Highly Conductive Flexible Sensor Integrated With Personal Devices For Practical Bio-Signal Measure
So good morning. Today. We have. John john lee, from university, of korea, integrated, by, bio. Electronics. Lab. To give a talk about high conductive, and flexible, sensory. Integrated, with personal, device for practical. Bio signal, measurement. And applications. Without further ado. You have the. Floor. Thank you for. Introductions. Today, i'm gonna announce to you the topic, i study at the university. I have fabricate. Highly conductive, and flexible, sensors. And, developed, the. Wearable. Biosensor. Biosensing. Device. And conducted, a studied about the. Healthcare, applications. With the biosignals. So. I'm, gonna. Present, a selection, of topic. That. Matches the theme of my summer internship. So the topic. The title of toffee, is, a highly conductive, and flexible, sensor. Integrated, with personal, device for. Practical, bios. Signal measurements, and applications. We generally, measure the electrical. Biosignals. On our skin. The source of the electrical. Potential. Is, uh. Generated, by the neurons, and cells, activity. And. The onstar, action potential. Exists, the certain stressful, voltages. It flew through the ion channels. Of our body. So our body is in. Homogeneous. Bone conductor. And. If, the ion fluxes, can create the electric, potential. On the surface of our body. So we can, measure, the. Summation, of action potential. Generally, by the neurons. On our skin. We call this. Biosignals. As you can see here. We can. Measure the lots of vital, signs, on our skin. Through the measurements, of the biosignals. We can easily, determine, whether or not, our, organ, is our each organism. Normally, performed. By the way we call the, each biosignal. Spiritually. The brain signal, is electro, as hologram. We called eeg. And the heart signal, is. Electrocardiogram. We called ecg. And the muscle signal, is electromyogram. And we call the emg. And eye signal, is electro, oculogram. We called. Eog, something like that. So, among this type of many. Biosignals. The eeg. And ecg, is the. Very important. Biosignals. Of our body, related to our life. So i'm gonna focus, on to.
Present. With the eeg, signal, and the eg signal measurements, device. As i mentioned before. The eeg, signal, is the most, one of the most important, bio signals, of our body. So in the past, the eeg, signal, is. Normally. Used in the. Clinical, diagnosis. Areas. But as the technology, developed. It has been used, a lot of. Research, areas such as ubiquitous. Healthcare. Brain company interface. And even social applications. Areas. By using the general public. So this uh. This biosignal. Is more and more becoming, uh. Popular, among the general publics. Despite, the. Interest, of the, general public. There are several, drawbacks. To the, conventional. Easy recording, systems. There are some limitations. Due to the. Characteristic. Of the eeg, signals, coming from the head. So, the, conventional, easy recording system have, lots of electrodes. Limitation. On mobility. And, pace program. And even. Currently, developed. Wearable, eeg sensors, have obturative. Wearing. So nobody wants to wear this kind of. Devices. In their, daily life. So. I think new paradigm, of eeg, device. Will be, highly, required. For. Anyone to use in their everyday, life. So, i. I have developed, new paradigm, of wherever i had one device. Such as the eeg, device. With the five different. Visions. The new device, must be. Simple using. And, unobtrusive. Wearing. A wireless, recording, and also comfortable. Varying, and even bio-comfortable. For. Users. In the case of the bio body on sensor. That is attached, our bodies. It is more focused, on the functionality. Without, considering. Appearance. That is because. The body one sensor, are able to hide under, our closes. However. In the case of the, head run sensor. It is not. Able to hide, under. Our closest. That is because. Our. Face, and head is generally, exposed. So. The form factor of wearable, head-on, device. Is, very very. Important. So i i thought of the wearable device concept. Of a combining, easy sensor. With a personal, device. Such as the hadron, personal, device. Among the lots of personal, device. I choose. Earphone. And eyeglasses. From factor. To, measure the, eeg. Eeg. In, of the wearable sensor. So, it has some, advantages. About, user friendly. And easy to wear, and unobtrusive. Wearing, in our daily life. So with these advantages. We can. We can use widely, used this kind of wear device, in our daily applications. In health care areas, such as pci. And, human machine interface, and. Brain company interface. So the first topic. To introduce, is in-ear, easy from concept. Nowadays. You can easily see those who wears their earphones. In all the time. So they, are using it. During. Studying, reading a book, and even, doing a sports. So the earphones, have become a. Necessary, item, of our. Nowadays. So the earphone, is, a, kind of. Best form factor. To wear, on our head without, any efforts. By the way, the brain. Signal, can be detected. In our eye. In our ears. Because, the brain signal. Spread, out, radially. In the brain. So, i combined, these two, two different, ideas, together.
