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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 Tan
en Limba Engleză Paperback – oct 2025
Technology-Assisted Physical Gait Rehabilitation: How Robotics, Data Science, and Neuroscience are Changing Modern Physical Therapy explores computational modeling techniques, robotic assistance, data science, and other technological tools and how they can be jointly used in driving and guiding physical gait therapy in impairments such as stroke, traumatic brain injury, and incomplete spinal cord injury. This book gathers experts in robotics, human biomechanics, physical therapy, neuroscience, engineering, and medicine, presenting their ongoing work and discusses their views of the future direction of technology-assisted gait therapy, showcasing the latest advancements in the interdisciplinary and multidisciplinary field of technology-assisted gait therapy and strives to outline the developments in the coming years that are needed/likely to make the next big breakthrough in the field.

  • 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

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