motion capture systems can be wide range of methods but understanding how the mane systems work can help to understand how we can provide the low cost methods for biomechanical labs and took the reliable data
Simply, video-based mocap systems reconstruct 3D positions of markers placed on points of interest (e.g., joints) within a previously calibrated working volume from cameras' recordings and reconstruction algorithms.
thank you for your answer but i already know the details of how these instructions are working but my mane question was about how hardware are working !
Several infrared strobes are placed around the measured person/object. The strobes send infrared signals out and measure the time it takes for the infrared signal to reflect off infrared-reflective markers and then come back into the camera (similar to how sonar works). This measures distance of the marker. When two or more cameras are able to measure the distance of the same marker from different, pre-calibrated angles, then the location of the marker can be triangulated, and recorded. This process is repeated for every marker in the recording space, and for each moment in time (i.e. frame rate).
If you are specifically looking for low-cost mocap set-ups, you may want to look for papers that use an Xbox Kinect sensor to conduct kinematic measurements. You could start your reading with these papers:
Müller, B., Ilg, W., Giese, M. A., & Ludolph, N. (2017). Validation of enhanced kinect sensor based motion capturing for gait assessment. PloS one, 12(4), e0175813. https://doi.org/https://doi.org/10.1371/journal.pone.0175813
Zhao, N., Zhang, Z., Wang, Y., Wang, J., Li, B., Zhu, T., & Xiang, Y. (2019). See your mental state from your walk: Recognizing anxiety and depression through Kinect-recorded gait data. PloS one, 14(5), e0216591. https://doi.org/10.1371/journal.pone.0216591
Li, B., Zhu, C., Li, S., & Zhu, T. (2016). Identifying emotions from non-contact gaits information based on microsoft kinects. IEEE Transactions on Affective Computing, 9(4), 585-591. https://doi.org/10.1109/TAFFC.2016.2637343
Li, Q., Wang, Y., Sharf, A., Cao, Y., Tu, C., Chen, B., & Yu, S. (2018). Classification of gait anomalies from kinect. The Visual Computer, 34(2), 229-241. https://doi.org/10.1007/s00371-016-1330-0
Hy fellows,
High speed video movie camera and 3 software for video acquisition (180f/s), video processiNg using special technique for AMX radar and a displaing software to create and print the gait spectrum Analoc-E is a NON INVASIVE SYSTEM FOR HORSE LOCOMOTION ANALYSIS.
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