5] N. A. Bernshteĭn. The co-ordination and regulation of movements , 1967 .
[6] D. B. Welbourn,et al. Paper 8: A Self-Adaptive Gripping Device: Its Design and Performance , 1968 .
[7] M. Rakić. Paper 11: The ‘Belgrade Hand Prosthesis’ , 1968 .
[8] D H Weir,et al. Theory of manual vehicular control. , 1969, Ergonomics.
[9] S. D. Reimers,et al. Kinesthetic Sensing for the EMG Controlled "Boston Arm" , 1970 .
[10] Thomas R. Schori,et al. Tracking Performance as a Function of Precision of Electrocutaneous Feedback Information , 1970 .
[11] J Kawamura,et al. [Sensory feedback device for the artificial arm]. , 1971, Nihon Seikeigeka Gakkai zasshi.
[12] F. Clippinger,et al. A sensory feedback system for an upper-limb amputation prosthesis. , 1974, Bulletin of prosthetics research.
[13] R E Prior,et al. Supplemental sensory feedback for the VA/NU myoelectric hand. Background and preliminary designs. , 1976, Bulletin of prosthetics research.
[14] Daniel E. Whitney,et al. Force Feedback Control of Manipulator Fine Motions , 1977 .
[15] H. Schmidt. The importance of information feedback in prostheses for the upper limbs1 , 1977 .
[16] D C Simpson,et al. An externally powered controlled complete arm prosthesis. , 1977, Journal of medical engineering & technology.
[17] George A. Bekey,et al. Tactile Information Processing by Human Operators in Control Systems , 1978, IEEE Transactions on Systems, Man, and Cybernetics.
[18] Carlo J. De Luca,et al. Physiology and Mathematics of Myoelectric Signals , 1979 .
[19] Frank A. Saunders,et al. Electrocutaneous Stimulation for Sensory Communication in Rehabilitation Engineering , 1982, IEEE Transactions on Biomedical Engineering.
[20] D. Childress,et al. Design and evaluation of a prosthesis control system based on the concept of extended physiological proprioception. , 1984, Journal of rehabilitation research and development.
[21] L. Ince,et al. Experimental foundations of EMG biofeedback with the upper extremity: A review of the literature , 1984, Biofeedback and Self-Regulation.
[22] D. Childress,et al. An analysis of extended physiological proprioception as a prosthesis-control technique. , 1984, Journal of rehabilitation research and development.
[23] T. Flash,et al. The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[24] D. Livesey,et al. Optimal Control Theory and Grants in Aid , 1986 .
[25] S C Jacobsen,et al. Extended physiologic taction: design and evaluation of a proportional force feedback system. , 1989, Journal of rehabilitation research and development.
[26] R. Scott. Feedback in myoelectric prostheses. , 1990, Clinical orthopaedics and related research.
[27] W.J. Tompkins,et al. Electrotactile and vibrotactile displays for sensory substitution systems , 1991, IEEE Transactions on Biomedical Engineering.
[28] K. J. Cole,et al. Sensory-motor coordination during grasping and manipulative actions , 1992, Current Opinion in Neurobiology.
[29] P E Patterson,et al. Design and evaluation of a sensory feedback system that provides grasping pressure in a myoelectric hand. , 1992, Journal of rehabilitation research and development.
[30] F A Mussa-Ivaldi,et al. Adaptive representation of dynamics during learning of a motor task , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[31] P H Chappell,et al. The Southampton Hand: an intelligent myoelectric prosthesis. , 1994, Journal of rehabilitation research and development.
[32] William A. Gruver,et al. Gripping force sensory feedback for a myoelectrically controlled forearm prosthesis , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.
[33] T. Elbert,et al. Phantom-limb pain as a perceptual correlate of cortical reorganization following arm amputation , 1995, Nature.
[34] J R Flanagan,et al. The Role of Internal Models in Motion Planning and Control: Evidence from Grip Force Adjustments during Movements of Hand-Held Loads , 1997, The Journal of Neuroscience.
[35] B. Rosén,et al. Artificial Sensibility Based on the Use of Piezoresistive Sensors , 1998, Journal of hand surgery.
[36] Daniel M. Wolpert,et al. Making smooth moves , 2022 .
