How do you get a decent ECG with a wearable that has a single point of contact with the skin. If you need to touch a contact on the device to get a two lead equivalent ECG then how can this be real time monitoring?
Real-time monitoring and continuous monitoring are different goals. The use case for something like this is probably a wearer who is experiencing heart palpitations, and has the time and clarity of thought to actually find the correct app on their device and start recording.
Continuous monitoring is extremely challenging still because ECG data needs to be sampled at a relatively high frequency (~200 Hz) to accurately identify the QRS complex in the waveform. That uses a lot of power, and the batteries we have still aren't good enough to support those types of demands. 200 * 60 * 60 = 720,000 samples per hour to collect and process.
It's possible that algorithmic approaches may be able to reduce the sampling frequency required. Power-constraints were the main issue when I studied this topic 10 years ago during my master's degree. I had looked into non-frequency domain techniques (such as empirical mode analysis/Hilbert-Huang transform) as a possible way to reduce sampling frequency and thus power consumption.
i would imagine you could take an ekg for 1-2 seconds every 30 seconds and run it through a much more simple model to determine if it should take a longer sample, no?
rather than reducing the frequency of the sampling, dynamically adjust the duty cycle of when sampling is happening?
this is probably a dumb suggestion, it seems pretty obvious. for example the apple watch doesn’t do o2 monitoring continuously, just for some fraction of the time.
do you need to sample every second to detect heart attacks? don’t they continue to show up on an ekg for more than 30 seconds?
> apple watch doesn’t do o2 monitoring continuously, just for some fraction of the time
Making it effectively useless? Unless the fraction of the time is multiple times per minute? E.g. in sleep apnea it's not uncommon for some desaturation to occur, triggering an arousal and deeper breaths, restoring saturation, only for the cycle to repeat 2 minutes later.
My Garmin has a similarly useless feature. I have no idea what the supposed benefit is. Maybe they hope that if they sample multiple nights they can detect some desaturation anyway and can get the user in for polysomnography? Might be worth it.
This kind of technology has been technologically viable for decades. The fact that we’re only now seeing prototypes, not mass adoption, is an indictment of the legal framework around medical devices.
The FDA classifies these devices as high-risk because they might give a false result but completely ignores the guaranteed harm of not having them at all. It’s a system that punishes action and rewards delay.
Article seems very light on details. Is this trying to detect ECG markers of heart attacks (like ST segment issues)? Is it somehow detecting troponin in the blood stream? How? And how are they going to prevent false positives if this is indeed a wrist-based device as I imagine it will be?
Can't read the full article. Abstract mentions 92% accuracy. That could be abysmal depending on how it's calculated? Correctly identifying 92% of heart attacks and missing 8% might be pretty good. But reporting false positives 8% of the time would be awful.
How do you get a decent ECG with a wearable that has a single point of contact with the skin. If you need to touch a contact on the device to get a two lead equivalent ECG then how can this be real time monitoring?
Real-time monitoring and continuous monitoring are different goals. The use case for something like this is probably a wearer who is experiencing heart palpitations, and has the time and clarity of thought to actually find the correct app on their device and start recording.
Continuous monitoring is extremely challenging still because ECG data needs to be sampled at a relatively high frequency (~200 Hz) to accurately identify the QRS complex in the waveform. That uses a lot of power, and the batteries we have still aren't good enough to support those types of demands. 200 * 60 * 60 = 720,000 samples per hour to collect and process.
It's possible that algorithmic approaches may be able to reduce the sampling frequency required. Power-constraints were the main issue when I studied this topic 10 years ago during my master's degree. I had looked into non-frequency domain techniques (such as empirical mode analysis/Hilbert-Huang transform) as a possible way to reduce sampling frequency and thus power consumption.
https://github.com/AshwinSundar/Empirical-Mode-Decomposition...
i would imagine you could take an ekg for 1-2 seconds every 30 seconds and run it through a much more simple model to determine if it should take a longer sample, no?
rather than reducing the frequency of the sampling, dynamically adjust the duty cycle of when sampling is happening?
this is probably a dumb suggestion, it seems pretty obvious. for example the apple watch doesn’t do o2 monitoring continuously, just for some fraction of the time.
do you need to sample every second to detect heart attacks? don’t they continue to show up on an ekg for more than 30 seconds?
> apple watch doesn’t do o2 monitoring continuously, just for some fraction of the time
Making it effectively useless? Unless the fraction of the time is multiple times per minute? E.g. in sleep apnea it's not uncommon for some desaturation to occur, triggering an arousal and deeper breaths, restoring saturation, only for the cycle to repeat 2 minutes later.
My Garmin has a similarly useless feature. I have no idea what the supposed benefit is. Maybe they hope that if they sample multiple nights they can detect some desaturation anyway and can get the user in for polysomnography? Might be worth it.
This kind of technology has been technologically viable for decades. The fact that we’re only now seeing prototypes, not mass adoption, is an indictment of the legal framework around medical devices.
The FDA classifies these devices as high-risk because they might give a false result but completely ignores the guaranteed harm of not having them at all. It’s a system that punishes action and rewards delay.
Article seems very light on details. Is this trying to detect ECG markers of heart attacks (like ST segment issues)? Is it somehow detecting troponin in the blood stream? How? And how are they going to prevent false positives if this is indeed a wrist-based device as I imagine it will be?
It seems to be using ECG, the (correct) springer link is https://link.springer.com/chapter/10.1007/978-3-031-82377-0_...
Can't read the full article. Abstract mentions 92% accuracy. That could be abysmal depending on how it's calculated? Correctly identifying 92% of heart attacks and missing 8% might be pretty good. But reporting false positives 8% of the time would be awful.