Chakraborty / Venture | Modern Methods for Affordable Clinical Gait Analysis | Buch | 978-0-323-85245-6 | sack.de

Buch, Englisch, 194 Seiten, Format (B × H): 216 mm x 276 mm, Gewicht: 390 g

Chakraborty / Venture

Modern Methods for Affordable Clinical Gait Analysis

Theories and Applications in Healthcare Systems
Erscheinungsjahr 2021
ISBN: 978-0-323-85245-6
Verlag: William Andrew Publishing

Theories and Applications in Healthcare Systems

Buch, Englisch, 194 Seiten, Format (B × H): 216 mm x 276 mm, Gewicht: 390 g

ISBN: 978-0-323-85245-6
Verlag: William Andrew Publishing


Modern Methods for Affordable Clinical Gait Analysis: Theories and Applications in Healthcare Systems is a handbook of techniques, tools and procedures for the study and improvement of human gait. It gives a concise description of clinical gait analysis, especially gait abnormality detection problems and therapeutic interventions using inexpensive devices. A brief demonstration on validation testing of these devices for its clinical applicability is also presented. Content coverage also includes step-by-step processing of the data acquired from these devices. Future perspectives of low-cost clinical gait assessment systems are explored.

This book bridges the gap between engineering and biomedical fields as it diagnoses and monitors neuro-musculoskeletal abnormalities using the latest technologies. The authors discuss how early detection technology allows us to take precautionary measures, in order to delay the degeneration process, through development of a clinical gait analysis tool. One unique feature of this book is that it pays significant attention to the challenges of conducting gait analysis in developing countries with limited resources. This reference will guide you through setting up a low-cost gait analysis lab. It explores the relationship between vision-based pathological gait detection, the design of tools for gait diagnosis and therapeutic interventions.
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Zielgruppe


<p>Post graduate students and research scholars, faculties from disciplines such as computer science, biomechanics, pathology, medicine, biomedical engineering.</p>

Weitere Infos & Material


1. Introduction 2. Statistics and computational intelligence in clinical gait analysis 3. Low-cost sensors for gait analysis 4. Validation study of low-cost sensors 5. Gait segmentation and event detection techniques 6. Methodologies for vision-based automatic pathological gait detection 7. Pathological gait pattern analysis using inertial sensor 8. A low-cost electromyography (EMG) sensor-based gait activity analysis 9. Low-cost systems-based therapeutic intervention 10. Prevention, rehabilitation, monitoring, and recovery prediction for musculoskeletal injuries 11. Design and development of pathological gait assessment tools 12. Conclusion


Chakraborty, Saikat
Saikat Chakraborty obtained his MTech from Jadavpur University. Currently he is a PhD research scholar in the Computer Science and Engineering Department at NIT, Rourkela. Beside human gait analysis, he has research experience of two years in machine learning in the field of video summarization and sentiment analysis. His current research interests include computational neuroscience and computational biomechanics. He also worked as a visiting researcher in GV lab, TUAT, Japan.

Venture, Gentiane
Gentiane Venture is a French Roboticist working in academia in Tokyo. She is a distinguished professor with TUAT and a cross appointed fellow with AIST. She obtained her MSc and PhD from Ecole Centrale/University of Nantes in 2000 and 2003, respectively. She worked at CEA in 2004 and for six years at the University of Tokyo. In 2009, she started with TUAT where she has established an international research group working on human science and robotics. With her group she conducts theoretical and applied research on motion dynamics, robot control, and nonverbal communication to study the meaning of living with robots. Her work is highly interdisciplinary, collaborating with therapists, psychologists, neuroscientists, sociologists, philosophers, ergonomists, artists, and designers.

Chakraborty, Jayeeta
Jayeeta Chakraborty is a PhD scholar in the department of Computer Science and Engineering in NIT, Rourkela. Her current research interests include Machine Learning, Human Gait Analysis, Signal and Image Processing. She has previous research experience in the domain of Data Mining, Recommendation Systems, and Semantic Web.


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