1. Introduction

2. Materials and Methods: Ear-EEG Toolkit Design and Validation

2.2. Ear-EEG Phantom - Design and Validation

A physical test bench to evaluate ear-EEG devices was developed. The basis for the prototype was similar to the most common type of EEG phantoms: a mold that creates the proper shape and fit for use with an ear-EEG device and that can be filled with a conductive mixture.

In contrast to most common EEG phantoms, this work focused on developing a compact design solely focused on the ear anatomy instead of a complete head-shaped phantom. We also set out to create a modular ear section for the mold, allowing for testing different ear form factors without having to rebuild an entirely new mold, as well as having a way to secure the signal antennas in place during the setting process of the filling material.

The phantom was designed using the Fusion 360 Computer Aided Design (CAD) software and then exported as a .stl file for 3D printing. The base design is an 18 cm modular cylinder split into two parts along its length, with open ends. The bottom half has two longitudinal railings where the top fits, leaving two round holes centered in the middle for inserting antennas. The cylinder sides can then be closed with the lids. The top has two square openings for pouring of the conductive mixtures. A 0.1 mm gap was used for all fitting parts to account for the 3D printing resolution. The rendered prototype is shown in Figure 16, and the phantom prototype’s full dimensions are presented in Appendix B.

The inside of these lids can then accommodate the outer ear canal and concha shape to create an imprint on the material inside, where an ear-EEG device can be placed for testing. The current methodology used ear canal scans done professionally by a local audiologist, digitally scanned on-site, and delivered as a .stl file (as shown in Figure 17), which can be imported as a mesh to Fusion 360 and easily fused with the lid mesh by using the Mesh Menu - Modify - Combine - Join Operation.

Ear canal scans were centered on the lid’s mesh with the concha cymba outline parallel to the mesh’s top/bottom. Meshes intersected to a considerate adequate depth as long as the ear canal and concha structures were visible and protruding, similar to Figure 18.

The ear-EEG phantom prototype was 3D printed on a Prusa i3 MK3 3D printer using Polylactic Acid (PLA). PLA was chosen due to its ease of use, fast printing times, affordability, non-warping nature, and lack of post-processing requirements, making it an optimal choice for this design. The printing settings on the Prusa software were set to a 0.15mm QUALITY printing resolution, using Prusament PLA filament with a default structural infill of 15%. The software automatically added necessary support structures Everywhere required. The combined printing time of the phantom body and lids was approximately 33 hours. To minimize difficult to remove supports, the cylinder halves were printed vertically. If the phantom’s form-fitting factor needs to be changed, printing just another set of lids with the ear impression takes only 6 hours. Figure 19 shows the different modular parts after printing and support removal.

2.2.1. Phantom assembly and bulk materials

To assemble the phantom, the antennas (pair of 3.5 mm AUX cables) were adjusted to fit the diameter of the cylinder holes by inserting one side of each cable inside PVC tubing and sealing it with duct tape. The cables are placed on the bottom half, then joined by the top and the lids with ear imprints on the side, holding the prototype together. Three strips of plumbing tape are used on the railing fittings, cables, and the inner circumference of the phantom lids to prevent leaks, as in Figure 20. The phantom can then be filled with a conductive substance.

Here, three materials were tested with our design: agar doped with salt, BG doped salt, and silicone doped with carbon fiber (CF), as a non-perishable option.

