Learning of Temporal and Spatial Movement Aspects: A Comparison of Four Types of Haptic Control and Concurrent Visual Feedback

In literature, the effectiveness of haptics for motor learning is controversially discussed. Haptics is believed to be effective for motor learning in general; however, different types of haptic control enhance different movement aspects. Thus, in dependence on the movement aspects of interest, one type of haptic control may be effective whereas another one is not. Therefore, in the current work, it was investigated if and how different types of haptic controllers affect learning of spatial and temporal movement aspects. In particular, haptic controllers that enforce active participation of the participants were expected to improve spatial aspects. Only haptic controllers that provide feedback about the task's velocity profile were expected to improve temporal aspects. In a study on learning a complex trunk-arm rowing task, the effect of training with four different types of haptic control was investigated: position control, path control, adaptive path control, and reactive path control. A fifth group (control) trained with visual concurrent augmented feedback. As hypothesized, the position controller was most effective for learning of temporal movement aspects, while the path controller was most effective in teaching spatial movement aspects of the rowing task. Visual feedback was also effective for learning temporal and spatial movement aspects.

[1]  R. J. Beers,et al.  Motor Learning Is Optimally Tuned to the Properties of Motor Noise , 2009, Neuron.

[2]  Robert Riener,et al.  A reconfigurable, tendon-based haptic interface for research into human-environment interactions , 2012, Robotica.

[3]  James L. Patton,et al.  Augmented Dynamics and Motor Exploration as Training for Stroke , 2013, IEEE Transactions on Biomedical Engineering.

[4]  David J. Reinkensmeyer,et al.  Slacking by the human motor system: Computational models and implications for robotic orthoses , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[5]  Holger Wendland,et al.  Piecewise polynomial, positive definite and compactly supported radial functions of minimal degree , 1995, Adv. Comput. Math..

[6]  S. Swinnen,et al.  Motor learning with augmented feedback: modality-dependent behavioral and neural consequences. , 2011, Cerebral cortex.

[7]  D. Reinkensmeyer,et al.  Human-robot cooperative movement training: Learning a novel sensory motor transformation during walking with robotic assistance-as-needed , 2007, Journal of NeuroEngineering and Rehabilitation.

[8]  Richard A. Schmidt,et al.  Frequent Augmented Feedback Can Degrade Learning: Evidence and Interpretations , 1991 .

[9]  Antonio Frisoli,et al.  Vibrotactile perception assessment for a rowing training system , 2009, World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems.

[10]  J. Patton,et al.  Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors , 2005, Experimental Brain Research.

[11]  H. P. Crowell,et al.  Gait retraining to reduce lower extremity loading in runners. , 2011, Clinical biomechanics.

[12]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part II—Implementation , 1985 .

[13]  Peter Wolf,et al.  Sonification and haptic feedback in addition to visual feedback enhances complex motor task learning , 2014, Experimental Brain Research.

[14]  Lorna M. Brown,et al.  DESIGN GUIDELINES FOR AUDIO PRESENTATION OF GRAPHS AND TABLES , 2003 .

[15]  Reza Shadmehr,et al.  Learning of action through adaptive combination of motor primitives , 2000, Nature.

[16]  D. C. Shapiro,et al.  Summary knowledge of results for skill acquisition: support for the guidance hypothesis. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[17]  Keith Nesbitt Designing multi-sensory displays for abstract data , 2003 .

[18]  J. Burdick,et al.  Implications of Assist-As-Needed Robotic Step Training after a Complete Spinal Cord Injury on Intrinsic Strategies of Motor Learning , 2006, The Journal of Neuroscience.

[19]  R. Riener,et al.  Path Control: A Method for Patient-Cooperative Robot-Aided Gait Rehabilitation , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[20]  Herbert Heuer,et al.  The Influence of Robotic Guidance on Different Types of Motor Timing , 2013, Journal of motor behavior.

[21]  T. Hornby,et al.  Metabolic Costs and Muscle Activity Patterns During Robotic- and Therapist-Assisted Treadmill Walking in Individuals With Incomplete Spinal Cord Injury , 2006, Physical Therapy.

[22]  Robert Riener,et al.  ARMin: a robot for patient-cooperative arm therapy , 2007, Medical & Biological Engineering & Computing.

[23]  J. Klein,et al.  Breaking It Down Is Better: Haptic Decomposition of Complex Movements Aids in Robot-Assisted Motor Learning , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[24]  D.J. Reinkensmeyer,et al.  Robot-enhanced motor learning: accelerating internal model formation during locomotion by transient dynamic amplification , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[25]  Herbert Heuer,et al.  Robotic guidance benefits the learning of dynamic, but not of spatial movement characteristics , 2012, Experimental Brain Research.

[26]  David J. Reinkensmeyer,et al.  Comparison of error-amplification and haptic-guidance training techniques for learning of a timing-based motor task by healthy individuals , 2010, Experimental Brain Research.

