We are four coworkers in medical IT development. We love to analyze and build medical constant and then extract strategic information. Today, the emotional impact and the interest on a product are the most important things for many firms. But how can we know the truth in a feedback writed by the client. It is impossible, that’s why we created Focus, a solution to extract the truth, the real interest and the real attention from a customer.

What it does

Focus use the captors of the Muse Headband and send the datas to the Algolia index. Datas are synchronized with the media during the analyze. On our web application, we retrieves those data and compute it to build and analyze workable outcome. To compute we used some medical article from the institutions such as University of Toronto or Max Planck Institute for Cognitive and Brain Science

How we built it

Focus is a solution composed of 2 parts:

  • The mobile part with :
    • An iOS native application built with Swift using the MuseSDK to manipulate data, the AlgoliaAPI to store data and the Youtube API to manage media
    • An Android native application build with Java using the MuseSDK to manipulate data, the AlgoliaAPI to store data and the Youtube API to manage media
  • The Web part is serverless, it uses the Algolia Index to manage datas. Then, those datas are computed with some algoritmics and at the end, displayed with D3js (Data Driven Document)

Challenges we ran into

We ran into the Hemera challenge. We built an innovating solution to answer about a real need. Today every company wants to know how customers feel about their products. Now they can with Focus, a deep conscious analyze to detect when a customer loose his attention. Actually, feedback are generally done with satisfaction forms, we really want to bring an revolution to the sector.

We also want to win the Bloomberg best tech challenge. In fact, we created three applications, two native mobile applications (Android and iOS) and front-end applications, all of them use Algolia solution. For the Android and iOS applications, we took control of the muse headband SDK. We also have used a lot of tools on our application like UnderscoreJS or D3.js. Finally, we found a solution to extract and compute data to detect the attention of the audience. For this we needed to learn about medical articles and implement it in our solution.

Accomplishments that we’re proud of

We are really proud about the data analysis, we know if we use acknowledgment of a doctor in neuroscience we can work deeply to offer to a company the best customer, spectators or any kind of audience, feedback.

What we learned

We work together since 3 years ago but the challenge revealed our capacity to balance work in each one of them and how we can build a Proof of concepts (POC) quickly.

What’s next for Focus

We think the focus solution can be exploited to create new firm, and try to revolution the feedback client. The next step for us is to build a business plan to decide if it’s the right way to go.

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