Abstract
In an attempt to gain more and more resources for dynamic assessment of movement, and especially more accessible ones, we tried to utilize open-source software like kinovea for data extraction and Python for automatization. By using these we can show the ease of creating patterns of investigation, after which further data is simply collected and manipulated on the system created. The best part about having these resources as means for biomechanical assessment is that they are cost free. We broke down the walking cycle into four main stages and extracted the data from those, after which we made it more comprehensible even for the trained naked eye. Video footage was taken from 10 healthy subjects. The hypothesis of this work was thus: If we modify the walking speed we can check out from low intensity to high intensity, we won’t see bigger amounts of deviation at ankle level. After analyzing the data collected, we couldn’t say that by increasing the walking we also increase the amount of deviation in the ankle Keywords: Assessment; Kinovea; open-source; Biomechanics; Python
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