To Develop, a. Wearable device, to measure the eeg, signal, in the. Year. Since the. Eeg signals, amplitude. Is quite. Small. So the sensing material, is highly most, highly. Conductive. And flexible. So. I developed. The. Shiba nano wires, cntpdms. Using. By mixing. Silver nanowires. And, carbon nanotubes, which are highly, conductive, materials. With the biocompatible. Pdms. Elastomers. What is pdms. Oh it's a. It's kind of a rubber. So it's a kind of elastomer. And the characteristic. Is. Quite. Soft, and flexible. And. Yeah it's a kind of silly, styling, oh silicone, yes yes. So. I made this, silver nanowire, cntpdms. Composite. And. The characteristic. And the. Carbon nanotubes. Provides, the. Conformer. Connectivity. Conductive, connectivity. In the elastomers. And the silver nanowire. Dramatically. Improves, the. Conductivities. So here's, our some, here shows some. Result, of the. Electrical, property. Characteristic. Of silver nanowire. Synthpdms. Composite. And especially, on the c, figures, it shows the, skin, and. Skin and electrodes, contact impedance. The result shows that. Silver nanowire, since pdms. Contact impedance. Is comparable, to the, commercial. Wet type of silver super chronic electrodes. That. So, i use these highly conductive, sensing materials. With the, eeg, sensing, device. Uh device, electrodes. Yes, why did you use both carbon, nanotubes, and silver. Oh, yes. Some, ones better than the other wire machines. Actually, on, for the, just, just using the carbon nanotubes. It has a. Conductivity. But it's not that high. For using, uh for measuring the eeg, signals. So i'm i. Uh. I put the. Simple nano wires. A little bit, it. Improves, dramatically. The conductivity. So it can. Take out the carbon. It's not as good you have to have both. Yes both, yes. So, the carbon nanotubes. Uh explain, explain. Explain the aspect, ratio, to patrick, of. Of the carbon nanotubes, that will maybe help him, understand. Oh, why, what's orientation. Aspect. Millennium, answer the question yes the. Uh. The diameter, of cnt. Carbon nanotubes. Is, about. 20 to 30, nanometers. And the long length is. 200. Micrometers. So it's quite long, and aspect, ratio is quite large, so it connected. It can connect the conduct, contact. Conductivity. Inside, the elastomers. Yes. So. Uh here shows the. Appearance, and the components, of in-ear ego, phone. As you can see here, the, in-ear eg earphone. Consists, of two parts. One is the. Simple nanowire, synth pdms, based in-ear cap sensor. And the other is erg, egf, phone, which is the.
