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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.
- Provides a concise tutorial on affordable clinical gait analysis
- Analyses clinical validation of low-cost sensors for gait assessment
- Documents recent and state-of-the-art low-cost gait abnormality detection systems and therapeutic intervention procedures
Post graduate students and research scholars, faculties from disciplines such as computer science, biomechanics, pathology, medicine, biomedical engineering
1. Introduction: This chapter discusses the preliminaries of gait analysis
2. Statistics and Computational Intelligence in Clinical Gait Analysis
3. Low-cost Sensors for Gait Analysis
4. Validation Study of Low-cost Sensor
5. Gait Segmentation and Event Detection Techniques
6. Methodologies for Vision-based Automatic Pathological Gait Detection
7. Low-cost Systems-based Therapeutic Intervention
8. Pathological Gait Pattern Analysis using Inertial Sensor
9. Prevention, Rehabilitation Monitoring and Recovery Prediction for Musculoskeletal Injuries
10. A Low Cost Electromyography Sensor (EMG)-based Gait Analysis
11. Design and Development of Pathological Gait Diagnosis Tool
12. Conclusion and Future Research Direction
- No. of pages:
- © Academic Press 2021
- 1st August 2021
- Academic Press
- Paperback ISBN:
Dr. Anup Nandy earned his Ph.D from IIIT Allahabad in 2016. His research interest includes Machine Learning, Image Processing, Human Cognition, Robotics, Human Gait Analysis. He received Early Careen Research Award from SERB, Govt. Of India in 2017 for conducting research on “Human Cognitive State Estimation through Multi-modal Gait Analysis”. He also received research funding for Indo- Japanese joint research project, funded by DST, Govt. Of India. He also received NVIDIA GPU GRANT AWARD in 2018 for his research on Human Gait Analysis for Abnormality Detection. Recently he received minor research grant for his research on big data analysis for gait abnormality detection from (TEQIP-III) NIT Rourkela in 2019.
Assistant Professor, Computer Science and Engineering Department, NIT Rourkela, Odisha, India
Saikat Chakraborty obtained his M.Tech from Jadavpur University. Currently he is a Ph.D research scholar in Computer Science and Engineering Department at NIT Rourkela. Beside human gait analysis, he has research experience of 2 years in machine learning in the field of video summarization and sentiment analysis. His current research interest includes computational neuroscience and computational biomechanics. He also worked as a visiting researcher in GV lab., Tokyo University of Agriculture and Technology (TUAT), Japan.
Ph.D Research Scholar in Computer Science and Engineering Department, NIT Rourkela, Odisha, India
Jayeeta Chakraborty is a Ph.D scholar in the department of Computer Science and Engineering in National Institute of Technology (NIT), Rourkela. Her research interests include Machine Learning, Human Gait Analysis, Signal and Image Processing, Data Mining and Semantic Web.
Ph.D Scholar, Department of Computer Science and Engineering in National Institute of Technology (NIT), Rourkela, India
Gentiane Venture has completed an Engineer's degree from the Ecole Centrale of Nantes (France) in 2000 in Robotics and Automation and a MSc from the University of Nantes (France) in Robotics. In 2003, she obtained her PhD from the University of Nantes (France). In 2004 she joined the French Nuclear Agency (Paris, France), to work on the control of a tele-operated micro-manipulator. Later in 2004 she joined Prof. Yoshihiko Nakamura's Lab. at the University of Tokyo (Japan) with the support of the JSPS. In 2006, still under Prof. Nakamura, she joined the IRT project as a Project Assistant Professor. In March 2009, she becomes an Associate Professor and starts a new lab at the Tokyo University of Agriculture and Technology (Japan). Since July 2016 she is a distinguished professor with the Tokyo University of Agriculture and Technology. Her main research interests include: Non-verbal communication, Human behaviour understanding from motion, Human body modelling, Dynamics identification, Control of robot for human/robot interaction, Human affect recognition.
Professor, Tokyo University of Agriculture and Technology, Tokyo, Japan
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