Smart Mouthguard: Bio-analytics for the development of a respiratory sensing device

运动过程中的损伤通常是由体力消耗引起的系统衰竭引起的。呼吸参数可以用来测量感知运动的变化，使运动员能够监测和检查他们是如何训练或比赛的。一种智能护齿器正在开发中，它结合了一种新的呼吸技术来评估和跟踪表现。它测量呼吸，可以使用基于模型的分析来评估身体疲劳。这些指标将帮助接触运动运动员了解他们的表现，并在不需要佩戴任何额外装备的情况下帮助他们制定个性化的训练方案。它还可以用来对运动员在训练或比赛中面临的潜在伤害风险做出决定。这一点尤其重要，因为越来越多的体育联合会要求所有参与者都必须使用护齿器，同时旨在减少由于接触性运动参与而导致的总体受伤率。随着世界各地体育运动的参与不断增加，对护齿器的需求将继续攀升。据估计，仅在美国，每年就有超过4000万个护齿器售出。这一数字预计将随着接触性运动运动员的增加而成比例增长。由于接触性体育运动包括世界上发展最快的一些体育项目，因此在接触性体育社区内，强烈需要证明这些运动可以安全地进行。准确的呼吸分析是必要的，以便对身体疲劳提供良好的估计。呼吸信号是嘈杂的，人与人之间差异很大。呼吸信号的计算模型减少了这种噪音，并允许更好地估计体力消耗。拥有生物分析专业知识的牛津大学将与Chiaro公司合作，开发一种使用智能护齿器跟踪疲劳的强大方法。该计划将包括分享有关最佳分析建模技术和硬件设计的知识，以开发用户友好的智能护齿器。开发的分析模型使用实验室数据进行测试，并在将其应用于现场测试之前对模型进行修改。该项目展示了在BBSRC资助的其他项目中开发的某些分析技术如何成功地转化为其他行业。

Injuries during sports participation are often caused by systemic failure due to physical exertion. Breathing parameters can be used to measure changes in perceived exertion allowing the athlete to monitor and check how they train or play the game. A smart mouthguard is being developed that incorporates a novel breathing technology to assess and track performance. It measures breathing, which can be analysed using model based analytics to estimate physical fatigue. The metrics will aid contact sport athletes in understanding their performance and assist in personalising their training regime without the requirement to wear any additional gear. It can also be used to make decisions regarding the potential injury risk athletes face during training or competition. This is particular relevant as more sport federations are making mouthguard use compulsory for all participants, while at the same time aiming to reduce overall injurie rates due to contact sport participation.As athletic participation continues to increase around the world, the need for mouthguards will continue to climb. It has been estimated that over 40 million mouthguards are sold annually in the US alone. This number is expected to grow proportional with the increase of contact sport athletes. There is a strong need within the contact sports community to show that these sports can be played safely, as contact sports include some of the fastest growing sports in the world.Accurate breathing analysis is required in order to provide good estimates of physical fatigue. The breathing signal is noisy and can vary widely between people. A computational model of the breathing signal reduces this noise and allows for better estimates of physical exertion. The University of Oxford with its expertise in bio-analytics will work together with Chiaro Ltd to develop a robust approach for tracking fatigue using a smart mouthguard. The project will consist of sharing knowledge on the best analytical modelling techniques and hardware designs to develop a user friendly smart mouthguard. The developed analytical model is tested using lab-based data and model modifications are made before applying it to field testing. The project shows how certain analytical techniques developed within other BBSRC's funded projects can successfully be translated to other industries.