[37] T. Elbert,et al. Plasticity of plasticity? Changes in the pattern of perceptual correlates of reorganization after amputation. , 1998, Brain : a journal of neurology.
[38] Mitsuo Kawato,et al. Internal models for motor control and trajectory planning , 1999, Current Opinion in Neurobiology.
[39] A. J. Harris,et al. Cortical origin of pathological pain , 1999, The Lancet.
[40] N. Birbaumer,et al. Does use of a myoelectric prosthesis prevent cortical reorganization and phantom limb pain? , 1999, Nature Neuroscience.
[41] D. L. Weeks,et al. Precision-grip force changes in the anatomical and prosthetic limb during predictable load increases , 2000, Experimental Brain Research.
[42] D. Wolpert,et al. Why can't you tickle yourself? , 2000, Neuroreport.
[43] E A Clancy,et al. Estimation and application of EMG amplitude during dynamic contractions. , 2001, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.
[44] R. Johansson,et al. Sensorimotor prediction and memory in object manipulation. , 2001, Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale.
[45] H. Flor,et al. The relationship of perceptual phenomena and cortical reorganization in upper extremity amputees , 2001, Neuroscience.
[46] H. Flor,et al. Phantom movements and pain. An fMRI study in upper limb amputees. , 2001, Brain : a journal of neurology.
[47] D S Childress,et al. Cineplasty as a control input for externally powered prosthetic components. , 2001, Journal of rehabilitation research and development.
[48] Kelvin E. Jones,et al. Sources of signal-dependent noise during isometric force production. , 2002, Journal of neurophysiology.
[49] 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.
[50] M. Ernst,et al. Humans integrate visual and haptic information in a statistically optimal fashion , 2002, Nature.
[51] D. Wolpert,et al. Abnormalities in the awareness of action , 2002, Trends in Cognitive Sciences.
[52] P. Haggard,et al. Voluntary action and conscious awareness , 2002, Nature Neuroscience.
[53] Andrew G. Barto,et al. The emergence of movement units through learning with noisy efferent signals and delayed sensory feedback , 2002, Neurocomputing.
[54] Michael I. Jordan,et al. Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.
[55] W.M. Grill,et al. Evaluation of command algorithms for control of upper-extremity neural prostheses , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[56] D. Wegner. The Illusion of Conscious Will , 2018, The MIT Press.
[57] C. Spence,et al. Multisensory integration and the body schema: close to hand and within reach , 2003, Current Biology.
[58] Rieko Osu,et al. Different mechanisms involved in adaptation to stable and unstable dynamics. , 2003, Journal of neurophysiology.
[59] D. Wegner. The mind's best trick: how we experience conscious will , 2003, Trends in Cognitive Sciences.
[60] M. Kawato,et al. Formation and control of optimal trajectory in human multijoint arm movement , 1989, Biological Cybernetics.
[61] R. Johansson,et al. Coordinated isometric muscle commands adequately and erroneously programmed for the weight during lifting task with precision grip , 2004, Experimental Brain Research.
[62] Yves Guiard,et al. Fitts' law 50 years later: applications and contributions from human-computer interaction , 2004, Int. J. Hum. Comput. Stud..
[63] E. Todorov. Optimality principles in sensorimotor control , 2004, Nature Neuroscience.
[64] S. Scott. Optimal feedback control and the neural basis of volitional motor control , 2004, Nature Reviews Neuroscience.
[65] R. Johansson,et al. Visual size cues in the programming of manipulative forces during precision grip , 2004, Experimental Brain Research.
[66] I. Scott MacKenzie,et al. Towards a standard for pointing device evaluation, perspectives on 27 years of Fitts' law research in HCI , 2004, Int. J. Hum. Comput. Stud..
[67] B. Sparrow,et al. Vicarious agency: experiencing control over the movements of others. , 2004, Journal of personality and social psychology.
[68] Yves Guiard,et al. Preface: Fitts' law 50 years later: Applications and contributions from human-computer interaction , 2004 .
[69] C. Spence,et al. Extending or projecting peripersonal space with tools? Multisensory interactions highlight only the distal and proximal ends of tools , 2004, Neuroscience Letters.
[70] Konrad Paul Körding,et al. The loss function of sensorimotor learning. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[71] Konrad Paul Kording,et al. Bayesian integration in sensorimotor learning , 2004, Nature.
