Research Dataset Catalog and ShareScore Ratings | ScienceDex

zenodo40/100

Demonstrations for imitation learning for the paper "Fitting parameters of linear dynamical systems to regularize forcing terms in Dynamical Movement Primitives"

Demonstrations for the coathanger experiment in the paper "Fitting parameters of linear dynamical systems to regularize forcing terms in Dynamical Movement Primitives". https://elib.dlr.de/205110/

opencc-by-4.0Nov 2024View details →

zenodo40/100

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

Data description <ol> <li>Repository structure</li> </ol> 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.   <table> <tbody> <tr> <td> Zip-files in repository </td> <td> description </td> </tr> <tr> <td> Labeled_MoCap_Data.zip </td> <td> Labeled motion capture data </td> </tr> <tr> <td> Joint_Angle_Data.zip </td> <td> Joint angles extracted from mocap data </td> </tr> <tr> <td> Analyzed_Data.zip </td> <td> Filtered and analyzed mocap data </td> </tr> <tr> <td> Audio_Data.zip </td> <td> Audio data participants </td> </tr> <tr> <td> Questionnaire_Data.zip </td> <td> Questionnaire data </td> </tr> <tr> <td> Scores.zip </td> <td> Scores played by participants </td> </tr> <tr> <td> Avatar_Data.zip </td> <td> All data collected for the avatars </td> </tr> </tbody> </table>  Table 1: overview of different zip-files in repository.   <ol> <li> </li> </ol> 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).   <table> <tbody> <tr> <td> File Name </td> <td> Labeled_MoCap_Data.zip </td> </tr> <tr> <td> Content </td> <td> Participant </td> <td> Trial </td> <td> Condition </td> <td> Piece </td> <td> Data Type </td> </tr> <tr> <td> P001_T1_2D_F2_MoCap.csv </td> <td> 1 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> Labeled MoCap Data </td> </tr> <tr> <td> P001_T2_2D_F2_MoCap.csv </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T3_2D_F2_MoCap.csv </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T4_2D_F2_MoCap.csv </td> <td> 1 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T1_3D_F1_MoCap.csv </td> <td> 1 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T2_3D_F1_MoCap.csv </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T3_3D_F1_MoCap.csv </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T4_3D_F1_MoCap.csv </td> <td> 1 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_2D_F1_MoCap.csv </td> <td> 2 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T2_2D_F1_MoCap.csv </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T3_2D_F1_MoCap.csv </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T4_2D_F1_MoCap.csv </td> <td> 2 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_3D_F2_MoCap.csv </td> <td> 2 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T2_3D_F2_MoCap.csv </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T3_3D_F2_MoCap.csv </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T4_3D_F2_MoCap.csv </td> <td> 2 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P003_T1_2D_F3_MoCap.csv </td> <td> 3 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T2_2D_F3_MoCap.csv </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T3_2D_F3_MoCap.csv </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T4_2D_F3_MoCap.csv </td> <td> 3 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T1_3D_F4_MoCap.csv </td> <td> 3 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T2_3D_F4_MoCap.csv </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T3_3D_F4_MoCap.csv </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T4_3D_F4_MoCap.csv </td> <td> 3 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P004_T1_2D_F1_MoCap.csv </td> <td> 4 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T2_2D_F1_MoCap.csv </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T3_2D_F1_MoCap.csv </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T4_2D_F1_MoCap.csv </td> <td> 4 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T1_3D_F2_MoCap.csv </td> <td> 4 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T2_3D_F2_MoCap.csv </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T3_3D_F2_MoCap.csv </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T4_3D_F2_MoCap.csv </td> <td> 4 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P005_T1_2D_F3_MoCap.csv </td> <td> 5 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T2_2D_F3_MoCap.csv </td> <td> 5 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T3_2D_F3_MoCap.csv </td> <td> 5 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T4_2D_F3_MoCap.csv </td> <td> 5 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T1_3D_F4_MoCap.csv </td> <td> 5 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T2_3D_F4_MoCap.csv </td> <td> 5 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T3_3D_F4_MoCap.csv </td> <td> 5 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T4_3D_F4_MoCap.csv </td> <td> 5 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P006_T1_2D_F1_MoCap.csv </td> <td> 6 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T2_2D_F1_MoCap.csv </td> <td> 6 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T3_2D_F1_MoCap.csv </td> <td> 6 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T4_2D_F1_MoCap.csv </td> <td> 6 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T1_3D_F2_MoCap.csv </td> <td> 6 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T2_3D_F2_MoCap.csv </td> <td> 6 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T3_3D_F2_MoCap.csv </td> <td> 6 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T4_3D_F2_MoCap.csv </td> <td> 6 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P007_T1_2D_F4_MoCap.csv </td> <td> 7 