Narrative video scene description task discriminates between levels of cognitive impairment in Alzheimer’s disease.

Abstract

The process of interpreting and acting upon the visual environment requires both intact cognitive and visual systems. The narrative description (ND) task, initially developed to detect changes in ecologically relevant visual function in people with impaired vision, is an objective measure of the ability to perceive, understand, and describe a visual scene in a movie clip. Objective: Because the ND task draws heavily on semantic and working memory ability in addition to basic visual perception, we aimed to assess the discriminative performance of this task across levels of cognitive impairment. Method: We recruited 56 participants with cognitive status ranging from normal cognition to mild dementia (median age 82, range 66 to 99 years) to watch 20 30-s video clips and describe the visual content without time constraints. These verbal responses were transcribed and processed to generate ND shared word scores using a "wisdom of the crowd," natural-language processing approach. We compared ND scores across diagnostic groups, and used linear mixed models to examine decrements in task performance. Results: There was a stepwise decline of ND scores with increasing levels of cognitive impairment. Additional analyses showed that ND performance was highly related to performance on the Montreal Cognitive Assessment (MoCA) and domain-specific neuropsychological tests for semantic fluency and set shifting. Other models demonstrated differences in ND performance related video content between cognitively normal and impaired participants. Conclusion: The ND test was able to detect decrements in task performance between levels of cognitive impairment and was related to other global neuropsychological measures.

Emerging Technologies of Natural Language‐Enabled Chatbots: A Review and Trend Forecast Using Intelligent Ontology Extraction and Patent Analytics

“…NLP also has many applications in other fields. Taking the medical industry as an example, NLP technology detects signs of cognitive impairment by analyzing the conversations between the elderly and patients with Alzheimer [7]. In the banking industry, optical character recognition (OCR) and NLP technologies are used to automatically capture key document text and perform document content reviews to speed up the lending process [8].…”

The Impact of Field of View on Understanding of a Movie Is Reduced by Magnifying Around the Center of Interest

“…IA scores tended to decrease with increasing importance of nature (B = −0.09; 95% CI = −021 to 0.01; z = 1.86; P = 0.06) and tended to increase with increasing importance of man-made objects (B = 0.24; 95% CI = 0.04 to 0.43; z = 2.39; P = 0.02). In an in-person study, Reeves et al 34 found similar effects, with man-made object importance increasing, and nature importance decreasing IA scores. The other content-related factors (importance of faces, human figures, or auditory content, or the number of cuts per clip, or lighting level) were not significant ( P > 010) so they were removed from the model.…”

An implementation of Bubble Magnification did not improve the video comprehension of individuals with central vision loss

“…Previously, we have found that IA scores can vary with age, education, gender 4,29,31,32 and with MoCA score in a study of participants with Alzheimer's disease. 32 We accepted p ≤ 0.01 as statistically significant, and report terms with 0.10 ≥ p > 0.01 as trends.…”

“…We have used this method to demonstrate impaired video comprehension due to defocus blur, 31 CVL, 4 hemianopia 29 and Alzheimer's disease. 32 In the present study, we examined the effect of Bubble Magnification on gaze behaviour and video comprehension in individuals with CVL. We hypothesised that: (1) participants with CVL would look at the Bubble Magnification, and thus their gaze coherence (measured as normalized scanpath saliency, NSS 27 ) would improve and (2) Bubble Magnification would improve video comprehension (measured as IA score 31 ).…”