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>> Remoting everyone welcome to fall trying to get ready in Anaheim serving our series and in this series we'll be focusing on point of care technology in health care and being an offense in our series is hosted by scenic which stands for Southeastern nanotechnology infrastructure corridor richest one of the 16 sites under a national program called national nanotechnology Quorn it infrastructure and scenic has nothing but in one line a national scale fabrication and categorization resource it's basically a partnership between 2 academic centers one is Georgia Tech Institute for electronic some nanotechnology and the other one is the joint school of nanoscience and an engineering so the whole idea behind scenic is that it provides easy user access to a wide variety of microanalysis fabrication and characterization.

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And process capabilities along with staff expertise to. Do researchers in nanotechnology So basically the idea behind this is that extra uses uses from our campus to Georgia Tech as well as Jess and then maybe able to go to one of ours our sides are seen excite and use the facility for their research needs the so so it's not only for internal Georgia Tech Jason and users but it's also for external users coming from off campus to Georgia Tech and years and they could be academic researchers or industry users they have access to all presently so more information is available at scenic dot gothic dot edu in one line scenic is all about a one stop shop for your nanotechnology research.

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But that said as he said none of France fall none of France where in our series focusing on point of care technology in health care and to raise revenue are will be present had by Dr David Myers he'll talk on motion and force based point of care technologies and I also want to give power to introducing him properly I'd like to give a promo of the upcoming non-offensive I've been arse.

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For the rest of those days and not in October it's always those days at 11 am he d.t. and we have lined up for speakers in the forthcoming days up about 8 Young best speak on pediatric and point of care technology at Georgia Tech and October 15th we'll have Professor Gendry drum join school of man of science and nano engineering he will speak on integrated nano class money by sensors for protein biomarkers.

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And then on October 22nd we had Professor Carlos Moreno from Emory School of Medicine would speak on the resonance the x. it's a their company name it's a Christic resonance sensing platform and the last week of this month on October 29th Rosa laid on mom from newest of Georgia will speak on federal hydrodynamic isolation of circulating tumor cells and excess of arms if you have not signed signed up yet go ahead and sign up and register at tiny u.r.l. dot com slash fall 2029 a fancy flyer if you have your colleagues and students who may be interested in art and being one of these baby nurse feel free to forward this flyer to them or this link to them as well with that said it's a pleasure to welcome.

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Dr David Myers to an offense for. He's currently an assistant professor in the department of biomedical engineering George attack and Emory University David's really been stressed have fuel and unusual education background that fuses engineering micro system design biology and clinical research they would receive his bachelor's degree in mechanical engineering and physics at words India Commonwealth University and his Ph d. in mechanical engineering from the nearest city of the University of Carolina at Berkeley.

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They would undertook up a structure fellowship and by medical and clinical research in the Department of Environmental Engineering at Emory and Georgia Tech. They would has authored a book on to be there to publications and. Find topic high impact journals such as nature materials nature communications being a house and blood and he's also recipient of an I and I charge 20 and proud laser award as well as an n.h. get ready for a walk so without further delay listen why David to speak on his topic motion and force based point of care technologies David it's all yours Thanks Bob And thank you so much for organizing this and for the great honor of kicking this off.

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Ok so today I'll be talking to you about maybe something a little unusual but the concept of motion and forced based point of care technologies. From Iceland is working so I think it can be a little useful to give a little background about me why my thinking about motion and force so I've actually always loved small things and mechanics and I remember the moment as an undergrad at v.c.u. that I wanted to go to grad school and its section when I saw this picture now live you may be looking at might not make sense but what I was really interested was the gear train right next to the white and I was so you know press like what can you do with this gear train and and you know.

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How do you make this so I immediately signed up for grad school and you know you can make but carousels which rose really important you can actually make these these q. trains move so this this technology and I know a lot of you are familiar with micro electrical mechanical systems and what's needed is that the pictures that inspired me to go to grad school or are still publicly available at Sandia National Labs since their summit elegy.

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So I think you know just I'm probably preaching to the choir here but you know memes have been quietly changing the way we interact with the world when you look at consumer electronics especially smartphones which will actually talk a lot about today. We can see they're just loaded with a lot of micro mechanical sensors and of course much there we'll see can see here you know there's over you know darn near 100 sensors now in your phones or at least memes components including microphones inertial measurement units which will be relevant to today's Talk.