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T2_2D_F4_MoCap.csv </td> <td> 7 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T3_2D_F4_MoCap.csv </td> <td> 7 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T4_2D_F4_MoCap.csv </td> <td> 7 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T1_3D_F3_MoCap.csv </td> <td> 7 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T2_3D_F3_MoCap.csv </td> <td> 7 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T3_3D_F3_MoCap.csv </td> <td> 7 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T4_3D_F3_MoCap.csv </td> <td> 7 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T1_2D_F4_MoCap.csv </td> <td> 8 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T2_2D_F4_MoCap.csv </td> <td> 8 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T3_2D_F4_MoCap.csv </td> <td> 8 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T4_2D_F4_MoCap.csv </td> <td> 8 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T1_3D_F3_MoCap.csv </td> <td> 8 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T2_3D_F3_MoCap.csv </td> <td> 8 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T3_3D_F3_MoCap.csv </td> <td> 8 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T4_3D_F3_MoCap.csv </td> <td> 8 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P009_T1_2D_F1_MoCap.csv </td> <td> 9 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T2_2D_F1_MoCap.csv </td> <td> 9 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T3_2D_F1_MoCap.csv </td> <td> 9 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T4_2D_F1_MoCap.csv </td> <td> 9 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T1_3D_F2_MoCap.csv </td> <td> 9 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T2_3D_F2_MoCap.csv </td> <td> 9 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T3_3D_F2_MoCap.csv </td> <td> 9 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T4_3D_F2_MoCap.csv </td> <td> 9 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_2D_F2_MoCap.csv </td> <td> 10 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T2_2D_F2_MoCap.csv </td> <td> 10 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T3_2D_F2_MoCap.csv </td> <td> 10 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T4_2D_F2_MoCap.csv </td> <td> 10 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_3D_F1_MoCap.csv </td> <td> 10 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T2_3D_F1_MoCap.csv </td> <td> 10 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T3_3D_F1_MoCap.csv </td> <td> 10 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T4_3D_F1_MoCap.csv </td> <td> 10 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P011_T1_2D_F4_MoCap.csv </td> <td> 11 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T2_2D_F4_MoCap.csv </td> <td> 11 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T3_2D_F4_MoCap.csv </td> <td> 11 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T4_2D_F4_MoCap.csv </td> <td> 11 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T1_3D_F3_MoCap.csv </td> <td> 11 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T2_3D_F3_MoCap.csv </td> <td> 11 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T3_3D_F3_MoCap.csv </td> <td> 11 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T4_3D_F3_MoCap.csv </td> <td> 11 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> </tbody> </table> Table 2: content and file structure of Labeled_MoCap_Data.zip.   <ol> <li> </li> </ol> 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).   <table> <tbody> <tr> <td> File Name </td> <td> Joint_Angle_Data.zip </td> </tr> <tr> <td> Content </td> <td> Participant </td> <td> Trial </td> <td> Condition </td> <td> Piece </td> <td> Data Type </td> </tr> <tr> <td> P001_T1_2D_F2_JointAngles.csv </td> <td> 1 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> Joint Angle Data </td> </tr> <tr> <td> P001_T2_2D_F2_JointAngles.csv </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T3_2D_F2_JointAngles.csv </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T4_2D_F2_JointAngles.csv </td> <td> 1 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T1_3D_F1_JointAngles.csv </td> <td> 1 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T2_3D_F1_JointAngles.csv </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T3_3D_F1_JointAngles.csv </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T4_3D_F1_JointAngles.csv </td> <td> 1 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_2D_F1_JointAngles.csv </td> <td> 2 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T2_2D_F1_JointAngles.csv </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T3_2D_F1_JointAngles.csv </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T4_2D_F1_JointAngles.csv </td> <td> 2 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_3D_F2_JointAngles.csv </td> <td> 2 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T2_3D_F2_JointAngles.csv </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T3_3D_F2_JointAngles.csv </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T4_3D_F2_JointAngles.csv </td> <td> 2 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P003_T1_2D_F3_JointAngles.csv </td> <td> 3 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T2_2D_F3_JointAngles.csv </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T3_2D_F3_JointAngles.csv </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T4_2D_F3_JointAngles.csv </td> <td> 3 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T1_3D_F4_JointAngles.csv </td> <td> 3 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T2_3D_F4_JointAngles.csv </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T3_3D_F4_JointAngles.csv </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T4_3D_F4_JointAngles.csv </td> <td> 3 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P004_T1_2D_F1_JointAngles.csv </td> <td> 4 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T2_2D_F1_JointAngles.csv </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T3_2D_F1_JointAngles.csv </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T4_2D_F1_JointAngles.csv </td> <td> 4 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T1_3D_F2_JointAngles.csv </td> <td> 4 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T2_3D_F2_JointAngles.csv </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T3_3D_F2_JointAngles.csv </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T4_3D_F2_JointAngles.csv </td> <td> 4 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P005_T1_2D_F3_JointAngles.csv </td> <td> 5 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T2_2D_F3_JointAngles.csv </td> <td> 5 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T3_2D_F3_JointAngles.csv </td> <td> 5 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T4_2D_F3_JointAngles.csv </td> <td> 5 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T1_3D_F4_JointAngles.csv </td> <td> 5 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T2_3D_F4_JointAngles.csv </td> <td> 5 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T3_3D_F4_JointAngles.csv </td> <td> 5 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T4_3D_F4_JointAngles.csv </td> <td> 5 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P006_T1_2D_F1_JointAngles.csv </td> <td> 6 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T2_2D_F1_JointAngles.csv </td> <td> 6 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T3_2D_F1_JointAngles.csv </td> <td> 6 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T4_2D_F1_JointAngles.csv </td> <td> 6 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T1_3D_F2_JointAngles.csv </td> <td> 6 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T2_3D_F2_JointAngles.csv </td> <td> 6 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T3_3D_F2_JointAngles.csv </td> <td> 6 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T4_3D_F2_JointAngles.csv </td> <td> 6 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P007_T1_2D_F4_JointAngles.csv </td> <td> 7 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T2_2D_F4_JointAngles.csv </td> <td> 7 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T3_2D_F4_JointAngles.csv </td> <td> 7 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T4_2D_F4_JointAngles.csv </td> <td> 7 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T1_3D_F3_JointAngles.csv </td> <td> 7 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T2_3D_F3_JointAngles.csv </td> <td> 7 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T3_3D_F3_JointAngles.csv </td> <td> 7 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T4_3D_F3_JointAngles.csv </td> <td> 7 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T1_2D_F4_JointAngles.csv </td> <td> 8 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T2_2D_F4_JointAngles.csv </td> <td> 8 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T3_2D_F4_JointAngles.csv </td> <td> 8 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T4_2D_F4_JointAngles.csv </td> <td> 8 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T1_3D_F3_JointAngles.csv </td> <td> 8 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T2_3D_F3_JointAngles.csv </td> <td> 8 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T3_3D_F3_JointAngles.csv </td> <td> 8 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T4_3D_F3_JointAngles.csv </td> <td> 8 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P009_T1_2D_F1_JointAngles.csv </td> <td> 9 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T2_2D_F1_JointAngles.csv </td> <td> 9 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T3_2D_F1_JointAngles.csv </td> <td> 9 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T4_2D_F1_JointAngles.csv </td> <td> 9 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T1_3D_F2_JointAngles.csv </td> <td> 9 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T2_3D_F2_JointAngles.csv </td> <td> 9 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T3_3D_F2_JointAngles.csv </td> <td> 9 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T4_3D_F2_JointAngles.csv </td> <td> 9 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_2D_F2_JointAngles.csv </td> <td> 10 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T2_2D_F2_JointAngles.csv </td> <td> 10 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T3_2D_F2_JointAngles.csv </td> <td> 10 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T4_2D_F2_JointAngles.csv </td> <td> 10 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_3D_F1_JointAngles.csv </td> <td> 10 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T2_3D_F1_JointAngles.csv </td> <td> 10 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T3_3D_F1_JointAngles.csv </td> <td> 10 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T4_3D_F1_JointAngles.csv </td> <td> 10 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P011_T1_2D_F4_JointAngles.csv </td> <td> 11 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T2_2D_F4_JointAngles.csv </td> <td> 11 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T3_2D_F4_JointAngles.csv </td> <td> 11 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T4_2D_F4_JointAngles.csv </td> <td> 11 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T1_3D_F3_JointAngles.csv </td> <td> 11 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T2_3D_F3_JointAngles.csv </td> <td> 11 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T3_3D_F3_JointAngles.csv </td> <td> 11 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T4_3D_F3_JointAngles.csv </td> <td> 11 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> </tbody> </table> Table 3: content and file structure of Joint_Angle_Data.zip.   <ol> <li> </li> </ol> Time series of filtered and analyzed data. The distances of the bow to the bridge and frog, are filtered so that only bow strokes with a certain bowing length and a certain loudness level are retained. The resulting collection of regions-of-interest (ROIs) is then analyzed for movement smoothness (as assessed with the SPARC index), and a comparison is made between the profile of avatar bowing movements and participant bowing movements by means of the Procrustes distance. These data are presented as csv files with 4 columns: SPARC index per ROI, Procrustes distance between the bow movement of the avatar and participant, index of start and end of each ROI. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (AnalyzedData), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_ AnalyzedData.csv’ for a participant (see Table 4).   <table> <tbody> <tr> <td> File Name </td> <td> Analyzed_Data.zip </td> </tr> <tr> <td> Content </td> <td> Participant </td> <td> Trial </td> <td> Condition </td> <td> Piece </td> <td> Data Type </td> </tr> <tr> <td> P001_T1_2D_F2_AnalyzedData.csv </td> <td> 1 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> Analyzed Data </td> </tr> <tr> <td> P001_T2_2D_F2_AnalyzedData.csv </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T3_2D_F2_AnalyzedData.csv </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T4_2D_F2_AnalyzedData.csv </td> <td> 1 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T1_3D_F1_AnalyzedData.csv </td> <td> 1 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T2_3D_F1_AnalyzedData.csv </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T3_3D_F1_AnalyzedData.csv </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T4_3D_F1_AnalyzedData.csv </td> <td> 1 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_2D_F1_AnalyzedData.csv </td> <td> 2 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T2_2D_F1_AnalyzedData.csv </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T3_2D_F1_AnalyzedData.csv </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T4_2D_F1_AnalyzedData.csv </td> <td> 2 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_3D_F2_AnalyzedData.csv </td> <td> 2 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T2_3D_F2_AnalyzedData.csv </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T3_3D_F2_AnalyzedData.csv </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T4_3D_F2_AnalyzedData.csv </td> <td> 2 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P003_T1_2D_F3_AnalyzedData.csv </td> <td> 3 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T2_2D_F3_AnalyzedData.csv </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T3_2D_F3_AnalyzedData.csv </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T4_2D_F3_AnalyzedData.csv </td> <td> 3 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T1_3D_F4_AnalyzedData.csv </td> <td> 3 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T2_3D_F4_AnalyzedData.csv </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T3_3D_F4_AnalyzedData.csv </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T4_3D_F4_AnalyzedData.csv </td> <td> 3 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P004_T1_2D_F1_AnalyzedData.csv </td> <td> 4 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T2_2D_F1_AnalyzedData.csv </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T3_2D_F1_AnalyzedData.csv </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T4_2D_F1_AnalyzedData.csv </td> <td> 4 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T1_3D_F2_AnalyzedData.csv </td> <td> 4 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T2_3D_F2_AnalyzedData.csv </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T3_3D_F2_AnalyzedData.csv </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T4_3D_F2_AnalyzedData.csv </td> <td> 4 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P005_T1_2D_F3_AnalyzedData.csv </td> <td> 5 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T2_2D_F3_AnalyzedData.csv </td> <td> 5 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T3_2D_F3_AnalyzedData.csv </td> <td> 5 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T4_2D_F3_AnalyzedData.csv </td> <td> 5 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T1_3D_F4_AnalyzedData.csv </td> <td> 5 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T2_3D_F4_AnalyzedData.csv </td> <td> 5 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T3_3D_F4_AnalyzedData.csv </td> <td> 5 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T4_3D_F4_AnalyzedData.csv </td> <td> 5 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P006_T1_2D_F1_AnalyzedData.csv </td> <td> 6 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T2_2D_F1_AnalyzedData.csv </td> <td> 6 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T3_2D_F1_AnalyzedData.csv </td> <td> 6 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T4_2D_F1_AnalyzedData.csv </td> <td> 6 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T1_3D_F2_AnalyzedData.csv </td> <td> 6 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T2_3D_F2_AnalyzedData.csv </td> <td> 6 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T3_3D_F2_AnalyzedData.csv </td> <td> 6 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T4_3D_F2_AnalyzedData.csv </td> <td> 6 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P007_T1_2D_F4_AnalyzedData.csv </td> <td> 7 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T2_2D_F4_AnalyzedData.csv </td> <td> 7 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T3_2D_F4_AnalyzedData.csv </td> <td> 7 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T4_2D_F4_AnalyzedData.csv </td> <td> 7 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T1_3D_F3_AnalyzedData.csv </td> <td> 7 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T2_3D_F3_AnalyzedData.csv </td> <td> 7 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T3_3D_F3_AnalyzedData.csv </td> <td> 7 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T4_3D_F3_AnalyzedData.csv </td> <td> 7 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T1_2D_F4_AnalyzedData.csv </td> <td> 8 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T2_2D_F4_AnalyzedData.csv </td> <td> 8 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T3_2D_F4_AnalyzedData.csv </td> <td> 8 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T4_2D_F4_AnalyzedData.csv </td> <td> 8 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T1_3D_F3_AnalyzedData.csv </td> <td> 8 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T2_3D_F3_AnalyzedData.csv </td> <td> 8 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T3_3D_F3_AnalyzedData.csv </td> <td> 8 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T4_3D_F3_AnalyzedData.csv </td> <td> 8 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P009_T1_2D_F1_AnalyzedData.csv </td> <td> 9 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T2_2D_F1_AnalyzedData.csv </td> <td> 9 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T3_2D_F1_AnalyzedData.csv </td> <td> 9 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T4_2D_F1_AnalyzedData.csv </td> <td> 9 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T1_3D_F2_AnalyzedData.csv </td> <td> 9 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T2_3D_F2_AnalyzedData.csv </td> <td> 9 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T3_3D_F2_AnalyzedData.csv </td> <td> 9 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T4_3D_F2_AnalyzedData.csv </td> <td> 9 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_2D_F2_AnalyzedData.csv </td> <td> 10 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T2_2D_F2_AnalyzedData.csv </td> <td> 10 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T3_2D_F2_AnalyzedData.csv </td> <td> 10 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T4_2D_F2_AnalyzedData.csv </td> <td> 10 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_3D_F1_AnalyzedData.csv </td> <td> 10 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T2_3D_F1_AnalyzedData.csv </td> <td> 10 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T3_3D_F1_AnalyzedData.csv </td> <td> 10 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T4_3D_F1_AnalyzedData.csv </td> <td> 10 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P011_T1_2D_F4_AnalyzedData.csv </td> <td> 11 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T2_2D_F4_AnalyzedData.csv </td> <td> 11 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T3_2D_F4_AnalyzedData.csv </td> <td> 11 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T4_2D_F4_AnalyzedData.csv </td> <td> 11 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T1_3D_F3_AnalyzedData.csv </td> <td> 11 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T2_3D_F3_AnalyzedData.csv </td> <td> 11 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T3_3D_F3_AnalyzedData.csv </td> <td> 11 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T4_3D_F3_AnalyzedData.csv </td> <td> 11 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> </tbody> </table> Table 4: content and file structure of Analyzed_Data.zip.   <ol> <li> </li> </ol> Wav-files are presented per participant (P001-P011), per trial (T1-T4), per condition (2D/3D). Audio files contain 2 tracks (left and right microphone), i.e., they are stereo recordings. Additionally, the data type (Audio), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_Audio.wav’ for a participant (see Table 5).   <table> <tbody> <tr> <td> File Name </td> <td> Audio_Data.zip </td> </tr> <tr> <td> Content </td> <td> Participant </td> <td> Trial </td> <td> Condition </td> <td> Piece </td> <td> Data Type </td> </tr> <tr> <td> P001_T1_2D_F2_Audio.csv </td> <td> 1 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> Audio Data </td> </tr> <tr> <td> P001_T2_2D_F2_Audio.csv </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T3_2D_F2_Audio.csv </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T4_2D_F2_Audio.csv </td> <td> 1 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T1_3D_F1_Audio.csv </td> <td> 1 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T2_3D_F1_Audio.csv </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T3_3D_F1_Audio.csv </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T4_3D_F1_Audio.csv </td> <td> 1 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_2D_F1_Audio.csv </td> <td> 2 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T2_2D_F1_Audio.csv </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T3_2D_F1_Audio.csv </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T4_2D_F1_Audio.csv </td> <td> 2 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_3D_F2_Audio.csv </td> <td> 2 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T2_3D_F2_Audio.csv </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T3_3D_F2_Audio.csv </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T4_3D_F2_Audio.csv </td> <td> 2 