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 lectures 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 this material is useful to you and I am open to suggestions or comments.

• Biomechanics
• The Biomechanics and Motor Control Laboratory @ UFABC

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

• Scalar and vector
• Basic trigonometry
• Matrix
• Descriptive statistics
• Confidence and prediction intervals
  • Prediction ellipse and prediction ellipsoid
• Curve fitting
  • Polynomial fitting
• Propagation of uncertainty
• Frequency analysis
  • Basic properties of signals
  • Fourier series
  • Fourier transform
• 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)
  • Detection of sequential data
• Time normalization of data
• Ensemble average
• Open files in C3D format

• Kinematics
  • Frame of reference
  • Kinematics of 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
    • Zebris pressure platform
  • Lagrangian Mechanics

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

• The inverted pendulum model of the human standing posture
• Measurements in stabilography
• Rambling and Trembling decomposition of the COP

• Introduction to data analysis in electromyography

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}}  
}  

The non-software content of this project is licensed under a Creative Commons Attribution 4.0 International License, and the software code is licensed under the MIT license.