## 4 Discussion  
The experimental protocol in this study was able to induce multiple alterations in the ANS activities in the subjects, as evident in the changes in the HRV features. The significant increase in heart rate, along with significant decrease in the RRI, while playing Game 1 suggests that the game was able to induce sympathetic activity. This is also further corroborated by the other features, with a significant decrease in RMSSD and HF and a significant increase in the LF/HF ratio. The subjects recovered from this during Rest 2, as indicated by the significant difference in the HR, RRI, HF and LF/HF between Rest 2 and Game 1, and the lack of a significant difference between Rest 1 and Rest 2.  
However, from the results in the Robust Mixed-Model ANOVA, the cognitive status of the subjects had no significant effect on the HRV. This is different from what we expected, as the NC group were significantly younger than the MCI group, and age can affect the measured HRV. The changes in the HRV features were more due to the experiment session the subject was engaged in. There is also the lack of interaction between cognitive status and the experiment session on their effects on the HRV. Thus, elderly people regardless of cognitive status can play these games and experience similar changes in their HRV.  
In terms of the subjects' game performance, the cognitively normal group had better scores and lower response times compared to the group with cognitive impairment. With these results, the serious games used in this study can be used for cognitive evaluation of the elderly. This is also supported by the high accuracy achieved from classifying the subjects using game performance features.  
Some of the results presented in this study differed from some of the literature that focused on cognition and HRV. As mentioned, the cognitive status did not have a significant effect on the HRV, but some studies found a relationship between some HRV features and cognitive function. This could be because not all cognitive domains have a direct correlation to HRV. Based on two review papers, 8 out of 10 studies that used global cognitive tests found a significant positive relationship between HRV parameters and global cognition. For the executive function, 14 out of 26 studies confirm a relationship [25, 26]. Lower HRV predicts poorer performance, but this relationship is also dependent on the cognitive task [26]. For memory, three studies found a positive correlation [54, 55, 56], while seven studies did not [57, 58, 59, 60, 61, 62, 63]. Two studies found a relationship between HRV and language [55, 64], but another two did not [57, 60]. Six studies investigating the relationship of HRV and processing speed did not find a correlation to HRV features [62, 63, 65, 66, 67, 68], while only one study showed a correlation [59].  
Using machine learning to classify the cognitive status of the subjects generated moderate to high accuracy, specificity and sensitivity. This does show the potential of using the changes in HRV to evaluate the cognitive status of the subject, but still, using game performance features can gave better results. However, these results need to be confirmed in other experiments with larger sample sizes. Cognitive impairment can exhibit multiple sources of variability, thus having a larger sample size is essential for obtaining reliable results.  
In addition to the limitations due to sample size, the experiment flow was carried out in a sequential order. The order of the games was not counterbalanced, thus there could be order effects. However, based on the results, the HRV features between the two resting periods showed no significant difference, indicating that the HRV returned to baseline.