Intelligent Gait Assistive Technologies: Gait Biomechanics and Machine Learning Applications in Rehabilitation and Injury Prevention
Autor Rezaul Begg, Hanatsu Naganoen Limba Engleză Paperback – 30 noi 2024
- Combines gait biomechanics, assistive technologies, and machine learning to showcase applications in healthcare
- Presents a state-of-the-art reference with exoskeletons and assistive devices and emerging techniques
- Introduces an easy-to-understand format by engineers and health professionals
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Specificații
ISBN-13: 9780443141041
ISBN-10: 0443141045
Pagini: 300
Dimensiuni: 151 x 229 mm
Editura: ELSEVIER SCIENCE
ISBN-10: 0443141045
Pagini: 300
Dimensiuni: 151 x 229 mm
Editura: ELSEVIER SCIENCE
Cuprins
Part I: Gait Biomechanics - Tripping, Slipping and Balance Loss
1. Fundamentals of Gait Biomechanics
2. Kinematics and Kinetics of Lower Limb Swing Phase Trajectory Control
3. Minimum Foot-Ground Clearance (MFC) and Tripping Probability Modelling
4. Required Coefficient of Friction (RCOF) and Slipping Prediction
5. Gait Adaptations due to Ageing, Injury and Pathologies
6. Gait Impairments Causing Tripping, Slipping and Balance Loss
Part II: Gait Assisting Techniques and Devices
7. Biofeedback-Based Gait Training Interventions
8. Passive Exoskeletons
9. Active Exoskeletons
10. Intelligent Footwear: Smart Insoles, Shoe-Mounted Sensors
Part III: Machine Learning Applications to Gait Assisting Techniques
11. Predicting Gait Kinematics from Inertial Sensors
12. Limb Trajectory Prediction (i): Critical Failure Events
13. Limb Trajectory Prediction (ii): Intelligent Assistive Device Control and Tripping Hazard Recognition
Part IV Conclusions, Emerging Techniques and Future Directions
14. Future Challenges in Rehabilitation and Injury Prevention
15. Research Directions in Gait Biomechanics and Machine Learning
16. References
1. Fundamentals of Gait Biomechanics
2. Kinematics and Kinetics of Lower Limb Swing Phase Trajectory Control
3. Minimum Foot-Ground Clearance (MFC) and Tripping Probability Modelling
4. Required Coefficient of Friction (RCOF) and Slipping Prediction
5. Gait Adaptations due to Ageing, Injury and Pathologies
6. Gait Impairments Causing Tripping, Slipping and Balance Loss
Part II: Gait Assisting Techniques and Devices
7. Biofeedback-Based Gait Training Interventions
8. Passive Exoskeletons
9. Active Exoskeletons
10. Intelligent Footwear: Smart Insoles, Shoe-Mounted Sensors
Part III: Machine Learning Applications to Gait Assisting Techniques
11. Predicting Gait Kinematics from Inertial Sensors
12. Limb Trajectory Prediction (i): Critical Failure Events
13. Limb Trajectory Prediction (ii): Intelligent Assistive Device Control and Tripping Hazard Recognition
Part IV Conclusions, Emerging Techniques and Future Directions
14. Future Challenges in Rehabilitation and Injury Prevention
15. Research Directions in Gait Biomechanics and Machine Learning
16. References