Biomechanics4All

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Study program: Creative Computing
Lecture: Applied Artificial Intelligence
Lecturer(s): Djordje Slijepčević
Team leader: Michael Zeller
Team members:

Michael Zeller (cc231050)
Niklas Hofstetter (cc231056)
Maximilian Barry (cc231065)
Boris Kodzhabashev (cc231069)
Selina Hacker (cc231072)

Short description: An AI-based system that uses a single markerless smartphone video to generate a human skeletal model and analyze gait for accessible movement evaluation.

Project description:

The aim of this project is to create an AI system that can analyze a single video recorded by a smartphone and automatically generate a human skeleton and perform gait analysis for movement evaluation. The idea is to provide a cheaper and more convenient solution compared to traditional methods of movement analysis that involve the use of markers and special equipment. With the help of computer vision and machine learning, the system will be able to identify the human body from a regular smartphone video and obtain movement information in the form of a skeletal structure. Based on the information gathered from the video, the system will be able to evaluate the gait pattern and movement characteristics that may help in the evaluation of the movement. The aim of the project is to show the capability of AI to transform a video recorded by a smartphone into a meaningful movement analysis tool with a variety of applications