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That's actually a good point. So when we start comparing across different methods, there's a few percentage points different. When we go from skinfolds to underwater, weighing to the bod pod, to bioimpedance to DEXA. So we started cycling through, and if we're trying to track changes, we want to make sure that the person is being measured with the same technique. Every time we can't just use those interchangeably and assume that one measure taken on one machine is going to be the same as something we would get from a different method. So we started looking at that and some of the assumptions that you mentioned, people are all different. And so there's changes in muscle mass that come naturally, as we age there's changes in body fat, that happened because of the normal aging process there's differences between men and women and muscle mass and fat mass there's differences in bone density and the density of fat free mass. Maybe if we look at different racial and ethnic groups and children versus adolescents. And so these are all things that ASCO and I deal with almost on a daily basis, as part of our research is trying to figure out how to more accurately measure what someone has made of accounting for all these external factors. We work a lot with underwater weighing or with the egg, like the bod pod, like you mentioned. And we figured out that we can measure how big someone is based on the amount of space that they take up in a picture. So just like the underwater weighing tank is measuring fluid displacement or water displacement, and the bod pod is measuring air displacement. We figured out that we could actually measure somebody's size or body volume with about 99.8% accuracy from a picture just by looking at how many pixels they displaced or how much space they take up in the image. And from there, we can take that volume measure and estimate density based on how heavy they are, and then convert that to fat, using some pretty standard lab techniques that we have. And then boom, we get numbers that are right in line with what we would get with the egg or with the bod pod or with underwater weighing or skin folds. And the data that it was all based off of at the sample that we had collected were adults 18 up into their eighties. We had a pretty good representation of men and women. We had different race and ethnic groups. And so we had data that we had collected that was pretty representative of the general population. We had a couple athletes in there. And so we knew that we were onto something and we've kind of refined the algorithm a few times to account for differences in age and sex and race and fitness level. And I think we actually have a product that we can use it in a research setting to get comparable values to what we get from our lab based techniques. But the benefit like you kind of already mentioned is that it's portable and it does exist on a smartphone. And the measurements that we can get are so quick and so accurate that a coach could take this and they could scan their entire team one right after another boom, boom, boom, boom. And you could go through the entire basketball team or the entire football team in minutes where it would take hours, days or weeks to go through an entire series of data collection on a big athletics team like that.
Absolutely. The cool thing about the app too, when you're taking those pictures to track changes over time, the device doesn't store the app, doesn't store the images. So when we're analyzing those images, the app doesn't see them like a person never actually sees the picture that you take. So it's not stored. And we did that for privacy reasons. We didn't want images getting out or to be a hack or something happened to where everybody's personal health information. And in these images of people are floating around the internet. So we decided to just completely walk away from that. And so we take the image, it goes up to the cloud, it's analyzed. And then the only place that had ever exists is on your phone. And so if you don't have it stored to your camera roll, it goes away completely, which we did again, very, very kind of strategically and changes over time. We've been have been really cool to look at. Obviously we just finished Thanksgiving and we're kind of going into the holiday season and we were tracking changes in our body, composition the holidays in our group message. Cause I think you have Thanksgiving and everybody goes, Oh my gosh, I gained like seven pounds this week. This is crazy. And you take a scan and you realize that 95% of that is waterway . And so it's not that big of a deal because the app is sensitive enough to capture those changes to where the scale may have increased. And so you are heavier, but most of that is being tracked as fat free mass. Cause you haven't gotten any bigger in a week to where they would cause significant changes in body fat. So that is one of the cool things about the app is that we're sensitive enough to detect those really small changes. And we can pinpoint which part of you is changing fat mass or fat free mass with really good accuracy, 153554b96e
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