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Harness the Power of Garmin Wearables for Health Research with Ethica Integration

At Ethica, we support all Garmin wearable devices and help you integrate them easily into your studies. In this article, we will show you how you can use Ethica to integrate data from Garmin wearables into your health research with just a few clicks.
Harness the Power of Garmin Wearables for Health Research with Ethica Integration


In today's rapidly evolving healthcare landscape, researchers are increasingly turning to wearable devices to collect accurate and reliable health data for their studies. One of the leading wearable technology brands, Garmin, offers a wide range of devices that can track various health and fitness metrics. As part of Ethica’s researcher dashboard, we offer seamless integration with Garmin wearables, allowing you to take full advantage of the rich data these devices provide.

In this blog post, I'll explore the benefits of using Garmin devices in health research projects and how Ethica's integration can help you obtain valuable data to drive your studies forward.

Why Choose Garmin for Health Research?

Garmin wearables are known for their accuracy, reliability, and wide range of sensors. From heart rate and sleep patterns to stress levels and body composition, Garmin devices collect a wealth of data that can be invaluable to health research projects. By integrating Garmin with Ethica, you can leverage these data sources to gain insights into participants' health and wellness, and in turn have more informed decision-making and better study outcomes.

Another advantage of using Garmin is its cost-effectiveness. Unlike higher-end options such as Apple Watch, Garmin offers a wide range of devices that suit various budgets, making it particularly an attractive option for projects with limited funding, or for studies with large sample size which does not use BYOD model. At the same time, Garmin's wearables are designed with the everyday consumer in mind, making them a favorable choice for study participants. Unlike bulky wearables often used in research, Garmin devices are sleek, stylish, and user-friendly. This consumer-oriented design not only makes the devices more attractive to participants, but also increases their adherence to the study.

Lastly, unlike manufacturers such as Fitbit, Garmin maintains an open platform that enables researchers to access detailed data using their API. This level of openness allows you to tap into the full potential of Garmin devices and harness a wealth of information for your studies.

What data sources are available?

Understanding the available data and how they can be used to address specific research questions is crucial for maximizing the potential of Garmin devices in your studies. While Garmin offers many different types of wearables, the type of data that you can get from them can be categorized into ten groups. Below I will list these ten groups, and provide a short description for each of them. Note that not all wearables offer all of these data types.

  • Garmin Health: This is a general data source that encompasses a range of health and wellness data points collected by Garmin devices, including but not limited to sleep, activity, stress, and heart data. It serves as a comprehensive resource for users to access and analyze their overall health and wellness information.
  • Garmin Health Daily: This data source provides daily summaries of various health and activity metrics, such as steps taken, calories burned, active minutes, and distance traveled. It enables users to monitor their daily activity levels and set goals to achieve or maintain a healthy lifestyle.
  • Garmin Health User Metrics: This data source offers a collection of user-specific metrics such as age, gender, weight, height, and activity level. These metrics can be used to personalize and enhance the accuracy of other Garmin health data analyses.
  • Garmin Health Heart: This data source focuses on heart-related data, including heart rate, heart rate variability, and resting heart rate. It can be used to monitor cardiovascular health, fitness levels, and stress, as well as to analyze heart rate patterns during various activities.
  • Garmin Health Respiration: This data source provides information on a user's respiration rate, typically measured in breaths per minute. It can be used to monitor and analyze breathing patterns during various activities or while at rest.
  • Garmin Health Sleep: This data source offers insights into a user's sleep patterns, including sleep stages (light, deep, REM) and sleep duration. It helps users understand their sleep quality and identify areas for improvement to promote better overall health and well-being.
  • Garmin Health Sleep Daily: This data source provides daily summaries of a user's sleep data, such as total sleep duration, sleep efficiency, and the number of awakenings during the night. This information can be used to track trends in sleep habits over time and make adjustments to promote better sleep quality.
  • Garmin Health PulseOx: This data source delivers information on the user's blood oxygen saturation levels (SpO2), which is essential for understanding oxygen delivery and utilization in the body. This can be useful for monitoring overall health, fitness, and altitude acclimatization.
  • Garmin Health Stress: This data source measures a user's stress levels based on various physiological parameters, including heart rate variability. It can help users identify periods of high stress and develop strategies to manage and reduce stress.
  • Garmin Health Body Composition: This data source provides information on a user's body composition, including body fat percentage, lean mass, and bone mass. This data can help users track their progress and make informed decisions about their fitness and nutrition goals.

How to Use Garmin in Your Ethica Study

Integrating Garmin into your study in Ethica is very similar to including any other data source in your study, like GPS or Pedometer. All you need to do is to go to the Researcher Dashboard, choose your study, navigate to the Data Sources page, click on Add New Data Source, and in the dialog that opens, scroll to find the Garmin category. There, you can choose the data source that you are interested in.

Of course, depending on your study protocol, this may complicate the participant selection, enrollment, and onboarding. Most people do not own a Garmin wearable, let alone a suitable device that can provide the data you are looking for. So you need to plan how to provision wearables and provide it to participants. Further, participants need to have an active account with Garmin via their mobile app before they can set up and use the wearable. All these steps can be done during a participant onboarding process, though they inevitably make the onboarding session lengthier.

Assuming you have added the data source to your study, and planned for providing participants with the proper wearable, and help them set up their device, you should be all set. Ethica’s mobile app will take care of connecting to the Garmin app, requesting the proper permissions from the participants, and periodically move the data from participant’s Garmin account to your study’s database. You can use Ethica’s researcher dashboard to monitor the data flow and visualize the incoming data.


Incorporating Garmin wearables into your health research projects with Ethica's seamless integration offers a multitude of benefits. From cost-effectiveness to consumer-friendly design, Garmin devices have the potential to revolutionize your study. By leveraging the wealth of health metrics available through these devices, you can gain a deeper understanding of various factors affecting human health and well-being.

In this post, I tried to introduce this new feature in Ethica, and explain how Garmin may benefit your research. You can check our documentation for in-depth description of the above topics. In the future posts, I will go deeper and discuss different interesting use-cases, from how you can use the data coming in real-time to prompt surveys and interventions, to visualizations and data analysis.