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And you know even to the point that we can walk in just looking at our phones but they're also revolutionizing the world around us you know the concept of drones you know drivers driverless automobiles you know having your groceries delivered by a robot These are all powered by the sensor revolution that we're undergoing now and the question is why why are these so ubiquitous and the answer is you know they're lightweight they're small really low power they're sensitive you know they're useful.

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But when we look at the clinic which is an interest of mine majority of these sensors are not lightweight and they're not small and they're not low power so if you look here you can see there's some noninvasive human Amec but these are pretty big and clunky cardiac Cardium Ems is nice and small implantable we do have this new revolution of wearable devices but again they tend to be kind of on the large science.

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Making important progress in health or heart rate. And for me personally you know if you look at this list where the mechanical sensors and you know other than blood pressure which was you know created in the late 1900 we really don't do a lot of mechanical sensing So you know with this problem in mind and my background in Madame's I've started a new lab so we're the sensors for a Living Systems Laboratory and we started you know just a few months before the pandemic so you know that was a great start you know you get get the lab all set up and shut down but you know where we're recovering and we're moving along but in general we look at new sensor science and transduction principals who are interested in developing new types of sensors but then past that I think what.

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Our special interest is really applying these we don't want to just make them in the lab we want to get them into the clinic or we want to get them making important contributions to biomedical research so high throughput type of systems now this is very prominent this is a very broad concept and the question is you know as they feel more specific the answer is yes so I almost always have all of our projects have some component of mechanics.

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Actually I just check in and say can you all see my point here or do I need to change the style. Crickets never a good. Like when the phone drops and you don't even know if you're talking to anybody. You know he can see it breaks great Sorry sorry there's always that moment when you're wondering if you're still there Ok sorry Ok so I have an interest in mechanics and also an interest in sensors and our interest span scales so some of our sensors are going to be on the tissue scale and we're going to go all the way down to the molecular which I won't talk about in this talk we're still working on those but eventually I'd love to share those with you and with regards to sensors some of them are going to be more on the basic science side and we also have an interest in translational in clinical research so we're And when you look at all of these kind of axes together I'm especially interested in the concept of bio physical diagnostics or you know more broadly this concept of mechanical medicine how does mechanics.

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How can that be used in a medical setting and then all of these are towards this concept of personalized medicine so in the in the idea by physical diagnostics I'll start with a project that we had done previously that's kind of on the tissue scale and translational. So just to give you a little background on the project itself there has been a need for telehealth that precedes the global pandemic so you know in today's world and with with social distancing measures in place yeah it makes sense that you'd want to have a tele health appointment so a perfect example is.

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My son he needs to check in with the pediatrician every few months we just do a virtual phone call and boy it's great it's so much faster than when I used to have to take him into the office but you know before Cove in 1000 I think it's important to highlight that over 20 percent of Americans live in a medically underserved area and a medically underserved area is one that's defined as too few or geographically distant clinics so if you need to try 3040 minutes to the clinic that's an under served area and so if you look at the United States you can see that all of these blue areas are defined already as medically underserved areas so you can imagine that if there's too few providers or their geographically distant that maybe telehealth could make an important contribution to this area.

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And it it does help and it can help but it has a few key shortcomings to the advantages I think is you consider if you've had a tele health appointment recently you know 1st of all it's definitely reducing visit position time spent on Consols we see in research suggesting that that's true it definitely curbs demand on facilities you know the physician just needs to be in their office there doesn't need to be these these same infrastructure in place for you to go to and it definitely can improve the access to medical resources and improve patient comfort which.

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In the grand scheme of things I think can be easily overlooked but making yours making your patients comfortable can really improve the interaction between the physician and the patient but there are some disadvantages so here's an example of a study that was done where they looked at you know the premise of health care effectiveness for a couple of different measures So for example appropriate testing for Ferengi itis was that.

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Was this done correctly and was in a biopics prescribed and honestly telemedicine that pretty horrible pass rate so when it was correct was only 3.4 percent versus about 50 percent for a physician office there are and I think the same thing is the avoidance of antibiotics for viral infections and that only happens in 16 percent of telemedicine appointments versus you know 27 percent of physicians office which neither one is great but you know we were looking for equivalency would tell health in this case however as you might imagine there are cases where it excelled so even though it wasn't statistically significant there was at least comparable performance to.

