Validation of a Velostat-Based Pressure Sensitive Mat for Center of Pressure Measurements. Dataset.
This dataset presents the measurements corresponding to the article "Validation of a Velostat-Based Pressure Sensitive Mat for Center of Pressure Measurements". You will find the data corresponding to an affordable commercial mat, a Velostat-based mat prototype, and a commercial force platform. The results obtained in the above-mentioned article can be reproduced with them. In the article there is a set of experiments involving people standing on these platforms simultaneously and the center-of-pressure (CoP) path was analyzed by extracting standard deviation along the axes and mean radius.In this dataset you can find the CoP displacement obtained by the software of the force platform, which are along with the measurements extracted from the commercial mat software, the raw data of the Velostat-Based prototype, and the post-processed data from the Velostat-Based prototype. The scripts section also includes the code to extract the CoP from the mat pressure maps, the post-processing of the prototype pressure maps, the computation of the standard deviation along the axes and mean radius. Besides, it prints on the screen a table with the summary of this computation.
In the dataset, every user has a folder. In the folder of each user there are six subfolders with the name of the balance exercises, and in each subfolder there are several files: the file of the force platform (pasco.txt), the file of the commercial mat (.json) and the files of the prototype (raw: matVelo_file.txt, post-processed: .npy). The force platform files have two headers. The second header has the name of the columns including ‘Yc (cm)’ and ‘Xc (cm)’. The commercial mat files present a dictionary with the data of the 16x16 arrays ordered sequentially. Data can be accessed by means of a sequence of keys: ‘pressureData’, ‘n’, ‘pressureData’, ’i’, ‘j’ for n = 0,1, … and i,j contained in [0,15]. The prototype post-processing files contains the data as a numpy array (time,16,16). Finally, the prototype raw files contain the sequence of 16x16 array as a comma separated vector (256 numbers per row).If the folder of the code and the folder of the dataset are at the same level and the requirements has been installed, the code can be executed showing the summary table.