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Positive with limitationsSystematic review with risk-of-bias and GRADE certainty assessment

Electroencephalography in Subjective Cognitive Decline and Mild Cognitive Impairment: Systematic Review of Biomarkers, Classification, and Prognostic Evidence.

EEG research shows promising group differences and early classification signals in subjective cognitive decline and mild cognitive impairment. The review found that the evidence is not yet strong enough to support EEG as an established clinical screening or diagnostic test.

Lu S, Hu S, Huang J, Shi Y, Yu D, Cao W, Yin M, Petersen JD, Huang B.
Journal of medical Internet research · Publication date: 2026-09-30
Added to site: 2026-10-01
DOI: 10.2196/92709

Electronic publication date verified in PubMed, Crossref and the full text. This source date is separate from the site's addition date.

Modalities
EEG, QEEG, ERP, AI
Clinical focus
Subjective cognitive decline, Mild cognitive impairment, Biomarker validation
Population
Older adults with subjective cognitive decline, mild cognitive impairment, Alzheimer disease or other dementias, plus healthy comparison participants
Sample
20 reports with a maximum of 3,853 confirmed-deduplicated participants, including 2,927 with SCD, MCI, Alzheimer disease or other dementias
Intervention / method
Systematic review of group-level EEG and ERP differences, classification models, screening or diagnostic evaluations and prognostic studies across English- and Chinese-language databases
Comparator
Healthy controls and diagnostic groups used by the included studies; no pooled clinical test-accuracy comparator was available

Clinician summary

Twenty reports were included after correcting cohort overlap. Ten were prediction or AI reports, nine were nondiagnostic observational reports and one was prognostic. No conventional diagnostic test-accuracy study was identified, and GRADE certainty was very low across all four evidence bodies.

How to interpret the findings

The full text documents heterogeneous populations, recording and preprocessing methods, feature definitions and model evaluation. Several reports shared cohorts, prospective pathway-based accuracy studies were absent, and representative recruitment, prespecified thresholds, participant-level separation and independent external validation remain needed.

Equipment and disclosures

The included studies used varied EEG and ERP systems and analytical approaches. This review does not validate a specific amplifier, normative database, classifier or clinical workflow.

The authors declared no conflicts. Funding came from the National Natural Science Foundation of China, Hainan Province Science and Technology Special Fund and Hainan Natural Science Foundation Innovation Research Team Project; the funders had no reported role in the review.

Related evidence

Compare findings from the same clinical area, including mixed results.

Full text checked · Checked 2026-10-01

Summary prepared with AI assistance. Source verification does not imply an independent replication or a clinician's endorsement. Read our review method.