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Diagnosing back pain and so if if we kind of consider you know telemedicine and the concept of telehealth and the shortcomings the question is can can kind of break down a medical encounter and understand where and why tell health isn't working as well. And if you think about a typical medical encounter in person there's going to be a patient history.

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There's going to be a physical examination set a physical examination usually a physician will inspect they may feel more palpitate they may tap or perk us and they may listen so that's you know your stuff a scope and in a lot of cases there's diagnostic tests now the question is this and smartphones you know replace or at least act as a surrogate for some of these key components of a medical encounter and you know we are seeing a lot of progress so there's the cell scope OTOH which is actually you put a small attachment on your smartphone and it becomes an Ota scope so you can actually see whether you're a kid has.

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Your infection there are some really cool work that came out of You'd. See I guess a year or 2 ago where you know the possibility of using a smartphone to listen for an ear infection we can see that smartphones have been used for stethoscopes there's even in the diagnostic area the idea that you could use your smartphone to tell whether you have an yes it was some phenomenal work on a wolf or lamp group and with Romney you know and you know amazingly there's even you know handheld ultrasound that can be done with your smartphone so when we when we look at what smart phones have done and we look at the in person medical counter we can see that you know a patient history that's easy it's a video chat inspecting a lot of times video chats will suffice the listening you know you can see the stethoscope and we're making progress and diagnostic tests we still have some some work to do but but we're going in the right direction but what are the gaps it's definitely not possible to palpitate you know it's your physician can't reach out and touch you through that through the screen and then percussion I think is along the same line there needs to be some work done to it to get better tapping and percussion.

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So that's kind of where this project started can we can we make some progress on these glaring holes and so in smartphones address this gap and palpation And you know would even be useful so what is a population I think many of you familiar with a physical exam where you know the dark comes in applies pressure to an area and is literally feeling around.

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Various parts of the body including abdomen shoulder wherever an element or possible concern maybe and so if you think about this this is a physical motion and a smartphone could address this gap when you consider the inertial measurement units onboard so smartphone in particular has Excel or Amir's better able to deduce whether the smartphone is moving in 3 dimensions x. y. and z. and today's ones which were present when I was in grad school have now gyroscopes included as well.

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Which can also sense rotation and so just as a quick reminder you know acceleration is very different and can seem very different then than physical motion so it's just good to always remember that if you have a motion that motion can be described by an acceleration and if you have an acceleration you can just integrate twice with respect to time and you get a motion they just want to emphasize the concept that you know a physician is undergoing a motion smartphone has an accelerometer on it and you can these 2 are fairly interchangeable if you think about it they're linked so how could you know telehealth.

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You know palpation remote virtual palpation work well you know it starts with I'm hurting and you're going to call the physician of course hurting always happens at 9 o'clock at night right right before you're shutting down so you can't get into the office the physician is on call they're going to self-help 8 with their own phone and they're going to send this calibration to the patient smartphone.

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To the patient is going to now have the calibration with their smartphone. And they are going to pay themselves in the goal of their self-help patient is to repeat what the physician does so the idea is that you know. Whatever motion the physician decides to use to Prop 8 for abdominal pain you may do this as well and then after the patient's pates they can send the data back to the physician and then the population can guide the physician recommendation and when this really could be useful is when you consider appendicitis so appendicitis is acute pain that is especially apparent when you palpitate in a specific area on the abdomen and so if you can have a patients help our pate with a prescribed motion and assess their pain levels as they're doing this you can get a very quick judgment or at least an idea as to whether they may be suffering from appendicitis or not and the guy that the key concept here is is true if they are suffering from appendicitis or you're concerned that they're suffering from appendicitis they need to go to the emergency room now.

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If they do not experience severe pain during the palpation then perhaps they could wait until the next day and go to the doctor's office which is much less costly than an emergency department. So the 1st question we had to answer was you know can excel or honors in a standard smartphone measure relevant patient motion so this work was you know you get these amazing people at both Georgia Tech and Emory So Alex was just a phenomenal undergraduate student at Georgia Tech who just took this project and ran with it and you know a lot of the credit goes to him for actually I would say the majority of the credit goes to him for the work done it was really phenomenal So Alex he built this school servo structure and we got you know abdomen mimic and we we look at you know.

