Validating skin electrodes: Paving the way for non-invasive ERG use in psychiatry
Bibliographic record
Abstract
Electroretinography (ERG) shows promise for identifying psychiatric biomarkers. The gold-standard approach relies on Dawson-Trick-Litzkow (DTL) electrodes and desktop equipment, but high costs and the expertise required for reliable electrode placement limit its implementation. This study evaluates a cost-effective alternative: a handheld ERG device paired with less invasive self-adhesive skin electrodes, which require minimal training. ERG responses to cone and rod luminance stimuli were recorded from 49 participants: 15 controls (8 women, 7 men), 18 with bipolar disorder (12 women, 6 men), and 16 with schizophrenia (4 women, 12 men). Each participant underwent ERG testing with both electrode types. Skin electrodes produced significantly smaller amplitudes and shorter latencies than DTL electrodes, except for longer scotopic b-wave latency. Women showed higher amplitudes and shorter latencies than men for both electrode types, with the photopic a-wave amplitude relative difference doubling when using skin electrodes. Reproducibility between eyes was high for both electrode types, though slightly lower for photopic a-wave with skin electrodes (ICC 0.76 vs. 0.86 for DTL). Skin electrodes paired with handheld ERG devices offer a viable, accessible alternative to traditional DTL electrodes paired with desktop equipment. This approach has the potential to expand the applicability of ERG in clinical settings by addressing barriers like cost, complexity, and invasiveness, while highlighting the need to consider sex differences in ERG assessments, particularly with skin electrodes. • ERG amplitudes are ∼60 % smaller with skin electrodes compared to DTL electrodes. • Waveform morphology remains consistent between electrode types. • Sex-specific amplitude differences are more pronounced with skin electrodes. • Skin electrodes demonstrate strong interocular reproducibility (ICC >0.75). • Skin electrodes improve accessibility of ERG for psychiatric research and care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".