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 IPython 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.
- Python for scientific computing, V.2 - Slides of a talk
- How to install Python
- 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
- Curve fitting
- Propagation of uncertainty
- Frequency analysis
- Data filtering in signal processing
- Ordinary Differential Equation
- Optimization
- Change detection
- Time normalization of data
- Ensemble average
- Open files in C3D format
- Kinematics
- Kinetics
- Muscle modeling
- Muscle simulation
- Musculoskeletal modeling and simulation
- Multibody dynamics of simple biomechanical models
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}}
}
This work is licensed under the Creative Commons Attribution 4.0 International License.