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In a very repeatable way what is a smart phone record during this motion. Which you can see is that. You know for a variety of populations from deep and slow which is in this black to shallow and fast and light blue and the smart phone is capable of recording all of these in a fairly consistent manner you can see that are standard deviation is quite small and that gave us confidence that perhaps this could be useful for an application Intel health 1st question is does the sensor in the system work like you expect and the answer in this case was Yes So after we did the testing with this you know abdomen mimic then we ask the question is What does it look like when a person does it is the curve the same shape or is it a different shape and.

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A little bit of both so what we see is that as a person this is data from an actual patient. As they place the phone up to their abdomen you can see that there's this moment and 0 acceleration because it's just resting you have them and then they begin to compress and you can see that there's a fairly constant acceleration for this person and that makes sense they're kind of slow there they're driving it in.

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And then for a lot of people there is this very sharp peak where if the acceleration rapidly increases and decreases because you're going from a compression to really step and then you end back at 0. So one question is if this is what an actual person is doing.

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You know there's there's this constant question of you know what is the physician doing what is what would a patient do and so we started with What do physicians do when they saw Poppy. And what's interesting is that so in this particular case this is the 1st population of 9 different physicians and what we're trying to do in this case the reason we wanted to show the 1st population was we wanted to show the unbiased one or is at least as unbiased as we could where the physician just self-help tapes.

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And this is the data that we collected And what's interesting is that. First you can see that physicians have this. Kind of almost 2 styles so one is very similar where there's this compression increase and decrease that's pretty sharp and you can see that in physicians 1678 and 9 and then you also have some physicians that once policies that have kind of this by modal distribution where it's more of a push and whole phenomenon that was 23 and 4 are later data showed that physicians can actually switch between these so we had one physician self-help 89 times and in some cases the physician.

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Did the exact same motion. Or I guess I should say that the physician had kind of categories somewhere more of a push and release like you see right here and some were pushing hold but they were able to at least understand. I think they were very conscious of these differences and were considerate as to which one they would want to use for a patient the next question is if a zisha ins and can self help a what does it look like if a patient's just picks up a phone and self-help aids on themselves are they even in the ballpark of what a physician is doing who's had medical training and the answer is yes so physicians typically.

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Patients at least especially a patient number 8 sometimes push a lot harder than physicians accelerations recorded were much higher for patient 8 most of our physicians peaked out at 2.5 or much less but you can see very similar motion curves to the physicians themselves so that was kind of a nice finding because we can see that you know there's not something magical going on here physicians have a certain way of doing it patients on their own native if we can can at least get close to it to now the question becomes how do you make sure that a patient at home is how painting in the same way that attending physician is and we've built an algorithm.

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To do that so you have a physician that would set an ideal population so they have a max depth and a target speed that they're going for this is the Ron the refined data our algorithm identified the key the 1st peak so one thing to keep in mind is that with our 1st pass we only focused on the compression and release type of.

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Our patients for the physicians that prefer the double peak that would need more work down the road but we identified the peak and then we defined a region of interest around it so this is the acceptable range that if of if a patient. Makes this motion in a similar way that it would be acceptable.

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So in this case we have. Actually an m.d. posing as a patient she was very kind and took the pictures for us who is attempting to match this ideal situation so in the 1st pass. Her peak was too soft and too fast in this quadrant. Her 2nd attempt was too hard and too slow and she was in this quadrant and then the final attempt was a match so she matched the target depth and the target timing.

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And so this is what the general concept would look like and this is what a specific patient did set a goal it was sent to the patient smartphone you can see that is the patient try this is 12 and 3 they progressive we were getting harder and harder and a little bit slower until eventually they got a match on the 5th try and actually this is what we found for most of our patients the median number of tries was 5 average of 6 to recapitulate what the.

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Physician had done in the 1st place so we broaden this a little bit further and we actually looked at 26 patients around. Georgia Tech and what we found was each patient was given 4 sets of 9 tries to self-help 8 nights important to note that each patient takes about 8 seconds though at most we ask these individuals to spend up to 4 minutes roughly though what if we find well there's always some people that can magically you know.

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Just nail it on the 1st attempt I am not one of those but I really admire those individuals and this is a perfect example we're about 10 percent of people perfectly matched with the physician that in the 1st attempt. Overall for these 4 sets of 9 tries 81 percent were able to match this together there were 21000 percent they just couldn't and that's fine this goal of this project is to.

