Technology-Assisted Physical Gait Rehabilitation: How Robotics, Data Science, and Neuroscience are Changing Modern Physical Therapy
Editat de Tomislav Bacek, Denny Oetomo, Dana Kulic, Ying Tanen Limba Engleză Paperback – oct 2025
- Summarizes the latest knowledge on the topic and proposes how new technologies could be deployed
- Focuses on computational modelling of the neuro-motor system, particularly recent developments leveraging data driven and optimization methods
- Synthesizes the different aspects of technology-assisted physical gait rehabilitation into an integrated context
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Specificații
ISBN-13: 9780443217487
ISBN-10: 0443217483
Pagini: 400
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
ISBN-10: 0443217483
Pagini: 400
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
Cuprins
1. Introduction
PART I: Neuroscience perspective on motor recovery
2. Clinical perspective on functional gait disorders
3. Motor learning - what constitutes, enables, and improves outcomes in neuro-impaired individuals
PART II: Opinion pieces on the main technology
4. Closing the loop between wearable technology and human biology
5. Crunching through data - how machine learning is transforming human movement analysis
6. Challenges in making neuromusculoskeletal models clinically useful
PART III: The role of human biomechanics in motor recovery
7. The outcomes and lessons from a constrained walking study
8. Motion and joint function in human gait
9. The role of muscle synergies in maximizing motor recovery
10. Optimality in human gait - the role of symmetry in motor learning
11. Error augmentation and haptic interventions during motor learning
PART IV: Technology-assisted motor function recovery
12. An overview of technology-assisted gait rehabilitation
13. Predictive simulations for better understanding neuromechanics of gait
15. Portable gait lab - taking mocap into clinical and community environments
16. Analyzing human gait using machine learning and explainable artificial intelligence
17. Concluding remarks
PART I: Neuroscience perspective on motor recovery
2. Clinical perspective on functional gait disorders
3. Motor learning - what constitutes, enables, and improves outcomes in neuro-impaired individuals
PART II: Opinion pieces on the main technology
4. Closing the loop between wearable technology and human biology
5. Crunching through data - how machine learning is transforming human movement analysis
6. Challenges in making neuromusculoskeletal models clinically useful
PART III: The role of human biomechanics in motor recovery
7. The outcomes and lessons from a constrained walking study
8. Motion and joint function in human gait
9. The role of muscle synergies in maximizing motor recovery
10. Optimality in human gait - the role of symmetry in motor learning
11. Error augmentation and haptic interventions during motor learning
PART IV: Technology-assisted motor function recovery
12. An overview of technology-assisted gait rehabilitation
13. Predictive simulations for better understanding neuromechanics of gait
15. Portable gait lab - taking mocap into clinical and community environments
16. Analyzing human gait using machine learning and explainable artificial intelligence
17. Concluding remarks