Introduction to Digital Human Modeling bridges the gap in current literature by providing a comprehensive resource on digital human modeling for beginners and researchers. The content includes step-by-step procedures for building a digital human model, fundamental human kinematics and dynamics, advanced topics such as motion prediction and injury prevention, and industrial applications.
The book covers theoretical concepts and experimental validation, including human anatomy, degrees of freedom, skeletal and musculoskeletal modeling, equations of motion, reach envelopes, lifting prediction, muscle fatigue model, and injury analysis. It teaches readers how to build simulation-based human models, set up equations of motion, analyze human biomechanics, and utilize simulations and experiments to study worker injuries.
Furthermore, the book introduces both fundamental and advanced digital human modeling methods and optimization techniques aimed at improving performance and preventing injuries in manual material handling, as well as addressing lifting and gait biomechanics and ergonomics.
1. Chapter 1. Introduction - p. 1 2. Chapter 2. Anthropometric modeling - p. 5 3. Chapter 3. Human anatomy and kinematic skeleton - p. 11 4. Chapter 4. Denavit–Hartenberg method - p. 27 5. Chapter 5. Kinematics and sensitivity analysis - p. 35 6. Chapter 6. Dynamics and sensitivity analysis - p. 45 7. Chapter 7. Numerical interpolation - p. 65 8. Chapter 8. Reach envelope and zone differentiation - p. 75 9. Chapter 9. Kinematics-based posture prediction - p. 101 10. Chapter 10. Physics-based posture prediction - p. 119 11. Chapter 11. Hand modeling - p. 141 12. Chapter 12. Joint strength surface - p. 169 13. Chapter 13. Skeletal symmetric and asymmetric lifting predictions - p. 181 14. Chapter 14. Musculoskeletal lifting prediction and OpenSim model - p. 211 15. Chapter 15. Gait - p. 243 16. 1 Introduction - p. 243 17. 2 Musculoskeletal dynamics - p. 244 18. 3 Recursive B-spline discretization - p. 245 19. 4 Inverse dynamics optimization - p. 246 20. 5 Musculoskeletal gait prediction - p. 247 21. 6 3D symmetric gait prediction - p. 252 22. 7 3D symmetric gait model - p. 255 23. 8 3D skeletal gait optimization formulation - p. 262 24. 9 Numerical results of 3D skeletal gait - p. 267 25. 10 3D asymmetric skeletal gait optimization formulation - p. 276 26. 11 3D asymmetric skeletal gait results - p. 279 27. 12 Problems - p. 284 28. Chapter 16. Jumping - p. 287 29. Chapter 17. Sit-to-stand - p. 315 30. Chapter 18. Multiobjective optimization on lifting - p. 361 31. Chapter 19. Fatigue model - p. 377 32. Chapter 20. Lifting posture prediction with fatigue - p. 419 33. Chapter 21. Repetitive lifting prediction with fatigue - p. 437 34. Chapter 22. Team lifting and human–robot interaction - p. 457 35. 1 Introduction - p. 457 36. 2 Multibody human-box system - p. 457 37. 3 Sensitivity equations - p. 459 38. 4 Team lifting formulation - p. 461 39. 5 Team lifting simulation results - p. 467 40. 6 Human–robot system - p. 474 41. 7 Human–robot lifting experiment - p. 477 42. 8 Optimization formulation - p. 481 43. 9 Numerical results for human-robot lifting - p. 484 44. 10 Problems - p. 488 45. Chapter 23. Experiments - p. 491 46. Index - p. 527
Introduction to Digital Human Modeling bridges the gap in current literature by providing a comprehensive resource on digital human modeling for beginners and researchers. The content includes step-by-step procedures for building a digital human model, fundamental human kinematics and dynamics, advanced topics such as motion prediction and injury prevention, and industrial applications.
The book covers theoretical concepts and experimental validation, including human anatomy, degrees of freedom, skeletal and musculoskeletal modeling, equations of motion, reach envelopes, lifting prediction, muscle fatigue model, and injury analysis. It teaches readers how to build simulation-based human models, set up equations of motion, analyze human biomechanics, and utilize simulations and experiments to study worker injuries.
Furthermore, the book introduces both fundamental and advanced digital human modeling methods and optimization techniques aimed at improving performance and preventing injuries in manual material handling, as well as addressing lifting and gait biomechanics and ergonomics.
1. Chapter 1. Introduction - p. 1 2. Chapter 2. Anthropometric modeling - p. 5 3. Chapter 3. Human anatomy and kinematic skeleton - p. 11 4. Chapter 4. Denavit–Hartenberg method - p. 27 5. Chapter 5. Kinematics and sensitivity analysis - p. 35 6. Chapter 6. Dynamics and sensitivity analysis - p. 45 7. Chapter 7. Numerical interpolation - p. 65 8. Chapter 8. Reach envelope and zone differentiation - p. 75 9. Chapter 9. Kinematics-based posture prediction - p. 101 10. Chapter 10. Physics-based posture prediction - p. 119 11. Chapter 11. Hand modeling - p. 141 12. Chapter 12. Joint strength surface - p. 169 13. Chapter 13. Skeletal symmetric and asymmetric lifting predictions - p. 181 14. Chapter 14. Musculoskeletal lifting prediction and OpenSim model - p. 211 15. Chapter 15. Gait - p. 243 16. 1 Introduction - p. 243 17. 2 Musculoskeletal dynamics - p. 244 18. 3 Recursive B-spline discretization - p. 245 19. 4 Inverse dynamics optimization - p. 246 20. 5 Musculoskeletal gait prediction - p. 247 21. 6 3D symmetric gait prediction - p. 252 22. 7 3D symmetric gait model - p. 255 23. 8 3D skeletal gait optimization formulation - p. 262 24. 9 Numerical results of 3D skeletal gait - p. 267 25. 10 3D asymmetric skeletal gait optimization formulation - p. 276 26. 11 3D asymmetric skeletal gait results - p. 279 27. 12 Problems - p. 284 28. Chapter 16. Jumping - p. 287 29. Chapter 17. Sit-to-stand - p. 315 30. Chapter 18. Multiobjective optimization on lifting - p. 361 31. Chapter 19. Fatigue model - p. 377 32. Chapter 20. Lifting posture prediction with fatigue - p. 419 33. Chapter 21. Repetitive lifting prediction with fatigue - p. 437 34. Chapter 22. Team lifting and human–robot interaction - p. 457 35. 1 Introduction - p. 457 36. 2 Multibody human-box system - p. 457 37. 3 Sensitivity equations - p. 459 38. 4 Team lifting formulation - p. 461 39. 5 Team lifting simulation results - p. 467 40. 6 Human–robot system - p. 474 41. 7 Human–robot lifting experiment - p. 477 42. 8 Optimization formulation - p. 481 43. 9 Numerical results for human-robot lifting - p. 484 44. 10 Problems - p. 488 45. Chapter 23. Experiments - p. 491 46. Index - p. 527