Measuring, System. So the eeg cap sensor. Is. Made by. Attaching. The conductive, interconnection, layer, with the silver nanowire, cntpdms. Composite, together. On the memory foam. Memory foam so. And. This in-ear cap sensor is also designed. And, plug out is a resp, replaceable. So the in-ear cam. The eeg signal, is measured, by. With the, in-ear cap sensor. And transmitted, to the. Metal layer, of the. Frame of each earphone. And transmit. Transfer, to the. Circuit system. Through the signal lines. Also the mechanical. Modulus, of in-ear cap sensor, is much lower. Than that of the, bark polymers, that. Spark polymers. So this result shows that. In your cap sensor. Provides. Comfort, wearing. Of. In your easier. Phone. I also did the, comfort, study of the in-ear cap sensor. The finite, element, analysis. Simulation. Was conducted. To study, degree, of the comfort. When, wearing the near eager, phone. Of our eyes, our, ears. So i carefully, designed, the model, of ears. And. Each part of the inner cap sensor. And, i also. Did a. A, study about. Applied, pressures. When, the in-ear cap sensor come into our. Ears. As a result. The applied pressure, is more, loading, enough, to, cause the discomfort. And the electrical. Resistance. Change, of the, sensor, is did not change. Significantly. So, with this result. I indirectly. Learned that, this, in-ear cap sensor, is suitable, for, measuring. And, wearing. Of our ears. Here's just the easy recording, system. Uh the recording, system is one channel system, and consists, of three electrodes. Source, reference, and ground. So the measure of the easy signal, is transmitted, to the wirelessly. To the. Smart. Devices, such as smartphone, and laptops. Through the. Analog, filters, and application. Systems. So you do can you go back, so you do differential, amplification. Where is the reference. Right what are in the linear electrode, yes okay. So. Uh. The sensor position, optimization. Test was performed. To, optimize, the sensor. Position, inside the ear. So i carefully, divide, the, each experiments. Into the several groups. So and then finally, found the, best position. Of the linear. Cap sensor. Of the electrodes. So, the best, optimized, position, is when the source electrode, is upward, of the right. Earphone. And the reference. Electrodes, is upward, and ground, electrodes, is downward, of the. Left earphones. So with this optimized. Sensor positions. I. I measured, some. Eeg, signals. Of the feasibility, test. The feasibility, test was performed, to. Evaluate. The. Developed. Device. So three, feasibility, tests was performed. Two is. Two is related to the visual, stimulation. And one is related, to the auditory, stimulations. The first. Feasibility, test was alpha rhythm detection, test. In general. People, are in. Rest state. Or, close their eyes. The, 8 to 14 heads of the alpha rhythm, is highly. Expressed. In our. Brain. So with this biological. Mechanism. Mechanism. I, measure, the upper region. By. Closing, our eyes. So. For the experiment. Setup. We instructed. The. Subject, to. Open their eyes. Before, 60 seconds. And close their eyes. Another, 60 seconds. So, as you can see, at the a, figures, you can easily. Figure out the signal, differences. Before. And after 60 seconds. And also, the, on the b figures, the spectrogram. Results. The x-axis. Shows the time, and y-axis. Shows the frequency. So. On this, figures, you can also. Figure out the. Alpha reading. On the. Near the 10 hertz, after 60, seconds. Although, the amplitude. Of the energy. Earphones. Is. Lower than that of a commercial, system. Which is, attached on our. Head. But, we successfully, measured, the alpha rhythm. With the linear easier, phone. So please clarify. All. The two, spectrograms. Yes, on the right we have a signal from a cap, yes, and on the left is your, yes. So you still can see yes yes, yes. But uh. Amplitude. Is quite different, yes. The second, and third. Feasibility, tests was. Related to the ebook potential. So. The ebook potential, is brain. Brain response. Against the, external. Stimulation. So, the second, is, about. Visually, stimulation. And third is about. Auditory, stimulation. We also successfully, measure. Can measure the. Both. Visually. And auditory, stimulations. Brain, activities. For the practical, application. Of, uh, our. Inner easy earphone. We. We try to measure the thrusting. State, of, people. So, we usually. Do the concentration. Work. Such as, studying, and reading a book and reading papers. While, wearing, our, earphones. So. And we often. Fall asleep, and. Getting a dressing, state, without our knowing. So here is our. Motivation. Of this applications. That. If if the earphone, can await the people. During the drastic, state. The work. Efficiency, will be improved. So. For the. Generally. When the people, are, uh in the transiting, state. The four to seven hertz of that event, and. Eight to fourteen health of the alphabet. Is, getting, stronger. So with this, uh biological. Uh. Biological, mechanism. We measure that we try to measure the drastic, state. So for the uh. Experiment. Setup. We had a, repetitive. Clicking, task. On the subject, who was, limited, their sleep. Before, before the.
