Wearlab Beach Volleyball Serves and Games
A dataset of beach volleyball serves movements annotated in 4 types (i.e. long float, long top spin, short float, short top spin) and free games. The dataset comprises the data of 10 users in 4 sessions, recorded using 4 inertial sensors per user.
The dataset comprises data from 10 users in 4 sessions of 4 players each (2 players were present in two sessions). The data were recorded using 4 BlueSense  inertial platforms per user. The sensors were placed on the torso, and on each segment of the dominant arm (i.e. upper arm, lower arm and hand).
The players were asked to perform 12 repetition of 4 type of serves, i.e. long float, long top spin, short float and short top spin. After the completion of the 48 serves (12 serves x 4 types), the players were asked to play freely in 2-vs-2 games, following the standard beach volleyball rules.
The dataset include one file per user per session. In the file, the data are formatted in single .txt files for every user. - Each file contains 54 columns:
- 1 timestamp in milliseconds
- 13 x 4 body position (torso, upper_arm, lower_arm, hand):
- 9 for sensor data
- 3 x accelerometer
- 3 x gyroscope
- 3 x magnetometer
- 4 for quaternion format of orientation data (w, x, y, z)
- 1 for the activity label ID:
- 1001 Long float serve
- 1002 Long top spin serve
- 1003 Short float serve
- 1004 Short top spin serve
 Daniel Roggen, Arash Pouryazdan, and Mathias Ciliberto. 2017. BlueSense: designing an extensible platform for wearable motion sensing, sensor research and IoT applications. In Proceedings of the 2018 International Conference on Embedded Wireless Systems and Networks. ACM.
Use of this dataset in publications must be acknowledged by referencing the following publication:
Mathias Ciliberto, Luis Ponce Cuspinera, and Daniel Roggen. 2021. Collecting a dataset of gestures for skill assessment in the field: a beach volleyball serves case study. In Proceedings of the ACM International Joint Conference and International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, 2021.