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P003_T1_2D_F3_Audio.csv </td> <td> 3 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T2_2D_F3_Audio.csv </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T3_2D_F3_Audio.csv </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T4_2D_F3_Audio.csv </td> <td> 3 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T1_3D_F4_Audio.csv </td> <td> 3 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T2_3D_F4_Audio.csv </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T3_3D_F4_Audio.csv </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T4_3D_F4_Audio.csv </td> <td> 3 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P004_T1_2D_F1_Audio.csv </td> <td> 4 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T2_2D_F1_Audio.csv </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T3_2D_F1_Audio.csv </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T4_2D_F1_Audio.csv </td> <td> 4 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T1_3D_F2_Audio.csv </td> <td> 4 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T2_3D_F2_Audio.csv </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T3_3D_F2_Audio.csv </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T4_3D_F2_Audio.csv </td> <td> 4 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P005_T1_2D_F3_Audio.csv </td> <td> 5 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T2_2D_F3_Audio.csv </td> <td> 5 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T3_2D_F3_Audio.csv </td> <td> 5 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T4_2D_F3_Audio.csv </td> <td> 5 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T1_3D_F4_Audio.csv </td> <td> 5 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T2_3D_F4_Audio.csv </td> <td> 5 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T3_3D_F4_Audio.csv </td> <td> 5 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T4_3D_F4_Audio.csv </td> <td> 5 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P006_T1_2D_F1_Audio.csv </td> <td> 6 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T2_2D_F1_Audio.csv </td> <td> 6 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T3_2D_F1_Audio.csv </td> <td> 6 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T4_2D_F1_Audio.csv </td> <td> 6 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T1_3D_F2_Audio.csv </td> <td> 6 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T2_3D_F2_Audio.csv </td> <td> 6 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T3_3D_F2_Audio.csv </td> <td> 6 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T4_3D_F2_Audio.csv </td> <td> 6 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P007_T1_2D_F4_Audio.csv </td> <td> 7 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T2_2D_F4_Audio.csv </td> <td> 7 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T3_2D_F4_Audio.csv </td> <td> 7 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T4_2D_F4_Audio.csv </td> <td> 7 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T1_3D_F3_Audio.csv </td> <td> 7 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T2_3D_F3_Audio.csv </td> <td> 7 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T3_3D_F3_Audio.csv </td> <td> 7 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T4_3D_F3_Audio.csv </td> <td> 7 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T1_2D_F4_Audio.csv </td> <td> 8 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T2_2D_F4_Audio.csv </td> <td> 8 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T3_2D_F4_Audio.csv </td> <td> 8 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T4_2D_F4_Audio.csv </td> <td> 8 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T1_3D_F3_Audio.csv </td> <td> 8 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T2_3D_F3_Audio.csv </td> <td> 8 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T3_3D_F3_Audio.csv </td> <td> 8 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T4_3D_F3_Audio.csv </td> <td> 8 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P009_T1_2D_F1_Audio.csv </td> <td> 9 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T2_2D_F1_Audio.csv </td> <td> 9 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T3_2D_F1_Audio.csv </td> <td> 9 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T4_2D_F1_Audio.csv </td> <td> 9 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T1_3D_F2_Audio.csv </td> <td> 9 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T2_3D_F2_Audio.csv </td> <td> 9 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T3_3D_F2_Audio.csv </td> <td> 9 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T4_3D_F2_Audio.csv </td> <td> 9 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_2D_F2_Audio.csv </td> <td> 10 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T2_2D_F2_Audio.csv </td> <td> 10 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T3_2D_F2_Audio.csv </td> <td> 10 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T4_2D_F2_Audio.csv </td> <td> 10 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_3D_F1_Audio.csv </td> <td> 10 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T2_3D_F1_Audio.csv </td> <td> 10 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T3_3D_F1_Audio.csv </td> <td> 10 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T4_3D_F1_Audio.csv </td> <td> 10 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P011_T1_2D_F4_Audio.csv </td> <td> 11 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T2_2D_F4_Audio.csv </td> <td> 11 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T3_2D_F4_Audio.csv </td> <td> 11 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T4_2D_F4_Audio.csv </td> <td> 11 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T1_3D_F3_Audio.csv </td> <td> 11 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T2_3D_F3_Audio.csv </td> <td> 11 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T3_3D_F3_Audio.csv </td> <td> 11 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T4_3D_F3_Audio.csv </td> <td> 11 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> </tbody> </table> Table 5: content and file structure of Audio_Data.zip.   <ol> <li> </li> </ol> The results of 5 standardized questionnaires are presented: the Makransky Multimodal Presence Questionnaire (the social presence subset or MPQS and the physical presence subset or MPQP), the Witmer Presence Questionnaire (WPQ), the Immersive Tendencies Questionnaire (ITQ), the Musical Sophistication Index (MSI), and the Sense of Musical Agency Questionnaire (SOMA). Additionally, demographic data (DQ) were collected, along with some open questions (OQ). The answers to the questionnaires are organized in 3 csv files: ‘MB.csv’, containing answers to the questionnaires presented before the first session (ITQ, MSI and some DQ); and ‘C1.csv’ and ‘C2.csv’, containing the answers to the questionnaires presented before and after each session (MPQS, MPQP, WPQ, SOMA, some DQ and some OQ) in the first and second condition, respectively. A csv file named ‘Legend.csv’ indicates the codes of all the questions, and where the answers to the questions can be found (see Table 6). Since some participants answered in Dutch, all responses were translated to English before adding them to the repository.   <table> <tbody> <tr> <td> File Name </td> <td> Questionnaire_Data.zip </td> </tr> <tr> <td> Content </td> </tr> <tr> <td> C1.csv </td> <td> questionnaires and answeres of condition 1 </td> </tr> <tr> <td> C2.csv </td> <td> questionnaires and answeres of condition 2 </td> </tr> <tr> <td> MB.csv </td> <td> questionnaires and answers related to musical background </td> </tr> <tr> <td> Legend.csv </td> <td> questions and question codes </td> </tr> </tbody> </table> Table 6: content and file structure of Questionnaire_Data.zip.   <ol> <li> </li> </ol> The scores which were played by both the avatar and the participants are provided, with the correct bowings and articulations. The fragment and the violin section are indicated in the filename. E.g., ‘First_Violin_F2.pdf’, contains the scores of fragment F2, as played by the first violins. See Table 7 for an overview of the file structure and the content.   <table> <tbody> <tr> <td> File Name </td> <td> Scores.zip </td> </tr> <tr> <td> Content </td> </tr> <tr> <td> First_Violin_F1.pdf </td> <td> Fragment F1 as played by the first violin section </td> </tr> <tr> <td> First_Violin_F2.pdf </td> <td> Fragment F2 as played by the first violin section </td> </tr> <tr> <td> Second_Violin_F3.pdf </td> <td> Fragment F3 as played by the second violin section </td> </tr> <tr> <td> Second_Violin_F4.pdf </td> <td> Fragment F4 as played by the second violin section </td> </tr> </tbody> </table> Table 7: content and file structure of Scores.zip.   <ol> <li> </li> </ol> This directory contains files in 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. One data file per avatar (First Violin or Second Violin) 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., ‘First_Violin_F2_MoCap.csv’ for an avatar (see Table 8). Additionally, the directory contains files in 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 the distances of the bow to the strings, respectively. One data file per avatar (First Violin or Second Violin) 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., ‘Second_Violin_F3_JointAngles.csv’ for an avatar (see Table 8). Finally, this directory contains wav-files per avatar (First Violin or Second Violin). Audio files contain 2 tracks (left and right microphone), i.e., they are stereo recordings. Additionally, the data type (Audio), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘First_Violin_F1_Audio.wav’ for an avatar (see Table 8).   <table> <tbody> <tr> <td> File Name </td> <td> Avatar_Data.zip </td> </tr> <tr> <td> Content </td> </tr> <tr> <td> First_Violin_F1_MoCap.csv </td> <td> MoCap data of the first violin avatar, playing fragment F1 </td> </tr> <tr> <td> First_Violin_F1_JointAngles.csv </td> <td> Joint angle data of the first violin avatar, playing fragment F1 </td> </tr> <tr> <td> First_Violin_F1_Audio.wav </td> <td> Audio data of the first violin avatar, playing fragment F1 </td> </tr> <tr> <td> First_Violin_F2_MoCap.csv </td> <td> MoCap data of the first violin avatar, playing fragment F2 </td> </tr> <tr> <td> First_Violin_F2_JointAngles.csv </td> <td> Joint angle data of the first violin avatar, playing fragment F2 </td> </tr> <tr> <td> First_Violin_F2_Audio.wav </td> <td> Audio data of the first violin avatar, playing fragment F2 </td> </tr> <tr> <td> Second_Violin_F3_MoCap.csv </td> <td> MoCap data of the second violin avatar, playing fragment F3 </td> </tr> <tr> <td> Second_Violin_F3_JointAngles.csv </td> <td> Joint angle data of the second violin avatar, playing fragment F3 </td> </tr> <tr> <td> Second_Violin_F3_Audio.wav </td> <td> Audio data of the second violin avatar, playing fragment F3 </td> </tr> <tr> <td> Second_Violin_F4_MoCap.csv </td> <td> MoCap data of the second violin avatar, playing fragment F4 </td> </tr> <tr> <td> Second_Violin_F4_JointAngles.csv </td> <td> Joint angle data of the second violin avatar, playing fragment F4 </td> </tr> <tr> <td> Second_Violin_F4_Audio.wav </td> <td> Audio data of the second violin avatar, playing fragment F4 </td> </tr> </tbody> </table> Table 8: content and file structure of Avatar_Data.zip.

