Special thanks to Rob Wallace for inviting me to speak to triathlon coaches in Australia about HRV and our work with HRV4Training. In the one hour webinar, I cover:

• Theory about heart rate variability
• How to collect data (available technologies)
• Guidelines (measurements, confounding factors)
• Data analysis and interpretation (normal values, case studies)
• HRV4Training Pro & teams 

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The webinar was recorded and is available at the link below. Enjoy.

In this series of posts, I discuss Heart Rate Variability (HRV) Biofeedback, and in particular:

• Part One: Rationale for using HRV Biofeedback (this post)
• Part Two: Important metrics
• Part Three: Common Protocols
• Part Four: Expected physiological, psychological and performance outcomes

While part Four of this guide is mainly focused on athletic performance, Parts One, Two, and Three are generic and cover aspects applicable to any other population in terms of the benefits of improved emotional self-regulation for health and performance.

​Learn more at this link.

We have partnered with the Biomedical department of the University of Milan to provide free Heart Rate Variability apps in the context of a new study investigating the effect of home isolation on the cardiac autonomous nervous system.

Prolonged isolation studies during quarantines have focused mainly on the clinical effects of isolation, reporting emotional disorders, irritability, insomnia, poor concentration, deterioration of working capacity, stress symptoms and decision-making skills. The reduction in physical activity seems to contribute to the establishment of these dynamics.

The purpose of this project is instead to monitor the psycho-physiological impact of home isolation that is occurring in Italy as a consequence of the general lockdown aimed at containing the pandemic spread of covid-19.

Psychological monitoring will focus, through the remote administration of validated questionnaires, on sleep disorders (Pittsburg Sleep Quality, PSQI), affective and emotional states (UCLA Loneliness scale, Profile of Mood States, POMS), on trait and state anxiety (State-Trait anxiety Inventory, STAI) and on the level of physical activity (International Physical Activity Questionaire, IPAQ).

Physiological monitoring will evaluate the modulation of heart rate by the autonomic nervous system (HRV), as measured using the Camera HRV app, so that questionnaires data and objective physiological stress levels can both be analyzed.

I would like to thank professor Giampiero Merati of the University of Milan for involving us in this project and I hope our tools we'll be helpful to gather objective data on ANS activity. Our own data tells quite a clear story, as we still struggle to adapt to the new normal. 

In the past weeks, we have developed a free (and private) camera-based heart rate app to support self-awareness as well as data donation projects in the context of the current covid-19 pandemic. 

Since the start of the outbreak, I've been approached by many doctors and scientists that have been looking into simple and cost-effective methods to identify and manage individuals that might require additional care. Physiological measurements (for example resting heart rate, HRV or temperature), are all great candidates as these parameters have shown a consistent response to infections (you can find some data here).

At the same time, many research institutions and governments are starting data donation initiatives to track covid-19 symptoms, at a much larger scale. One of the main examples of this approach is the corona-datenspende app launched by the Robert Koch Institute (the National Health Institute in Germany), which also aims at integrating (anonymized) objective physiological data collected with wearables such as Fitbit and Garmin smart watches. 

I was recently made aware of the project by my former PhD supervisor, professor Oliver Amft, who is actively involved with the Robert Koch Institute and also familiar with our work on camera-based measurements. Needless to say, a free camera-based heart rate monitoring app could empower people from a self-awareness point of view, as well as give them the opportunity to contribute to these project. Hence, in the past week we have developed Camera Heart Rate, a free app that can be used to measure resting heart rate, and can share data only via the Health app, so that each user is in total control of their data and privacy.

​The app relies on HRV4Training's technology and is currently available on iOS in selected areas. Please read below to learn more.

Something as simple as measuring resting heart rate, is a very useful tool to capture changes in physiology due to our body fighting various forms of stress, including infections [1]. In particular, infections tend to show up in the data as increased heart rate (and reductions in HRV). You have probably noticed these changes in the past if you were ever sick while also collecting data longitudinally. This can happen a short time before we actually realize that something is going on (say a day or two in my experience).
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​Already years ago, Michael Snyder at Stanford University ran studies in free-living using commercially available sensors and found quite striking relationships between heart rate and infection (if you are into papers, I highly recommend this one [2]). We have also shown reductions in HRV and increases in HR with respect to self annotated sick days, in this blog post.

​Infections or getting sick in general, are one of the few conditions in which I would almost consider heart rate superior to HRV (or at least equal). Why is that? First, heart rate does not change much on a day to day basis, and is less sensitive than HRV to changes in physiological stress due to for example training, lifestyle stress, etc. (we have previously quantified these differences, with heart rate changing only 0.5–1% in response to hard training sessions for example, and HRV changing on average 5–8%, full paper here [3]). Secondly, heart rate changes to a much greater extent when facing an infection. Hence heart rate can be a simpler marker to look at, less affected by other stressors, and we could look at changes in heart rate to make sure things are staying within a normal range (based on your historical data).

Camera Heart Rate is powered by HRV4Training, the first validated camera-based heart rate variability (HRV) app. You can learn more about resting heart rate and measurement guidelines at the Camera Heart Rate FAQ page.

Camera Heart Rate is currently available on iOS and supports English, Italian and German. We have released the app only in selected areas, but if you are interested in potentially using it also for your initiative, please feel free to reach out. 

[1] Buchan, C. A., Bravi, A., & Seely, A. J. (2012). Variability analysis and the diagnosis, management, and treatment of sepsis. Current infectious disease reports, 14(5), 512–521.
Chicago.
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[2] Li, X., Dunn, J., Salins, D., Zhou, G., Zhou, W., Rose, S. M. S. F., … & Sonecha, R. (2017). Digital health: tracking physiomes and activity using wearable biosensors reveals useful health-related information. PLoS biology, 15(1), e2001402.
Chicago.
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[3] Altini, M., & Amft, O. (2016, August). Hrv4training: Large-scale longitudinal training load analysis in unconstrained free-living settings using a smartphone application. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 2610–2613). IEEE.