TECHNOLOGY-ENABLED MOTION SENSING AND ACTIVITY TRACKING FOR REHABILITATION

This book concentrates on sensing and measurement technologies for rehabilitation applications. The book looks at motion sensing technologies, human motion and exogames and healthcare applications including speech, respiration, and recovery from stroke or accident.

Detalles Bibliográficos
Autor principal: ZHAO, WENBING
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [S.l.] : INST OF ENGIN AND TECH, 2023.
Temas:
Motion detectors.
Machine learning.
Medical rehabilitation.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Title
  • Copyright
  • Contents
  • About the author
  • List of figures
  • List of tables
  • Introduction
  • Part I Motion sensing technologies
  • 1 Inertial measurement units
  • 1.1 Accelerometer
  • 1.2 Gyroscope
  • 1.3 Magnetometer
  • 1.4 Rehabilitation studies using IMUs
  • 1.4.1 Studies using low-level IMUs
  • 1.4.2 Studies using prepackaged professional sensors containing IMUs
  • 1.4.3 Studies using consumer-grade devices containing IMUs
  • 1.4.4 Studies using wearable trackers
  • 2 Force and pressure sensing
  • 2.1 Types of pressure sensors
  • 2.1.1 Piezoelectric pressure sensors
  • 2.1.2 Resistive pressure sensors
  • 2.1.3 Capacitive pressure sensors
  • 2.1.4 Optical pressure sensors
  • 2.2 Applications in motion tracking for rehabilitation
  • 2.2.1 Epionics SPINE system
  • 2.2.2 Force plates
  • 2.2.3 Smart insoles and smart shoes
  • 2.3 Energy harvesting in smart shoes
  • 3 E-Textile-based sensing
  • 3.1 Conductive elastomer
  • 3.1.1 Working principle
  • 3.1.2 Attaching conductive elastomer to fabric
  • 3.1.3 Motion tracking with conductive elastomer
  • 3.1.4 New development
  • 3.2 Commercial elastic sensors
  • 3.3 Other approaches
  • 4 Muscle activity sensing with myography
  • 4.1 Electromyography
  • 4.1.1 EMG in upper-extremity stroke therapy
  • 4.1.2 EMG in recovery progress evaluation of anterior cruciate ligament reconstructed subjects
  • 4.2 Machanomyography
  • 4.3 Force myography
  • 4.4 Optical myography
  • 4.5 Summary
  • 5 Vision-based motion sensing
  • 5.1 Microsoft Kinect sensor
  • 5.2 Feasibility studies of using Kinect in rehabilitation
  • 5.3 Kinect-based systems in rehabilitation
  • 5.3.1 Kinect-based system with visual feedback only
  • 5.3.2 Kinect-based system with performance quality feedback
  • 5.3.3 Integration of Kinect and other sensing modalities
  • 5.4 Beyond Kinect
  • 6 Instrumented gloves
  • 6.1 Gloves based on IMUs
  • 6.1.1 Calibration
  • 6.1.2 Signal processing
  • 6.1.3 Reference systems for evaluation
  • 6.1.4 Accuracy evaluation
  • 6.1.5 Repeatability and reliability evaluation
  • 6.1.6 Classification of activities
  • 6.2 Gloves based on flex sensors
  • 6.3 Gloves based on optical sensors
  • 6.3.1 FBG-based approach
  • 6.3.2 Light-attenuation-based approach
  • 6.3.3 Optical linear encoder
  • 6.4 Gloves based on Hall effect
  • Part II Human motion recognition and exergames
  • 7 Measurement of basic parameters
  • 7.1 Mechanics of body movements
  • 7.1.1 Anatomical planes
  • 7.1.2 Joints and their movements
  • 7.1.3 Range of motion
  • 7.2 Joint angle measurement with various sensing modalities
  • 7.2.1 Joint angle measurement with IMU
  • 7.2.2 Joint angle measurement with Kinect
  • 7.3 Measurement theories
  • 7.4 Evaluating a new measurement instrument
  • 7.4.1 Root mean square error
  • 7.4.2 Student's t-test
  • 7.4.3 Pearson's coefficient of correlation
  • 7.4.4 Intraclass correlation coefficient
  • 7.4.5 Bland-Altman limits of agreement

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