Previous. Day. Driving. Them, more. Drowning. State. So. We, instructed, the subject, to, click. The button. When the. Red. When when the black sign, changed the red sign. The black sign, the sign changes, randomly. So during the experiments. I measure the. Clicking, reaction, times. And name on the errors. When the clicking, reaction, time. Exists, the stress. Certain threshold, time. So during, the, experiments. I judged, the. Trusting, state of the people. When the number of errors, going high. So during, the. Transition, state, i successfully. Measured the. Change of the eeg, signals, the alpha van, and set events, getting stronger. So. As a result. That, this is the kind of, very, simple version of, applications. But we, successfully, measure the. Trust in state, with the linear ego, phone. So. This is a, very promising. Easy. Wearable, eeg device, for the practical, use in our daily life. The second topic, is smart eyeglasses. Concept. As you know. The. Eyeglass, is so familiar, to us. So it is no. Exaggeration. Say that, one, third of populations. Using, the. Eyeglasses. By the way. Uh it's very surprisingly. More than 87, percent, of the human sensory, input, is can be, obtained, by, our head, such as the. Five senses. So we can measure, the, variety, of, biometric. Information. Such as, brain signals, and eye signals. And. The other five senses. With, several. Sensors. Of. At the. At our head. And we can. Use this kind of biometric. Information. To. Use, the command, signal, to. Manipulate. The machines. So on this topic. I'm going to show you the. Human machine, interface, applications. With. With some sensors, attached, on the. Eyeglasses. From vector. Yes form factor c. So this figure shows the, appearance, and the confidence, of multifunctional. Smart, electronic. Eyeglasses. So as you can see here. Some sensors, and systems, are embedded. In the. Eyeglasses. So, the frame, of eyeglasses. Is customizable. For users. And. Made by. Using, 3d printing technologies. And biosignal. Measurement, sensors, are attached. Five different, plates. To measure the eeg, signal, and eog, signals. And the, sensing material. Is. Similar, to the previous. Reported, one, so. It is, uh. Carbon nanotube, based elastomers. And the. Color, changeable, display. Is. For the. Protect, our, eyes from the uv, radiations. Actively. So, we, apply, some color changeable, materials, on the, lens of. Eyeglasses. And. The other commercial, sensor. And wireless system. Is embedded, in the. Frame of. Eyeglasses. For the material. Color changeable. Glass lens. We use the previously. Reported. Electrochromic. Gel. The electrochromic. Gel, can change their colors. By, oxidation. And reduction, reactions. In the, ionic, components, of. Electrochromic. Gel. By, applying. Certain voltages. To the, electrochromic. Gel. The characteristic. Of this gel, is, transparent. And. Freestandable. That. We. Can easily, apply, these, materials. To the length of our glasses. And then the. When the. 13. Or more. Intensity, of uv. Is detected. But detected, by, uv sensor.
The. Systems. The microcontroller. Actively. Applied the voltages, to the, electrochromic. Gel, to. Change their colors. So this, uh device, can. Change their colors. To. For the. Eyeglasses. To the sunglasses. And the reverse, reaction, can be up. Available. Just a question so, this is a. Film which goes over the, optical, lenses, yes. So this is the result, of, a smart. Rear image of the smart electronic, eyeglasses. So incestuous. Sunglasses. Modes. And. Some sensors, and. Systems, are embedded, in the eyeglasses. So. The. Biosignal. Measurement, electrodes, are embedded, here, and. Very complemently, contact, to our bodies. Just wearing, the eyeglasses. And the. Commercial, sensor, and electronic. Recording, systems. Are. Embedded, the body of the, eyeglasses. So. Various type of biomaterial. Informations. Can. Can measure. With the, smart monitoring, systems. I will show, this, slide i will show the. Machine interface. Applications. With commercial, components. So first is the color change of lens operation. And second, is, motion