scumechanics/BMC

Notes on Scientific Computing for Biomechanics and Motor Control

BMC

Notes on Scientific Computing for Biomechanics and Motor Control

Marcos Duarte

This repository is a collection of lecture notes and code on scientific computing and data analysis for Biomechanics and Motor Control. The notes are written using the Jupyter Notebook, part of the Python ecosystem for scientific computing. You can view these lectures in different ways: simply read on line by clicking on the links below; or download a single notebook or all the stuff or yet fork this entire repository using the GitHub resources and run the notebooks in your computer or in the cloud.
I hope you find this material useful and I am open to comments and suggestions (report an issue or do a pull request using the menu options above or write to me).

Introduction

• Biomechanics
• The Biomechanics and Motor Control Laboratory

Scientific programming

• Python for scientific computing
• How to install Python
• Python tutorial
• Version control with Git and GitHub
• Code structure for data analysis

Numerical data analysis

• Scalar and vector
• Basic trigonometry
• Matrix
• Descriptive statistics
• Confidence and prediction intervals

• Prediction ellipse and prediction ellipsoid

• Curve fitting
• Propagation of uncertainty
• Frequency analysis

• Basic properties of signals
• Fourier series
• Fast Fourier Transform and Power Spectral Density

• Data filtering in signal processing

• Residual analysis for the optimal cutoff frequency

• Ordinary Differential Equation
• Optimization
• Change detection

• Detection of peaks
• Detection of onset
• Detection of changes using the Cumulative Sum (CUSUM)

• Time normalization of data
• Ensemble average
• Open files in C3D format

Mechanics

• Kinematics

• Frame of reference
• Kinematics of a particle
  • Projectile motion
  • Spatial and temporal characteristics
  • Minimum jerk hypothesis
• Angular kinematics (2D)
  • Kinematic chain
• Rigid-body transformations (2D)
• Rigid-body transformations (3D)
  • Determining rigid body transformation using the SVD algorithm

• Kinetics

• Fundamental concepts
• Body segment parameters
• Free body diagram
• Biomechanical analysis of vertical jumps
• Gait analysis (2D)
• Force plates
  • Kistler force plate calculation
  • Open AMTI .bsf file
  • Algorithm for force plate calibration
• Lagrangian mechanics
  • Lagrangian mechanics

Modeling and simulation of human movement

• Muscle modeling
• Muscle simulation
• Musculoskeletal modeling and simulation
• Multibody dynamics of simple biomechanical models

Stabilography

• The inverted pendulum model of the human standing posture
• Measurements in stabilography

Electromyography

• Introduction to data analysis in electromyography

How to cite this work

Here is a suggestion to cite this GitHub repository:

Duarte, M. (2015) Notes on Scientific Computing for Biomechanics and Motor Control. GitHub repository, https://github.com/demotu/BMC.

And a possible BibTeX entry:

@misc{Duarte2015,  
    author = {Duarte, M.},  
    title = {Notes on Scientific Computing for Biomechanics and Motor Control},  
    year = {2015},  
    publisher = {GitHub},  
    journal = {GitHub repository},  
    howpublished = {\url{https://github.com/demotu/BMC}}  
}  

License

This work is licensed under the Creative Commons Attribution 4.0 International License.