| Description |
1 online resource (x, 179 pages) : color illustrations |
| Contents |
Front Cover -- MODERN METHODS FOR AFFORDABLE CLINICAL GAIT ANALYSIS -- MODERN METHODS FOR AFFORDABLE CLINICAL GAIT ANALYSIS -- Copyright -- Contents -- About the authors -- Preface -- Acknowledgment -- 1 -- Introduction -- 1.1 What is gait? -- 1.2 Gait cycle -- 1.3 Features of gait -- 1.3.1 Spatio-temporal -- 1.3.2 Kinematic -- 1.3.3 Kinetic -- 1.3.4 Anthropometric -- 1.3.5 Electromyography -- 1.4 Model-based versus model-free gait assessment -- 1.4.1 Model-based human gait analysis -- 1.4.2 Model-free human gait analysis -- 1.5 Applications of gait analysis |
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1.6 Clinical aspects of human gait -- 1.6.1 Gait signal segmentation -- 1.6.2 Pathological gait detection -- 1.6.3 Injury prevention and recovery prediction -- 1.7 Sensors for gait data acquisition -- 1.8 Summary -- References -- 2 -- Statistics and computational intelligence in clinical gait analysis -- 2.1 Introduction -- 2.2 Statistics in clinical gait data -- 2.2.1 Confidence interval, p-value, and effect size -- 2.2.2 Statistics in clinical trials -- 2.2.3 Systematic review and meta-analysis -- 2.3 Computational intelligence in clinical gait data |
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2.3.1 Why computational intelligence is important? -- 2.3.2 Learning paradigm -- 2.3.3 Applications of computational intelligence in clinical gait data -- 2.4 Statistics versus computational intelligence -- 2.5 Summary -- References -- 3 -- Low-cost sensors for gait analysis -- 3.1 Introduction -- 3.2 Motion capture sensors for gait -- 3.2.1 Classification of sensors -- 3.2.2 Gold standard sensors -- 3.2.3 Affordable sensors -- 3.3 Microsoft kinect -- 3.3.1 First and second generation -- 3.3.2 Hardware and software specification -- 3.3.3 Data streams of kinect |
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3.3.4 Application in clinical gait assessment -- 3.4 Wearable sensors -- 3.4.1 Inertial sensors -- 3.4.1.1 Types of inertial sensors -- 3.4.1.2 Cost analysis of inertial sensors -- 3.4.1.3 Applications of inertial sensor in clinical gait assessment -- 3.4.2 Electromyography sensors -- 3.4.2.1 MyoWare muscle sensor -- 3.4.3 Others: force sensitive resistors, goniometers -- 3.5 Summary -- References -- 4 -- Validation study of low-cost sensors -- 4.1 Introduction -- 4.2 Kinect validation for clinical usages -- 4.3 Inertial sensor validation on estimating joint angles |
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4.3.1 Evaluation metrics for validation of estimated joint angles -- 4.4 Summary -- References -- 5 -- Gait segmentation and event detection techniques -- 5.1 Introduction -- 5.2 Why gait cycle segmentation? -- 5.3 Vision sensor-based gait cycle segmentation -- 5.3.1 Threshold-based methods -- 5.3.2 Machine learning-based methods -- 5.4 Kinect in gait cycle segmentation -- 5.5 Inertial sensor-based gait segmentation -- 5.5.1 Threshold-based methods -- 5.5.2 Machine intelligence-based methods -- 5.6 Electromyography sensor-based gait segmentation -- 5.6.1 Statistical methods |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Gait disorders.
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Gait disorders -- Diagnosis -- Equipment and supplies
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Motion detectors.
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Gait in humans.
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Medical instruments and apparatus.
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Gait Analysis
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Gait
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Equipment and Supplies
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Motion detectors
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Gait disorders
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Gait in humans
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Medical instruments and apparatus
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Lopen.
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Bewegingsleer.
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Diagnostiek.
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| Form |
Electronic book
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| Author |
Chakraborty, Saikaat
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Chakraborty, Jayeeta
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Venture, Gentiane
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| ISBN |
9780323852463 |
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0323852467 |
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