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Deep Learning and Procrustes Analysis for Early Dysgraphia Risk Detection with a Tablet Application - DATASET

<p>Data to support the findings reported in the journal paper</p> <p>Lomurno, E., Dui, L. G., Gatto, M., Bollettino, M., Matteucci, M., &amp; Ferrante, S. (2023). Deep Learning and Procrustes Analysis for Early Dysgraphia Risk Detection with a Tablet Application.&nbsp;<em>Life</em>,&nbsp;<em>13</em>(3), 598.</p> <ul> <li>Caratterizzazione_y3b_pulito.xls:&nbsp; <ul> <li>Subject ID</li> <li>Age at the beginning of the study</li> <li>Handedness</li> <li>Sex</li> </ul> </li> <li>Score_BVSCO_pulito.xls: <ul> <li>Subject ID</li> <li>columns B-D: graphemes in the three tests of the BVSCO-2</li> <li>columns E-G: z-score computed on normative data for&nbsp;the three tests of the BVSCO-2</li> <li>median z-score: computed on columns E-G</li> <li>at risk: if median z-score is under the -2 threshold (0=not at risk, 1=at risk)</li> </ul> </li> <li>executions.mat: a matrix for each time point (y1, y2a, y2b, y3a, y3b) and game (copa_q = copy square, copia_seq = copy sequence, tunnel_q = tunnel square, tunnel_ele = tunnel word). <ul> <li>first column of all the cell arrays: subject ID</li> <li>second column for the copy games: three sub-matrices with an execution for each level (spontaneous, big, small)</li> <li>columns 2:N for the tunnel games: an average execution for each index of difficulty</li> <li>for each execution, the columns of the sub-matrices are&nbsp;normalized time, normalized x, normalized y and pressure</li> </ul> </li> </ul> <p>&nbsp;</p> <p>Copy games</p> <ul> <li>A matrix for each game and each time point with a number of rows equal to the number of children and a number of columns equal to 2: <ul> <li>First column: array with school and child code</li> <li>Second column: executions</li> </ul> </li> <li>For the two copy games, the data has a dimension of 3 x 1, where 3 are the modalities (spontaneous, big, small) and 1 is the data matrix.</li> <li>By accessing the data matrix we have four variables, i.e., normalized time, normalized x, normalized y and pressure.</li> </ul> <p>&nbsp;</p> <p>Tunnel games</p> <ul> <li>A matrix for each game and each time point with a number of rows equal to the number of children and a number of columns equal to index of difficulty number +1: <ul> <li>First column: array with school and child code</li> <li>From the second column onwards: executions, each column corresponds to the &quot;typical&quot; execution (the average) of an ID (5 for square tunnel and 8 for ele tunnel). Sub-matrices contain the data matrix with its four variables. i.e., normalized time, normalized x, normalized y and pressure.</li> </ul> </li> </ul>