# Analysis of Facial Cues for Cognitive Decline Detection Using In-the-Wild Data
## 6 Conclusions  
Unlike traditional methods that rely on controlled environments and subjective assessments, this work demonstrates the feasibility of an automated and accessible screening tool for dementia detection in real-world settings. This study investigated facial cues--eye blink rate (EBR) and head movement (HM) features--as reliable indicators of CI in in-the-wild conditions, individually and fused.  
In this work, we improve on the MTs approach for EBR calculation, enhancing its robustness for real-world applications. Our results show that EBR remains a reliable CI indicator in in-the-wild settings. Additionally, we investigate the role of HM features in video-based dementia detection, using a larger dataset for the first study of its kind. This dataset consists of ND, MCI, FMD, and HC participants. Our findings show that HM features enhance classification performance beyond using EBR alone, and their fusion further improves results, highlighting their combined effectiveness. In this work, we achieved promising results using an in-the-wild dataset, comparable to results in previous work that uses controlled datasets.  
Furthermore, this study demonstrates that a visual-only approach can achieve competitive accuracy compared to multimodal methods, reinforcing its potential as a scalable and cost-effective diagnostic tool. However, a key limitation of this study is the small sample size, which may affect the generalizability of the findings. Despite this, the results suggest that behavioral features hold promise for future applications in home-based assessments. With further work, including a larger dataset and additional features, such as facial expressions and speech, this approach could be refined to enhance its robustness and applicability in real-world settings.  
Conceptualization, F.A., S.M., and H.C.; data curation, F.A. and H.C.; formal analysis, F.A.; funding acquisition, F.A.; investigation, F.A.; methodology, F.A.; project administration, S.M. and H.C.; resources, H.C.; software, F.A.; supervision, S.M. and H.C.; validation, F.A., S.M., and H.C.; visualization, F.A.; writing--original draft, F.A.; writing--review and editing, F.A., S.M., and H.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported by a PhD scholarship from Umm Al-Qura University, Mecca, Saudi Arabia  
**Institutional Review Board Statement:** The data used in this work were provided by the Hallamshire Hospital Memory Clinic in Sheffield, UK. Ethical approval for collecting and using these data was given by the National Research Ethics Service (NRES) Committee South West-Central Bristol (Rec number 16/LO/0737) in May 2016.  
**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.  
**Data Availability Statement:** These data are not publicly available and cannot be shared due to privacy and confidentiality restrictions involving participants' sensitive personal information.  
**Acknowledgments:** This research was supported by Umm Al-Qura University in Saudi Arabia. The authors acknowledge the use of the IVA dataset provided by the Hallamshire Hospital Memory Clinic in Sheffield, UK.  
**Conflicts of Interest:** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.