[72] G.S. Dhillon,et al. Direct neural sensory feedback and control of a prosthetic arm , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[73] P. Haggard. Conscious intention and motor cognition , 2005, Trends in Cognitive Sciences.
[74] Emanuel Todorov,et al. Stochastic Optimal Control and Estimation Methods Adapted to the Noise Characteristics of the Sensorimotor System , 2005, Neural Computation.
[75] J. Houk,et al. Deciding when and how to correct a movement: discrete submovements as a decision making process , 2007, Experimental Brain Research.
[76] A. Kargov,et al. Design and Evaluation of a Low-Cost Force Feedback System for Myoelectric Prosthetic Hands , 2006 .
[77] M. Zafar,et al. Effectiveness of supplemental grasp-force feedback in the presence of vision , 2000, Medical and Biological Engineering and Computing.
[78] John Lyman,et al. Comparison of codes for sensory feedback using electrocutaneous tracking , 1977, Annals of Biomedical Engineering.
[79] Dudley S. Childress,et al. Closed-loop control in prosthetic systems: Historical perspective , 2006, Annals of Biomedical Engineering.
[80] G. F. Shannon,et al. A comparison of alternative means of providing sensory feedback on upper limb prostheses , 2006, Medical and biological engineering.
[81] T. A. Rohland. Sensory feedback for powered limb prostheses , 2006, Medical and biological engineering.
[82] T. Beeker,et al. Artificial touch in a hand-prosthesis , 2006, Medical and biological engineering.
[83] R. N. Scott,et al. Sensory-feedback system compatible with myoelectric control , 2006, Medical and Biological Engineering and Computing.
[84] G. Shannon. A myoelectrically-controlled prosthesis with sensory feedback , 2006, Medical and Biological Engineering and Computing.
[85] Miles C. Bowman,et al. Control strategies in object manipulation tasks , 2006, Current Opinion in Neurobiology.
[86] A. Anani,et al. Afferent electrical nerve stimulation: Human tracking performance relevant to prosthesis sensory feedback , 1979, Medical and Biological Engineering and Computing.
[87] Robert A Jacobs,et al. Near-Optimal Human Adaptive Control across Different Noise Environments , 2006, The Journal of Neuroscience.
[88] Lloyd L. Salisbury,et al. A mechanical hand with automatic proportional control of prehension , 1967, Medical and biological engineering.
[89] Elaine Biddiss,et al. Consumer design priorities for upper limb prosthetics , 2007, Disability and rehabilitation. Assistive technology.
[90] Kenneth M Heilman,et al. Mirror therapy for phantom limb pain. , 2007, The New England journal of medicine.
[91] Emanuel Todorov,et al. Iterative linearization methods for approximately optimal control and estimation of non-linear stochastic system , 2007, Int. J. Control.
[92] Emanuel Todorov,et al. Evidence for the Flexible Sensorimotor Strategies Predicted by Optimal Feedback Control , 2007, The Journal of Neuroscience.
[93] Konrad P. Kording,et al. Decision Theory: What "Should" the Nervous System Do? , 2007 .
[94] Peter Carruthers,et al. The illusion of conscious will , 2007, Synthese.
[95] Blair A. Lock,et al. Redirection of cutaneous sensation from the hand to the chest skin of human amputees with targeted reinnervation , 2007, Proceedings of the National Academy of Sciences.
[96] Robert D. Lipschutz,et al. Targeted reinnervation for enhanced prosthetic arm function in a woman with a proximal amputation: a case study , 2007, The Lancet.
[97] E. Biddiss,et al. Upper-Limb Prosthetics: Critical Factors in Device Abandonment , 2007, American journal of physical medicine & rehabilitation.
[98] Nitish V. Thakor,et al. Testing a Prosthetic Haptic Feedback Simulator With an Interactive Force Matching Task , 2008 .
[99] D. Nowak,et al. Preserved and Impaired Aspects of Feed-Forward Grip Force Control After Chronic Somatosensory Deafferentation , 2008, Neurorehabilitation and neural repair.
[100] J. Bradshaw,et al. Mechanisms underlying embodiment, disembodiment and loss of embodiment , 2008, Neuroscience & Biobehavioral Reviews.
