Opportunity in self tracking

The capability to track and measure your fitness, activity and health are one of the main features for wearables such as the smart watch and fitness bands.

Even though it´s hard to design to create a real purpose it´s a powerful application. As Lundin and Zhang wrote when they researched about e-society and the subject “virtual” version of e-society in the article Understanding e-Society by E, D and V¹.

“Visibility can be dedicated to describe phenomena brought from a virtual world. In the real world we see only what can be seen like a mountain and a house due to our limited seeing ability. […] The biggest advantage of such kind of visibility lies in that we control what we don’t see.“

And they also write on the same page:

“It has provided us more than another virtual world, but also visions from a real world development, values for being virtualized and some visibility for being able to see invisible things, and great milestones achieved ever in human’s history.”

This is some of the applications you as a consumer can use right now:

Fitbit Fitbit

Google Fit Google Fit

Moves Moves

Apple health Apple health

Human Human

Do you see any similarities and deficiencies?

My rambling thoughts on these applications are that they take it one step too short. They only measure maybe steps, time, food intake, sleep etc. It feels like they are using the easy way to create a interface for your fitness and health.

Because of the interface currently showing only the steps there are a knowledge gap and the only people interested in these kinds of applications are the people that can understand the impact of the data measured in their life.

From my perspective it seems like we are still in the command line era of computing with wearables and measuring health and fitness. You need to know and have real expertise to use these products at least efficiently.

There needs to be a interface that really can create a opportunity for people to use and collect their data in a more meaningful way. When I take and measure my 1000 extra steps what do I benefit from it? Do I feel happier, more satisfied, calmer, am I more productive, am I more social? If we can answer these kind of questions, qualitative and quantitative data of what I send out (output?) and the combinations of these we can create a real interface for what wearables should have (in my current opinion).

Because of when “regular” people (a dangerous expression I know) want to change and get healthier it´s not the 1000 extra steps that are the interesting part. Their mental model of the activity have a goal and the tracking should aid them in that goal. Right now the application and their interface only show the fitness data. The effect is that from my point of view it´s only the people that are interested in the data that use them. The collection and fascination of their own fitness data are the purpose of using the applications, not to get healthier or meet some other goal. The goal of the use of the applications are to collect data and not to change or act upon it. And the applications don’t show any data that you can actually act upon.

A study by researchers from Washington University looked at data collected with the Moves app. Afterward, the researchers sliced into the data generated by each person to pull out “cuts,” or subsets, to help participants explore their data and discover trends.

They then displayed these relationships through a series of visualizations, including graphs, tables and maps.

All of the participants found the information to be more helpful in achieving fitness and activity goals than if they simply used the smartphone app.

Now this result are not really that surprising. Having scientist comb through your data and presenting it in a easy digestible way are not really an revolutionary idea. But it shows that we still have not found a good solution for this kind of information.

And if we want to look at the problem a little more we could look at it with the activity theory framework. Activity theory are a framework pioneered by Lev Vygotsky, Alexei Leont’ev and Sergei Rubinstein. Further developed by scandinavian researches in the 80s, Yrjö Engström and more.

First Generation Activity Theory Model First Generation Activity Theory Model

Further Developed Activity Theory Further Developed Activity Theory

The activity theory² framework is object orientedness where actors are engaged in activities. The artifacts are tools which mediates (are used) by the actor in the system. The tools influence the actors and the structure. Tools are influenced by culture and are a transmission of social knowledge.

If you think about these apps as tools and try to force these activities in the activity framework (in a first generation framework, coz im lazy :) ) the actors (users in our case) are involved in when they use these apps. We can see in my idealistic world the applications should act as tools to mediate the object to get leaner, fitter, healthier etc. And the outcome are more personal as, getting a partner, feeling happier etc.

My ideal applied activity theory framework My ideal applied activity theory framework

If I would try to fit how users now are involved in the activity theory framework the object are the data collected and the fascination of it. The outcome are to get fitter and healthier maybe.

Applied activity theory, how it is now? Applied activity theory, how it is now?

One question I ask myself is if the users are entering their use of these apps with this object or if the tool (app) are influencing them to be more interested in the data collected or if the users attracted to these kind of apps already have this interest.

When more of this wearables and health tracking devices get more common we as “designers” might think about how we create behaviour and how our tools mediate our users.

If their goals are really met or if they might lose track of their goals and really find your data to be more interesting…

I would advocate to measure the outcome or/and object a user wants to achieve. Then we really have something where wearables and data tracking might provide real value.

  1. Zhang, X., & Lundin, H. (2004). Understanding e-Society by E, D and V. ,
  2. Kaptelinin, Victor (2013): Activity Theory. In: Soegaard, Mads and Dam, Rikke Friis (eds.). “The Encyclopedia of Human-Computer Interaction, 2nd Ed.”. Aarhus, Denmark: The Interaction Design Foundation. Available online at
  3. D A. Epstein, F. Cordeiro, E. Bales, J. Fogarty, S. A. Munson (2014) Taming Data Complexity in Lifelogs: Exploring Visual Cuts of Personal Informatics Data, University of Washington,

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