AI summary · arXiv: 1605.02783v2 · cs.CV
Estimacion de carga muscular mediante imagenes
The essentials
- Measurement of biomechanical variables in human movement is important in occupational, ergonomic and sports science.
- Current methods involve using impractical, intrusive and expensive devices to capture data.
- This study proposes an automated, non-intrusive and cost-effective alternative using images to capture data.
- The goal is to automate the entire calculation process of these variables.
- Specifically, this study focuses on estimating the level of muscular load exerted by arm muscles from static images while holding a weight.
- Support Vector Machines are used for classification combined with pre-processing techniques that extract visual features using various methods such as Bag of Keypoints, Local Binary Patterns (LBP), Color Histograms and Contour Moments.
- The best-performing methods (LBP and Contour Moments) achieve classification performance measures exceeding 90%.
- This approach represents a promising alternative to traditional methods for measuring biomechanical variables involved in human movement.
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