[101] Marjolein P. M. Kammers,et al. What is embodiment? A psychometric approach , 2008, Cognition.
[102] A. Newen,et al. Beyond the comparator model: A multifactorial two-step account of agency , 2008, Consciousness and Cognition.
[103] C. Murray. Embodiment and Prosthetics , 2008 .
[104] J. Krakauer,et al. A computational neuroanatomy for motor control , 2008, Experimental Brain Research.
[105] Silvestro Micera,et al. On the Shared Control of an EMG-Controlled Prosthetic Hand: Analysis of User–Prosthesis Interaction , 2008, IEEE Transactions on Robotics.
[106] T. Poggio,et al. BOOK REVIEW David Marr’s Vision: floreat computational neuroscience VISION: A COMPUTATIONAL INVESTIGATION INTO THE HUMAN REPRESENTATION AND PROCESSING OF VISUAL INFORMATION , 2009 .
[107] Emanuel Todorov,et al. Efficient computation of optimal actions , 2009, Proceedings of the National Academy of Sciences.
[108] G.E. Loeb,et al. Grip Control Using Biomimetic Tactile Sensing Systems , 2009, IEEE/ASME Transactions on Mechatronics.
[109] T. Kuiken,et al. Examination of Force Discrimination in Human Upper Limb Amputees With Reinnervated Limb Sensation Following Peripheral Nerve Transfer , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[110] A. Panarese,et al. Humans Can Integrate Force Feedback to Toes in Their Sensorimotor Control of a Robotic Hand , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[111] D. Wegner,et al. Modulating the sense of agency with external cues , 2009, Consciousness and Cognition.
[112] T. Kuiken,et al. Sensory capacity of reinnervated skin after redirection of amputated upper limb nerves to the chest , 2009, Brain : a journal of neurology.
[113] Daniel A. Braun,et al. Motor Task Variation Induces Structural Learning , 2009, Current Biology.
[114] Etienne Burdet,et al. Dissociating Variability and Effort as Determinants of Coordination , 2009, PLoS Comput. Biol..
[115] T. Kuiken,et al. Vibrotactile detection thresholds for chest skin of amputees following targeted reinnervation surgery , 2009, Brain Research.
[116] P. Rossini,et al. Double nerve intraneural interface implant on a human amputee for robotic hand control , 2010, Clinical Neurophysiology.
[117] S. Vijayakumar,et al. A Computational Model of Limb Impedance Control Based on Principles of Internal Model Uncertainty , 2010, PloS one.
[118] S Micera,et al. Control of Hand Prostheses Using Peripheral Information , 2010, IEEE Reviews in Biomedical Engineering.
[119] Marcia K. O'Malley,et al. Toward improved sensorimotor integration and learning using upper-limb prosthetic devices , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[120] Cara E. Stepp,et al. Relative to direct haptic feedback, remote vibrotactile feedback improves but slows object manipulation , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[121] Daniel A. Braun,et al. Risk-Sensitive Optimal Feedback Control Accounts for Sensorimotor Behavior under Uncertainty , 2010, PLoS Comput. Biol..
[122] José González,et al. Multichannel audio biofeedback for dynamical coupling between prosthetic hands and their users , 2010, Ind. Robot.
[123] Daniel A. Braun,et al. Structure learning in action , 2010, Behavioural Brain Research.
[124] J. Wheeler,et al. Investigation of Rotational Skin Stretch for Proprioceptive Feedback With Application to Myoelectric Systems , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[125] Robert F Kirsch,et al. Virtual Reality Environment for Simulating Tasks With a Myoelectric Prosthesis: An Assessment and Training Tool , 2011, Journal of prosthetics and orthotics : JPO.
[126] Keehoon Kim,et al. Robotic touch shifts perception of embodiment to a prosthesis in targeted reinnervation amputees. , 2011, Brain : a journal of neurology.
[127] Christine L. MacKenzie,et al. The Grasping Hand , 2011, The Grasping Hand.
[128] S. Vijayakumar,et al. The role of feed-forward and feedback processes for closed-loop prosthesis control , 2011, Journal of NeuroEngineering and Rehabilitation.
