Intelligent Gait Assistive Technologies

Gait Biomechanics and Machine Learning Applications in Rehabilitation and Injury Prevention

Häftad, Engelska, 2027

1 483 kr

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Beskrivning

Intelligent Gait Assistive Technologies: Gait Biomechanics and Machine Learning Applications in Rehabilitation and Injury Prevention brings together contemporary research and applications to show how gait biomechanics combined with machine learning can be used to develop techniques to provide safer, more mechanically efficient locomotion to individuals with significant visual, musculoskeletal, or neurological deficits. Developments in gait rehabilitation and injury prevention outlined in this book will contribute to improved quality of life for individuals with gait-related impairments, with a major contribution to medical cost savings due to reduction in falls.

Researchers, engineers, and students in biomedical engineering and biomechanics will find this a welcomed reference in better understanding the role of machine learning and intelligent technologies in the advancement of gait rehabilitation and injury reduction to both impaired and healthy individuals.

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

Produktinformation

Utgivningsdatum:2027-03-01
Mått:152 x 229 x undefined mm
Vikt:450 g
Format:Häftad
Språk:Engelska
Antal sidor:300
Förlag:Elsevier Science
ISBN:9780443141041

Utforska kategorier

Biokemisk teknik inom Naturvetenskap och teknik
Artificiell intelligens inom Data och IT
Biomedicinsk teknik inom Medicin

Mer om författaren

Rezaul Begg is chair in Assistive Technologies within the Program in Assistive Technology Innovation (PATI) at Victoria University. He leads a multidisciplinary “Gait and Intelligent Technologies research group focused on technologies with application to both unimpaired and pathological gait. He uses a combination of engineering and biomechanical principles to understand and diagnose locomotion-related deficits, and to provide intelligent technology solutions to improving walking efficiency and safety. Professor Begg has published five books and over 300 refereed papers in scientific journals and conferences proceedings. He is associate editor of Frontiers in Bioengineering and Biotechnology, and an editorial board member of the Journal of Biomechanics and Sensors. He has received several Best Paper awards in conferences, the Victoria University Vice Chancellor’s citation award for Excellence in Research, a Gold Medal from BUET and Chancellor’s Prize from Bangladesh Government for Academic Excellence. Hanatsu Nagano specializes in gait biomechanics with special focus on application for practical interventions. He invented the special shoe-insole that reduces tripping, falls, and improves dynamic balance, which was awarded ‘Most Innovative New Care Product in the World’ for the three consecutive years. He is experienced in working closely with industry-leading research & development projects including regenerative medical technology, management of knee osteoarthritis, wearable sensor application, artificial intelligence, exercise intervention, and active exoskeletons. His entrepreneurship and business communication skills have successfully established various international academia-industry-government collaborations. He sets his current missions in developing smart footwear for safe walking, inventing regenerative technology integrated knee orthosis, coordinating health enhancing intervention programs for government-leading initiatives, establishing further synergy effects based on research-industry linkage, and promoting Hybrid Assistive Limb (HAL) and its core philosophy, Cybernics, worldwide.

Innehållsförteckning

Part I: Gait Biomechanics - Tripping, Slipping and Balance Loss1. Fundamentals of Gait Biomechanics2. Kinematics and Kinetics of Lower Limb Swing Phase Trajectory Control3. Minimum Foot-Ground Clearance (MFC) and Tripping Probability Modelling4. Required Coefficient of Friction (RCOF) and Slipping Prediction5. Gait Adaptations due to Ageing, Injury and Pathologies6. Gait Impairments Causing Tripping, Slipping and Balance LossPart II: Gait Assisting Techniques and Devices7. Biofeedback-Based Gait Training Interventions8. Passive Exoskeletons9. Active Exoskeletons10. Intelligent Footwear: Smart Insoles, Shoe-Mounted SensorsPart III: Machine Learning Applications to Gait Assisting Techniques11. Predicting Gait Kinematics from Inertial Sensors12. Limb Trajectory Prediction (i): Critical Failure Events13. Limb Trajectory Prediction (ii): Intelligent Assistive Device Control and Tripping Hazard RecognitionPart IV Conclusions, Emerging Techniques and Future Directions14. Future Challenges in Rehabilitation and Injury Prevention15. Research Directions in Gait Biomechanics and Machine Learning16. References