Blog post by Marco Altini Our validation paper comparing camera based acquisition, Polar H7 (chest strap) and electrocardiography (ECG) was accepted for publication in the International Journal of Sports Physiology and Performance. The paper is titled "Comparison of heart rate variability recording with smart phone photoplethysmographic, Polar H7 chest strap and electrocardiogram methods" and the main author is Daniel Plews, who I'd like to thank, together with all other co-authors (Ben Scott - who carried out the entire data collection, and also enjoyed participating in the study as shown below, as well as M. Wood, A.E. Kilding and Paul Laursen), for their work on this paper. In this study we had the luck to collect a wide range of rMSSD values, Ben himself provided us with his own ridiculously high HRV data (rMSSD ~300ms), something that triggered the need for a different way to handle artifacts and correct for ectopic beats, as the current standard used in clinical practice (discarding beats that are more than 20-25% apart) would overcorrect in case of such high HRV (these changes have been implemented in the app almost a year ago).
If you've been following this blog, we've shown plenty of samples already to validate the accuracy of the camera based measurement with respect to regular chest straps, for example here, here for iOS10, here for the iPhone 7+ and the double camera drama, and finally here where we compared many different PPG devices. However, this is the first time we show also ECG data, the gold standard (see a sample here). We think it's very important to go through peer reviewing as well and being clear and transparent on our work, and this paper is a good step forward. I'd like to take the opportunity to stress again that while validated, PPG measurements need to be taken in a certain way, as they are more prone to noise with respect to other methods. It's important to limit movement as much as possible, and in general to follow the simple steps we covered in this blog post. Note also that PPG doesn't work for everyone, for example low perfusion might cause trouble in detecting blood flow with this method, even though we haven't seen many of these cases. This being said, the app is typically pretty good at detecting when things go wrong and informing you. Make sure to obtain optimal signal quality when measuring and to practice using the practice mode under Menu / Resources in the app, if you have trouble obtaining optimal signal quality. Comments are closed.
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