Workload Management System for Cricketers

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 Mea...

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Bibliographic Details
Published in:	2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) Vol. 2021; pp. 7292 - 7295
Main Authors:	Ekanayaka, E. M. S. B., Gunawardhana, A. A. S., Mihirani, M. B., Silva, P., Prins, N. W.
Format:	Conference Proceeding Journal Article
Language:	English
Published:	United States IEEE 01-11-2021
Subjects:	Activity recognition Athletes Athletic Injuries Biology Convolutional Neural Network (CNN) Convolutional neural networks Engineering profession Human Activity Recognition (HAR) Humans Inertial Measurement Unit (IMU) Injuries Measurement units Neural networks Workload
Online Access:	Get full text
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Summary:	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.
ISSN:	2694-0604
DOI:	10.1109/EMBC46164.2021.9631106