Abstract
Cricketers are dynamic players in the field and hence more vulnerable to injuries. The injury rate of Sri Lankan cricketers is very high, resulting in their careers being shortened. Therefore, we established a workload management system for cricketers to resolve this issue with wearable Inertial Measurement Unit (IMU) sensors mounted on their bodies. In order to mitigate their accidents, we evaluated kinds of the activities performed by an athlete using Convolutional Neural Network (CNN) and computed the workload parameters after the session. The expected results of our project were to develop a system to collect and analyze the critical workload parameters of cricketers and showcase results in a user-friendly manner.
| Original language | English (US) |
|---|---|
| Title of host publication | 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 7292-7295 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781728111797 |
| DOIs | |
| State | Published - 2021 |
| Externally published | Yes |
| Event | 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico Duration: Nov 1 2021 → Nov 5 2021 |
Publication series
| Name | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
|---|---|
| ISSN (Print) | 1557-170X |
Conference
| Conference | 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 |
|---|---|
| Country/Territory | Mexico |
| City | Virtual, Online |
| Period | 11/1/21 → 11/5/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
Keywords
- Convolutional Neural Network (CNN)
- Human Activity Recognition (HAR)
- Inertial Measurement Unit (IMU)