長者日常對話與認知執行功能關係探討：使用詞向量與迴歸模型

Discussion on the relationship between elders’daily conversations and cognitive executive function: using word vectors and regression models

隨著國人平均壽命攀升，老年人口的健康照護問題也更加多元，而且長期照護的需求也日漸增加，因此如何幫助高齡長者擁有良好生活品質與尊嚴之維持，是我們需要思考的。本研究欲藉由深度模型進一步探討正常老化者自然語言的特性。首先以焦點團體的方式收集資料，使長者在過程中自然地與其他參與者互動。接著透過詞向量模型與迴歸模型建立基於對話資料的EF預測模型，幫助了解EF的退化軌跡與建立預警。

As the average life expectancy of Chinese people rises, the health care problems of the elderly are becoming more diverse, and the demand for long-term care is also increasing. Therefore, how to help the elderly have a good quality of life and maintain their dignity is what we need to think about. This research intends to explore the characteristics of natural language of normal aging people through a deep model. First, we collect information through focus groups so that the elders can naturally interact with other participants in the process. Then, through the word vector model and regression model, an executive function prediction model based on dialogue data is established to help understand the degradation trajectory of executive function and establish an early warning.