Agar and BG

Agar is a gelatinous vegan substance derived from certain types of seaweed, making a stable gel structure when cooled down after being boiled. An agar phantom can be created by mixing agar, water, and salt at the recommended weight percentages (% w/w) of 4% and 0.5%, of agar and salt, respectively, as per Equations 4, with A being the weight of agar, s the weight of salt and w the weight of water [10].

$$\left\{\begin{array}{c}\frac{A}{A+w+s}=4.0\%\hfill \\ \frac{s}{A+w+s}=0.5\%\hfill \end{array}\right.\Rightarrow \left\{\begin{array}{c}A=\frac{8}{191}w\hfill \\ s=\frac{1}{191}w\hfill \end{array}\right.$$

(4)

The phantom was overestimated to have a capacity of 700 ml (equivalent to 700 g of water). By substituting w for that value in the solved equations mentioned above, we get the necessary quantities of 30 g of agar (Hoosier Hill Farm, 10.20€ for 115 g, in Amazon) and 4 g of salt, rounded up to the nearest unit. The mixture was prepared as follows:

• Boil 700 ml of regular tap water (or deionized water)
• Add 30 g of agar slowly while stirring the mixture
• Add 4 g of table salt while stirring until no granules are present - keep mixing while letting it cool down at room temperature for 10 minutes
• Pour the mix into the assembled phantom through the top vents until the liquid reaches half the vent’s height, let it sit in a refrigerator until it fully solidifies (minimum 2 hours, preferably overnight), which can be checked through the top

BG is a common material for EEG phantom making, usually made of cattle/pork gelatin. Various weight percentage combos of both gelatin and NaCl are shown to be an appropriate conductive medium [17]. Due to an accessible lesser amount of acquired gelatin bulk powder (YouHerbIt 240 Bloom, around 20€ for 350 g of powder, in Amazon), values within the middle range of the above study were used, aiming for a 15% weight percentage on gelatin and 8% weight percentage of NaCl, with BG meaning the weight of gelatin powder instead of agar, which when solved wield the Equations shown in 5.

$$\left\{\begin{array}{c}\frac{BG}{BG+w+s}=15.0\%\hfill \\ \frac{s}{BG+w+s}=8\%\hfill \end{array}\right.\Rightarrow \left\{\begin{array}{c}BG=\frac{15}{77}w\hfill \\ s=\frac{8}{77}w\hfill \end{array}\right.$$

(5)

The same steps as for agar were followed to prepare the gelatin solution, with 140 g of gelatin powder mixed with 70 g of salt in 700 ml of hot (not boiling) water. Unlike agar, gelatin is better mixed at a lower temperature to prevent the formation of air pockets.

Both agar and BG ear-EEG phantoms are shown in Figure 21.

Silicone doped with carbon fiber

A non-perishable phantom that can maintain signal integrity indefinitely was also envisioned, as the aforementioned organic materials tend to deteriorate over time.

Conductive fillers have been tested to make silicone rubbers conductive, with carbon fibers found to be the most effective even at a 0.5% weight percentage measuring a 2 kohm resistance. Increasing to 1% further lowered resistance to 200 ohm, and higher percentages gave similar resistance, indicating that the percolation threshold (filler concentration at what a conductive network is fully established) was reached [33].

A Do-It-Yourself (DIY) approach in doping the silicone was followed [34], the acquired materials being:

• Chopped carbon fibers, 3 mm in length, 30€ for 500 g, on Amazon
• Two-part A/B system platinum curable silicone, mixing ratio of 1:1, 23€ for around 630 ml, on Amazon (two were acquired for the phantom)

The silicone was estimated to have a density of 1.11 g/cm³. Various weight of carbon fiber percentages were tried according to Equation 6 to establish a percolation threshold:

$$\frac{CF}{CF+S}=X\%(whereX=0.5,1.0,1.5,2.0...)$$

(6)

With CF being the weight of carbon fibers and S the weight of silicone. It was observed that when the weight percentage of CF exceeded 1%, the mixture became too dense and unsuitable for molding with the current mixing methods. Therefore, only 0.5% and 1.0% percentages were considered and prepared according to Equations 7:

$$\left\{\begin{array}{c}CF=\frac{S}{199},forX=0.5\hfill \\ CF=\frac{S}{99},forX=1.0\hfill \end{array}\right.$$

(7)