detection. With uh acceleration, sensor. So. On the first uh, human mesh interface, applications. We can measure the ambient. Uv, intensity. With the uv sensor of our system. And. When the uv. Intensity. Is detected, by the sensor. The, system, actively. Applied, the. Voltages. To operate, the sunglasses. So, on the. Especially, on the ee graph. E figures. The when the uv light is turned on. The. Eyeglasses. Change the, sunglasses. In directly. And, the transmittance. Of. Sunglasses. With the. Uv, wavelength. Is, extremely. Low. So. This, figure. This result shows that. The sunglasses, mode can. Actually, protect, our, eyes from the. Uv. Radiations. So this kind of, applications. Can be used, for. Our daily life, and, also, for the. Using the displays. With the ar, and vr, technologies. The second, is motion detections. So, we're combining. The three. Different. Components, of. Each axis. Data. Together, and. We, figure out the different. Motion differences. Patterns. Such as working, and running, and, stand, sit down and stand up like that. So. We. Recognize. The. Emergency. Situations. Such as the falling down. So. These. Applications. Can be used for the. Patient, who needs, help, when they're. Falling down, these. Wearable. Devices, can. Contact, their families. With the smartphone. And you use it just a three-axis. Accelerometer. No gyro, no compass. Just no okay. Here shows the human machine, interface, with the brain activity. Results, we also successfully. Measure the. Brain activities. With, such as, alpha rhythms. And. We apply the. This, technologies. With, the direction, controls. So. For the human machine applications. With the eeg, signals. We, had a direction, control, that. Actually, uh generally, on the humans. When see the. See the. Certain, frequency, of the, visual, stimulations. The brain. Modulated. With the same frequency, of the. Visual, stimulation. And we can detect the peak of the. Stimulation, that. We call this ssbp. Visually. Stimulation. Steady state visually, stimulate, evoked potentials. So we use this technology. When the subjects. Want to. Select the right directions. The subjects. Stared at, for a while. For the 14 heads. So, if the. Subject, shows these, uh. Stimulations. Their, brain. Modulate, with the 14 headers, so we can, measure the 14 hertz of the peak. With the. Frequency, areas. And. We use this. Peak. Signal, with the command, signal, to. For the direction control. So this kind of, technology. Is quite common, in the, brain company interface. Areas. And. We, also, demo with, this, kind of technology. With the, eyeglasses. So this. This is for useful, for the. Patients, who, can. Moving their limbs, freely. And also it can, useful, for the ar, or br, technologies. This is shows the human motion interface, with the eyeglasses. Eye activities. The eog, signals. The eog signal. Is quite, clear, signals. Such as our, heart activities. So. So this, eog, signal, has much. Advantages. To use, as a command, signal, to manipulate. The machines. So, the sakari, eye movement, which is one of the eog, signals. The sakurai, eye movement, is a. Electrical, signal. That occurs, when the eyes moves, quickly. Left to right, and right to left. So. As you can see here. The sig. And the amplitude. And shape of the sakaragai, movements. Is depending, on the. Angles. Eye movements, angles. And. Directions. So as you can see here, you can figure out the difference. Shape of the left, signal, and the right signals. So, we use this, technologies. We measure the ichi. Sakariya. Movement, signals. Up to 40 degrees, by the 10 degrees. And we classify. It. So with this. Result. We apply, this, technology, to the very. Very. Basic, game controls. The tetris. Uh block movements. So, when the subjects. Uh, shows. Subjects moves their eyes, 20 degrees. The block moves one step. And. 40 degrees, it moves two steps. So. Here's just the, eog signals. And, we. Control, the, blocks, in real time, something like that. So, this is the kind of very. Basic. Applications. With the usg signals. But. We, chose the. Possibility. With the eog signals, to.
