Blog post by Marco Altini As previously reported we have added support for the CorSense sensor by Elite HRV. CorSense is a sensor you can use rather than a cheststrap, and it is compatible with most Apple iOS and Android OS devices. In this post, we'll show a few minutes of data collected under different conditions, highlighting how the sensor is very accurate in detecting RR intervals and can therefore be used reliably for HRV analysis. Data collectionData was acquired using the CorSense sensor and a Polar H7 (previously validated with respect to ECG here), both connected to a different device running the HRV Logger app, which is an app that simply records everything coming from the sensor plus additional features. During data acquisition, we collected data a few minutes while breathing freely, and a few minutes while deep breathing, to elicitate higher HRV due to RSA. You will see in the plots below visually the effect of deep breathing as we get greater swings in RR intervals. A final note on data synchronization: data cannot be perfectly synchronized because it is not timestamped by the sensors. What we can do is either to log real time and then to split data in windows based on when data was collected, then compute HRV features on these windows or to sum up RR intervals over time. For this analysis we went with the second option and also tried to visually align the data streams. RR intervalsWe will start by looking at RR intervals, the basic unit we need to compute HRV features. RR intervals (peak to peak differences in consecutive heart beats) are provided by the two sensors directly, so we don't really need to do much to collect them, apart from linking the sensor to the HRV Logger app and export the csv files. What can we derive from these data? You can see clearly almost perfect correlation between Polar H7 and CorSense for all conditions (relaxed vs paced breathing as highlighted by bigger oscillations in RR intervals or instantaneous heart rate), meaning that the sensor works really well in this modality. Heart rate variability: rMSSDAs features, we will look only at rMSSD, the only feature we really care about. rMSSD is a clear marker of parasympathetic activity and the main feature we use for our analysis in HRV4Training, similarly to what other apps do as well. Additionally, the sports science community seems to have settled on this feature for several reasons (practical as well as it is easy to acquire, compute and reliable over short time windows and less controlled conditions), and therefore we'll stick to it. What we expect given the data above is to see extremely close values between the Polar H7 chest strap and CorSense data. For the plot below, I computed rMSSD for each time window (60 seconds in this case): Results are very good considering normal variation in physiology and limitations in data synchronization. Summary and other useful resourcesThat's all for this post. We are very pleased to see more and more sensors manufacturers spending time to work on 'HRV modalities' in which accurate RR intervals are sent via standard protocols, and hope that more will come in the future, making it easier for users to gather reliable data. Elite HRV did great work on the CorSense, as shown in the plots reported in this blog post.
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