DOI: 10.5281/zenodo.8147434
title: Dataset for the assessment of presence and performance in an augmented reality environment for motor imitation learning: a case-study on violinists.

description: <strong>Data description</strong> Repository structure The repository contains several zip files, which contain a set of individual data files. We describe the general content of every zip file and supplement this information with a table describing the individual data files in the zip file. An overview of the different zip-files is given in Table 1. Zip-files in repository description Labeled_MoCap_Data.zip Labeled motion capture data Joint_Angle_Data.zip Joint angles extracted from mocap data Analyzed_Data.zip Filtered and analyzed mocap data Audio_Data.zip Audio data participants Questionnaire_Data.zip Questionnaire data Scores.zip Scores played by participants Avatar_Data.zip All data collected for the avatars Table 1: overview of different zip-files in repository. Csv format with labeled MoCap Data, including data labels. Every column is a data stream from a marker. Every marker has 3 data streams, referring to the x, y, and z coordinates of the marker position. In addition, the violin (3-4 markers) and the violin bow (3 markers) are labelled as well. An overview of the different labels and their meaning is given in Table 2. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (MoCap), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_MoCap.csv’ for a participant (see Table 2). File Name Labeled_MoCap_Data.zip Content Participant Trial Condition Piece Data Type P001_T1_2D_F2_MoCap.csv 1 1 2 2 Labeled MoCap Data P001_T2_2D_F2_MoCap.csv 1 2 2 2 P001_T3_2D_F2_MoCap.csv 1 3 2 2 P001_T4_2D_F2_MoCap.csv 1 4 2 2 P001_T1_3D_F1_MoCap.csv 1 1 3 1 P001_T2_3D_F1_MoCap.csv 1 2 3 1 P001_T3_3D_F1_MoCap.csv 1 3 3 1 P001_T4_3D_F1_MoCap.csv 1 4 3 1 P002_T1_2D_F1_MoCap.csv 2 1 2 1 P002_T2_2D_F1_MoCap.csv 2 2 2 1 P002_T3_2D_F1_MoCap.csv 2 3 2 1 P002_T4_2D_F1_MoCap.csv 2 4 2 1 P002_T1_3D_F2_MoCap.csv 2 1 3 2 P002_T2_3D_F2_MoCap.csv 2 2 3 2 P002_T3_3D_F2_MoCap.csv 2 3 3 2 P002_T4_3D_F2_MoCap.csv 2 4 3 2 P003_T1_2D_F3_MoCap.csv 3 1 2 3 P003_T2_2D_F3_MoCap.csv 3 2 2 3 P003_T3_2D_F3_MoCap.csv 3 3 2 3 P003_T4_2D_F3_MoCap.csv 3 4 2 3 P003_T1_3D_F4_MoCap.csv 3 1 3 4 P003_T2_3D_F4_MoCap.csv 3 2 3 4 P003_T3_3D_F4_MoCap.csv 3 3 3 4 P003_T4_3D_F4_MoCap.csv 3 4 3 4 P004_T1_2D_F1_MoCap.csv 4 1 2 1 P004_T2_2D_F1_MoCap.csv 4 2 2 1 P004_T3_2D_F1_MoCap.csv 4 3 2 1 P004_T4_2D_F1_MoCap.csv 4 4 2 1 P004_T1_3D_F2_MoCap.csv 4 1 3 2 P004_T2_3D_F2_MoCap.csv 4 2 3 2 P004_T3_3D_F2_MoCap.csv 4 3 3 2 P004_T4_3D_F2_MoCap.csv 4 4 3 2 P005_T1_2D_F3_MoCap.csv 5 1 2 3 P005_T2_2D_F3_MoCap.csv 5 2 2 3 P005_T3_2D_F3_MoCap.csv 5 3 2 3 P005_T4_2D_F3_MoCap.csv 5 4 2 3 P005_T1_3D_F4_MoCap.csv 5 1 3 4 P005_T2_3D_F4_MoCap.csv 5 2 3 4 P005_T3_3D_F4_MoCap.csv 5 3 3 4 P005_T4_3D_F4_MoCap.csv 