MODEM - Monitoring Of Dementia using Eye Movements

越来越多的证据表明，跳眼和眼球平滑运动的缺陷是痴呆症的特征。这些缺陷可以在实验室或临床环境中使用专门的眼球追踪设备检测到，但这对患者来说不方便，对NHS来说成本高昂，而且由于诊所就诊不可避免地是间歇性的，因此会带来抽样偏差的风险。“眼动监测痴呆”（MODEM）项目旨在以低成本和最少不便的方式纵向收集数据，为痴呆症的预后和诊断提供一个新的平台。我们建议通过家庭眼动追踪和嵌入患者日常活动的眼动计算分析来解决疾病进展监测问题。这是一种全新的方法，因此风险很高。然而，它有可能带来重大突破，原因有三：(i)眼球运动和认知健康密切相关，包括痴呆症诊断标志物的初步证据。（ii）眼动仪正处于从实验室仪器向广泛部署的传感器逐步转变的边缘，采用眼动仪进行非接触式健康监测正成为一个现实的命题。（iii）人们/患者在日常生活中使用他们的眼睛，这些日常生活具有视觉吸引力，并且提供了丰富的背景，可以收集有关他们的眼球运动如何随时间变化的信息，作为疾病进展的功能。我们的愿景是，患者不必去诊所或实验室，而是在技术环境和人们行为放松自然的环境中收集眼动数据。目标设置是人们自己的家和护理院。眼动仪可以策略性地放置以观察日常工作中的眼球运动。例如，他们可以用来跟踪手眼协调在日常任务中，如泡茶，以寻找可能的变化迹象；这些可能在日常生活受到更明显影响之前就预示着认知能力的下降。眼动仪也可以交互式部署。人们在日常生活中花费大量的时间作为视觉媒体的消费者，特别是通过电视，它提供了眼球运动的互动刺激。例如，内容（如电视节目）可以被设计成引起对诊断感兴趣的行为。人们还可以为互动提供主动凝视控制，例如作为电视遥控器功能的替代品。使用凝视控制刺激特定的眼球运动，可以用于测试。虽然超出了项目范围，但这也可能导致该技术的治疗应用。此外，由于眼动仪基于摄像头和计算机视觉，这为与其他基于视觉的方法（如面部表情分析）集成开辟了道路，用于多模态认知健康分析。

There is mounting evidence that deficits in saccadic and smooth pursuit eye movements are characteristic of dementia. These deficits can be detected in a lab or clinical setting using specialised eye-tracking equipment but this is inconvenient for the patient, costly for the NHS and introduces the risk of sampling bias because clinic visits are inevitably intermittent. The aim of the Monitoring Of Dementia using Eye Movements (MODEM) project is to enable the longitudinal collection of data at low cost and with minimal inconvenience, to provide a novel platform for prognosis and diagnosis of dementia. We propose to tackle monitoring of disease progression with in-home eye tracking and computational analysis of eye movement embedded with patients' everyday activity. This is an entirely novel approach, and hence high risk. However, it has the potential to lead to major breakthroughs, for three reasons: (i) Eye movement and cognitive health are closely linked, including initial evidence of markers for dementia diagnosis. (ii) Eye trackers are on the verge of a step change from lab instrument to widely deployed sensor, and their adoption for contact-less health monitoring is becoming a realistic proposition. (iii) People/patients use their eyes in daily routines that are visually engaging, and that present rich contexts for collection of information about how their eye movement changes over time, as a function of disease progression.Our vision is that rather than patients having to attend a clinic or laboratory, eye movement data can be collected in settings where the technology is ambient and peoples' behaviour is relaxed and natural. The target settings are peoples' own homes and care homes. Eye trackers can be placed strategically to observe eye movement in the context of everyday tasks. For example they can be used to track hand-eye coordination in routine tasks such as tea-making for possible signs of change; these might signal cognitive decline long before routines become more obviously affected. Eye trackers can also be deployed interactively. People spend significant amounts of their daily lives as consumers of visual media, especially through TV, which affords interactive stimulation of eye movement. For example, content (e.g. TV programmes) can be designed to elicit behaviours of interest for diagnosis. People can also be provided with active gaze controls for interaction, for instance as alternative to remote control functions of a TV. Use of gaze for control stimulates specific eye movements which can be used for testing. Though beyond the scope project, this could also lead to therapeutic application of the technology. Moreover, as eye trackers are based on cameras and computer vision, this opens up avenues for integration with other vision-based approaches such as analysis of facial expressions, for multimodal cognitive health analysis.