[129] Wenwei Yu,et al. Psycho-physiological assessment of a prosthetic hand sensory feedback system based on an auditory display: a preliminary study , 2012, Journal of NeuroEngineering and Rehabilitation.
[130] K. Horch,et al. Object Discrimination With an Artificial Hand Using Electrical Stimulation of Peripheral Tactile and Proprioceptive Pathways With Intrafascicular Electrodes , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[131] 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.
[132] Peter H. Veltink,et al. Vibro- and Electrotactile User Feedback on Hand Opening for Myoelectric Forearm Prostheses , 2012, IEEE Transactions on Biomedical Engineering.
[133] David J. Reinkensmeyer,et al. A computational model of use-dependent motor recovery following a stroke: Optimizing corticospinal activations via reinforcement learning can explain residual capacity and other strength recovery dynamics , 2012, Neural Networks.
[134] Y. Matsuoka,et al. Vibrotactile Sensory Substitution for Object Manipulation: Amplitude Versus Pulse Train Frequency Modulation , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[135] P. Fletcher,et al. Sense of agency in health and disease: A review of cue integration approaches☆ , 2012, Consciousness and Cognition.
[136] Keehoon Kim,et al. Haptic Feedback Enhances Grip Force Control of sEMG-Controlled Prosthetic Hands in Targeted Reinnervation Amputees , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[137] Thomas R. Reppert,et al. Evidence for Hyperbolic Temporal Discounting of Reward in Control of Movements , 2012, The Journal of Neuroscience.
[138] O. Witte,et al. Sensory feedback prosthesis reduces phantom limb pain: Proof of a principle , 2012, Neuroscience Letters.
[139] G. Lundborg,et al. Sensory feedback from a prosthetic hand based on air-mediated pressure from the hand to the forearm skin. , 2012, Journal of rehabilitation medicine.
[140] Lionel Rigoux,et al. A Model of Reward- and Effort-Based Optimal Decision Making and Motor Control , 2012, PLoS Comput. Biol..
[141] Y. Matsuoka,et al. Comparison of remote pressure and vibrotactile feedback for prosthetic hand control , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).
[142] R. Riener,et al. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review , 2012, Psychonomic Bulletin & Review.
[143] Heidi Johansen-Berg,et al. Phantom pain is associated with preserved structure and function in the former hand area , 2013, Nature Communications.
[144] Christian Antfolk,et al. Sensory feedback in upper limb prosthetics , 2013, Expert review of medical devices.
[145] C. Antfolk,et al. Artificial Redirection of Sensation From Prosthetic Fingers to the Phantom Hand Map on Transradial Amputees: Vibrotactile Versus Mechanotactile Sensory Feedback , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[146] Christian Balkenius,et al. Transfer of tactile input from an artificial hand to the forearm: experiments in amputees and able-bodied volunteers , 2013, Disability and rehabilitation. Assistive technology.
[147] P. Rossini,et al. Stanisa Raspopovic Prostheses Restoring Natural Sensory Feedback in Real-Time Bidirectional Hand , 2014 .
[148] H. Flor,et al. Mirror therapy for phantom limb pain: Brain changes and the role of body representation , 2014, European journal of pain.
[149] Jonathon W. Sensinger,et al. Does EMG control lead to distinct motor adaptation? , 2014, Front. Neurosci..
[150] M. Keith,et al. A neural interface provides long-term stable natural touch perception , 2014, Science Translational Medicine.
[151] Christian Cipriani,et al. Humans can integrate feedback of discrete events in their sensorimotor control of a robotic hand , 2014, Experimental Brain Research.
[152] Dario Farina,et al. Time-division multiplexing for myoelectric closed-loop control using electrotactile feedback , 2014, Journal of NeuroEngineering and Rehabilitation.
[153] Dario Farina,et al. Stereovision and augmented reality for closed-loop control of grasping in hand prostheses , 2014, Journal of neural engineering.
[154] Dario Farina,et al. Closed-Loop Control of Grasping With a Myoelectric Hand Prosthesis: Which Are the Relevant Feedback Variables for Force Control? , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[155] Luca Citi,et al. Restoring Natural Sensory Feedback in Real-Time Bidirectional Hand Prostheses , 2014, Science Translational Medicine.