This non-perishable phantom was ultimately made for a 1% percentage, with 8 g of carbon fibers (rounded to nearest unit) being used for a total of 700 ml of silicone, following the next steps [34]:

• Measure 8 g of carbon fibers into a disposable cup (use a mask/gloves when handling carbon fibers)
• Wet the carbon fibers with a small amount of rubbing alcohol, spread them around, and let almost entirely evaporate (to release strands of hair that surround the carbon fibers)
• Add the carbon fibers to 350 ml of part A silicone and mix thoroughly (an electric mixer with a wider spatula attachment was used) until the mix presents a grey/blueish tint
• Add 350 ml of part B silicone and keep mixing for up to 25 minutes to the same tint
• Pour into the phantom, equally through each vent, and let cure for 6 hours

To characterize the conductivity profiles of our chosen materials, fine strips of each material (30mm x 10mm x 2mm) were prepared specifically for conductivity testing. Both ends of each sample were coated with conductive silver ink and standard two-wire method was employed to measure the resistance across the sample. Conductivity of the samples was then calculated according to Equation 8.

$$\left\{\begin{array}{c}\rho =R\frac{A}{L}\hfill \\ \sigma =\frac{1}{\rho }\hfill \end{array}\right.\Rightarrow \sigma =\frac{L}{R\times A}$$

(8)

Where $\rho$ is the material resistivity, R is the measured resistance, A is the area of the cross-section of the sample, and L is the sample’s length. $\sigma$ is the material’s conductivity as the inverse of resistivity. . The reference conductivity values for each material are listed in Table 1.

While the sample preparation for the carbon-doped silicone samples was successful, the mixing method employed was not suitable for a homogeneous distribution of carbon fibers in the for the larger phantom mold. This resulted in the creation of conductive (darker) and non-conductive (translucent, low or no carbon fibers) areas as perceived in Figure 22. Therefore this material was discarded from further testing.

2.2.2. Ear-EEG phantom testing protocol and setup

The agar and BG phantoms were tested over eight days, alternating daily for a total of four sessions each (i.e., "Day 4" is the last testing day per phantom), and refrigerated while not in use (4ºC). All phantoms were made using the ear scans of the same subject, for this reason, the same pair of ear-EEG sensors were used for all phantom testing.

The phantom was first weighed without the side lids and with the AUX cables stacked on top. The antennas were connected to a signal generator, simulating a 10 Hz (alpha band) 100 mV square wave. The oscilloscope probe was jammed in the side of the phantom to measure the signal through the material alone and test for the material’s integrity. Then, both earpieces were inserted, and electrode contact impedances were measured using an analog impedance meter (D175, Digitimer), capable of measurement values up to 50 kOhm. The impedance meter’s reference electrode was connected to electrode Ex1. The oscilloscope probe was then connected directly to each electrode to visualize the simulated signal, which allowed to test if any electrode wasn’t functioning or had a diminished signal amplitude compared to the one measured through the material. To simulate an ear-EEG acquisition, the earbuds were then connected to an OpenBCI Cyton amplifier (8 channels, 250 Hz sampling rate, 24 bits ADC) and connected per the recommended settings EEG acquisitions [35,36]. Ex1 was assigned to the bottom SRB2 pin (reference), and Ex2 was assigned to the bottom BIAS pin (noise-canceling), a priori. The remaining electrodes were connected in ascending order to the bottom N1P to N6P analog input pins (Ex3 is N1P, and Ex8 is N6P, on the board). Impedance values were also rechecked through the OpenBCI GUI. Then 20 s recordings were obtained through the amplifier on each ear, with a gain of 24: a recording with the simulated wave and an acquisition with no signal to assess the recorded noise floor at each electrode, both offline filtered between 0.3 Hz and 100 Hz.

The protocol was repeated after applying conductive paste (Ten20) to each ear electrode. The testing setup is illustrated in Figure 23.

