1.1 Camera acquisition
Current generation phones include both a camera and a light emitting diode, which can be used for reflection based bio-optical imaging. The technique is called photoplethysmography (PPG for short) and consists in detecting changes in blood volume during a cardiac cycle, by illuminating the skin and measuring changes in light absorption. HRV4Training uses the phone camera to extract PPG and then determine markers of the autonomous nervous system activity PPG has been used for a long time in clinical settings, and has been validated multiple times, proving to be a reliable measurement of HRV, as good as standard electrocardiograms with sticky gel electrodes. Check out our validation at this link Here are some practical tips in case you are using the camera:
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2.1 History, Baseline and Training Annotations
Once you've collected a few days of measurements, use the history tab to browse through it and look at the different features that were extracted during the test. You'll also be able to see the impact of some of your tags (e.g. travel, alcohol intake, injuries, etc.) on your physiological stress level The Baseline page helps you in going beyond short daily variability, and get a better overview of your physical condition in the past few weeks. In particular, the line is a 7 days moving average, which captures the global trend of your HRV, without being too affected by daily swings HRV4Training automatically computes your recent trend by analyzing changes in heart rate and HRV in the past 2 weeks. |
2.3 Population comparisons
In this page you can see how you compare with respect to other HRV4Training users. You'll be able to pick different physiological parameters (heart rate, rMSSD, HRV) as well as stratify by age and gender You can learn more about HR and HRV population values on this blog post In the context of HRV analysis, we always stress the importance of looking at your own relative changes over time. Our baseline HRV is probably affected by some factors that we cannot easily measure (genetics, for example, as reported once again recently), other factors that change but we have no control on (e.g. age), and factors we can probably influence (lifestyle) Hence, we highly recommend to focus only on relative changes, which is the most powerful way to make sense of your data |
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