[156] Yei Hwan Jung,et al. Stretchable silicon nanoribbon electronics for skin prosthesis , 2014, Nature Communications.
[157] P. Lum,et al. Internal models of upper limb prosthesis users when grasping and lifting a fragile object with their prosthetic limb , 2014, Experimental Brain Research.
[158] Luigi Acerbi,et al. On the Origins of Suboptimality in Human Probabilistic Inference , 2014, PLoS Comput. Biol..
[159] Dario Farina,et al. Virtual Grasping: Closed-Loop Force Control Using Electrotactile Feedback , 2014, Comput. Math. Methods Medicine.
[160] Jacqueline S. Hebert,et al. Applications of sensory feedback in motorized upper extremity prosthesis: a review , 2014, Expert review of medical devices.
[161] Max Ortiz-Catalan,et al. An osseointegrated human-machine gateway for long-term sensory feedback and motor control of artificial limbs , 2014, Science Translational Medicine.
[162] F. Sup,et al. A Haptic Feedback Scheme to Accurately Position a Virtual Wrist Prosthesis Using a Three-Node Tactor Array , 2015, PloS one.
[163] Dario Farina,et al. Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis , 2015, Journal of neural engineering.
[164] A. V. Smirnov,et al. Visualization of arc and plasma flow patterns for advanced material processing , 2015, J. Vis..
[165] R. Brent Gillespie,et al. An exploration of grip force regulation with a low-impedance myoelectric prosthesis featuring referred haptic feedback , 2015, Journal of NeuroEngineering and Rehabilitation.
[166] Dario Farina,et al. The impact of the stimulation frequency on closed-loop control with electrotactile feedback , 2015, Journal of NeuroEngineering and Rehabilitation.
[167] Peter H Veltink,et al. Vibrotactile grasping force and hand aperture feedback for myoelectric forearm prosthesis users , 2015, Prosthetics and orthotics international.
[168] Kevin Englehart,et al. Do Cost Functions for Tracking Error Generalize across Tasks with Different Noise Levels? , 2015, PloS one.
[169] Dario Farina,et al. EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis , 2015, Journal of NeuroEngineering and Rehabilitation.
[170] Dario Farina,et al. Building an internal model of a myoelectric prosthesis via closed-loop control for consistent and routine grasping , 2015, Experimental Brain Research.
[171] Kianoush Nazarpour,et al. Artificial Proprioceptive Feedback for Myoelectric Control , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[172] Dustin J. Tyler. Restoring the human touch: Prosthetics imbued with haptics give their wearers fine motor control and a sense of connection , 2016, IEEE Spectrum.
[173] Thierry Keller,et al. Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis , 2016 .
[174] Daniel Tan,et al. Sensory feedback by peripheral nerve stimulation improves task performance in individuals with upper limb loss using a myoelectric prosthesis , 2016, Journal of neural engineering.
[175] Christian Cipriani,et al. Non-Invasive, Temporally Discrete Feedback of Object Contact and Release Improves Grasp Control of Closed-Loop Myoelectric Transradial Prostheses , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[176] Dario Farina,et al. Electrotactile EMG feedback improves the control of prosthesis grasping force , 2016, Journal of neural engineering.
[177] Dario Farina,et al. High-Density Electromyography and Motor Skill Learning for Robust Long-Term Control of a 7-DoF Robot Arm , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[178] Dario Farina,et al. Multichannel electrotactile feedback for simultaneous and proportional myoelectric control , 2016, Journal of neural engineering.
[179] Benoit P. Delhaye,et al. The neural basis of perceived intensity in natural and artificial touch , 2016, Science Translational Medicine.
[180] Dario Farina,et al. Tactile feedback is an effective instrument for the training of grasping with a prosthesis at low- and medium-force levels , 2017, Experimental Brain Research.
[181] Thierry Keller,et al. Short- and Long-Term Learning of Feedforward Control of a Myoelectric Prosthesis with Sensory Feedback by Amputees , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[182] Dario Farina,et al. User adaptation in Myoelectric Man-Machine Interfaces , 2017, Scientific Reports.
[183] Peter F. Stadler,et al. Similarity-Based Segmentation of Multi-Dimensional Signals , 2017, Scientific Reports.