Manipulate, The mushes. By just wearing, our, eyeglasses. And moving our eyes. So. Conclusion. Uh, i have introduced, the, promising. Personalized. Head one devices. For practical, healthcare, applications. Of the first is in your ego, phone, and second is multifunctional. Smart eye glasses. Both devices. Are. Combining. Biosignal, measurement, sensors, with a. Personal, device. And, the characteristic. Of this device, is. 3d printing, and customizable. Design, for anyone. And, very. Simple, and convenient, and comfort to using for. Anyone, to use, and. The, appearance, is very reasonable. For. In daily life using. Also. Many kinds of has, information. Can be detected. From the head. The. System, is fully wearable. Due to the wireless. System. So i think this, two. Head one biosignal, devices, is, promising, for. Health care areas, for pci. And. Hmi. Areas. Before i finish, the, presentation. I'm gonna. Introduce. Uh briefly. For my research, topic, of summer internship. I'm, currently. Trying to fabricating. The, wearable, stress detection. Detector, with the biosignals. We usually, feel the. Stress. Stressful. But. We just thinking, about, is not a big deal. But. The, chronic stress. Can be a serious. Uh disease. So. So our body feels, uh some, some stress. The body. Uh, makes some symptoms, like. Anxiety. Anger, and headache, something like that. So. And then according, to some surveys. More than 75. Percent, of the u.s authors, report that. They. Have a, at least one symptoms. Of the stress. And more surprisingly. More than uh 85. Percent of disease. Are related, to the stress. So almost all kinds of diseases, are related to our stress. So. It is very important. To. Know, and. Manage, our, individual. Stress level. So. The stress level detector, is highly record. Highly, required. In future, daily life. So among the. According, to the. Previous, reported. Papers. There are some kinds of. Biosignals. Related, to our, stress level. So i, among the among those biosignals. I choose. Three. Three, bio signals, the eeg. And ecg. And the gsr. The skin conductance. That's because, these three. Bio signals, are deeply. Related, to the, our healthy, life, and, also the. Stress level. So. I tried to measure the fully wearable. In-ear, biometric, stress detector. And. I used the. Form factor. As a earphone, type as i mentioned, above. And. Especially. I, motivated, with the. Sporty, type of commercial, earphone. That's because, this type of, earphone. Have a lot of content, areas of our, heads. And, it can, stabilize. Fixes. This device, on our head. So i use this uh. Form factor. And some of the bio signal measurements. Electrodes, are attached. Near the ear, and.
Our Neck. So, ultimately. Our, research core. Our research goal is to. Alert. Our. Users. When the user have a. High stress level, and drives, them to rest and release the, stress. So, we are, working on, the. We are now working on. With, the. Kite paper. And. Uh. Actually, uh. Currently. Our. In progress, is. Just. Trying to acquiring. The bio signals. The eeg. And ecg, and gsr. And. Actually we need some. Machine learning. Technologies. So. I would like to. Collaborate. With the. Expert, of the. Machine learning, and. Familiar, to biosignal. Signal processing. So. Please contact me anyone, who. Interested, in this topic. With this. Email, address, yes. Thank you for. Listening. You think. Uh, so. Going back to the linear, electrodes. You did the. You did the. Electronics. Right, yes. Tell me a little bit about the analog, part and what kind of a2d converter, you use it. What is the. The gain of that, differential, amplifier. Okay. Oh yes, the gain is. About, 3, 000. Gain, is applied, for measuring, the eeg, signals. With. I met i use the. Operation, amplifier. With the, amplifications. Yes. What is the bandwidth, of the band pass filter. Uh fantastic, filter, is, a third, uh. Degree of the uh, butterworth. Whatever's. Been passed filters. So it is, one half, to. 35. Health. Uh, the band pass error, to 35. Order butterworth, for both low pass and for, for high pass you have separate, quarterback, yes yes. Nice. So your input signal is in the magnitude, of 10 micro volts. Yes yes, with 3 000, it goes. 300. Millivolts. Yes yes. Okay this is already now good for day to day. Yes. You go to the next slide i'm interested to know where, the census and the. References, are. Next slide. Yeah. So, i. Um, i did, some. Sensor position. Test. So. For uh. For the ground electrodes, and reference, electrodes. I fixed it upward, and, downwards. And i changed the, uh each, direction, of, source electrodes, like that, so. As i. Found