Multimodal Capture of Patient Behaviour for Improved Detection of Early Dementia: Clinical Feasibility and Preliminary Results
Multimodal Capture of Patient Behaviour for Improved Detection of Early Dementia: Clinical Feasibility and Preliminary Results
复制标题
多模式捕捉患者行为以改进早期痴呆的检测：临床可行性和初步结果
DOI：
10.3389/fcomp.2021.642633
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发表时间：
2021-04-19
影响因子：
2.6
通讯作者：
Beskow, Jonas
中科院分区：
文献类型：
--
作者：
Jonell, Patrik;Moell, Birger;Beskow, Jonas
阿尔茨海默病的非侵入性自动筛查有可能提高诊断准确性，同时降低医疗成本。先前的研究表明，说话、语言、凝视和绘画的模式可以帮助发现认知能力下降的早期迹象。在本文中，我们描述了一个高度多模式系统，用于在真实临床访谈中不显眼地捕获数据，作为阿尔茨海默病认知评估的一部分。该系统使用9种不同的传感器设备（智能手机、平板电脑、眼动仪、麦克风阵列和腕带）来记录专家与患者首次临床面谈时的互动数据，目前在瑞典斯德哥尔摩的卡罗林斯卡大学医院使用。此外，每位患者还可获得脑成像、心理测试、语言治疗师评估和临床元数据等形式的补充信息。我们详细介绍了我们的数据收集和分析过程，并根据迄今为止收集的25名患者的数据，提出了从多模式记录中提取的措施与临床评估和已建立的生物标志物相关的初步发现。我们的研究结果证明了我们提出的方法的可行性，并表明收集的数据可用于改善早期痴呆的临床评估。
Non-invasive automatic screening for Alzheimer's disease has the potential to improve diagnostic accuracy while lowering healthcare costs. Previous research has shown that patterns in speech, language, gaze, and drawing can help detect early signs of cognitive decline. In this paper, we describe a highly multimodal system for unobtrusively capturing data during real clinical interviews conducted as part of cognitive assessments for Alzheimer's disease. The system uses nine different sensor devices (smartphones, a tablet, an eye tracker, a microphone array, and a wristband) to record interaction data during a specialist's first clinical interview with a patient, and is currently in use at Karolinska University Hospital in Stockholm, Sweden. Furthermore, complementary information in the form of brain imaging, psychological tests, speech therapist assessment, and clinical meta-data is also available for each patient. We detail our data-collection and analysis procedure and present preliminary findings that relate measures extracted from the multimodal recordings to clinical assessments and established biomarkers, based on data from 25 patients gathered thus far. Our findings demonstrate feasibility for our proposed methodology and indicate that the collected data can be used to improve clinical assessments of early dementia.