Noise floor Root Mean Square (RMS) values were obtained with the rms function and the alpha simulation SNR (at 1% confidence) was calculated as per Equation 2.

Figure 23. Schematic testing setup of the proposed ear-EEG phantom.

Figure 23. Schematic testing setup of the proposed ear-EEG phantom.

2.2.3. Phantom integrity and durability

When measuring the signal through the phantom, it is important to track the usability of this tool over time. This was achieved by monitoring the net weight of each phantom and measuring the input signal through the medium.

Table 2 shows that during a week-long testing period (by Day 4), the agar and BG phantoms lost no more than 10g in weight (with a higher percentage loss on agar). The reason for this weight loss can be attributed to the evaporation of water in both phantoms.

Table 3. shows the measurement of signal integrity passing through the phantom over a one week period. The agar phantom had the more significant amplitude loss, from the initial 100 mV, only achieving 44 mV on day one, declining to 36 mV by the last testing day. The BG phantom started at 80 mV and lost half its amplitude throughout testing due to the phantom material drying up. The phantoms suffered extensive pilot testing before the first day of quantified measurements and were kept in suboptimal refrigerating conditions.

2.2.4. Electrode impedance

Figure 24 shows an example of electrode contact impedances (measured via the OpenBCI Cyton board and validated via the analog impedance meter) for wet and dry electrode conditions with the agar phantom’s second day of recordings. Impedance measurements show a clear improvement across electrodes when applying conductive paste to the electrodes, reliably bringing the impedance under 10 kOhm, which is acceptable for EEG data collection (the same effect happened for BG measurements, with overall even lower values than agar). From this data we can see that the Ex3, EL7, and EL8 electrodes had the most difficulty achieving suitable impedance for dry electrode conditions, with impedance values over 50 kOhm, indicative of no or very poor contact on the electrodes. This effect was consistent across testing sessions (suggesting ER4 as a better channel than ER3 for dry recordings, at least on this specific subject). However, applying conductive paste brings these electrodes’ impedance down to usable equivalent levels.

2.2.5. Noise floor measurements

Like impedance, noise floor measurements (without the input simulated signal) greatly benefit from the usage of paste at each electrode site, bringing the values across all channels close or under 1 µVrms across the board, as seen in Figure 25 for the second day of testing (first for noise measurements) on an agar phantom. These observations indicate that the electrode material and shape are adequate for wet electrode recordings. Comparing the left ear to the right ear results in the same table on a dry setting, we can predict that the left ear is more prone to have noisier channels (with RMS values in the order of hundreds of µV), when compared to the right side electrodes, suggesting a better performance when assessing the right earpiece on this subject.

2.2.6. Alpha wave simulation

When simulating a known signal into the phantom through the two antennas, the input frequency (10 Hz - within the alpha band) was successfully recorded at all ear electrode sites for the first day of testing in agar and BG. As expected, the modulation SNR value was higher when measured in the ear canal electrodes like ER8 (further away from the within-ear reference at ER1) than, for example, ER3 or ER4, which are closer to the reference.

In Figure 26, the resulting alpha modulation spectra at ER8 are present, with clear peaks at the 10 Hz and 30 Hz odd harmonic frequencies that compose the square wave. The noise floor aspect of the spectra resembles what would be expected from an EEG recording, although that was not always the case in the following days of testing when the agar or BG phantom noise floor readings started to increase. Nonetheless, the phantom antenna signal delivery and materials proved efficient in simulating a given signal, and the present methods regarding this aspect were positively validated, with our prototype and employed methods show feasibility for this type of testing.

3. Results: Toolkit Use Case: Validation of an ear-EEG sensor

3.2. EaR-P Lab Applied to Ear-EEG Study

This section presents the result obtained per paradigm of EaR-P Lab for wet ear electrode conditions, showing this tool being applied in the assessment of ear-EEG devices.

