Validation Research on the Application of Depth-wise Separable Convolutional AI Facial Expression Recognition in Non-pharmacological Treatment of BPSD
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Keywords

Depth-wise separable convolution
Emotion
BPSD
Dementia
Nursing

DOI

10.26689/jcnr.v5i4.2325

Abstract

One of the most obvious clinical reasons of dementia or The Behavioral and Psychological Symptoms of Dementia (BPSD) are the lack of emotional expression, the increased frequency of negative emotions, and the impermanence of emotions. Observing the reduction of BPSD in dementia through emotions can be considered effective and widely used in the field of non-pharmacological therapy. At present, this article will verify whether the image recognition artificial intelligence (AI) system can correctly reflect the emotional performance of the elderly with dementia through a questionnaire survey of three professional elderly nursing staff. The ANOVA (sig.=0.50) is used to determine that the judgment given by the nursing staff has no obvious deviation, and then Kendall’s test (0.722**) and spearman’s test (0.863**) are used to verify the judgment severity of the emotion recognition system and the nursing staff unanimously. This implies the usability of the tool. Additionally, it can be expected to be further applied in the research related to BPSD elderly emotion detection.

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