Conventional electroencephalography (EEG) requires placement of several electrode sensors on the scalp and, accompanied by lead wires and bulky instrumentation, makes for an uncomfortable experience. Recent efforts in miniaturization and system integration have enabled smaller systems, such as wearable, in-ear EEG devices that are gaining popularity for their unobtrusive form factor. Although in-ear EEG has been demonstrated in recent works, dynamics of the ear and ear canal that directly affect electrophysiological measurements have been largely ignored. Here, we present a quantitative analysis of electrode-skin impedance for dry-contact in-ear EEG that accounts for cerumen (earwax) and electrodermal (sweat gland) response. Custom fitted earmolds with 16 embedded electrodes were developed to map the skin conductance in the ear canal of 3 subjects. In the presence of cerumen, the measured average dry-contact impedance in the ear canal was 86% higher than canals removed of cerumen. Electrodermal activity was also found to play a role in electrode-skin impedance, showing up to 25% decrease in dry-contact impedance in response to tactile stimulation. The better understanding of the dynamics of in-ear conditions serves to improve consistency and accuracy of in-ear electrophysiology.
more »
« less
Flexible polyimide based 34-channel electrode arrays for mouse EEG measurement
Electroencephalogram (EEG) recording is a widely used method to measure electrical activity in the brain. Rodent EEG brain recording not only is noninvasive but also has the advantages to accomplish full brain monitoring, compared with that of the invasive techniques like micro-electrode-arrays. In comparison to other noninvasive recording techniques, EEG is the only technique that can achieve sub-ms scale time resolution, which is essential to obtain causal relationship. In this work, we demonstrated a simple microfabrication process for developing a high-density polyimide-based rodent EEG recording cap. A 34-channel rodent electrode array with a total size of 11mmx8mm, individual electrode diameter 240μm and interconnect wire linewidth 35μm was designed and fabricated. For the fabrication process, we first deposit 350nm SiO2 on a silicon substrate. We then fabricate 6-7μm thick first layer polyimide caps with fingers and contact holes. Gold deposition and then lithography etching of 34 channel contact-electrodes and their interconnects were fabricated in the second step. The third step was to cover metal interconnects with a 10μm thick second layer polyimide, which was fabricated with photolithography before the final film released by HF undercutting etching of SiO2 layer. Then the fabricated EEG cap is interfaced with a commercial 34-channel female connector, which is soldered with 34-line wires. These wires are then connected to an ADC to record the EEG data in computer for post-processing. With polyimide, the EEG cap is biocompatible, and flexible which makes it suitable for good contact with rodent skulls.
more »
« less
- Award ID(s):
- 1631820
- PAR ID:
- 10109664
- Date Published:
- Journal Name:
- SPIE Proceedings Smart Biomedical and Physiological Sensor Technology XV; 110200T (2019)
- Volume:
- 11020
- Page Range / eLocation ID:
- 28
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Scalp electroencephalography (EEG) is a neural source signal that is extensively used in neuroengineering due to its non-invasive nature and ease of collection. However, a drawback to the use of EEG is the prevalence of physiological artifacts generated by eye movements and eye blinks that contaminate the brain signals. Previously, we have proposed and validated an H ∞ -based Adaptive Noise Cancellation (ANC) technique for the real-time identification, learning and removal of eye blinks, eye motions, amplitude drifts and recording biases from EEG simultaneously. However, the standard electroocu- lography (EOG) electrode configuration requires four elec- trodes for EOG measurement, which limits its applicability for reduced-channel mobile applications, such as brain-computer interfaces (BCI). Here, we assess multiple configurations with varying number of EOG electrodes and compare the ANC effectiveness of these configurations to the ideal four-electrode configuration. From an analysis of the root mean squared error (RMSE) and differences in signal to noise ratios (SNR) between the ideal four-electrode case and the alternative configurations, it is reported that several three-electrode alternative configu- rations were effective in essentially replicating the ability to remove EOG artifacts in an experimental cohort of ten healthy subjects. For nine subjects, it was shown that only two to three EOG electrodes were needed to achieve similar performance as compared to the four-electrode case. This study demonstrates that the typical four-electrode configuration for EOG recordings for adaptive noise cancellation of ocular artifacts may not be necessary; by using the proposed new EOG configurations it is possible to improve electrode allocation efficiency for EOG measurements in mobile EEG applications.more » « less
-
Researchers can improve the ecological validity of brain research by studying humans moving in real-world settings. Recent work shows that dual-layer EEG can improve the fidelity of electrocortical recordings during gait, but it is unclear whether these positive results extrapolate to non-locomotor paradigms. For our study, we recorded brain activity with dual-layer EEG while participants played table tennis, a whole-body, responsive sport that could help investigate visuomotor feedback, object interception, and performance monitoring. We characterized artifacts with time-frequency analyses and correlated scalp and reference noise data to determine how well different sensors captured artifacts. As expected, individual scalp channels correlated more with noise-matched channel time series than with head and body acceleration. We then compared artifact removal methods with and without the use of the dual-layer noise electrodes. Independent Component Analysis separated channels into components, and we counted the number of high-quality brain components based on the fit of a dipole model and using an automated labeling algorithm. We found that using noise electrodes for data processing provided cleaner brain components. These results advance technological approaches for recording high fidelity brain dynamics in human behaviors requiring whole body movement, which will be useful for brain science research.more » « less
-
Kalra, Jay Lightner (Ed.)This study aims to discover a possible relationship between electroencephalogram (EEG) signature changes as physiological indicators of one’s current state, and performance on the Vestibular Ocular Motor Screening (VOMS) assessment. A Muse 2 generated a baseline EEG scan for each participant, allowing for the collection of data associated with one’s brain activity. The subjects were then taken through several VOMS domain tests with a continued recording by the device. A comparable analysis was conducted between the participant’s baseline recording and VOMS recording with an intent to identify the consistent correlations in between. In conclusion the findings of this study show potential for characteristic brain activity patterns dependent upon what VOMS domain is being tested. Therefore, when any deviations from those features are observed, the likelihood of the presence of a concussion is much greater.more » « less
-
null (Ed.)OBJECTIVES/GOALS: Spinal cord stimulation (SCS) is an intervention for patients with chronic back pain. Technological advances have led to renewed optimism in the field, but mechanisms of action in the brain remain poorly understood. We hypothesize that SCS outcomes will be associated with changes in neural oscillations. METHODS/STUDY POPULATION: The goal of our team project is to test patients who receive SCS at 3 times points: baseline, at day 7 during the trial period, and day 180 after a permanent system has been implanted. At each time point participants will complete 10 minutes of eyes closed, resting electroencephalography (EEG). EEG will be collected with the ActiveTwo system, a 128-electrode cap, and a 256 channel AD box from BioSemi. Traditional machine learning methods such as support vector machine and more complex models including deep learning will be used to generate interpretable features within resting EEG signals. RESULTS/ANTICIPATED RESULTS: Through machine learning, we anticipate that SCS will have a significant effect on resting alpha and beta power in sensorimotor cortex. DISCUSSION/SIGNIFICANCE OF IMPACT: This collaborative project will further the application of machine learning in cognitive neuroscience and allow us to better understand how therapies for chronic pain alter resting brain activity.more » « less
An official website of the United States government

