5 ms·

> There are also a number of people who die of heart attacks with no symptoms. If Apple can get even 1% of them to the ER that would be a huge win. The Apple W

> There are also a number of people who die of heart attacks with no symptoms. If Apple can get even 1% of them to the ER that would be a huge win. The Apple Watch cannot detect heart attacks.

reaperducer 8y ago
Six months ago, the Apple Watch couldn't detect a-fib.
- JshWright 8y ago
  A "heart attack" is the common term for a condition where part of the heart isn't receiving blood flow, and the tissue there is starting to be starved of oxygen (an infarction). That will show up on an ECG as elevation of a certain part of the tracing (the "ST" segment, between when the main part of the heart contracts and when it "resets"). In order to be clinically significant, you need to see that elevation in at least two adjacent leads, and each lead is only looking at a narrow "slice" of the heart, so you need several of them to be sure you're seeing the part that's involved (it's not at all uncommon for a heart attack to only show up on 2-3 leads (out of 12 on a typical ECG)). A watch cannot provide more than one lead (and the lead it does provide is really useless for detecting ST elevation, since it's a view across the "top" of the heart, which is not an area that will be involved in the infarction). It is not physically possible to detect a a heart attack from a watch. If you had asked me six months ago if a watch could detect atrial fibrillation, my answer would have been "sure, why not?". Just because one thing is possible with the advancement of technology, it doesn't mean all things are possible...
  - Steko 8y ago
    Currently can't do it but saying it'll never be possible seems like you're setting yourself up to get burned by deep learning.
    - JshWright 8y ago
      I've got a fair bit of domain knowledge and experience (in both the medical and software engineering aspects of this topic). I'm pretty comfortable taking that "risk".
      - Steko 8y ago
        Here's a more in depth argument of why maybe you shouldn't be: https://www.reddit.com/r/apple/comments/9fkb3t/im_an_emergency_physician_and_wanted_to_talk/e5x9w5c/ https://www.reddit.com/r/apple/comments/9fkb3t/im_an_emergen... "Medical grade" is hard to define, but you might actually be very surprised by how accurate this simple sensor could be in an era of deep learning AI. Earlier this year, there was a paper published at AAAI (https://arxiv.org/pdf/1802.02511.pdf https://arxiv.org/pdf/1802.02511.pdf) that found that just using the sparse, noisy data from the AW sensors (non-continuous, noisy heart rate measurements and a handful of HRV estimates every day), they could diagnose diabetes, high cholesterol, high blood pressure, and sleep apnea with relatively high accuracy. In fact, the diabetes diagnoses were comparable in accuracy to cheap lab tests specifically for diabetes. And even more surprisingly, the sleep apnea diagnoses could be made even if one doesn't wear the watch during sleep. There are other recent papers showing extremely good accuracy in detecting rhythm abnormalities. Deep learning can often magnify the power of cheap, simple sensors in ways that can in many cases seem unimaginable. Partly because of the power of multi-dimensional inference, and partly because the volume of data you get from wearing a device 24/7 helps to compensate for all the noise and sparsity. And that was with the current gen AW sensors, which now are a generation behind some other consumer devices -- I'm sure the AW4 catches up (and can likely gather data like continuous HRV). Add in another data point like ECG, even if it's the simplest possible form of ECG, and I wouldn't be surprised if the diagnostic accuracy for many conditions is higher than some lab tests. Especially for transient rhythm abnormalities like transient afib, which might show up late at night after drinking, but not occur during a lab test, which probably makes detecting transient afib hard in a lab until a lot of cardiac changes have occurred. Commenter /y/AlanYx continues in grandchild: Yup. Humans also have difficulty thinking and reasoning multi-dimensionally, especially with conditional probabilities across those dimensions. So while the watch probably can't apply the "simplistic fill-in-the-blank style" of reading EKGs taught in the Dubin book that someone recommended above (because the sensors are just too simplistic and the data collected too limited), deep learning can see through the data in ways people often can't. There's a good example of this in the DeepHeart paper I linked to -- the authors mention that no diagnostically predictive relationship between heart rate patterns during waking hours and sleep apnea was known prior to the work, likely because it is too complex to spot by just looking at heart rate graphs in the way humans do. (And in fact because a convolutional neural network is used, it's not easy right now to tease out in an explainable way to humans exactly what the computer is "seeing", although its specificity and sensitivity characteristics are known.)
  - gondo 8y ago
    what about a combination of devices? watch on a wrist, phone in a palm of another hand, AR glasses on a nose and side of a head, (going to the extreme) maybe some necklace or a ring
    - JshWright 8y ago
      They would need to be electrically connected. Are you going to run wires between them?
      - lz400 8y ago
        Couldn't they be connected wirelessly and send the electric signal they receive digitized?
        JshWright 8y ago
        It works by comparing the voltage potential across two or more points (in the case of the watch it's comparing the right arm against the left)
        deleted 8y ago
        [deleted]
  - breckuh 8y ago
    In 2020 alone we will collect more high-dimensional health data than from the beginning of history to the present day combined. Given the improving sensors on the wrist generating high-dimensional data (heart beat, ecg, perspiration, blood oxygen, motion, vibration, body temperature, etc), and a sample size of 100M+ people, is it not possible that there is some previously unknown signal in there that could be detected by deep learning? I'm not saying there is, I just wonder if heart attacks might cause some discernible but very complex pattern visible in high-dimensional data that we haven't discovered yet, or if there is just too much physical distance between the wrist and heart to drown out all signal.
    - someguydave 8y ago
      I donno, I'm an electrical (non-medical) engineer and I think I would wager on the "false positive costs outweigh the new screening benefits" side.

