Abstracts

Clinical Evaluation of Sevo Systems: Equitable EEG for Coarse, Curly Hair

Abstract number : 3.412
Submission category : 5. Neuro Imaging / 5B. Functional Imaging
Year : 2021
Submission ID : 1886470
Source : www.aesnet.org
Presentation date : 12/6/2021 12:00:00 PM
Published date : Nov 22, 2021, 06:56 AM

Authors :
Jasmine Kwasa, PhD - Carnegie Mellon University; Arnelle Etienne, BS - Research Associate, Electrical and Computer Engineering, Carnegie Mellon University; Evangeline Mensah-Agyekum, n/a - Research Assistant, Electrical and Computer Engineering, Carnegie Mellon University; Harper Weigle, BS - Research Assistant, Electrical and Computer Engineering, Carnegie Mellon University; Vikram Marmer, n/a - Research Assistant, Electrical and Computer Engineering, Carnegie Mellon University; Shawn Kelly, PhD - Adjunct Associate Professor, Biomedical Engineering, Carnegie Mellon University; Christina Patterson, MD - Associate Professor, Pediatric Neurology, University of Pittsburgh Medical Center; Pulkit Grover, PhD - Associate Professor, Electrical and Computer Engineering, Carnegie Mellon University

Rationale: To provide quality care for all, it is pivotal that we develop effective EEG solutions for individuals of all hair types. Recent work from our team established that existing EEG systems do not work well for individuals with coarse, curly hair, which is common in the Black population [Etienne et al., IEEE EMBC’20; 6151-6154]. With > 1 billion individuals of African descent across the globe, we must innovate around this gap in a culturally respectful manner. In the same work, we also provided the first solutions to the problem by developing “Sevo electrodes” and demonstrated, in a lab setting, that they obtain low electrode-to-scalp impedance by leveraging the strength of braided hair to improve contact. In the current work, we sought to address two limitations of our prior work: a) assess improvements directly in EEG signal quality, and not just indirectly with contact impedance; b) and compare with clinical standard electrodes in a clinical setting. 

Methods: We evaluated  the clinical viability of Sevo electrodes with pediatric epilepsy patients by assessing signal quality improvements over clinical standard gold-cup electrodes. Two pediatric epilepsy patients, aged 9 and 20, were monitored in 3 conditions: i) gold-cup electrodes, with unbraided hair; ii) gold-cup electrodes with hair braided to expose scalp at the locations corresponding to the standard 10-20 arrangement; iii) Sevo electrodes with hair braided similarly, i.e., exposing scalp consistent with the 10-20 arrangement. 

Four metrics were used to qualitatively compare the electrodes: 1. Fraction of time for which data was “acceptable”, e.g., not contaminated by instrumentation artifacts or noise. 2. How pronounced the alpha power (8-12 Hz) peak was over surrounding frequencies in the EEG power spectrum. 3. The frequency at which the spectrum ceases to decay as 1/f. (If large white noise is present, 1/f decay will stop at a lower frequency.) 4. Localization of alpha power in the occipital region.

Results: In all four metrics, Sevo electrodes with braiding outperformed the other two conditions. For instance, as shown in the example figure for the 9-year-old patient, we observed several peaks in power corresponding to brain activity over the noise floor (most prominently alpha, 8-12 Hz) that were largely absent in the gold cup, braided condition. We also observed fewer erratic channels, a consistent 1/f decay, and more sensible activity spread at all frequencies tested (see inset scalp topographies). 

Conclusions: Based on qualitative measures from two pilot pediatric subjects, we have shown an improvement in EEG signal quality for coarse, curly hair by using Sevo electrodes above traditional gold cup electrodes. Our work is the first step towards mitigating racial biases embedded in this popular technology that may lead to misdiagnosis in the clinic and misunderstanding of brain science in research settings. 

Funding: Please list any funding that was received in support of this abstract.: JK was supported by the NIH F99/K00 DSPAN fellowship. Work was supported by the Carnegie Mellon University Block Center, the Chuck Noll Foundation, and the National Science Foundation under Award no. 2111735, and a Pittsburgh Innovation Challenge (PInCh) prize.

Neuro Imaging