Investigating applications of machine learning in observing, mapping, and modelling movements of vocal organs for applications within dental healthcar

研究机器学习在观察、绘制和建模发声器官运动方面的应用，以应用于牙科医疗保健中

• 批准号: 2689617
• 金额: --
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2689617
• 关键词: Investigating; applications; machine; learning; observing

Currently, the use of dental devices and prosthetics requires individuals to adjust their oral behaviour so that activities such as speech and eating feel as natural as possible. However, such adjustments often end up producing unnatural speech patterns and/or unusual oral movements leading to complications, like an irregular bite.With the growing interest in healthy ageing and good oral health, new approaches are needed that allow the effective development of customised dental devices and adhesive formulation that will require minimal adjustments, whilst achieving natural oral movement. The primary aim of this research is to develop technologies and approaches that will allow us to realise this goal. To achieve this, detailed models of the mouth and relevant facial/ oral structures will be developed, to help us understand the changes in speech and food processing that occur in a denture-wearing individual. Real time MRI (rtMRI) and Electromagnetic Articulography (EMA) are currently being used as the primary tools for such developments. However, such machinery is expensive, invasive, and labour-intensive; resources that are scarce in dental practices.This leads to two main research questions. Firstly, is it possible to 3D-model the movements of the tongue during speech and food-processing, by recording only the head and neck with a 360-degree camera? Secondly, how can this technology be applied in visualising the effect of dental prosthetics on one's oral motion?The research plans to employ Artificial Intelligence and computer vision in creating a system capable of quantifying these changes in speech and food processing, without the need of individual rtMRI and EMA recordings i.e., the possibility of recording the external face and being able to successfully predict the movements of the internal structures responsible for speech (tongue, teeth etc.). The results would then be used to identify common abnormalities occurring from denture use and allow for an appropriate solution. Owing to its multidisciplinary nature, the research would be of great interest to various academic domains. It will entail the development of computer vision tracking algorithms optimised to capture oral behaviour, with the use of a digital camera. These will provide the enhanced capability of capturing movements of the mouth.It also has significant real-world applications. In the dental field, this may result in a financially and technologically feasible system that can truly allow to produce personalised dental prosthetics, without the associated cost of having to undergo several expensive rtMRI and EMA scans. The technology is not limited to just the face, rather any biological structure that shares a similarity in its internal and external movement patterns could be modelled with such a technology, for example hip joints. It would be possible to diagnose such problems without the need of an MRI. This technology would not eliminate the need of an MRI in any serious scenario but will rather serve as an alternative or supplementary in situations where such scans are currently not feasible. This includes where MRI and EMA machines are not available due to financial and specialist staff requirements.

目前，牙科设备和假肢的使用要求个人调整他们的口腔行为，以便言语和饮食等活动感觉尽可能自然。然而，这种调整往往最终会产生不自然的语音模式和/或不寻常的口腔运动，导致并发症，如不规则的咬合。随着人们对健康老龄化和良好口腔健康的日益关注，需要新的方法来有效开发定制的牙科设备和粘合剂配方，这些设备和粘合剂配方需要最小的调整，同时实现自然的口腔运动。这项研究的主要目的是开发技术和方法，使我们能够实现这一目标。为了实现这一目标，将开发详细的口腔模型和相关的面部/口腔结构，以帮助我们了解戴假牙的个体在言语和食物加工方面的变化。真实的时间MRI（rtMRI）和电磁关节造影（EMA）目前被用作这种发展的主要工具。然而，这样的机械是昂贵的，侵入性的，劳动密集型的;资源是稀缺的牙科实践。这导致了两个主要的研究问题。首先，是否有可能通过360度摄像头只记录头部和颈部来对说话和食物加工过程中舌头的运动进行3D建模？第二，这项技术如何应用于可视化假牙对口腔运动的影响？该研究计划采用人工智能和计算机视觉来创建一个能够量化语音和食品加工中这些变化的系统，而不需要单独的rtMRI和EMA记录，即，记录外部面部的可能性，并能够成功地预测负责讲话的内部结构（舌头，牙齿等）的运动。结果将被用来确定常见的异常发生的义齿使用，并允许适当的解决方案。由于其多学科的性质，研究将是极大的兴趣，以各种学术领域。这将需要开发计算机视觉跟踪算法，优化以使用数码相机捕捉口腔行为。这将提供增强的捕捉嘴部运动的能力。它也有重要的现实世界的应用。在牙科领域，这可能会产生一个经济和技术上可行的系统，可以真正允许生产个性化的牙科修复体，而无需进行几次昂贵的rtMRI和EMA扫描的相关成本。该技术不仅限于面部，而且可以用这种技术模拟任何在其内部和外部运动模式中具有相似性的生物结构，例如髋关节。这将是可能的诊断这样的问题，而不需要一个MRI。这项技术不会在任何严重的情况下消除对MRI的需求，而是在目前这种扫描不可行的情况下作为替代或补充。这包括由于财务和专业人员要求而无法使用MRI和EMA机器的情况。