COR

An exceptional life begins with exceptional data.

11 followers

An exceptional life begins with exceptional data.

11 followers

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COR moves beyond averages to provide deep, personalized, and actionable feedback on lifestyle design.

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Launch tags:Health & Fitness•Wearables•Quantified Self

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Looks promising! What biomarkers are actually being measured? Seems like you can't provide actual raw values (to get around FDA regulations) so can only show proprietary "scores"? Where can we see more images/videos of your app in use?

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4yr ago

COR

Maker

@bobtroia Hi Bob, in fact the COR response patterns are not biomarkers being measured or quantified. Our raw data is a spectroscopic pattern that is evoked over 21 days in a cohort of people all doing the same nutrition or fitness intervention. Our aim is not to tell you your cholesterol level or anything like that. Goal is to determine your level of response to healthy strategies. Why blood? Because that's where the data is. I truly think of this like Fitbit data or Apple Watch data, except with much keener insight because there is so much more information in the blood response.

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4yr ago

@bobtroia @bobme I get the value for users that need to make lifestyle changes. But do I understand correctly that there’s no option to get up the raw data for one’s own personal quantification? Or do you quantify any of the signatures in the blood across the cohort?

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4yr ago

COR

Maker

@bobtroia @newalexandria Not in the way that you are probably thinking about it. We are not measuring biomarkers and so there is nothing to report replaced to biomarkers. We measure a response to food and fitness and so in this sense, you are seeing the raw data, I mean not down to the ones and zeroes, but. pretty raw. Make sense?

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4yr ago

@bobme So to clarify, what you are doing is generating an individual's spectrum, then comparing that spectrum to another "target" individual (i.e., elite cyclist, centenarian, etc.)? Your ML model then tries to predict what interventions (certain foods, exercise, etc.) will help bring the user's existing spectrum in alignment with the target?

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4yr ago

COR

Maker

@bobtroia That's possible down the road. We are at the very beginning of this and so while it is great to dream about that future, right now we need all the data to train one global model to find response to a driving function, let's say eating pistachios. The training set is hundreds of participants eating pistachios and the model finds a "pure component spectrum" CORrelated to pistachio-eating across the cohort. By scaling that to a score we can tell you whether you are highly responsive to pistachios or more towards the low end. That information could be valuable to you to know whether it is worth your effort to eat pistachios regularly or if you should search for something else for which you have greater response. In this manner it might be possible to find your own best strategies for life improvement. This is the basic use case. Eventually we think everyone will have a COR spectrometer in their home and what we will be able to learn from that data truly boggles the mind.

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4yr ago

COR

Maker

Hello Product Hunt, Bob here, founder of COR. Glad to be back after a long hiatus, heads down building and making. I’ve always been fascinated with how deep, personalized information about your health can be made accessible– so much so that I helped pioneer Apple Health as an architect of the Apple Watch. Nowadays, there’s a huge movement toward collecting the best data to inform our lifestyle–as I’ve come to believe, an exceptional life begins with exceptional data. The problem is, tools in the market don’t provide a deep data set. COR was born from the need to answer a simple, profound question: how do we truly know what works for each of us, individually? Every research study on nutrition and fitness practices shows a range of benefits amongst a range of participants. Yet we know that even identical twins have hugely different metabolic responses. That’s why my team and I created COR - the world’s first at-home infrared spectrometer that measures personal blood response to food and fitness. Infrared spectrometers use specific wavelengths of light to identify and quantity molecular changes. They are in use all over the world from making consumer products to evaluating food crops. COR consists of a digital app and a physical machine that’s about the size of a Wi-Fi router. Users enroll in programs in the app that introduce modest lifestyle changes to their daily routines – like incorporating salmon into their diet or adding protein before a workout – over a 21-day period. Starting from the first day and every seven days after that, users will prick their finger to gather a small sample of blood that will provide insights into the effective changes brought about by the chosen program. In only 21 days, you can get a report (with data-backed evidence) of what lifestyle practices are highly beneficial for you. At COR, we want to equip people with the necessary data to make the most personally beneficial lifestyle choices possible. We hope that every family will eventually have a COR spectrometer in their home. We’d love to hear your feedback and questions so that we can continue to make COR the best product it can be. – Bob Messerschmidt, CEO, and Founder of COR

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4yr ago

Raycast

Hunter

"Google Analytics for your health" is based on the underlying data of your blood chemistry is a fascinating idea — especially when made accessible to consumers. Would love to try this!

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4yr ago

I am a PhD chemist, I commercialised an FTIR product for point-of-care diagnostics and I have been using an Apple Watch since Series 1 was launched. So I get It and you are definitely on to a winner. I won't ask you for your secret sauce but maybe reference data are needed to train the algorithms analysing the raw spectra (which if I understood correctly are not accessible to the user). I guess you have worked out the user feedback loop which (I am guessing) is a combination of Apple Watch data and direct user input. Is the NHS looking at this? Will there be an API so that 3rd parties can integrate it to their platforms?

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4yr ago

COR

Maker

@omer_casher Hi Omer nice to meet you and thanks for the kind words. We don't use any external reference data to train the models. Models are trained through patterns or correlations as research participants in a cohort do food and fitness items for 3 weeks. Our spectrometer is broadly sensitive, as you know since you are an IR guy. No API currently but I would not rule it out. Thanks for your interest! - Bob

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4yr ago

@bobme Hi Bob. Glad to meet you too. My own estimate for a decent training set would have been 1K-2K participants using a commercial FTIR spectro but it appears that COR is more research grade if it can work on a smaller set.

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4yr ago

Uggozi

Wow an at-home spectrometer! Would definitely love to try this.

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4yr ago

Invisibility

This looks awesome. Taking at home health tracking to the next level

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4yr ago

Love the idea of being able to track how my body responds to things like getting in 10,000 steps a day. Is that effort really worth it, or should I be incorporating things like fish into my diet (or both). Can't wait to find out!

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4yr ago

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