Hi! This is a really interesting article, and I’d like to share a few thoughts. If sleep detection algorithms are biased in a consistent way, why would they be such a bad option for tracking trends? For example, if I want to see if I’m sleeping better or worse than last week, it doesn’t matter too much if the algorithm mistakenly detects me as sleeping while I’m reading before bed, as long as it happens consistently, right? (Of course, this assumes my habits are mostly the same over time.)
In my case, I’ve found that self-questionnaires can be problematic (though I understand they may not be for everyone). I struggle with sleep issues and try not to look at the time when I have insomnia. Over the last year with my Coros watch, I’ve found that the algorithm is quite accurate. When I have a bad night, the metrics reflect that, and when I sleep well, they show that too.
thanks Victor! I understand what you are saying and certainly agree that there can be cases in which things are tracked better, also depending on the individual, our habits and behavior, as well as our physiology. Regarding the bias, there is no proof that this bias is consistent over time, as studies tend to look at different individuals and trackers for very short periods (one night or a few nights), hence I would not assume that there isn't a random error in there that makes even long term tracking ineffective within individuals (this is the case for me, I use the same device you use, a Coros watch, and it can't even track well my recent reduction in sleep time, which is obvious when looking at the data I manually log - again, not saying this can't work for others, but there are huge limitations and I think it is important to stress them, as many people seem overly confident in these devices, given the great marketing efforts the companies selling them make). I understand also that questionnaires are not for everyone, I don't think there is an ideal way to do this that works for everyone but we need to find tools and approaches that fit with our lifestyle and eventually provide valuable data, while being aware of the limitations. I think we could even question the whole sleep tracking idea... personally I find no value in it, apart from adding context for parameters and outcomes that are more interesting, e.g. my resting physiology, health or performance. I never spent a minute looking at made-up sleep scores or estimated sleep stages :) All the best for your training!
I have worn an Oura since they first came out and it tracks my sleep perfectly since I put it on when I put my Kindle down after reading in bed and take it off when I wake up! Problem solved. Kind of….
Hi! This is a really interesting article, and I’d like to share a few thoughts. If sleep detection algorithms are biased in a consistent way, why would they be such a bad option for tracking trends? For example, if I want to see if I’m sleeping better or worse than last week, it doesn’t matter too much if the algorithm mistakenly detects me as sleeping while I’m reading before bed, as long as it happens consistently, right? (Of course, this assumes my habits are mostly the same over time.)
In my case, I’ve found that self-questionnaires can be problematic (though I understand they may not be for everyone). I struggle with sleep issues and try not to look at the time when I have insomnia. Over the last year with my Coros watch, I’ve found that the algorithm is quite accurate. When I have a bad night, the metrics reflect that, and when I sleep well, they show that too.
thanks Victor! I understand what you are saying and certainly agree that there can be cases in which things are tracked better, also depending on the individual, our habits and behavior, as well as our physiology. Regarding the bias, there is no proof that this bias is consistent over time, as studies tend to look at different individuals and trackers for very short periods (one night or a few nights), hence I would not assume that there isn't a random error in there that makes even long term tracking ineffective within individuals (this is the case for me, I use the same device you use, a Coros watch, and it can't even track well my recent reduction in sleep time, which is obvious when looking at the data I manually log - again, not saying this can't work for others, but there are huge limitations and I think it is important to stress them, as many people seem overly confident in these devices, given the great marketing efforts the companies selling them make). I understand also that questionnaires are not for everyone, I don't think there is an ideal way to do this that works for everyone but we need to find tools and approaches that fit with our lifestyle and eventually provide valuable data, while being aware of the limitations. I think we could even question the whole sleep tracking idea... personally I find no value in it, apart from adding context for parameters and outcomes that are more interesting, e.g. my resting physiology, health or performance. I never spent a minute looking at made-up sleep scores or estimated sleep stages :) All the best for your training!
I have worn an Oura since they first came out and it tracks my sleep perfectly since I put it on when I put my Kindle down after reading in bed and take it off when I wake up! Problem solved. Kind of….
haha that works indeed!
the night is also the only moment in which wearables data is worth collecting, I used to wear it only then as well
That is very true. And have ordered a Velia Smart Ring and hopefully that will have a more wearable design if they ever come out.