過去的研究顯示出孩童在輸和贏的情緒差異很大，但是我們卻不易從自閉症童的臉部表情看出他們的真實情緒，也沒辦法得知孩童在遊戲輸贏之中的情緒反應，必須透過臉部表情以外的生理訊息，來了解自閉症孩童的情緒狀態。本研究利用Empatica E4手環量測自律神經受情緒影響所產生的變化，記錄在自閉症孩童與典型發展孩童遊玩記憶翻牌遊戲時的皮膚電活動與光體積變化訊號，比較兩組孩童在輸和贏的兩種結果下皮膚電活動訊號的皮膚電導反應特徵與光體積變化訊號的心率變異特徵各自的差異以及兩類特徵間的相關性之後以分類器進行分類。根據結果顯示，皮膚電活動不論是在自閉症孩童與一般孩童間或於遊戲贏與輸的不同情境下都有顯著差異，並且經過利用特徵進行分類的結果發現，在自閉症孩童組內區分輸和贏的兩種狀態的準確率達到83.3%。因此，我們是可以透過膚電活動與光體積訊號特徵區分出自閉症孩童在遊戲中輸和贏兩種結果中的情緒狀態。

Past studies have shown significant differences in the emotional responses of children between winning and losing situations. However, it is challenging to accurately determine the true emotions of children with autism spectrum disorder (ASD) solely based on their facial expressions. Moreover, it is difficult to gauge their emotional reactions during game outcomes. Therefore, it is necessary to rely on physiological signals other than facial expressions to understand the emotional states of children with autism. In this study, we utilized the Empatica E4 wristband to measure autonomic nervous system responses influenced by emotions. We recorded electrodermal activity (EDA) and photoplethysmography (PPG) signals while children with ASD and typically developing children played a memory matching game. We compared the skin conductance response characteristics of EDA signals and heart rate variability features of PPG signals between the two groups in both winning and losing scenarios. We also examined the correlation between these two types of features and used a classifier for classification purposes. The results revealed significant differences in EDA signals between children with ASD and typically developing children, as well as between winning and losing scenarios. After utilizing these features for classification, an accuracy rate of 83.3% was achieved in differentiating between winning and losing states within the ASD group. Thus, it is possible to differentiate the emotional states of children with autism during game outcomes using EDA and PPG signal features.

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