Topic

# Kinematics

About: Kinematics is a research topic. Over the lifetime, 30809 publications have been published within this topic receiving 527006 citations.

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01 May 1990TL;DR: The Fourth Edition of Biomechanics as an Interdiscipline: A Review of the Fourth Edition focuses on biomechanical Electromyography, with a focus on the relationship between Electromyogram and Biomechinical Variables.

Abstract: Preface to the Fourth Edition. 1 Biomechanics as an Interdiscipline. 1.0 Introduction. 1.1 Measurement, Description, Analysis, and Assessment. 1.2 Biomechanics and its Relationship with Physiology and Anatomy. 1.3 Scope of the Textbook. 1.4 References. 2 Signal Processing. 2.0 Introduction. 2.1 Auto- and Cross-Correlation Analyses. 2.2 Frequency Analysis. 2.3 Ensemble Averaging of Repetitive Waveforms. 2.4 References. 3 Kinematics. 3.0 Historical Development and Complexity of Problem. 3.1 Kinematic Conventions. 3.2 Direct Measurement Techniques. 3.3 Imaging Measurement Techniques. 3.4 Processing of Raw Kinematic Data. 3.5 Calculation of Other Kinematic Variables. 3.6 Problems Based on Kinematic Data. 3.7 References. 4 Anthropometry. 4.0 Scope of Anthropometry in Movement Biomechanics. 4.1 Density, Mass, and Inertial Properties. 4.2 Direct Experimental Measures. 4.3 Muscle Anthropometry. 4.4 Problems Based on Anthropometric Data. 4.5 References. 5 Kinetics: Forces and Moments of Force. 5.0 Biomechanical Models. 5.1 Basic Link-Segment Equations-the Free-Body Diagram. 5.2 Force Transducers and Force Plates. 5.3 Bone-on-Bone Forces During Dynamic Conditions. 5.4 Problems Based on Kinetic and Kinematic Data. 5.5 References. 6 Mechanical Work, Energy, and Power. 6.0 Introduction. 6.1 Efficiency. 6.2 Forms of Energy Storage. 6.3 Calculation of Internal and External Work. 6.4 Power Balances at Joints and Within Segments. 6.5 Problems Based on Kinetic and Kinematic Data. 6.6 References. 7 Three-Dimensional Kinematics and Kinetics. 7.0 Introduction. 7.1 Axes Systems. 7.2 Marker and Anatomical Axes Systems. 7.3 Determination of Segment Angular Velocities and Accelerations. 7.4 Kinetic Analysis of Reaction Forces and Moments. 7.5 Suggested Further Reading. 7.6 References. 8 Synthesis of Human Movement-Forward Solutions. 8.0 Introduction. 8.1 Review of Forward Solution Models. 8.2 Mathematical Formulation. 8.3 System Energy. 8.4 External Forces and Torques. 8.5 Designation of Joints. 8.6 Illustrative Example. 8.7 Conclusions. 8.8 References. 9 Muscle Mechanics. 9.0 Introduction. 9.1 Force-Length Characteristics of Muscles. 9.2 Force-Velocity Characteristics. 9.3 Muscle Modeling. 9.4 References. 10 Kinesiological Electromyography. 10.0 Introduction. 10.1 Electrophysiology of Muscle Contraction. 10.2 Recording of the Electromyogram. 10.3 Processing of the Electromyogram,. 10.4 Relationship between Electromyogram and Biomechanical Variables. 10.5 References. 11 Biomechanical Movement Synergies. 11.0 Introduction. 11.1 The Support Moment Synergy. 11.2 Medial/Lateral and Anterior/Posterior Balance in Standing. 11.3 Dynamic Balance during Walking. 11.4 References. APPENDICES. A. Kinematic, Kinetic, and Energy Data. Figure A.1 Walking Trial-Marker Locations and Mass and Frame Rate Information. Table A.1 Raw Coordinate Data (cm). Table A.2( a ) Filtered Marker Kinematics-Rib Cage and Greater Trochanter (Hip). Table A.2( b ) Filtered Marker Kinematics-Femoral Lateral Epicondyle (Knee) and Head of Fibula. Table A.2( c ) Filtered Marker Kinematics-Lateral Malleolus (Ankle) and Heel. Table A.2( d ) Filtered Marker Kinematics-Fifth Metatarsal and Toe. Table A.3( a ) Linear and Angular Kinematics-Foot. Table A.3( b ) Linear and Angular Kinematics-Leg. Table A.3( c ) Linear and Angular Kinematics-Thigh. Table A.3( d ) Linear and Angular Kinematics-1/2 HAT. Table A.4 Relative Joint Angular Kinematics-Ankle, Knee, and Hip. Table A.5( a ) Reaction Forces and Moments of Force-Ankle and Knee. Table A.5( b ) Reaction Forces and Moments of Force-Hip. Table A.6 Segment Potential, Kinetic, and Total Energies-Foot, Leg, Thigh, and1/2 HAT. Table A.7 Power Generation/Absorption and Transfer-Ankle, Knee, and Hip. B. Units and Definitions Related to Biomechanical and Electromyographical Measurements. Table B.1 Base SI Units. Table B.2 Derived SI Units. Index.