opencc-by-4.0Jul 2023View details →

dryad36/100

Using machine learning to distinguish between authentic and imitation Jackson Pollock poured paintings: Art images

Jackson Pollock's abstract poured paintings are celebrated for their striking aesthetic qualities. They are also among the most financially valued and imitated artworks, making them vulnerable to high-profile controversies involving Pollock-like paintings of unknown origin. Given the increased employment of artificial intelligence applications across society, we investigate whether established machine learning techniques can be adopted by the art world to help detect imitation Pollocks. The low number of images compared to typical artificial intelligence projects presents a potential limitation for art-related applications. To address this limitation, we develop a machine learning strategy involving a novel image ingestion method which decomposes the images into sets of multi-scaled tiles. Leveraging the power of transfer learning, this approach distinguishes between authentic and imitation poured artworks with an accuracy of 98.9%. The machine also uses the multi-scaled tiles to generate novel visual aids and interpretational parameters which together facilitate comparisons between the machine's results and traditional investigations of Pollock's artistic style.

opencc-zeroJun 2024View details →

dryad36/100

Using machine learning to distinguish between authentic and imitation Jackson Pollock poured paintings: Art images

Open the record for dataset details and reuse information.

publicJul 2024View details →

dryad28/100

Data from: Trial-and-error copying of demonstrated actions reveals how fledglings learn to 'imitate' their mothers

Understanding how humans and other animals learn to perform an act from seeing it done has been a major challenge in the study of social learning. To determine whether this ability is based on 'true imitation', many studies have applied the two-action experimental paradigm, examining whether subjects learn to perform the specific action demonstrated to them. Here, we show that the insights gained from animals' success in two-action experiments may be limited, and that a better understanding is achieved by monitoring subjects' entire behavioural repertoire. Hand-reared house sparrows that followed a model of a mother demonstrator were successful in learning to find seeds hidden under a leaf, using the action demonstrated by the mother (either pushing the leaf or pecking it). However, they also produced behaviours that had not been demonstrated but were nevertheless related to the demonstrated act. This finding suggests that while the learners were clearly influenced by the demonstrator, they did not accurately imitate her. Rather, they used their own behavioural repertoire, gradually fitting it to the demonstrated task solution through trial and error. This process is consistent with recent views on how animals learn to imitate, and may contribute to a unified process-level analysis of social learning mechanisms.

opencc-zeroDec 2016View details →

zenodo28/100

Data: Imitation learning of fish and swarm behavior with Recurrent Neural Networks

Data for the Master's Thesis Imitation learning of fish and swarm behavior with Recurrent Neural Networks

opencc-by-4.0Sep 2019View details →

dryad28/100

Data from: Trial-and-error copying of demonstrated actions reveals how fledglings learn to ‘imitate’ their mothers

Open the record for dataset details and reuse information.

publicFeb 2017View details →

dryad28/100

Data from: Ability to modulate birdsong across social contexts develops without imitative social learning

Open the record for dataset details and reuse information.

publicFeb 2018View details →

Find research datasets worth reusing

Dataset results

Demonstrations for imitation learning for the paper "Fitting parameters of linear dynamical systems to regularize forcing terms in Dynamical Movement Primitives"

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

Using machine learning to distinguish between authentic and imitation Jackson Pollock poured paintings: Art images

Using machine learning to distinguish between authentic and imitation Jackson Pollock poured paintings: Art images

Data from: Trial-and-error copying of demonstrated actions reveals how fledglings learn to 'imitate' their mothers

Data: Imitation learning of fish and swarm behavior with Recurrent Neural Networks

Data from: Trial-and-error copying of demonstrated actions reveals how fledglings learn to ‘imitate’ their mothers

Data from: Ability to modulate birdsong across social contexts develops without imitative social learning

Understand access before you commit

Allen Brain Atlas

Annotated Behaviour and Observability Dataset (ABODe)

DANDI Archive for NWB datasets

International Brain Laboratory public data

OpenNeuro

Your academic CV and NIH biosketch