Gait analysis is the study of the walking or running pattern of an individual. This can include spatial and temporal measurements such as step length, stride length and speed along with angular measurements of various joints and the interplay between various parts like the foot, hip, pelvis or spine when walking. Gait analysis can be used to assess clinical conditions and design effective rehabilitation; for example, following limb injury or amputation, or other disorders such as a stroke or Parkinson's diagnosis. It can be used to influence intervention decisions, such as whether a patient should undergo surgery, further physiotherapy, or begin a particular treatment regime. Gait analysis can also be used in sports science to monitor and review performance and technique.
Gait can be recorded in a variety of ways, including pressure sensors, force plates, in-shoe pressure systems, through marker-based or marker-less systems using various cameras or sensors to calculate body positions in a set sequence of movements.
This book focuses on both the hardware systems for collecting data as well as data visualisation and mathematical models for interpreting the data. It is written by a range of international researchers from academia, industry, and clinical settings, providing a complete overview of gait analysis technologies suitable for an audience of engineers in rehabilitation technologies or other biomedical engineering fields.
Author(s): Nachiappan Chockalingam
Series: Healthcare Technologies Series, 31
Publisher: The Institution of Engineering and Technology
Year: 2022
Language: English
Pages: 377
City: London
Cover
Contents
About the editor
1 Introduction to gait analysis
1.1 Describing the basic gait pattern: spatiotemporal variables
1.2 Segment and joint kinematics
1.3 Overview of kinematic techniques used in gait analysis
1.3.1 Video
1.3.2 Camera-based motion capture systems
1.3.3 Non-camera-based motion capture systems
1.4 Gait analysis – beyond kinematics
1.4.1 Measuring forces
1.4.2 Combining kinematics and kinetics – modelling
1.4.3 Measuring pressures
1.4.4 Measuring physiology
1.5 Introduction to healthy gait biomechanics
1.6 Uses and applications of gait analysis
1.6.1 Fundamental understanding of gait
1.6.2 Athletic performance and injury prevention
1.6.3 Footwear design
1.6.4 Pathological gait
1.6.5 Gait and ageing
1.6.6 Gait and prosthetics
1.6.7 Clinical applicability
1.7 Conclusion
References
2 Gait analysis – a historical perspective
2.1 Introduction
2.2 The ancient world
2.3 The renaissance
2.4 The enlightenment and the nineteenth century
2.5 The twentieth century
2.6 Post Second War
2.7 Electromyography
2.8 The development of motion analysis systems
2.9 The introduction of the computer
2.10 Retro-reflectivity
2.11 The commercialisation of optical motion capture technologies
2.12 The rise of clinical gait analysis
2.13 The introduction of solid-state camera technologies
2.14 The development of unified biomechanical models
2.15 Wider applications of motion capture
References
3 Gait analysis – kinematics
3.1 Introduction
3.2 Optoelectronic stereophotogrammetric marker-based systems
3.3 Soft tissue artefact
3.4 Kinematic modelling of the pelvis and lower limbs
3.5 Pelvis alternative models
3.6 Kinematic modelling of the spine and trunk
3.6.1 Two-dimensional modelling of the trunk and spine
3.6.2 Three-dimensional modelling of the thoracic region
3.6.3 3-D modelling of the lumbar region
3.7 Inertial measurement units
3.8 Quantifying kinematic parameters related to walking and running
3.8.1 Number of steps and cadence
3.8.2 Stride length, speed and distance
3.8.3 Stance and swing
3.9 Application of kinematic parameters related to walking and running
3.9.1 Number of steps and cadence