that. When. For this. Position, is very. Best for. Detect. Eeg, inside the ear. Have you. Uh collected, experiments, when the subjects moved their eyes. Oh yes yes. Uh. The eyes. Movement, is, detected. Inside the eeg, signals. But, it can, reduce. Reject, with, signal, processing. Yes i understand that. Your configuration. Of where the electrodes, are it's also optimal for eog. Oh so you ended up getting a lot of eog, just because of the configuration. Oh yes yes because you're picking exactly that dipole. Oh yes, so, as you mentioned, the eog, sum of eog, is. Detected. Inside, the eeg, signals. But we, can. Reject. The kind of, eog signals, inside the eeg signals, yeah. And the same question about ecg. So in your last design you have your in-ear, electrodes, for eeg, yes, and your residues. Right electrodes, are here yes. I'm pretty sure you'll, see, plenty, of ecg. In the. Image electrodes. How you deal with that. Uh. Actually, i. Separate, the. Measuring, system. Of the. I use the two, two band pass filters. With the ecg, and eegs. So. I separately. Measure the analog, signals, to. Microcontroller. So. It's not that yeah. Measuring she is a very broadband, signal compared, to eeg, pretty much the bandwidth, of the electrical, geographic, signal. Is all over the place for of the eeg. Uh actually. Uh i i have the same example, here which. The, basically, the health activity. Was, projected, on this, on this line, actually, uh for my. Experiments. I cannot. Find the. Uh. Ecg, signals. Inside the ear. So uh. Interesting. Yes. They'll be not that problem. Down here because we couldn't find it in the ear, so, so even with even with filtering, you couldn't, couldn't parse it out, so, which is contrary to what you told me two weeks ago or three a month ago, where you said it was going to be so strong it was going to drown everything out, we had just the opposite, challenge so maybe, so so this is an area where maybe we have some learnings to do. Or, there needs to be some. You know. Some, deep. Deep, uh signal processing, we'll also separate out mg2. So in magnetometers. You pick it up anywhere, but eeg, that's not necessarily the case, but in a more general sense, there's no reason why you only have one. Sensor on the right. Since you have, this two channel on the left, you should just do it legit generic two by two and then just work out, what type of signals that you actually want that's where. And, and then go from there you don't have to say that's a reference in the ground. Because your sensory profile would be different you can treat that as a beamformer. So any more questions. Colleagues. The earwax. Is that an insulator, or a conductor, i mean does that, make it signal degrade over time after we wear this all day. Uh. Actually, at the, long term measurements. Experiments, is not conducted, there.
I Think. The. For the ear. Measurements. There's some. Uh. Generate, some heat. From. Inside, our body, so. I'm not sure about that but. The electrodes, is very. Dry, type of electrodes. So when the. Sweat is. Exposed, by the our. Skin, it doesn't matter to. Measure the signals, yeah. It's also cultural dependent. So. Depending, on on ethnicity. Um their conductivity. Their form, of the e-wax, is different. The density, of the facilities, yeah. And caucasians. More liquid. And there's the fifth percentile, shrek right. Help you yeah i just have a question wearing the ssvp, uh stimulation. So, uh did you display it on the glasses or, just uh. Uh yes. Averaging. For the pst how much was it how long. Oh it's uh we, measure the, 30. Uh seconds. Yeah, so. It's there so it's one subject it's one trial 30 seconds, yes yes yes it's quite long. But your eyes are left, right, yeah yeah, so it's basically an overt. Concentrated, floating person, yeah if you don't see anything. More. Questions. Um i guess. Yeah i see the, mechanical. And sensor, setup but. Do you have results at this point or not kind of. Research. Yeah i mean are you able to classify. So eyes open closed. Like, blinks can you do blinks i mean i'm trying to see what's the limit of what you can see. On the. Previous slides you were seeing eye blinks. Yes. You know some other times. These. Experiments. We. Instructed. Subjects, to. Stay stay their eyes. In yeah yeah so we, reject the eye, clicking, and blinking, like that, so, yeah for. Our, measurements, yeah okay. And you have a. Place where you want this to, end up. Like are you trying to drive the. Signal processing, to a point where you can pick up more things or, were you kind of. Finished with your study, what's, yeah. More questions. If not let's thank our speaker. Again. You.