Technical Analysis of the Ceribell EEG Device
Abstract number :
1.111
Submission category :
3. Neurophysiology / 3C. Other Clinical EEG
Year :
2017
Submission ID :
344866
Source :
www.aesnet.org
Presentation date :
12/2/2017 5:02:24 PM
Published date :
Nov 20, 2017, 11:02 AM
Authors :
Joseph Munaretto, Ceribell Inc.; Raymond Woo, Ceribell Inc.; Alex Grant, Ceribell Inc.; Jane Chao, Ceribell Inc.; and Josef Parvizi, Ceribell Inc.
Rationale: Rapidly obtaining EEG signals in the ED and ICU for at-risk patients can enhance diagnosis accuracy and speed, while cutting down time until treatment. Currently the use of EEGs in EDs and ICUs is limited by device availability, technologist availability, and lengthy setup time (~ 30 min). Ceribell a startup company based in Mountain View, California, has developed a portable EEG data recorder and electrode headset with rapid setup (~ 5 min) technology designed to overcome the inaccessibility of EEG in urgent situations when non-convulsive and subclinical seizures are suspected. The purpose of this study is to evaluate the signal quality and performance of the Ceribell system compared to a reputable clinical EEG system. Methods: We collected EEG samples both in the laboratory and as part of an ongoing clinical pilot study at Stanford University Medical Center. Laboratory collections on healthy volunteers included simultaneous collection of EEG using Ceribell and Nihon Kohden systems, as well as a split signal that recorded the EEG to both data recorders from the same set of electrodes. In the clinical setting, EEG data was first recorded with the Ceribell system in the ICU on 25 patients and subsequently with the clinical EEG system on the same patients. The data was pre-processed with a [1Hz, 70Hz] band-pass filter and a 60 Hz notch filter. Spectral densities were computed using Welch’s method. Metrics commonly used to characterize spectral distributions were computed including: Mean Frequency, Spectral Entropy, and 75% Spectral Edge Frequency (SEF75) in addition to other metrics. Results: In the split-signal test, the waveforms consistently appeared similar by visual inspection (see figure). The analysis of Ceribell data revealed Mean Freq = 22.46 Hz, Entropy = 8.51, SEF75 = 21.56 similar to the commercial system (Mean Freq = 22.86 Hz, Entropy = 8.52, SEF75 = 21.58). In the simultaneous test, the Ceribell system produced Mean Freq = 14.3 Hz, Entropy = 8.4, SEF75 = 17.36 similar to the commercial system (Mean Freq = 15.5 Hz, Entropy = 8.58, SEF75 = 18.84). Other metrics showed similar differences between systems for both tests. In the clinical setting, the Ceribell system showed spectral density distributions comparable with the commercial system. Conclusions: Our results indicate that the signal quality of the Ceribell system is similar to a commercially available EEG used widely in the clinical setting, while requiring less setup time and allowing more portability. Funding: Ceribell
Neurophysiology