Face-specific memory deficits and changes in eye scanning patterns among patients with amnestic mild cognitive impairment

Kawagoe, Toshikazu; Matsushita, Mitsunori; Hashimoto, Mamoru; Ikeda, Manabu; Sekiyama, Kaoru

doi:10.1038/s41598-017-14585-5

Cited by 22 publications

(36 citation statements)

References 49 publications

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“…the past 20 years. Crutcher et al, 2009;Lagun et al, 2011;Zola et al, 2013;Kawagoe et al, 2017;Granholm et al, 2015. Inhibitory control Hellmuth et al, 2012Alichniewicz et al, 2013.…”

Section: Table 1 -Overview Of Et-based Cognitive Studies In Neurodegementioning

confidence: 99%

Eye tracking – The overlooked method to measure cognition in neurodegeneration?

2019

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…the past 20 years. Crutcher et al, 2009;Lagun et al, 2011;Zola et al, 2013;Kawagoe et al, 2017;Granholm et al, 2015. Inhibitory control Hellmuth et al, 2012Alichniewicz et al, 2013.…”

Section: Table 1 -Overview Of Et-based Cognitive Studies In Neurodegementioning

confidence: 99%

Eye tracking – The overlooked method to measure cognition in neurodegeneration?

2019

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“…Generally, an infrared camera light source is used to detect the position of the subject’s pupils and determine the gaze points using some mathematical algorithms. The eye-tracking technology enables quantitative and objective assessment of eye movements in a non-invasive manner, which can be applied to neuroscience research to assess cognitive function or impairment, such as traumatic brain injury, autism spectrum disorder, and neurodegenerative diseases 13–27 .…”

Section: Introductionmentioning

confidence: 99%

Novel Method for Rapid Assessment of Cognitive Impairment Using High-Performance Eye-Tracking Technology

Oyama

Takeda

Ito

et al. 2019

Sci Rep

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A rapid increase in the number of patients with dementia has emerged as a global health challenge. Accumulating evidence suggests that early diagnosis and timely intervention can delay cognitive decline. The diagnosis of dementia is commonly performed using neuropsychological tests, such as the Mini-Mental State Examination (MMSE), administered by trained examiners. While these traditional neuropsychological tests are valid and reliable, they are neither simple nor sufficiently short as routine screening tools for dementia. Here, we developed a brief cognitive assessment utilizing an eye-tracking technology. The subject views a series of short (178 s) task movies and pictures displayed on a monitor while their gaze points are recorded by the eye-tracking device, and the cognitive scores are determined from the gaze plots data. The cognitive scores were measured by both an eye tracking-based assessment and neuropsychological tests in 80 participants, including 27 cognitively healthy controls (HC), 26 patients with mild cognitive impairment (MCI), and 27 patients with dementia. The eye tracking-based cognitive scores correlated well with the scores from the neuropsychological tests, and they showed a good diagnostic performance in detecting patients with MCI and dementia. Rapid cognitive assessment using eye-tracking technology can enable quantitative scoring and the sensitive detection of cognitive impairment.

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“…To prevent misreporting because of erroneous recognition, the accurate state is determined through the feedback UI response of the user after the abnormal state is recognized ( Figure 5 shows that user feedback check state)). Ordinary elderly people do not suffer severe memory decline, as in dementia or Alzheimer's disease but their ability to identify faces is deteriorated [32]. In particular, they have difficulty identifying people quickly.…”

Section: (A)mentioning

confidence: 99%

“…The elderly who often experience problems associated with long-term memory exhibit reduced ability to recognize faces [32]. In particular, they have difficulty identifying people quickly.…”

Section: (B) Smart Iot Intercommentioning

confidence: 99%

Deep-cARe: Projection-Based Home Care Augmented Reality System with Deep Learning for Elderly

Park

Lee

et al. 2019

Applied Sciences

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Developing innovative and pervasive smart technologies that provide medical support and improve the welfare of the elderly has become increasingly important as populations age. Elderly people frequently experience incidents of discomfort in their daily lives, including the deterioration of cognitive and memory abilities. To provide auxiliary functions and ensure the safety of the elderly in daily living situations, we propose a projection-based augmented reality (PAR) system equipped with a deep-learning module. In this study, we propose three-dimensional space reconstruction of a pervasive PAR space for the elderly. In addition, we propose the application of a deep-learning module to lay the foundation for contextual awareness. Performance experiments were conducted for grafting the deep-learning framework (pose estimation, face recognition, and object detection) onto the PAR technology through the proposed hardware for verification of execution possibility, real-time execution, and applicability. The precision of the face pose is particularly high by pose estimation; it is used to determine an abnormal user state. For face recognition results of whole class, the average detection rate (DR) was 74.84% and the precision was 78.72%. However, for face occlusions, the average DR was 46.83%. It was confirmed that the face recognition can be performed properly if the face occlusion situation is not frequent. By object detection experiment results, the DR increased as the distance from the system decreased for a small object. For a large object, the miss rate increased when the distance between the object and the system decreased. Scenarios for supporting the elderly, who experience degradation in movement and cognitive functions, were designed and realized, constructed using the proposed platform. In addition, several user interfaces (UI) were implemented according to the scenarios regardless of distance between users and the proposed system. In this study, we developed a bidirectional PAR system that provides the relevant information by understanding the user environment and action intentions instead of a unidirectional PAR system for simple information provision. We present a discussion of the possibility of care systems for the elderly through the fusion of PAR and deep-learning frameworks. Appl. Sci. 2019, 9, 3897 2 of 22 were usually attended to by their families; however, they are currently forced to lead independent lives [2]. There has been increasing interest in social welfare and medical support owing to the increasing aging rate. The social government is increasing social welfare and medical benefits to support elderly self-sustenance; however, most elderly people attend to various problems in their daily life on them own. Moreover, various diseases as well as physical and mental deterioration can occur with aging [3]. Muscle weakness is a representative example of physical deterioration. Muscle strength of people in their 60's decreases to approximately one half of that in their 20s, resulting in sign...

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Face-specific memory deficits and changes in eye scanning patterns among patients with amnestic mild cognitive impairment

Cited by 22 publications

References 49 publications

Eye tracking – The overlooked method to measure cognition in neurodegeneration?

Eye tracking – The overlooked method to measure cognition in neurodegeneration?

Novel Method for Rapid Assessment of Cognitive Impairment Using High-Performance Eye-Tracking Technology

Deep-cARe: Projection-Based Home Care Augmented Reality System with Deep Learning for Elderly

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