# Analysis of Facial Cues for Cognitive Decline Detection Using In-the-Wild Data
## 5 Discussion  
As seen in the previous section, feature fusion shows better results than feature selection. A possible explanation for this could be that every feature contributes to differentiating groups from each other. For a better understanding of the results obtained, an analysis was conducted using a confusion matrix. Figure 13 shows the confusion matrices for all the classification tasks using the IQR approach to detect the UB--IQR was chosen because it provided better results than the SD approach for most of the classification tasks. It can be seen that ND and MCI are misclassified as MCI and ND, respectively, in the four-way classification task due to the overlap between these groups. Another reason is that ND participants who were misclassified as MCI attended the session alone, whereas MCI participants who were misclassified as ND attended with a partner/caregiver. In addition, another source of confusion can be seen in FMD participants, who were mostly classified as MCI in the four-way, three-way, and two-way classifications tasks. The reason behind this confusion is due to the existing overlap between these groups, which makes it a very challenging task, consistent with previous findings [33]. From Figure 13, it is apparent that there is a significant difference between the following conditions when predicted using the selected HC participants who only used a laptop as a recording device and were in environmental conditions similar to other groups: ND/HC, MCI/HC, and FMD/HC. Even in the four-way classification task, most of the HC participants are correctly classified. On the other hand, for MP/HC groups and D/Non-D groups, the misclassified participants are not limited to a particular class; instead, misclassification is related to variations in the recording environments and the devices used. These findings suggest that these possible sources of error could have been caused by the lack of diagnostic details regarding the type of dementia that participants have. Certain types of dementia, such as vascular dementia (VaD) and DLB, may not exhibit a head turn cue [35], which could contribute to misclassification. Including more diagnostic information is essential for improving error analysis and developing an automatic tool to handle overlapping conditions, such as AD, VaD, DLB, and behavioral-variant frontotemporal dementia (FTD). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Study** & **Participants** & **Data Settings** & **Modality** & **Classifier** & **Performance** \\ \hline
[10] & 18 (9 with dementia) & Lab-controlled & Audiovisual & SVM & 84\% \\ \hline
[7] & 29 (14 with dementia including (NPH, AD, DLB, MCI)) & Lab-controlled & Audiovisual & LR & 93\% \\ \hline
[8] & 24 (12 with dementia) & Lab-controlled & Visual & LR & 82\% \\ \hline
[12] & IVA\({}_{18}\) (6 ND, 6 MCI, and 6 FMD) & In-the-wild & Visual & SVM & 89\% \\ \hline
[25] & IVA\({}_{18}\) (6 ND, 6 MCI, and 6 FMD) & In-the-wild & Visual & SVM & 78\% \\ \hline
[11] & 32 videos (MCI and HCs) & Semi-in-the-wild & Visual & DL & 87\% \\ \hline \multirow{3}{*}{Our} & IVA\({}_{52}\) (29 MP, 23 HCs) & In-the-wild & Visual & KNN & 59\% \\  & IVA\({}_{52}\) subset (11 ND, 10 MCI, and 8 FMD) & In-the-wild & Visual & KNN & 81\% \\ \cline{1-1}  & IVA\({}_{52}\) subset (10 MCI, 9 HCs) & In-the-wild & Visual & KNN & 89\% \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Classification results (%) for dementia detection compared to previous work. Looking more closely at the interaction between sex, age and whether a partner is present is of interest. [PERSON]. [6; 37] suggested that 'attending with' is an additional cue to the head turn due to its effect on the latter. In the IVA\({}_{52}\) dataset, the number of participants who came with a partner is 12 participants (7 ND, 3 MCI, 1 FMD, 1 HC). The data show that participants who came with a partner generally show significant head turns and movements, which is consistent with related work findings [6; 38]. Moreover, they suggested that the presence of head turn indicates CI and AD.