3.9.2 Stride length, speed and distance
3.9.3 Stance and swing
References
4 Gait analysis – kinetics
4.1 Introduction
4.2 Force transducers
4.2.1 Introduction and properties
4.2.2 Strain gauge transducers
4.2.3 Piezoelectric transducers
4.2.4 The six components of the load in a real transducer
4.3 Force platforms
4.4 Force platform calibration
4.4.1 An active calibration device, oriented to six-component platforms
4.4.2 A passive calibration device, oriented to three-component platforms
4.5 Foot-ground pressure measurement systems
4.6 Pressure sensors
4.6.1 Sensor response and main sources of error
4.7 Pressure platform types and assemblies
4.7.1 Comparison of force and pressure platforms performance in posturography
4.8 Pressure insoles
4.9 Calibration of foot pressure measurement devices
4.10 Recommendations for data collection
4.11 Conclusions
References
5 Assessment of muscle function
5.1 Introduction
5.1.1 Terminology
5.1.2 History of EMG
5.2 Muscle physiology
5.2.1 Neuromuscular anatomy
5.2.2 Signal propagation
5.3 Measuring neuromuscular function
5.3.1 Innervation zone (IZ)
5.3.2 Sensor placement
5.3.3 Tissue properties
5.3.4 Skin preparation
5.3.5 Signal quality check
5.4 EMG electrode and system design
5.4.1 Electrode design
5.4.1.1 Intramuscular EMG
5.4.1.2 sEMG
5.4.2 Sensor and system design
5.4.3 Sampling rate
5.4.4 Reference electrode
5.4.5 Inter-electrode spacing
5.5 EMG decomposition
5.5.1 Decomposition techniques
5.5.2 EMG decomposition metrics
5.6 Real-time EMG decomposition
5.7 High-density surface EMG
5.7.1 Instrumentation
5.7.2 What can be found in the signal
5.7.3 A look to the future
5.8 Summary
References
6 Considerations for data analysis
6.1 Introduction
6.2 Time domain analyses
6.2.1 Strain gauge force transducers and socket reaction moments
6.2.2 Force plates and GRF
6.2.3 Motion capturing systems (3D)
6.3 Frequency domain
6.3.1 Accelerometry studies
6.3.2 Application of FFT to quantify neural control
6.4 Wavelet analyses
6.4.1 Wavelets and wavelet transforms
6.4.2 Wavelet families
6.4.3 Continuous and discrete wavelet transforms
6.4.4 Choosing the proper mother wavelet
6.4.4.1 Wavelet type
6.4.4.2 Wavelet length of support
6.4.4.3 Vanishing moments
6.4.4.4 Level of decomposition
6.4.5 Applications of wavelets
6.5 Factor analyses
6.6 Data visualization approaches
6.7 Summary
References
7 Novel technologies for gait analysis
7.1 Introduction
7.2 Application of gait analysis measurement technologies
7.3 Wearable devices
7.3.1 EMG
7.3.2 Goniometers
7.3.3 Insole pressure and force sensors
7.3.4 IMUs
7.3.5 Example of a clinical application using a single IMU – diabetic peripheral neuropathy
7.3.6 Example of a single or dual limb IMU – sports science
7.3.7 Capture of human ambulatory motion using IMU groups
7.4 Floor-mounted kinematic and kinetic capture technologies
7.4.1 Instrumented walkways
7.4.2 Pressure measurement systems (pedobarograph)
7.4.3 GRF plates
7.5 Image processing motion capture
7.5.1 Passive optical motion capture systems
7.5.2 Retro-reflectivity
7.5.3 Confirmation of retro-reflective marker performance
7.5.4 Motion capture cameras
7.5.5 Illuminating markers and removing background from images
7.5.6 Detecting marker images in two-dimensions
7.5.7 Compensating for lens non-linearity
7.5.8 Three-dimensional calibration
7.5.9 Marker labelling and trajectory management
7.5.10 Performance of motion capture systems
7.5.11 Independent protocol for quantifying the accuracy of motion analysis systems
7.5.12 Biomechanical modelling
7.5.13 Active marker motion capture systems
7.6 Energy expenditure and oxygen consumption
7.7 Clinical gait analysis, review and reporting
7.8 Systematic review of the efficacy of clinical gait analysis
References
8 Clinical gait analysis
8.1 Introduction