[184] Christian Antfolk,et al. A review of invasive and non-invasive sensory feedback in upper limb prostheses , 2017, Expert review of medical devices.
[185] Dario Farina,et al. GLIMPSE: Google Glass interface for sensory feedback in myoelectric hand prostheses , 2017, Journal of neural engineering.
[186] Graham Morgan,et al. Deep learning-based artificial vision for grasp classification in myoelectric hands , 2017, Journal of neural engineering.
[187] Maurizio Valle,et al. A System for Electrotactile Feedback Using Electronic Skin and Flexible Matrix Electrodes: Experimental Evaluation , 2017, IEEE Transactions on Haptics.
[188] Dario Farina,et al. Humans Can Integrate Augmented Reality Feedback in Their Sensorimotor Control of a Robotic Hand , 2017, IEEE Transactions on Human-Machine Systems.
[189] 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.
[190] Reva E. Johnson,et al. Adaptation to random and systematic errors: Comparison of amputee and non-amputee control interfaces with varying levels of process noise , 2017, PloS one.
[191] Thierry Keller,et al. Multichannel Electrotactile Feedback With Spatial and Mixed Coding for Closed-Loop Control of Grasping Force in Hand Prostheses , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[192] Adam Wilson,et al. Assessing the quality of supplementary sensory feedback using the crossmodal congruency task , 2017, Scientific Reports.
[193] Jason Friedman,et al. Visuomotor behaviors and performance in a dual-task paradigm with and without vibrotactile feedback when using a myoelectric controlled hand , 2018, Assistive technology : the official journal of RESNA.
[194] Christian Cipriani,et al. Improving internal model strength and performance of prosthetic hands using augmented feedback , 2018, Journal of NeuroEngineering and Rehabilitation.
[195] Kevin Englehart,et al. Conventional analysis of trial-by-trial adaptation is biased: Empirical and theoretical support using a Bayesian estimator , 2018, PLoS Comput. Biol..
[196] Dario Farina,et al. Myocontrol is closed-loop control: incidental feedback is sufficient for scaling the prosthesis force in routine grasping , 2018, Journal of NeuroEngineering and Rehabilitation.
[197] Dustin J Tyler,et al. Artificial tactile and proprioceptive feedback improves performance and confidence on object identification tasks , 2018, PloS one.
[198] W. Miltner,et al. Leg Prosthesis With Somatosensory Feedback Reduces Phantom Limb Pain and Increases Functionality , 2018, Front. Neurol..
[199] Nitish V. Thakor,et al. Prosthesis with neuromorphic multilayered e-dermis perceives touch and pain , 2018, Science Robotics.
[200] Linda Resnik,et al. Home Use of a Neural-connected Sensory Prosthesis Provides the Functional and Psychosocial Experience of Having a Hand Again , 2018, Scientific Reports.
[201] Silvestro Micera,et al. Biomimetic Intraneural Sensory Feedback Enhances Sensation Naturalness, Tactile Sensitivity, and Manual Dexterity in a Bidirectional Prosthesis , 2018, Neuron.
[202] Ahmed W. Shehata,et al. Evaluating Internal Model Strength and Performance of Myoelectric Prosthesis Control Strategies , 2017, bioRxiv.
[203] Silvestro Micera,et al. A closed-loop hand prosthesis with simultaneous intraneural tactile and position feedback , 2018 .
[204] Dario Farina,et al. The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis , 2018, Journal of NeuroEngineering and Rehabilitation.
[205] A Mazzoni,et al. Comparison of linear frequency and amplitude modulation for intraneural sensory feedback in bidirectional hand prostheses , 2018, Scientific Reports.
[206] Kianoush Nazarpour,et al. Myoelectric control with abstract decoders , 2018, Journal of neural engineering.
[207] Rafael Granja-Vazquez,et al. Illusory movement perception improves motor control for prosthetic hands , 2018, Science Translational Medicine.
[208] Ahmed W Shehata,et al. Audible Feedback Improves Internal Model Strength and Performance of Myoelectric Prosthesis Control , 2018, Scientific Reports.
[209] A. Drohomirecka,et al. Low-level light therapy reduces platelet destruction during extracorporeal circulation , 2018, Scientific Reports.
[210] Albert H Vette,et al. Using synchronized eye and motion tracking to determine high-precision eye-movement patterns during object-interaction tasks. , 2018, Journal of vision.
