{
  "abstract": "Background Head-on-head impacts are a risk factor for concussion, which is a concern for sports. Computer vision frameworks may provide an automated process to identify head-on-head impacts, although this has not been applied or evaluated in rugby.Methods This study developed and evaluated a novel computer vision framework to automatically classify head-on-head and non-head-on-head impacts. Tackle events from professional rugby league matches were coded as either head-on-head or non-head-on-head impacts. These included non-televised standard-definition and televised high-definition video clips to train (n=341) and test (n=670) the framework. A computer vision framework consisting of two deep learning networks, an object detection algorithm and three-dimensional Convolutional Neural Networks, was employed and compared with the analyst-coded criterion. Sensitivity, specificity and positive predictive value were reported.Results The overall performance evaluation of the framework to classify head-on-head impacts against manual coding had a sensitivity, specificity and positive predictive value (95% CIs) of 68% (58% to 78%), 84% (78% to 88%) and 0.61 (0.54 to 0.69) in standard-definition clips, and 65% (55% to 75%), 84% (79% to 89%) and 0.61 (0.53 to 0.68) in high-definition clips.Conclusion The study introduces a novel computer vision framework for head-on-head impact detection. Governing bodies may also use the framework in real time, or for retrospective analysis of historical videos, to establish head-on-head rates and evaluate prevention strategies. Future work should explore the application of the framework to other head-contact mechanisms and also the utility in real time to identify potential events for clinical assessment.",
  "authors": [
    {
      "affiliations": [
        "Carnegie Applied Rugby Research (CARR) centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK"
      ],
      "name": "Manish Mohan"
    },
    {
      "affiliations": [
        "Carnegie Applied Rugby Research (CARR) centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK",
        "The University of Newcastle, Callaghan, New South Wales, Australia",
        "Edge Hill University, Ormskirk, UK"
      ],
      "name": "Dan Weaving"
    },
    {
      "affiliations": [
        "Carnegie Applied Rugby Research (CARR) centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK",
        "Sydney School of Health Sciences, The University of Sydney, Camperdown, New South Wales, Australia"
      ],
      "name": "Andrew J Gardner"
    },
    {
      "affiliations": [
        "Carnegie Applied Rugby Research (CARR) centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK",
        "Division of Physiological Sciences, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Sharief Hendricks"
    },
    {
      "affiliations": [
        "Centre for Health and Injury and Illness Prevention in Sport, University of Bath, Bath, UK",
        "Rugby Football Union, Twickenhamn, UK",
        "UK Collaborating Centre on Injury and Illness Prevention in Sport (UKCCIIS), University of Bath, Bath, UK"
      ],
      "name": "Keith A Stokes"
    },
    {
      "affiliations": [
        "Carnegie Applied Rugby Research (CARR) centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK",
        "England Performance Unit, Rugby Football League, Manchester, UK",
        "Uno-X Mobility Pro Cyclining Team, Oslo, Norway"
      ],
      "name": "Gemma Phillips"
    },
    {
      "affiliations": [
        "Carnegie Applied Rugby Research (CARR) centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK",
        "Premiership Rugby, London, UK"
      ],
      "name": "Matt Cross"
    },
    {
      "affiliations": [
        "Carnegie Applied Rugby Research (CARR) centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK",
        "England Performance Unit, Rugby Football League, Manchester, UK"
      ],
      "name": "Cameron Owen"
    },
    {
      "affiliations": [
        "Carnegie Applied Rugby Research (CARR) centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK",
        "Division of Physiological Sciences, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa",
        "England Performance Unit, Rugby Football League, Manchester, UK",
        "Premiership Rugby, London, UK",
        "School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Brisbane, Queensland, Australia"
      ],
      "name": "Ben Jones"
    }
  ],
  "title": "Can a novel computer vision-based framework detect head-on-head impacts during a rugby league tackle?",
  "uid": "0210c650-1206-5ef5-a5bc-b770c6029277"
}