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Improve but we don't expect perfection on tell. And then you know as I mentioned the median was 5 the average was 6 attempts to match the physician and then what we did was we looked very carefully at the data and we were specifically looking for do the curves roughly match and what is the sensitivity and specificity we found 95 percent sensitivity and specificity with this particular algorithm there were some egregious looking curves that you know had you know maybe a bunch of points and the algorithm picked the 1st point and those were you know either false and I guess or Paul positives that we threw out.

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So we're going to be useful you know it's like and David did you just make another widget that nobody wants and that's always the risk as an engineer so you have to work really closely with your clinical colleagues to make sure that you don't do this. But there's a couple of things to keep in mind this is incredibly accessible should just need a smartphone that's it you don't maybe an app but there are no which it's to attach to your smartphone you are ready to go with hardware that is already on your smartphone and you have a chance at Self Help Haiti and possibly save yourself a trip to Urgent Care The other thing he can mind is that about 10 percent 10 percent of all emergency department visits are for abdominal pain.

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And only one percent of all of these visits were actually urgent so 9 percent of emergency department visits for abdominal which are related to vomit all pain but have waited didn't need to go to the expensive emergency room so what does that translate to in the u.s. alone that's 9000000 emergency department visits pretty here and then so this work is published Alex and I are co 1st authors on it and you know just we're excited about it so.

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And then the next steps would just be trying to refine the algorithm and maybe instead of just using a single Excel around or can we actually use all of the inertial measurement unit sensors on the phone so that's kind of this project that's one example of a motion or for space sensor and I think what I'll do is.

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I will talk about one more project real quick that is focused more on the cell mechanics and translational side I will note that this project has the potential to be point of care but it isn't quite there yet. So just to give you a quick background on. Circulation and blood and human status and clotting when you get a blood clot in your body it's mostly composed of platelets which are the smaller nucleus cells that activate and fiber and which is this polymer Eric kind of mash what's interesting about platelets is they actually contract and they will pull your clot together and it's really significant event so if we just take some platelets and fiber and throw it in a tube you can actually see that there's an order of magnitude change in the volume and the stiffness.

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And this this significant changes mediated by just these individual platelets pulling on the fiber in mash to turn red fibers in green Now you may be looking at this in and you may ask the question so what and you're right you should ask the question so what and what's fascinating is that the mechanical properties of blood clots have been linked to disease so in in young patients that have had a myocardial infarction their clots can be 50 percent stiffer and more resistant to dissolution and in patients with bleeding disorders their clots can actually be 50 percent softer The question is why.

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And what dictates blood clot mechanics and to a large extent blood clot mechanics this is dictated by platelet forces how platelets are polling on this vibrant mesh. And what's been missing for a long time is very good tools to measure the forces of individual platelets so I actually developed one of these as part of my post doc with liberal am so we have these micro pattern dots.

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In this case these are 5 bridge and dots that are crossed linked to a movable hydrogels surface and so single plate will actually come down and land on the start and reach across and pull and displace them in so since the mechanical properties of this hydrogen all are very well known and since the plate was pulling on it at the applied force is directly proportional to the microdrive displacement and so what you can see here as this is a pair and contract this is the reference microdots and this platelet here is pulling with a moderate force in this play that here is point the high force you can see the difference in the.

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Distance. And so we actually the system is actually incredibly scalable so you can you know make thousands and thousands or tens of thousands of these dots and you can put them on cover slips or you can inject them in microfluidics so that you can have multiple biochemical and stiffness and flow conditions tested at the same time.

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And I think what's really cool is that we've started applying these to the clinic and in this particular case so if you're a healthy individual your forces tend to be between you know rate around 30 to 40 Nana Newtons here and then the 1st set of patients that we looked at were patients that we expected to have low forces so that's here in pink send individual with was got altered syndrome has a wasp mutation so the act inside the skeleton of the plate what is going to grow differently or form differently and since the force platelet force is mediated by actin and minus and we would expect them to have low forces in this case and indeed they do similar with this disorder called me Hegland disorder it's a non muscle mice into mutation and again if there's a mutation in myosin and contraction forces mediated by mice and we would expect a lot of force and indeed you do.

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Where I think it's really exciting is that. In the clinic there is a significant number of patients for some patients to come in and they have symptoms of bleeding so maybe they've had very long nose bleeds they have something called the Tiki a which are small purple dots which indicate capillary bleeding.

