Systematic Evaluation of Wearable EEG for Mild Cognitive Impairment Detection

Overview

This systematic review analyzed 21 studies evaluating 16 wearable EEG devices for detecting mild cognitive impairment (MCI), revealing classification accuracies ranging from 46% to 95%. Key system-level factors optimizing diagnostic performance and usability were identified, alongside methodological recommendations to advance wearable EEG applications in real-world MCI screening.

Background

Mild cognitive impairment (MCI) is a critical prodromal stage of dementia, including Alzheimer's disease, where early detection can facilitate timely intervention. Wearable EEG devices offer a portable, non-invasive means to monitor brain activity and potentially identify neurophysiological biomarkers indicative of MCI. Despite their promise, variability in device performance and lack of standardized protocols have limited their clinical translation. This study systematically evaluates wearable EEG technologies to clarify their diagnostic utility and guide future research and development.

Data Highlights

Key Findings

• Classification accuracy of wearable EEG devices for MCI detection varied widely from 46% to 95% across studies.
• Seven critical system-level factors optimize the balance between diagnostic performance, portability, and affordability: moderate channel density, frontal and parietal electrode placement, elderly-friendly multi-domain cognitive tasks, adaptive signal preprocessing, multi-domain feature extraction, ensemble classifiers, and multimodal integration.
• Standardization of MCI diagnostic frameworks and recording protocols is essential to improve comparability and reliability of wearable EEG studies.
• Increasing sample diversity and validating devices in real-world settings are necessary to ensure generalizability and practical utility.
• Optimizing device usability and technical specifications can enhance adoption in community and primary care environments.
• Comprehensive reporting guidelines and harmonized data processing pipelines will facilitate reproducibility and clinical translation.

Clinical Implications

Wearable EEG technology shows promise as an accessible tool for early MCI screening, potentially enabling timely intervention in community and primary care settings. Clinicians and researchers should prioritize devices and protocols that incorporate the identified critical factors to maximize diagnostic accuracy and usability. Standardized methodologies and real-world validations are crucial before widespread clinical implementation.

Conclusion

Wearable EEG devices represent a promising avenue for objective, non-invasive MCI detection, but variability in performance and methodological heterogeneity currently limit their clinical application. Addressing identified system-level factors and methodological gaps can accelerate the development of effective, user-friendly wearable EEG systems for early cognitive impairment screening.

References

1. Nichols et al. 2022 -- Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050
2. Dubois & Albert 2004 -- Amnestic MCI or prodromal Alzheimer’s disease?
3. Braillon 2018 -- Practice guideline update summary: mild cognitive impairment
4. Tahami Monfared et al. 2022 -- Alzheimer’s disease: epidemiology and clinical progression
5. Chen & Wang 2013 -- Mild cognitive impairment: a concept useful for early detection and intervention of dementia
6. Edmonds et al. 2016 -- “Missed” mild cognitive impairment: high false-negative error rate based on conventional diagnostic criteria