Udemy - Biomechanics Data in Python and AI
- Category Other
- Type Tutorials
- Language English
- Total size 2.2 GB
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- Last checked 1 month ago
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Infohash : C45F9BFA90F6892F4ACDD35F1B3F925C992DCC3A
Biomechanics Data in Python & AI
https://WebToolTip.com
Published 11/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 45m | Size: 2.28 GB
Learn to analyze, visualize, and interpret biomechanics data using Python, AI, and real human movement examples.
What you'll learn
Set up and work in Google Colab to run Python notebooks for biomechanics analysis, with zero installs.
Load and inspect C3D motion capture files, including markers, analog signals like force plates and EMG, and key metadata.
Read and write C3D in Python using ezc3d or c3dposeiq, then organize data for analysis.
Build a tidy analysis table from C3D data by extracting time, marker trajectories, vertical ground reaction force, normalizing units, and filtering noise.
Visualize biomechanics signals with matplotlib to create clear, publication-ready plots.
Apply a practical workflow from input to export that you can reuse in labs or research.
Requirements
A laptop or desktop with a modern web browser and an internet connection. You will run everything in Google Colab, in the browser, no installs needed.
A Google account for Colab access.
No prior coding or biomechanics experience required. The material is written for complete beginners, even if you have never heard of C3D.
Optional: very light Python familiarity helps. We review basics like lists, functions, assertions, arrays, and DataFrames inside the course.
Sample data is provided. If you do not have your own motion capture files, we use public C3D examples so you can practice right away.
Software is handled in-notebook. We install ezc3d and pandas with pip when needed.
Tools used in the course include NumPy and Matplotlib, which are available in Colab.
Nice to have, not required: curiosity about motion capture signals like markers, force plates, and EMG. We explain these as we go.
Files:
[ WebToolTip.com ] Udemy - Biomechanics Data in Python and AI- Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 1 - Introduction
- 1 - Introduction - 1-Intro.mp4 (352.2 MB)
- 1 - Introduction.mp4 (45.8 MB)
- 2 - Introduction to Motion Capture & C3D File Analysis & Google Colab.mp4 (42.0 MB)
- 3 - Reading and Plotting Ground Reaction Forces from C3D Files in Google Colab - Python code (Colab notebook).url (0.1 KB)
- 3 - Reading and Plotting Ground Reaction Forces from C3D Files in Google Colab.mp4 (45.7 MB)
- 3 -Python code (Colab notebook).url (0.1 KB)
- 4 - Working with C3D Motion Capture Files Free Tools & Datasets.mp4 (78.0 MB)
- 5 - Biomechanics Framework Made Simple Analyze Movement Using PythonColab.mp4 (22.0 MB)
- 6 - Learn Python with the help of AI in this quick and practical session.mp4 (52.3 MB)
- 7 - Introduction & Overview Motion Capture Data Analysis with Python in Colab.mp4 (19.9 MB)
- 1 - Motion Data Input Using Pandas – Basics.mp4 (33.4 MB)
- 2 - Working with C3D Motion Capture Files in Google Colab Meta Data.mp4 (39.7 MB)
- 3 - Learn How to Read & Work With Motion Capture Data (C3D, TRC, CSV) in Python!.mp4 (44.9 MB)
- 4 - Reading C3D and TRC Motion Capture Files in Google Colab using Python and Gemini.mp4 (50.6 MB)
- 5 - Understanding C3D File Structure and Reading Data with Python.mp4 (55.4 MB)
- 1 - Parsing Data.mp4 (21.9 MB)
- 2 - Chapter Transition – Short Course Section.mp4 (12.3 MB)
- 3 - Understanding Dictionaries in Python for Biomechanics Data Parsing.mp4 (46.3 MB)
- 4 - Parsing and Time Vector Creation in C3D Motion Capture Data (Python Tutorial).mp4 (49.9 MB)
- 5 - Parsing and Processing C3D Markers, Force Plates, Filtering, and Normalization.mp4 (61.8 MB)
- 6 - Parsing C3D Files in Python – Biomechanics Data Tutorial and Quiz.mp4 (68.3 MB)
- 1 - Introduction From Parsing to Analysis in Python Gait Events, Metrics.mp4 (20.0 MB)
- 2 - Understanding and Processing Biomechanics Data with Python Analysis.mp4 (76.9 MB)
- 3 - From Force Plate to Foot Contact Heel-Strike and Toe-Off from GRF Data.mp4 (87.5 MB)
- 4 - Step 2 – Key Gait Metrics from Force Plate Data (Peak GRF, Cadence & Symmetry).mp4 (35.2 MB)
- 5 - Gait Step & Stance Segmentation Across Force Plates.mp4 (56.1 MB)
- 6 - Step 4 – Low-Pass Filtering of Force and Marker Data.mp4 (57.7 MB)
- 7 - Summary C3D to Analysis-Ready Data Forces, COP & Markers in One Go.mp4 (54.8 MB)
- 1 - Visualizing Biomechanics Data Introduction.mp4 (41.9 MB)
- 2 - C3D Data Visualization & Gait Cycle Detection in Python (Full Walkthrough).mp4 (188.7 MB)
- 3 - Visualize Where Science Meets Art.mp4 (62.7 MB)
- 1 - Introduction to Exporting and Reporting Findings.mp4 (37.0 MB)
- 2 - Biomech Research Template Analyze, Visualize and Report in Colab.mp4 (72.2 MB)
- 3 - Summary and Final Report in Biomechanics Data Generation and Analysis.mp4 (65.5 MB)
- 1 - Introduction to MSK modeling in Biomechanics.mp4 (37.7 MB)
- 2 - Simple MSK Simulation in Colab.mp4 (127.9 MB)
- 3 - Hypothesis-Driven Machine Learning Workflow.mp4 (36.0 MB)
- 4 - Mini Demo Hypothesis-Driven GRF from Heel Height.mp4 (98.9 MB)
- Bonus Resources.txt (0.1 KB)
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