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Any number of features that would suggest that this person has an issue with bleeding and what's fascinating is that when we look at the standard tests for human status the standard tests that say whether or not this person has a bleeding problem they all say that they're fine and so that presents a real conundrum the tests say you're fine but you're clearly not fine and and it kind of points to the idea that there's there's more that controls bleeding and clotting than we're currently measuring and our test on contraction force was the 1st one that identified a difference in these types of patients with respect to healthy.

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Healthy individuals and it didn't happen in all of them but in 3 of the 5 patients that we tested they had lower platelet forces the other group that is very interesting is we got a lot of data which I won't have time to go into today but it's it's individuals with immune from the study peña so their body is destroying their platelets some of them bleed some of them don't we have no idea who does and who does not lead or why they do we don't believe because locally to look for load plate numbers should correlate with bleeding but it doesn't always correlate like you think and in this particular case it was the patient with the low platelet forces.

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That was actually the person that was displayed the most bleeding symptoms so in. Paying attention to the time in a skip ahead just a little bit and I have some acknowledgment so I just wanted to you know think Alex and Martin Rowlands for the work on the smartphone.

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Patients and then also Lam lab and our own lab sensors for living systems live where we're putting together a lot of really fun new biophysical and. Clinical diagnostic devices thanks. I guess with that if there is any question. Thank you David for your presentation and this time for Preston's let me see if there are some questions in the chat I have a question from Dr Harvey Singh he's asking for palpitation measurements that phones need to max around meter I want to hold all of the app.

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Who developed the app Yeah so we it didn't quite make it to full app deployed on. Either end road or iphone but Alex Weiss he wrote some really great script and we did it in Java. And he was able to get a self-contained app on his phone to get this at least at least facilitate the testing to the next question is from prism all O'Brien he's asking I'm wondering why the acceleration is always Bostom during pressing and reducing I would have expected a 0 crossing.

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We looked at the. Question We in this particular case. I believe we only did magnitudes exactly right so one of the questions I have is that. Does this need. You know f.d.a. approval for application and or fears what are the regular 3 process. And here. That's a great question.

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So I think you'd eventually want to. But see I have to be honest we didn't quite get to that point where we did get was really. The was sitting interest from our colleagues in this particular application. There there was both very high enthusiasm from some individuals and there were some individuals that had a lot of reservations about this particular system so I think to address those we we kind of put the project on par as and the next steps would really be focusing on.

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Our our 1st pass was just that when the Excel Romber but I think a much more sophisticated 3 the measurement using all 3 accelerometers and 3 gyros would have addressed some of those concerns but was needed thank you another question from Ok Ron Jeremy use you have some sort of collaborations are measurement using variable broader scope attached to the physician's hand no that's a great that's a great concept.

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And I think that would be a great area to look into one of the things that we did find was. You know I think before you can only really learn about something when you when you quantify it and measure it and you know how patient is is one of those things that's.

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Taught in medical school through kind of a you know mentor mentee situation but we always wondered if perhaps you know accelerometers and gyros on the hand especially ones that were kind of very small and you know unobtrusive if they could actually improve the transmission of knowledge from teacher to student with how to do proper compilation technique.

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Next question is from Peter shank of but the smartphone project can you provide the doctor with data on this difference or fondness of the particle or our patient location are they only looking for pain. That's a great question so I think the only thing that we can really provide the doctor is data on motion did did did the person's hand undergo a similar motion to to the physician's hand.

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The the concept the stiffness of the tissue that's a great one I I have thought about that a little bit I think in that particular case even the poly need some sort of pressure sensor attached to the phone. Together that in for your next question is from family Torah what are the requirements on frequency response and bandwidth for the actual raw meters but this application that's number one next thing is do you need to resolve very low frequencies accurately.

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The bandwidth was I mean the focal motion is a few seconds and I think we were sampling he killer heard it really was it's it's not it's nowhere close to the. The high performance applications and in part of it is that you're tracking the motion of you know your your abdomen is a fairly significant object so it's really how fast can that even move in the 1st place that's a that's a good question I don't have a quantifiable answer for you.

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At this moment but what I can tell you is that it was not it's not the high performance that you might expect was the 2nd part of the question Paul I'm sorry do you need to resolve very low preconceived accurately you. I mean there is a multi 2nd with.

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I don't know if it's necessarily resolving really low frequencies you do have to do some corrections to make sure that drip doesn't become an issue you know and since there are no questions. Let's thank David one more time for as. Valuable time here present in as. Research and I appreciate your coming do you think I'll.