8.1.1 Purpose of clinical gait analysis
8.1.2 Overview of the clinical gait analysis process
8.1.3 The team
8.1.4 Laboratory accreditation
8.2 Components of clinical gait analysis
8.2.1 Postural stability
8.2.1.1 Stability
8.2.1.2 Vestibular system
8.2.1.3 Visual and auditory systems
8.2.2 Temporal-distance parameters
8.2.2.1 Central pattern generator (CPG)
8.2.2.2 Gait pattern
8.2.2.3 Measurement approaches
8.2.3 3D kinematics
8.2.3.1 Introduction
8.2.3.2 Marker set (definition of limb segment coordinate systems)
8.2.3.3 Kinematic equations
8.2.3.4 Gait deviation index (GDI) and the gait profile score (GPS)
8.2.4 3D kinetics
8.2.4.1 Ground reaction force vector
8.2.4.2 Definitions of joint moment and power
8.2.4.3 Equations of motion
8.2.4.4 GDI – kinetics
8.2.5 Dynamic EMG
8.2.5.1 Muscle physiology
8.2.5.2 Amplitude modulation (AM) model for EMG
8.2.5.3 Amplitude demodulation – linear envelope detection
8.2.6 Plantar pressures
8.2.6.1 Foot type: another matter of structure and function
8.2.6.2 Masked plantar pressure parameters
8.2.6.3 Center of pressure excursion index
8.2.7 3D gait analysis interpretation
8.2.7.1 Clinical evidence consolidated by precision medicine
8.2.7.2 The reporting session
8.2.7.3 Standardizing the reporting of kinematics, kinetics, and surface EMG
8.2.7.4 3D gait analysis follow-up exam
8.2.8 Summary
8.3 Clinical cases
8.3.1 Case 1
8.3.1.1 Initial visit
8.3.1.2 Follow-up visit
8.3.2 Case 2
8.3.2.1 Initial visit
8.3.2.2 Post-operative visit
8.4 Summary
References
9 Gait analysis in rehabilitation
9.1 Introduction
9.2 Muscular dystrophies
9.2.1 Gait deviations
9.2.2 Rehabilitation
9.3 Multiple sclerosis
9.3.1 Gait deviations
9.3.2 Rehabilitation
9.4 Osteoarthritis and rheumatoid arthritis
9.4.1 Gait deviations
9.4.2 Rehabilitation
9.5 Spina bifida
9.5.1 Gait deviations
9.5.2 Rehabilitation
9.6 Poliomyelitis
9.6.1 Gait deviations
9.6.2 Rehabilitation
9.7 Spinal deformities
9.7.1 Kyphosis
9.7.1.1 Gait deviations
9.7.1.2 Rehabilitation
9.7.2 Scoliosis
9.7.2.1 Gait deviation
9.7.2.2 Rehabilitation
9.8 Cerebral palsy
9.8.1 Gait deviation
9.8.2 Rehabilitation
9.9 Cerebrovascular accident
9.9.1 Gait deviation
9.9.2 Rehabilitation
9.10 Aging and balance disorders
9.10.1 Gait deviation
9.10.2 Rehabilitation
9.11 Biomechanical optimization of ankle-foot orthoses and footwear combinations
9.12 Amputation and prosthetic management
9.12.1 Transtibial gait analysis
9.12.1.1 Transtibial gait deviations
9.12.2 Transfemoral gait analysis
9.12.2.1 Transfemoral gait deviations
9.12.3 Prosthetic prescription
9.12.3.1 Distal amputations
9.12.3.2 Transtibial amputation
9.12.3.3 Transfemoral amputation
References
10 Forensic gait analysis – Is there a case?
10.1 Introduction
10.2 Gait verification system
10.2.1 Target person selection module
10.2.2 Silhouette creation module
10.2.3 Feature extraction and posterior probability calculation module
10.2.3.1 Gait feature generation
10.2.3.2 Dissimilarity score calculation
10.2.3.3 Circumstance-dependent posterior probability calculation
10.2.4 Future direction of the gait verification system
10.3 Use cases of gait forensics in Japan
10.4 Conclusion and future prospects
References
11 Future of gait analysis
11.1 Introduction
11.2 Application of functional calibration to the routine analysis of human gait
11.3 Clinical gait analysis standardisation
11.4 Animation and computer graphics
11.5 Data fusion
11.6 Application of computer vision
11.7 Application of cameras with a depth measurement capability
11.8 Deep learning and neural networks
11.9 Markerless gait analysis
11.10 Application of artificial intelligence and machine learning
11.11 Gait analysis in the twenty-first century
References
Index
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