Emotion expressions and cognitive impairments in the elderly: review of the contactless detection approach

IF 3.2 Q1 HEALTH CARE SCIENCES & SERVICES
Di Jiang, Luowei Yan, Florence Mayrand
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Abstract

The aging population in Canada has been increasing continuously throughout the past decades. Amongst this demographic, around 11% suffer from some form of cognitive decline. While diagnosis through traditional means (i.e., Magnetic Resonance Imagings (MRIs), positron emission tomography (PET) scans, cognitive assessments, etc.) has been successful at detecting this decline, there remains unexplored measures of cognitive health that could reduce stress and cost for the elderly population, including approaches for early detection and preventive methods. Such efforts could additionally contribute to reducing the pressure and stress on the Canadian healthcare system, as well as improve the quality of life of the elderly population. Previous evidence has demonstrated emotional facial expressions being altered in individuals with various cognitive conditions such as dementias, mild cognitive impairment, and geriatric depression. This review highlights the commonalities among these cognitive health conditions, and research behind the contactless assessment methods to monitor the health and cognitive well-being of the elderly population through emotion expression. The contactless detection approach covered by this review includes automated facial expression analysis (AFEA), electroencephalogram (EEG) technologies and heart rate variability (HRV). In conclusion, a discussion of the potentials of the existing technologies and future direction of a novel assessment design through fusion of AFEA, EEG and HRV measures to increase detection of cognitive decline in a contactless and remote manner will be presented.
老年人的情绪表达和认知障碍:非接触式检测方法综述
过去几十年来,加拿大老龄人口持续增长。在这些人口中,约有 11% 的人患有某种形式的认知功能衰退。虽然通过传统手段(如磁共振成像(MRI)、正电子发射断层扫描(PET)、认知评估等)进行诊断已成功地检测出这种衰退,但仍有一些尚未探索的认知健康措施,包括早期检测和预防方法,可以减少老年人口的压力和成本。这些努力还有助于减轻加拿大医疗保健系统的压力和负担,并提高老年人的生活质量。以往的证据表明,患有痴呆症、轻度认知障碍和老年抑郁症等各种认知症的人的情绪面部表情会发生改变。本综述强调了这些认知健康状况的共性,以及通过情绪表达监测老年人群健康和认知福祉的非接触式评估方法背后的研究。本综述涵盖的非接触式检测方法包括自动面部表情分析 (AFEA)、脑电图 (EEG) 技术和心率变异性 (HRV)。最后,将讨论现有技术的潜力,以及通过融合 AFEA、EEG 和 HRV 测量来提高非接触式远程认知衰退检测的新型评估设计的未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.20
自引率
0.00%
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0
审稿时长
13 weeks
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