An emergency response system created to combat injuries during physical education training in a university using deep learning.

Purpose: The main goal of the physical education (PE) environment is that each individual trained should achieve self-fulfillment with the large group of students involved with their own efforts. Deep learning is applying transferrable knowledge in new situations to help the students master in tough...

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Published in:Electronic Library Vol. 39; no. 4; pp. 505 - 526
Main Authors: Leilei, Wang, Rajendiran, Sowmipriya, Gayathri, K.
Format: equations & formulas pictorial tables/charts Journal Article
Published: Emerald Publishing Limited 2021
Online Access:View this record in EBSCOhost
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      dt: 2021
      vid: 39
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      pub: Emerald Publishing Limited
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        10.1108/EL-07-2020-0175
        153418825
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        atl: An emergency response system created to combat injuries during physical education training in a university using deep learning.
      aug:
        au:
          Leilei, Wang
          Rajendiran, Sowmipriya
          Gayathri, K.
        affil: Huaihua University, Huaihua, China
      sug:
        subj:
          Deep Learning
          Colleges and Universities
          Physical Education and Training
          Wounds and Injuries Prevention and Control
          Deep Learning Utilization
          Emergency Medical Services
          Safety
          Human
          Global Positioning System
          Models, Theoretical
          Students, College
          Life Style
          Neural Networks (Computer)
          Psychological Well-Being
          Artificial Intelligence
          Liberal Arts Education
          Fractures
          Brain Concussion
      ab: Purpose: The main goal of the physical education (PE) environment is that each individual trained should achieve self-fulfillment with the large group of students involved with their own efforts. Deep learning is applying transferrable knowledge in new situations to help the students master in tough circumstances. In PE training, injuries occur when working together as a team. Safety measures are taken immediately as an emergency response to reduce the potential risk in students by providing first aid. To provide safety measures for the injured student immediately, the environment is monitored in real-time using a GPS. Design/methodology/approach: Theory of Humanities Education (ToHE) infers that it has less collection of theories and a wide range of applications than the state-of-the-art systems. ToHE allows students to think creatively and play a vital role in one's health which is a critical aspect in PE. The ToHE theory focuses on two main concepts, i.e. by using a methodological approach to analyse and deep learning to solve the problem. PE motivates college students to follow a healthy and active lifestyle. Findings: The proposed system is deployed in real time for monitoring the student's performance and provides an emergency response with an accuracy rate of 90%. Originality/value: The deep learning offers solutions to the injuries by using the deep convolutional neural network to provide interpretability of the consequence by training it with various injuries that occur in the playground and inappropriate use of sports equipment. A case study provided in this paper outlines an emergency response scenario to an injured student in sports training.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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