5 4 3 4 P006_T1_2D_F1_MoCap.csv 6 1 2 1 P006_T2_2D_F1_MoCap.csv 6 2 2 1 P006_T3_2D_F1_MoCap.csv 6 3 2 1 P006_T4_2D_F1_MoCap.csv 6 4 2 1 P006_T1_3D_F2_MoCap.csv 6 1 3 2 P006_T2_3D_F2_MoCap.csv 6 2 3 2 P006_T3_3D_F2_MoCap.csv 6 3 3 2 P006_T4_3D_F2_MoCap.csv 6 4 3 2 P007_T1_2D_F4_MoCap.csv 7 1 2 4 P007_T2_2D_F4_MoCap.csv 7 2 2 4 P007_T3_2D_F4_MoCap.csv 7 3 2 4 P007_T4_2D_F4_MoCap.csv 7 4 2 4 P007_T1_3D_F3_MoCap.csv 7 1 3 3 P007_T2_3D_F3_MoCap.csv 7 2 3 3 P007_T3_3D_F3_MoCap.csv 7 3 3 3 P007_T4_3D_F3_MoCap.csv 7 4 3 3 P008_T1_2D_F4_MoCap.csv 8 1 2 4 P008_T2_2D_F4_MoCap.csv 8 2 2 4 P008_T3_2D_F4_MoCap.csv 8 3 2 4 P008_T4_2D_F4_MoCap.csv 8 4 2 4 P008_T1_3D_F3_MoCap.csv 8 1 3 3 P008_T2_3D_F3_MoCap.csv 8 2 3 3 P008_T3_3D_F3_MoCap.csv 8 3 3 3 P008_T4_3D_F3_MoCap.csv 8 4 3 3 P009_T1_2D_F1_MoCap.csv 9 1 2 1 P009_T2_2D_F1_MoCap.csv 9 2 2 1 P009_T3_2D_F1_MoCap.csv 9 3 2 1 P009_T4_2D_F1_MoCap.csv 9 4 2 1 P009_T1_3D_F2_MoCap.csv 9 1 3 2 P009_T2_3D_F2_MoCap.csv 9 2 3 2 P009_T3_3D_F2_MoCap.csv 9 3 3 2 P009_T4_3D_F2_MoCap.csv 9 4 3 2 P010_T1_2D_F2_MoCap.csv 10 1 2 2 P010_T2_2D_F2_MoCap.csv 10 2 2 2 P010_T3_2D_F2_MoCap.csv 10 3 2 2 P010_T4_2D_F2_MoCap.csv 10 4 2 2 P010_T1_3D_F1_MoCap.csv 10 1 3 1 P010_T2_3D_F1_MoCap.csv 10 2 3 1 P010_T3_3D_F1_MoCap.csv 10 3 3 1 P010_T4_3D_F1_MoCap.csv 10 4 3 1 P011_T1_2D_F4_MoCap.csv 11 1 2 4 P011_T2_2D_F4_MoCap.csv 11 2 2 4 P011_T3_2D_F4_MoCap.csv 11 3 2 4 P011_T4_2D_F4_MoCap.csv 11 4 2 4 P011_T1_3D_F3_MoCap.csv 11 1 3 3 P011_T2_3D_F3_MoCap.csv 11 2 3 3 P011_T3_3D_F3_MoCap.csv 11 3 3 3 P011_T4_3D_F3_MoCap.csv 11 4 3 3 Table 2: content and file structure of Labeled_MoCap_Data.zip. Csv format with joint angles, including data labels. Every column is a data stream from a joint. Every joint has a varying number of data streams, depending on the calculated angles. In addition to joint angles, the angles of the instrument relative to the body are given as well, the distances of the bow to the bridge, and to distances of the bow to the strings, respectively. An overview of the different labels and their meaning is given in Table 3. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (JointAngles), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_JointAngles.csv’ for a participant (see Table 3). File Name Joint_Angle_Data.zip Content Participant Trial Condition Piece Data Type P001_T1_2D_F2_JointAngles.csv 1 1
description: {"references": ["Adriaan Campo, Aleksandra Micha\u0142ko, Bavo Van Kerrebroeck, Boris Stajic, Maja Pokric, Marc Leman, The assessment of presence and performance in an AR environment for motor imitation learning: A case-study on violinists, Computers in Human Behavior, Volume 146, 2023, 107810, ISSN 0747-5632, https://doi.org/10.1016/j.chb.2023.107810.", "Adriaan Campo, Extracting joint angles from MoCap Data: a Matlab package, 2023 Apr 5, Available from: https://zenodo.org/record/7802255"]}