Electro-deposited Nanoporous Platinum Electrode for EEG Monitoring

BACKGROUND: One of the key issues in electroencephalogram (EEG) monitoring is accurate signal acquisition with less cumbersome electrodes. In this study, the L2 phase electro-deposited nanoporous platinum (L2-ePt) electrode is introduced, which is a new type of electrode that utilizes a stable nanoporous platinum surface to reduce the skin-electrode impedance. METHODS: L2-ePt electrodes were fabricated using electro-deposition technique. Then, the effect of the nanoporous surface on the surface roughness and the electrode impedance were observed from the L2-ePt electrodes and the flat platinum (FlatPt) electrode. The skin-electrode impedances of the L2-ePt electrodes, a gold cup electrode, and the FlatPt electrode were evaluated when placed on the hairy occipital area of the head in ten subjects. For the validation of using the L2-ePt electrode, a correlational analysis of the alpha rhythms was performed in the same subjects for simultaneous EEG recordings using the L2-ePt and clinically-used EEG electrodes. RESULTS: The results indicated that the L2-ePt electrode with a roughness factor of 200 had the lowest mean impedance performance. Moreover, the proposed L2-ePt electrode showed a significantly lower mean skin-electrode impedance than the FlatPt electrode. Finally, the EEG signal quality recorded by the L2-ePt electrode (r = 0.94) was comparable to that of the clinically-used gold cup electrode. CONCLUSION: Based on these results, the proposed L2-ePt electrode is suitable for use in various high-quality EEG applications.

Unobtrusive Estimation of Cardiorespiratory Fitness with Daily Activity in Healthy Young Men

Despite the importance of cardiorespiratory fitness, no practical method exists to estimate maximal oxygen consumption (VO₂max) without a specific exercise protocol. We developed an estimation model of VO₂max, using maximal activity energy expenditure (aEEmax) as a new feature to represent the level of physical activity. Electrocardiogram (ECG) and acceleration data were recorded for 4 days in 24 healthy young men, and reference VO₂max levels were measured using the maximal exercise test. aEE was calculated using the measured acceleration data and body weight, while heart rate (HR) was extracted from the ECG signal. aEEmax was obtained using linear regression, with aEE and HR as input parameters. The VO₂max was estimated from the aEEmax using multiple linear regression modeling in the training group (n = 16) and was verified in the test group (n = 8). High correlations between the estimated VO₂max and the measured VO₂max were identified in both groups, with a 15-hour recording being sufficient to produce a highly accurate VO₂max estimate. Additional recording time did not significantly improve the accuracy of the estimation. Our VO₂max estimation method provides a robust alternative to traditional approaches while only requiring minimal data acquisition time in daily life.