3.2.1. Alpha block

Figure 30 shows the grand average alpha block power for different ear-EEG references. The modulation was of 3.7 dB for the scalp Cz reference, about 3 dB lower than the control group value at Oz. Referencing to T8, closer to the ear, the modulation decreases to 3.1 dB and 2 dB for the within-ear reference at ER3, with a lower value for the between-ears assessment.

3.2.2. ASSR

The ASSR SNR at ER8 (Figure 31) for the Cz reference has a value of 7.9 dB, a decrease of 1.5 dB over the best response in the control group. Comparing the T8 and ER3 references, we can see the SNR is 1.2 dB higher for the in-ear ER3 reference over the temporal site.

3.2.3. SSVEP

Comparing the results from Figure 32, all measured SNR results were lower when compared to the control group SNR values of 11 dB and 7.5 dB at Oz and T8, respectively. When looking at scalp references (Cz and T8), the SNR at ER8 holds up at 6.4 dB and 5.9 dB. However, the within-ear and between-ears referencing was systematically shown as not significant, even for other electrodes.

3.2.4. AEP (N100)

When referenced to Cz, the ER8 electrode acquired the N100 component (albeit inverted) at an amplitude of around 6 µV for wet electrode ear-EEG recordings. Referenced to T8, the significant component was diminished, with a peak amplitude of around 2 µV, as per Figure 33.

For the ear referenced assessments (Figure 34), only the between-ears configuration measuring at EL8 showed a significant N100 component with a 1 µV amplitude.

3.2.5. VEP

While the VEP waveform seen at Oz for the control group is not maintained near the ear, the resulting waveform is maintained from the Cz to the T8 referencing for ear-EEG, with a 2 µV drop in amplitude for the latter, as seen in Figure 35.

For the ear ER3 reference, only the in-between ears configuration presented statistical significance in the waveform with a later 200ms component being deemed significant at 1µV.

Figure 36. Grand average wet ear-EEG VEP waveform at EL8 for an ER3 reference. Statistically significant segments are highlighted in green, based on a t-test (p < 0.05).

Figure 36. Grand average wet ear-EEG VEP waveform at EL8 for an ER3 reference. Statistically significant segments are highlighted in green, based on a t-test (p < 0.05).

3.2.6. AEP Oddball (MMN)

Figure 37. Grand average wet ear-EEG MMN waveform at ER8 for a (Left) Cz and a (Right) T8 reference. Statistically significant segments are highlighted in green, based on a t-test (p < 0.05).

Figure 37. Grand average wet ear-EEG MMN waveform at ER8 for a (Left) Cz and a (Right) T8 reference. Statistically significant segments are highlighted in green, based on a t-test (p < 0.05).

For within-ear and between-ears referencing, no significant components resembling the MMN response were found.

3.2.7. VEP Oddball (P300)

Measured from the scalp to the ear, the greatest observed difference between the oddball and standard stimuli shows a negative deflection around the 350 ms latency, for Cz (5 µV to 6 µV amplitude) and T8 (1.5 to 2 µV amplitude) referencing as per Figure 38, suggesting a later onset for this component than on the scalp.

Ear-EEG referenced P300 waveforms didn’t show significant components at expected latencies.

3.2.8. EOG (Blinks and saccades)

Concerning EOG blink ratios, from Figure 39, the ER3 reference was about 1.5 times higher than scalp references near the ear, with diminished results for the between-ears configuration at EL8. The best ratio altogether was obtained for the within-ear ear-EEG reference, at a ratio of 3.

Measuring at the ER8, saccade profiles were maintained for the different directions, with greater amplitudes for the Cz reference but better differentiation when referencing to T8, with a 10µV difference between up and down saccades, per Figure 40.

For within referencing, the vertical saccade plane presents a better differentiation of 3 to 4µV, while recording across the ears shows the best results in amplitude and difference between right and left saccades (the vertical saccades present the same profile), as seen in Figure 41.

4. Discussion

Abbreviations

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