I was sitting in Tisch library, looking through other people’s Instagram feed, and I thought, “Wow, all these people are living a glamorous life, and I’m sitting here, in Tisch, for 4 hours, to figure out how to fix 19 errors in my program.

And then, I looked through my past Instagram posts, and the person I saw in my posts was not someone who I consider myself to be. I looked like I’m having so much fun in life.

We use social media to display our own image that we wish other people to see. When we look back through our feed, we often realize that our image displayed in social media doesn’t accurately depict us at all.

On Instagram, some of us might look like social media influencers that are only here for positive vibes; on twitter, some of us might look like monsters who have nothing but aggressive opinions.

But our lives cannot be defined with one single emotion we want to display. If we choose not to record certain emotions, we are losing access to those parts of our lives.

My mobile app, log’em, captures every memorable moment in your life and creates a journal for you automatically. log’em will remind you that life is a mosaic of vibrant colors of emotions, and every moment of your life has been worth remembering.

What it does

This product utilizes electrocardiogram (ECG) data that can be detected from smartwatches. According to a research published by the Institute of Electrical and Electronics Engineers, by using ECG data, we can extract heart rate variability (HRV) features based on time-domain, frequency-domain, and statistical analysis.

Then, HRV features could be classified into different emotional states by using support vectors machine (SVM). According to this research, we can identify basic emotions (e.g. happy, sad, angry, scared, and relaxed).

Based on this information, this app displays what emotions users have felt in different colors.

Users can be anonymous or even choose not to display their emotions to any other people. In this case, this app would serve its functionality as a digital diary.

Users can see how other people around them are feeling. They can instantly receive emotional information about certain locations. This functionality could be used as a safety alert.

How I built it

I used three user experience research methods (e.g. empathy interview, empathy map, and card sorting) to find out how users associate memory with space and how current social media apps make them feel.

Based on the results from card sorting method, I organized information architecture in a way that would be highly intuitive for users.

By using Adobe XD, I built an interactive prototype of a mobile app that will carry out basic functions from logging in, displaying certain emotions, checking .

Challenges I ran into

I had to conduct user experience research and design, analyze the data, and produce a high-fidelity prototype of a mobile app by myself. At the beginning, user research took up more time than I initially thought it would take. Nonetheless, I didn’t hastily move on to the actual development of the prototype because I believe that an app that is counterintuitive to use is worse than not having that app.

After using card sorting method, I could structure information that users can easily discover when they interact with log’em.

Accomplishments that I'm proud of

I am proud of conducting user experience research methods and applying the findings to the user interface design. Because I worked as an individual, I had to carry out a lot of different roles by myself. However, I believe I have created an aesthetically pleasing prototype that is also very intuitive for users.

What I learned

Before Polyhack, I knew how to conduct a variety of user experience research methods, but I wasn’t sure how to apply the findings into making a prototype. Through this experience, I learned a lot about how to apply user experience research methods, like empathy map, to discover what the users need and want and how to design my program that will display information in an intuitive way.

What's next for log'em

The next step would be to implement this by programming. After identifying an emotional state using HRV and SVM, I can parse the data through JSON. Then, by using MongoDB, I can store each dataset into a data structure. And based on user requests from the mobile application, I can pull a dataset from the database and display it accordingly on the Google Map API.

Also, there is a need for additional research on data visualization. To illustrate, I would have to calculate how to visualize ECG data into circles. Each emotional experience would have to be displayed that has a different width and color.

Built With

  • google-material-icon-ui-kit
  • ios-native-ui-kit
  • xd
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