Preface |
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xi | |
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1 Introduction and Main Concepts |
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1 | (14) |
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1.1 "Human Robotics" Approach to Model Human Motor Behavior |
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1 | (4) |
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1.2 Outline: How Do We Learn to Control Motion? |
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5 | (2) |
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7 | (6) |
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13 | (2) |
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2 Neural Control of Movement |
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15 | (20) |
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2.1 Bioelectric Signal Transmission in the Nervous System |
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15 | (4) |
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2.2 Information Processing in the Nervous System |
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19 | (2) |
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2.3 Peripheral Sensory Receptors |
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21 | (8) |
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2.4 Functional Control of Movement by the Central Nervous System |
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29 | (4) |
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33 | (2) |
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3 Muscle Mechanics and Control |
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35 | (22) |
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3.1 The Molecular Basis of Force Generation in Muscle |
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35 | (6) |
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3.2 The Molecular Basis of Viscoelasticity in Muscle |
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41 | (3) |
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3.3 Control of Muscle Force |
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44 | (4) |
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48 | (1) |
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3.5 Muscle Fiber Viscoelasticity |
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49 | (2) |
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51 | (2) |
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53 | (2) |
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55 | (1) |
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56 | (1) |
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4 Single-Joint Neuromechanics |
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57 | (26) |
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57 | (2) |
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59 | (2) |
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4.3 Joint Viscoelasticity and Mechanical Impedance |
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61 | (1) |
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4.4 Sensory Feedback Control |
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62 | (11) |
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73 | (5) |
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78 | (5) |
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5 Multijoint Multimuscle Kinematics and Impedance |
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83 | (28) |
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5.1 Kinematic Description |
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83 | (2) |
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85 | (1) |
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5.3 Direct and Inverse Kinematics |
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86 | (1) |
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5.4 Differential Kinematics and Force Relationships |
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87 | (3) |
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90 | (3) |
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5.6 Kinematic Transformations |
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93 | (2) |
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95 | (4) |
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99 | (2) |
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5.9 Redundancy Resolution |
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101 | (1) |
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5.10 Optimization with Additional Constraints |
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102 | (3) |
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5.11 Posture Selection to Minimize Noise or Disturbance |
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105 | (2) |
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107 | (4) |
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6 Multijoint Dynamics and Motion Control |
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111 | (20) |
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6.1 Human Movement Dynamics |
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111 | (2) |
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6.2 Perturbation Dynamics during Movement |
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113 | (1) |
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6.3 Linear and Nonlinear Robot Control |
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113 | (2) |
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6.4 Feedforward Control Model |
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115 | (3) |
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6.5 Impedance during Movement |
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118 | (1) |
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6.6 Simulation of Reaching Movements in Novel Dynamics |
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118 | (2) |
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120 | (4) |
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6.8 Nonlinear Adaptive Control of Robots |
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124 | (2) |
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6.9 Radial-Basis Function (RBF) Neural Network Model |
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126 | (3) |
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129 | (2) |
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7 Motor Learning and Memory |
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131 | (24) |
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7.1 Adaptation to Novel Dynamics |
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132 | (3) |
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7.2 Sensory Signals Responsible for Motor Learning |
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135 | (4) |
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7.3 Generalization in Motor Learning |
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139 | (6) |
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145 | (6) |
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7.5 Modeling Learning of Stable Dynamics in Humans and Robots |
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151 | (2) |
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153 | (2) |
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8 Motor Learning under Unstable and Unpredictable Conditions |
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155 | (30) |
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8.1 Motor Noise and Variability |
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156 | (4) |
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8.2 Impedance Control for Unstable and Unpredictable Dynamics |
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160 | (10) |
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8.3 Feedforward and Feedback Components of Impedance Control |
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170 | (6) |
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8.4 Computational Algorithm for Motor Adaptation |
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176 | (6) |
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182 | (3) |
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9 Motion Planning and Online Control |
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185 | (26) |
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9.1 Evidence of a Planning Stage |
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185 | (3) |
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9.2 Coordinate Transformation |
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188 | (1) |
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189 | (2) |
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9.4 Task Error and Effort as a Natural Cost Function |
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191 | (2) |
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9.5 Sensor-Based Motion Control |
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193 | (3) |
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196 | (2) |
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9.7 Stochastic Optimal Control Modeling of the Sensorimotor System |
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198 | (4) |
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9.8 Reward-Based Optimal Control |
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202 | (2) |
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9.9 Submotion Sensorimotor Primitives |
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204 | (3) |
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9.10 Repetition versus Optimization in Tasks with Multiple Minima |
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207 | (2) |
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9.11 Summary and Discussion on How to Learn Complex Behaviors |
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209 | (2) |
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10 Integration and Control of Sensory Feedback |
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211 | (24) |
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212 | (8) |
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220 | (5) |
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10.3 Purposeful Vision and Active Sensing |
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225 | (2) |
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10.4 Adaptive Control of Feedback |
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227 | (6) |
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233 | (2) |
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11 Applications in Neurorehabilitation and Robotics |
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235 | (18) |
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235 | (1) |
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11.2 Motor Learning Principles in Rehabilitation |
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236 | (2) |
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11.3 Robot-Assisted Rehabilitation of the Upper Extremities |
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238 | (2) |
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11.4 Application of Neuroscience to Robot-Assisted Rehabilitation |
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240 | (1) |
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11.5 Error Augmentation Strategies |
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241 | (2) |
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11.6 Learning with Visual Substitution of Proprioceptive Error |
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243 | (2) |
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11.7 Model of Motor Recovery after Stroke |
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245 | (1) |
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11.8 Concurrent Force and Impedance Adaptation in Robots |
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246 | (1) |
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11.9 Robotic Implementation |
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247 | (2) |
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11.10 Humanlike Adaptation of Robotic Assistance for Active Learning |
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249 | (1) |
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11.11 Summary and Conclusion |
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250 | (3) |
Appendix |
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253 | (4) |
References |
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257 | (18) |
Index |
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275 | |