MODEM - Monitoring Of Dementia using Eye Movements

越来越多的证据表明，眼跳和顺畅追逐眼球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跟踪设备检测到，但这对患者来说不方便，对NHS来说代价高昂，并引入了抽样偏差的风险，因为诊所的就诊不可避免地是间歇性的。使用眼动监测痴呆症(MODEM)项目的目的是以低成本和最小的不便实现数据的纵向收集，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球跟踪和嵌入患者日常活动的眼球运动计算分析来解决疾病进展的监测问题。这是一种全新的方法，因此风险很高。然而，它有可能导致重大突破，原因有三：(I)眼动和认知健康密切相关，包括痴呆症诊断标记物的初步证据。(Ii)眼球追踪器即将从实验室仪器转变为广泛部署的传感器，采用它们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，这些日常活动在视觉上很吸引人，并且提供了丰富的背景，用于收集关于他们的眼动如何随着疾病的进展而随时间变化的信息。我们的愿景是，可以在技术处于环境中、人们的行为放松和自然的环境中收集眼动数据，而不是患者必须去诊所或实验室。目标设置是人们自己的家和疗养院。眼球追踪器可以有策略地放置，以观察日常任务中的眼球运动。例如，它们可以用来跟踪日常工作中的手眼协调，比如泡茶，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很久就发出了认知衰退的信号。眼球追踪器也可以交互部署。作为视觉媒体的消费者，人们在日常生活中花费了大量的时间，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)可以被设计成引起诊断的感兴趣的行为。还可以为人们提供用于交互的主动凝视控制，例如作为电视遥控器功能的替代。使用凝视进行控制可以刺激特定的眼球运动，这可以用于测试。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，由于眼睛跟踪器基于摄像头和计算机视觉，这为与其他基于视觉的方法集成开辟了道路，例如面部表情分析，用于多模式认知健康分析。

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.