> There are also a number of people who die of heart attacks with no symptoms. If Apple can get even 1% of them to the ER that would be a huge win. The Apple Watch cannot detect heart attacks.

reaperducer 8y ago

Six months ago, the Apple Watch couldn't detect a-fib.

JshWright 8y ago
A "heart attack" is the common term for a condition where part of the heart isn't receiving blood flow, and the tissue there is starting to be starved of oxygen (an infarction). That will show up on an ECG as elevation of a certain part of the tracing (the "ST" segment, between when the main part of the heart contracts and when it "resets"). In order to be clinically significant, you need to see that elevation in at least two adjacent leads, and each lead is only looking at a narrow "slice" of the heart, so you need several of them to be sure you're seeing the part that's involved (it's not at all uncommon for a heart attack to only show up on 2-3 leads (out of 12 on a typical ECG)). A watch cannot provide more than one lead (and the lead it does provide is really useless for detecting ST elevation, since it's a view across the "top" of the heart, which is not an area that will be involved in the infarction). It is not physically possible to detect a a heart attack from a watch. If you had asked me six months ago if a watch could detect atrial fibrillation, my answer would have been "sure, why not?". Just because one thing is possible with the advancement of technology, it doesn't mean all things are possible...
- Steko 8y ago
  Currently can't do it but saying it'll never be possible seems like you're setting yourself up to get burned by deep learning.
  - JshWright 8y ago
    I've got a fair bit of domain knowledge and experience (in both the medical and software engineering aspects of this topic). I'm pretty comfortable taking that "risk".
    - Steko 8y ago
      Here's a more in depth argument of why maybe you shouldn't be: https://www.reddit.com/r/apple/comments/9fkb3t/im_an_emergency_physician_and_wanted_to_talk/e5x9w5c/ https://www.reddit.com/r/apple/comments/9fkb3t/im_an_emergen... "Medical grade" is hard to define, but you might actually be very surprised by how accurate this simple sensor could be in an era of deep learning AI. Earlier this year, there was a paper published at AAAI (https://arxiv.org/pdf/1802.02511.pdf https://arxiv.org/pdf/1802.02511.pdf) that found that just using the sparse, noisy data from the AW sensors (non-continuous, noisy heart rate measurements and a handful of HRV estimates every day), they could diagnose diabetes, high cholesterol, high blood pressure, and sleep apnea with relatively high accuracy. In fact, the diabetes diagnoses were comparable in accuracy to cheap lab tests specifically for diabetes. And even more surprisingly, the sleep apnea diagnoses could be made even if one doesn't wear the watch during sleep. There are other recent papers showing extremely good accuracy in detecting rhythm abnormalities. Deep learning can often magnify the power of cheap, simple sensors in ways that can in many cases seem unimaginable. Partly because of the power of multi-dimensional inference, and partly because the volume of data you get from wearing a device 24/7 helps to compensate for all the noise and sparsity. And that was with the current gen AW sensors, which now are a generation behind some other consumer devices -- I'm sure the AW4 catches up (and can likely gather data like continuous HRV). Add in another data point like ECG, even if it's the simplest possible form of ECG, and I wouldn't be surprised if the diagnostic accuracy for many conditions is higher than some lab tests. Especially for transient rhythm abnormalities like transient afib, which might show up late at night after drinking, but not occur during a lab test, which probably makes detecting transient afib hard in a lab until a lot of cardiac changes have occurred. Commenter /y/AlanYx continues in grandchild: Yup. Humans also have difficulty thinking and reasoning multi-dimensionally, especially with conditional probabilities across those dimensions. So while the watch probably can't apply the "simplistic fill-in-the-blank style" of reading EKGs taught in the Dubin book that someone recommended above (because the sensors are just too simplistic and the data collected too limited), deep learning can see through the data in ways people often can't. There's a good example of this in the DeepHeart paper I linked to -- the authors mention that no diagnostically predictive relationship between heart rate patterns during waking hours and sleep apnea was known prior to the work, likely because it is too complex to spot by just looking at heart rate graphs in the way humans do. (And in fact because a convolutional neural network is used, it's not easy right now to tease out in an explainable way to humans exactly what the computer is "seeing", although its specificity and sensitivity characteristics are known.)
- gondo 8y ago
  what about a combination of devices? watch on a wrist, phone in a palm of another hand, AR glasses on a nose and side of a head, (going to the extreme) maybe some necklace or a ring
  - JshWright 8y ago
    They would need to be electrically connected. Are you going to run wires between them?
    - lz400 8y ago
      Couldn't they be connected wirelessly and send the electric signal they receive digitized?
      - JshWright 8y ago
        It works by comparing the voltage potential across two or more points (in the case of the watch it's comparing the right arm against the left)
        deleted 8y ago
        [deleted]
- breckuh 8y ago
  In 2020 alone we will collect more high-dimensional health data than from the beginning of history to the present day combined. Given the improving sensors on the wrist generating high-dimensional data (heart beat, ecg, perspiration, blood oxygen, motion, vibration, body temperature, etc), and a sample size of 100M+ people, is it not possible that there is some previously unknown signal in there that could be detected by deep learning? I'm not saying there is, I just wonder if heart attacks might cause some discernible but very complex pattern visible in high-dimensional data that we haven't discovered yet, or if there is just too much physical distance between the wrist and heart to drown out all signal.
  - someguydave 8y ago
    I donno, I'm an electrical (non-medical) engineer and I think I would wager on the "false positive costs outweigh the new screening benefits" side.