9,092 citations

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22 Mar 1994

TL;DR: In this paper, the authors present a detailed overview of the history of multifingered hands and dextrous manipulation, and present a mathematical model for steerable and non-driveable hands.

Abstract: INTRODUCTION: Brief History. Multifingered Hands and Dextrous Manipulation. Outline of the Book. Bibliography. RIGID BODY MOTION: Rigid Body Transformations. Rotational Motion in R3. Rigid Motion in R3. Velocity of a Rigid Body. Wrenches and Reciprocal Screws. MANIPULATOR KINEMATICS: Introduction. Forward Kinematics. Inverse Kinematics. The Manipulator Jacobian. Redundant and Parallel Manipulators. ROBOT DYNAMICS AND CONTROL: Introduction. Lagrange's Equations. Dynamics of Open-Chain Manipulators. Lyapunov Stability Theory. Position Control and Trajectory Tracking. Control of Constrained Manipulators. MULTIFINGERED HAND KINEMATICS: Introduction to Grasping. Grasp Statics. Force-Closure. Grasp Planning. Grasp Constraints. Rolling Contact Kinematics. HAND DYNAMICS AND CONTROL: Lagrange's Equations with Constraints. Robot Hand Dynamics. Redundant and Nonmanipulable Robot Systems. Kinematics and Statics of Tendon Actuation. Control of Robot Hands. NONHOLONOMIC BEHAVIOR IN ROBOTIC SYSTEMS: Introduction. Controllability and Frobenius' Theorem. Examples of Nonholonomic Systems. Structure of Nonholonomic Systems. NONHOLONOMIC MOTION PLANNING: Introduction. Steering Model Control Systems Using Sinusoids. General Methods for Steering. Dynamic Finger Repositioning. FUTURE PROSPECTS: Robots in Hazardous Environments. Medical Applications for Multifingered Hands. Robots on a Small Scale: Microrobotics. APPENDICES: Lie Groups and Robot Kinematics. A Mathematica Package for Screw Calculus. Bibliography. Index Each chapter also includes a Summary, Bibliography, and Exercises

6,592 citations

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TL;DR: The goal is to combine kinetic and kinematic data to examine translational motions during microgravity adaptations to encourage fine-control motions as these reduce the risk of injury and increase controllability.

Abstract: Introduction: Astronauts soaring through space modules with the grace of birds seems counterintuitive. How do they adapt to the weightless environment? Previous spaceflights have shown that astronauts in orbit adapt their motor strategies to each change in their gravitational environment. During adaptation, performance is degraded and can lead to mission-threatening injuries. If adaptation can occur before a mission, productivity during the mission might improve, minimizing risk. The goal is to combine kinetic and kinematic data to examine translational motions during microgravity adaptations. Methods: Experiments were performed during parabolic flights aboard NASA's C-9. Five subjects used their legs to push off from a sensor, landing on a target 3.96 m (13 ft) away. The sensor quantified the kinetics during contact, while four cameras recorded kinematics during push-off. Joint torques were calculated for a subset of traverses (N = 50) using the forces, moments, and joint angles. Results: During the 149 traverses, the average peak force exerted onto the sensor was 224.6 ± 74.6 N, with peak values ranging between 65.8―461.9 N. Two types of force profiles were observed, some having single, strong peaks (N = 64) and others having multiple, weaker peaks (N = 86). Conclusions: The force data were consistent with values recorded previously in sustained microgravity aboard Mir and the Space Shuttle. A training program for astronauts might be designed to encourage fine-control motions (i.e., multiple, weaker peaks) as these reduce the risk of injury and increase controllability. Additionally, a kinematic and kinetic sensor suite was successfully demonstrated in the weightless environment onboard the C-9 aircraft.

5,639 citations

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TL;DR: A mathematical model is formulated which is shown to predict both the qualitative features and the quantitative details observed experimentally in planar, multijoint arm movements, and is successful only when formulated in terms of the motion of the hand in extracorporal space.

Abstract: This paper presents studies of the coordination of voluntary human arm movements. A mathematical model is formulated which is shown to predict both the qualitative features and the quantitative details observed experimentally in planar, multijoint arm movements. Coordination is modeled mathematically by defining an objective function, a measure of performance for any possible movement. The unique trajectory which yields the best performance is determined using dynamic optimization theory. In the work presented here, the objective function is the square of the magnitude of jerk (rate of change of acceleration) of the hand integrated over the entire movement. This is equivalent to assuming that a major goal of motor coordination is the production of the smoothest possible movement of the hand. Experimental observations of human subjects performing voluntary unconstrained movements in a horizontal plane are presented. They confirm the following predictions of the mathematical model: unconstrained point-to-point motions are approximately straight with bell-shaped tangential velocity profiles; curved motions (through an intermediate point or around an obstacle) have portions of low curvature joined by portions of high curvature; at points of high curvature, the tangential velocity is reduced; the durations of the low-curvature portions are approximately equal. The theoretical analysis is based solely on the kinematics of movement independent of the dynamics of the musculoskeletal system and is successful only when formulated in terms of the motion of the hand in extracorporal space. The implications with respect to movement organization are discussed.

4,226 citations

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3,862 citations