Computer Assisted Training (CAT) focused on sports is one of the fastest growing trends in technology, along with Cloud Computing and the appearance of various IoT devices. There are several mobile apps that attempt CAT by using ad-hoc sensors for acceleration and angular momentum recording. These are mostly paired via Bluetooth to a smartphone nearby. Boxing is one of the sports that is mostly lagging in terms of data collection and the continuous improvement loop. This paper proposes a cloud-based application to promote the use of technology for training in box named ABT, where hard data is difficult to obtain. To measure the boxer's movement, several sensors embedded in a mobile smartphone running Google Android was used. Then, the data was sent to a cloud service to perform calculations and determine different measurements of the action performed by the boxer. This data was also sent in real time via Bluetooth Low Energy to a paired tablet. ABT aims to help amateur and professional box fighters by having insights in each training session such as their average force, acceleration, and speed, therefore having a frame of reference to evaluate their progress against and by consequence helping the training of diverse boxing techniques to be more efficient. The application was reviewed and tested by a professional boxer and a group of 10 amateur fighters obtaining positive results for usability and utility for boxing.
|Title of host publication||2021 10th International Conference on Software and Information Engineering, ICSIE 2021|
|Publisher||Association for Computing Machinery|
|Number of pages||7|
|State||Published - 12 Nov 2021|
|Event||10th International Conference on Software and Information Engineering, ICSIE 2021 - Virtual, Online, Egypt|
Duration: 12 Nov 2021 → 14 Nov 2021
|Name||ACM International Conference Proceeding Series|
|Conference||10th International Conference on Software and Information Engineering, ICSIE 2021|
|Period||12/11/21 → 14/11/21|
Bibliographical noteFunding Information:
The authors would like to thank the Peruvian University of Applied Sciences (UPC) for the partial funding for this research.
© 2021 ACM.
- computer assisted training
- mobile applications