[211] M. Ortiz-Catalán. The Stochastic Entanglement and Phantom Motor Execution Hypotheses: A Theoretical Framework for the Origin and Treatment of Phantom Limb Pain , 2018, Front. Neurol..
[212] Z. C. Thumser,et al. Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets , 2018, Front. Psychol..
[213] Christian Cipriani,et al. Discrete Vibro-Tactile Feedback Prevents Object Slippage in Hand Prostheses More Intuitively Than Other Modalities , 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[214] Thomas Stieglitz,et al. Paradigms for restoration of somatosensory feedback via stimulation of the peripheral nervous system , 2017, Clinical Neurophysiology.
[215] Scott M Tintle,et al. Targeted Muscle Reinnervation Treats Neuroma and Phantom Pain in Major Limb Amputees: A Randomized Clinical Trial. , 2019, Annals of surgery.
[216] Gunnar Blohm,et al. Modeling in Neuroscience as a Decision Process , 2019 .
[217] Silvestro Micera,et al. Intraneural sensory feedback restores grip force control and motor coordination while using a prosthetic hand , 2019, Journal of neural engineering.
[218] Loredana Zollo,et al. Restoring tactile sensations via neural interfaces for real-time force-and-slippage closed-loop control of bionic hands , 2019, Science Robotics.
[219] A. Arnold,et al. XX sex chromosome complement promotes atherosclerosis in mice , 2019, Nature Communications.
[220] Elizaveta V Okorokova,et al. Biomimetic sensory feedback through peripheral nerve stimulation improves dexterous use of a bionic hand , 2019, Science Robotics.
[221] Ranu Jung,et al. Effects of vibrotactile feedback and grasp interface compliance on perception and control of a sensorized myoelectric hand , 2019, PloS one.
[222] G Baud-Bovy,et al. Optimal integration of intraneural somatosensory feedback with visual information: a single-case study , 2019, Scientific Reports.
[223] Matteo Bianchi,et al. Skin Stretch Haptic Feedback to Convey Closure Information in Anthropomorphic, Under-Actuated Upper Limb Soft Prostheses , 2019, IEEE Transactions on Haptics.
[224] Strahinja Dosen,et al. Psychometric characterization of incidental feedback sources during grasping with a hand prosthesis , 2019, Journal of NeuroEngineering and Rehabilitation.
[225] Jon W. Sensinger,et al. Optimized control mapping through user-tuned cost of effort, time, and reliability* , 2019, 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR).
[226] Ahmed W. Shehata,et al. When Less Is More – Discrete Tactile Feedback Dominates Continuous Audio Biofeedback in the Integrated Percept While Controlling a Myoelectric Prosthetic Hand , 2019, Front. Neurosci..
[227] Z. C. Thumser,et al. Using sensory discrimination in a foraging-style task to evaluate human upper-limb sensorimotor performance , 2019, Scientific Reports.
[228] Prostheses—Assistive Technology—Upper , 2019, Encyclopedia of Biomedical Engineering.
[229] Taro Toyoizumi,et al. A Bayesian psychophysics model of sense of agency , 2019, Nature Communications.
[230] Dustin J. Tyler,et al. Learning of Artificial Sensation Through Long-Term Home Use of a Sensory-Enabled Prosthesis , 2019, Front. Neurosci..
[231] Silvestro Micera,et al. A closed-loop hand prosthesis with simultaneous intraneural tactile and position feedback , 2018, Science Robotics.
[232] Maurizio Valle,et al. Dual-Parameter Modulation Improves Stimulus Localization in Multichannel Electrotactile Stimulation , 2020, IEEE Transactions on Haptics.
[233] Internal Models , 2020, Encyclopedia of Creativity, Invention, Innovation and Entrepreneurship.
[234] Z. C. Thumser,et al. Long-Term Home-Use of Sensory-Motor-Integrated Bidirectional Bionic Prosthetic Arms Promotes Functional, Perceptual, and Cognitive Changes , 2020, Frontiers in Neuroscience.
[235] Strahinja Dosen,et al. The Interaction Between Feedback Type and Learning in Routine Grasping With Myoelectric Prostheses , 2019, IEEE Transactions on Haptics.