RiMoDe

Rhythm Dance Movement Detection - automatic assessment of dance skills using smartphone accelerometer

File description

xxx - Session ID

xxx_acc.csv - Accelerometer data: timestamp,x,y,z

SongsProfiles.csv - includes the song names, bpm of the song as per Madmon, beats detected by Madmon For some songs (Que Seja and No Escurinho), the beats detected are 1/2 of the beats perceived by a dancer, so the BPM values were multiplied by 2.

SessionsProfile.csv - sessions id, song name, expert1 annotation for the student being on the rhythm (yes/no), expert2, expert3, expert4, expert5, expert6

Citation

Please cite these papers in your publications if it helps your research

@inproceedings{dias2017let,
  title={Let's dance: how to build a user model for dance students using wearable technology},
  author={Dias Pereira dos Santos, Augusto and Yacef, Kalina and Martinez-Maldonado, Roberto},
  booktitle={Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization},
  pages={183--191},
  year={2017},
  organization={ACM}
}

@inproceedings{dias2018you,
  title={You Are Off The Beat!: Is Accelerometer Data Enough for Measuring Dance Rhythm?},
  author={Dias Pereira dos Santos, Augusto and Tang, Lie Ming and Loke, Lian and Martinez-Maldonado, Roberto},
  booktitle={Proceedings of the 5th International Conference on Movement and Computing},
  pages={12},
  year={2018},
  organization={ACM}
}