Physiqual: a new method to combine sensor technology with ecological momentary assessments


Wearables like smartwatches have becoming more and more popular. They offer good opportunities for people to measure their body and mental health.

With a smartwatch or activity tracker, you can monitor your sleep patterns, calories used, heart rate, and mood.

These wearables can provide sufficient and accurate data, and they may replace self-report questionnaire about physical activities.

Nevertheless, it is not easy to integrate these data and get useful information because of the various data format and tracking service.

In a study recently published in Journal of Biomedical Informatics, researchers designed Physiqual to solve the problem.

Physiqual is an open-source platform for people to gather body data from wearables like smartwatches.

In one experiment, participants measure themselves using different smartwatches. Then the data were transferred to Physiqual online and integrated into one unified format for analysis.

Physiqual is designed to be compatible with several service providers. One is Google Fit, which can capture and manage data from lots of devices.

For instance, Android Wear, an OS for smartwatches and other wearables, has apps for Google Fit. One can track heart rate using a smartwatch.

Another service provider is Fitbit. It currently offers 8 different wearables, and their functions range from counting steps to monitoring heart rate and tracking locations.

Physiqual integrates data in several ways. For steps, distances, and used calories, it calculates their respective sums over a certain time-span. For heart rate, it calculates the rate that is measured most frequently during a time interval.

In the future, researchers will test how well Physiqual can integrate data from other platforms like NikeFuel, Jawbone, and Misfit.

Citation: Blaauw FJ, et al. (2016). Let’s get Physiqual – an intuitive and generic method to combine sensor technology with ecological momentary assessments. Journal of Biomedical Informatics, In Press. doi:10.1016/j.jbi.2016.08.001
Figure legend: This image is credited to Blaauw FJ et al.