What we might learn about ourselves by combining data from multiple wearables

Who knows your personal patterns best? If you thought of your friends and family — consider someone who never leaves your side, your wearable device(s). What could they tell you?

By combining information from all your wearables, including your phone, into the same place, you can look at your holistic data points and answer interesting questions. Well, at least start interesting arguments with and pose more questions. With Prifina, that “one place” is actually your personal data cloud. Having data on your side allows you to really utilize it and build on top of it.

During the previous pandemic year…


These days, more and more cities use sensors to track and measure different environmental conditions, from traffic flow to particles in the air like pollution and allergens. Many cities want to use this data to become “smarter”, giving them greater insight into the problems they face and the solutions to those problems. Individuals also have access to more and more data about their lives and activity, much of which is gathered by wearable sensors like FitBit and Oura Ring. This increase in both personal wearable data and public sensor data presents a unique opportunity to create smarter cities and even smarter residents.

Google Maps optimizes trips by looking at congestion in traffic. Municipal agencies push alerts and notifications to residents based on notable events, such as air quality deterioration during forest fires. These are great examples of how public data can be used on a large scale and pushing down actions to individual segments.

Image courtesy of Upklyak

By combining this large scale public data with data that measures my own patterns, such as exercise history and recovery, I can determine what may have impacted my general well-being by referencing exposure to environmental conditions with measurements gathered by my wearables (such as a correlation between drowsiness…


Combining personal data sources like Oura and Fitbit, we draw conclusions on how to handle errors, variance and complements

Using a graphing tool on Prifina, we can look at a user’s wearables data, compare different data points for the same time intervals, explore correlations and variations in the data itself. We can explore data from the same user, for the same interval (day, week, month) for different wearable devices.

Image via Drobotdean (Freepik)

Outside of the entertainment value of playing with fascinating data and potential insights from it, we find variance in the same data points and raise the question of what data point our application should trust, how to deal with the variance overall between a large pool of personal devices and…


Wearables are here to stay. Devices such as Fitbit now boast about 30M active users — which is greater than the number of active software developers on the planet — and are only growing more popular as time passes.

Photo by Cottonbro from Pexels

Wearables come in all shapes and sizes, and perform a variety of functions. I was privileged enough to get to test out a new device by the company Veri, which provides real time data on blood glucose. It got me thinking: outside of monitoring illnesses like diabetes, what benefits can we unlock by tracking our blood glucose levels?

But first, here…


The Prifina team wants to thank all our friends and colleagues for your support during 2020. In 2021, we expect to see significant market movements in personal data.

Photo by Jan Senderek of our dear and recovering San Francisco.

Inspired by a rapidly growing community of developers, we spent 2020 mostly focused on building tools for developers: we released a developer data sandbox, built a library of reusable react components, and provided contribution models (e.g., data format, retrieval function, mapping from raw to combined data) that show developers how to integrate new data sources into the data model.

We have also been working on a platform that allows individuals to manage, utilize, and control their personal data. …


Don’t we all love when songs make ‘our hearts melt’? Or when that climatic bridge throws our heart rate through the roof? What if we could engineer audio experiences based on real heart rate data?

Picture courtesy of Uncoveredlens

Even though these phrases are colloquial expressions and do not necessarily translate to your heart ‘melting’ per se, we can still use the HeartRate object as an interesting data point in designing an audio experience. Let’s look at how.

The hypothesis

In our experiment, let’s say we are looking to get our listener excited, which according to science and research says the average heart rate reading should be elevated. …


How to Sandbox Your Personal Data and Have It Work For You

What is ‘Sandboxing’?

Let’s begin by clarifying what ‘sandboxing’ can mean. Wikipedia defines a technical sandbox as:

a testing environment that isolates untested code changes and outright experimentation from the production environment or repository…

and further highlights that:

Sandboxing protects “live” servers and their data.’

For our intents and purposes, we can think of sandboxing as a way to partition a certain object (e.g. a piece of software or data) and isolate it from other objects (e.g., software or servers, in order to protect or guarantee the integrity of the certain object). …


Data portability sounds great, but it bloats data liability and still leaves the individual a prisoner of data. How can we give people true choice, without a data cost?

Data portability allows individuals to port or transfer data from one service provider to another. In practice, data portability establishes a system in which data is shared between companies under a user’s consent and direction. However, the ability to extract value directly from data still remains outside the individual’s control.

Image created by Kues on Freepik

How do we fix this? By making the user the ultimate data nexus.

Here’s how things currently work. You have a lot of shopping data with Amazon. You also have a lot of shopping data on Walmart. In fact, your data is held by Target, Safeway and many more companies. Each company has its own data silo that builds a profile about you…


People can now access all data that companies have collected about them. As per new regulations, platforms promptly* provide their customers copies of this data upon request. But are you getting all that you’re entitled to? Or are you getting short-changed?

Both GDPR and CCPA, new regulations that address data rights and data privacy, require companies to provide copies of data they’ve collected about their customers in a “consumer-friendly” format. Yet many of these reported data sets seem incomplete; why might that be the case?

(* ranges from processing the request in a matter of minutes to 30–45 days, the maximum processing time allowed under law.)

© Photo from Freepik

We’ve explored data archives from 40+ different data platforms, mainly those with the highest consumer engagement and activity (Amazon, Facebook, Google, 23andme, Ancestry, etc.).You can get copies of your data from these companies with a…


How I got my cookie data from an ad intelligence company, traced the tangled web of 3rd parties using my cookie data and felt left out.

Image by Master1305

There’s been a new category of data created along with new regulations that give individuals the right over their data, for example, the right to request their data from platforms where it exists.

Such personal data rights logically include platforms that you use. Besides, those personal data rights also extend to service providers and platforms that have data on you, even if you do not have a (known) relationship with them.

Let’s talk about those through the lens of cookies, and particularly third-party data use of cookies and data processing. In order to examine this, we used the data obtained…

Markus Lampinen

Entrepreneur in data, fintech. Likes puzzles. Passionate about personal freedom. Building separation of data from apps.

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