[27]  Seungmoon Choi,et al.  Effects of haptic guidance and disturbance on motor learning: Potential advantage of haptic disturbance , 2010, 2010 IEEE Haptics Symposium.

[28]  David J. Reinkensmeyer,et al.  Haptic Guidance Can Enhance Motor Learning of a Steering Task , 2008, Journal of motor behavior.

[29]  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.

[30]  Sunil K. Agrawal,et al.  Assisting Versus Repelling Force-Feedback for Learning of a Line Following Task in a Wheelchair , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[31]  M. Guadagnoli,et al.  Challenge Point: A Framework for Conceptualizing the Effects of Various Practice Conditions in Motor Learning , 2004, Journal of motor behavior.

[32]  Marcia Kilchenman O'Malley,et al.  Progressive haptic and visual guidance for training in a virtual dynamic task , 2010, 2010 IEEE Haptics Symposium.

[33]  Marcia K. O'Malley,et al.  On the Efficacy of Haptic Guidance Schemes for Human Motor Learning , 2009 .

[34]  Daniel Gopher,et al.  Transfer of Skill from a Virtual Reality Trainer to Real Juggling , 2011 .

[35]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation , 1984, 1984 American Control Conference.

[36]  R. Riener,et al.  Transfer of Complex Skill Learning from Virtual to Real Rowing , 2013, PloS one.

[37]  Martin A. Giese,et al.  Morphable Models for the Analysis and Synthesis of Complex Motion Patterns , 2000, International Journal of Computer Vision.

[38]  Marcia Kilchenman O'Malley,et al.  The Task-Dependent Efficacy of Shared-Control Haptic Guidance Paradigms , 2012, IEEE Transactions on Haptics.

[39]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part III—Applications , 1985 .

[40]  D. Reinkensmeyer,et al.  Review of control strategies for robotic movement training after neurologic injury , 2009, Journal of NeuroEngineering and Rehabilitation.

[41]  Robert Riener,et al.  Assistance or challenge? Filling a gap in user-cooperative control , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[42]  J. Hidler,et al.  Multicenter Randomized Clinical Trial Evaluating the Effectiveness of the Lokomat in Subacute Stroke , 2009, Neurorehabilitation and neural repair.

[43]  K. Newell Knowledge Of Results And Motor Learning , 1976, Exercise and sport sciences reviews.

[44]  George Tzanetakis,et al.  A FRAMEWORK FOR SONIFICATION OF VICON MOTION CAPTURE DATA , 2005 .

[45]  R. Riener,et al.  Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review , 2012, Psychonomic Bulletin & Review.

[46]  S. Micera,et al.  On the use of divergent force fields in robot-mediated neurorehabilitation , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[47]  C. Shea,et al.  Principles derived from the study of simple skills do not generalize to complex skill learning , 2002, Psychonomic bulletin & review.

[48]  Alex M. Andrew Nanomedicine, Volume 1: Basic Capabilities, by Robert A. Freitas Jr., Landes Bioscience, Austin, Texas, 1999, xxi + 509 pp., ISBN 1-57059-645-X Index (Hardback, $89.000) , 2000, Robotica.

[49]  Stephan P. Swinnen,et al.  Summary knowledge of results for skill acquisition: support for the guidance hypothesis , 1989 .

[50]  Ferdinando A. Mussa-Ivaldi,et al.  Robot-assisted adaptive training: custom force fields for teaching movement patterns , 2004, IEEE Transactions on Biomedical Engineering.

[51]  Peter Wolf,et al.  The effect of haptic guidance and visual feedback on learning a complex tennis task , 2013, Experimental Brain Research.

[52]  Frank Tendick,et al.  Haptic guidance: experimental evaluation of a haptic training method for a perceptual motor skill , 2002, Proceedings 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. HAPTICS 2002.

[53]  Robert Riener,et al.  A tendon-based parallel robot applied to motor learning in sports , 2010, 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[54]  R. Schmidt,et al.  Knowledge of results and motor learning: a review and critical reappraisal. , 1984, Psychological bulletin.

[55]  Marcia Kilchenman O'Malley,et al.  Efficacy of shared-control guidance paradigms for robot-mediated training , 2011, 2011 IEEE World Haptics Conference.

[56]  C. Winstein Knowledge of results and motor learning--implications for physical therapy. , 1991, Physical therapy.

[57]  J Liu,et al.  Learning to perform a new movement with robotic assistance: comparison of haptic guidance and visual demonstration , 2006, Journal of NeuroEngineering and Rehabilitation.

[58]  Dimitrios Gunopulos,et al.  Indexing multi-dimensional time-series with support for multiple distance measures , 2003, KDD '03.

[59]  J. Patton,et al.  Can Robots Help the Learning of Skilled Actions? , 2009, Exercise and sport sciences reviews.