透過短時生理訊號分析進行決策表現評估

Abstract

在神經科學、生理心理學以及傳播科技的領域中，情緒透過對人類生理狀態的調節，能夠影響並反應在決策、學習及記憶功能。近年來更隨著儀器與實驗架構的發展，情緒及其對於決策的影響已逐漸明朗。 本研究採用Iowa Gambling Task之實驗架構，藉由透過類神經網路分析心律變異度以了解不同情緒狀態下決策的品質的變化。結果發現人類在心跳速率驟降時，當下決策的品質較佳(p < 0.001)。 此外，在實驗中受過適當訓練之類神經網路透過心律變異度進行受試者個別決策之預測之結果亦達到平均65%以上的準確度 (遠超過純猜測之50%達統計顯著之水準)。在數據分析部分，更利用統計方法進一步檢驗決策前六秒內PQRST波相關之心律變異指標在不同決策下的差異，找出相對重要的參考指標。 相關結果說明了決策與當下生理狀態間存在某種關聯性，更為未來相關研究初步量化檢驗了「透過短時生理訊號進行決策表現分析」的可能性；這樣的結果將可能引發基於人類情緒狀態之相關決策支援技術的發展。

Researchers in the area of neural science, psychophysiology, communication and management technology believe that emotion plays an important role in decision making, learning and memory. In recent years, due to the development of instrument and experimental paradigm, emotion and its’ influence on decision making has become clear. This paper conducted an experiment based on Iowa Gambling Task (IGT) and utilized Artificial Neural Network (ANN) on Heart Rate Variability (HRV) analysis, and found out from between subject analysis that most subjects tend to make advantageous decisions rather than disadvantageous decisions when their heart rate slows down (p < 0.001). From within subjects analysis, through the difference of Inter Beat Interval (IBI), guessing accuracy of artificial neural network on the outcome of subjects’ decisions has reached above 65% (higher than 50%, which stands for guessing at random, p < 0.05), which means that there might exist relationships between the performance of human decision making and the psychophysiological activities appeared right before they made the decisions. The results might leads to a new path of development of decision support techniques based on the understanding of human emotions’ effects.