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About App

A smart app that would adapt your environment to your needs. Using (IoT),a wearable Device and the power of TensorFlow we try to detect and help you get through your struggles throughout the day and night youtube link

Announcement (Stila + Xtrinsic) cooperation for Mental health therapy

We are very pleased to announce that our meeting with Mr. Yingding Wang at the Google Networking event in Munich has resulted to a full cooperation between STILA and our project Xtrinsic. STILA Mr. Wang and we share the same goal of accelerating the development of wearable solutions for mental health therapy. This cooperation has a special meaning and impact, not only because the STILA project was a winner of the Google Developer Challenge 2020 but also because it saves us almost 2 years of development that Mr. Wang has invested in his project. Starting 1st of June the STILA stress detector is fully integrated in our Xtrinsic app through a content provider. We have already started developing smart actions based on the STILA Stress Score. (Stila app is required on Phone & Watch)

MVP Components and features checklist:

on The Watch Side:

  • finding a WearOS3 Device with the right sensors for data gathering (using Galaxy SmartWatch4)
  • Syncing Data between watch and phone, done using Google Health API (no need for extra WearableApp). API depricated May.2022, alternative solution using STILA content provider
  • Synch data directly with the Phone via bluetooth. (Using STILA watch app)

On The Phone Side:

  • Phone App with Graphs, Buttons and placeholders to present our Idea.
  • Phone UI, done using Flutter.
  • Backend for a button to send a text command to google Assisstant
  • Smart devices management: managed by Google home and triggered by google assisstant.
  • trigger simulator button: a button that would simulate how the app would function after all the features are implemented (for presenting and debugging )
  • develope algorithms for mental health and behavior therapy (long sitting sessions, Stress detection, Nightmare detection)

Done (during Google Mentorship phase)

  • integrate the developed algorithms in the app
  • convert the TensorFlow model to TensorFlow light
  • add firebase database for storing data
  • fetch the data on the PHone from the Google Health API (the API was deprecated on May 10th, we are looking for alternatives)

future steps (after top10 phase)

  • integrate DialogFlow in our app
  • starting a clinical study at one or more of the partner universities (TF-Freiburg, TU Munich, KPI Kyiv)
  • seeking a sponsor for server hosting and needed hardware (smartwatch or fitbit)
  • [ ]

Build The App

Using the Mobile Application

The Sign Up and Log in function does not work yet, so just click Sign Up to begin to use the application as it takes you directly to the onboarding screen explaining the aim of the app with how to use it.

Then next to the Home Screen, the first card under Features named Nightmare is clickable to show the main idea of the application.

On this Page,

Implemented Buttons/Features

The rate your sleep button works with the idea of allowing the user rate last nights sleep. Click the Enter a Google Home command button to enter a command and then click save to go back. Now you can click the simulate trigger to simulate the trigger of sending a command to Googl Assistant (this will be done by the watch for the main implementation).

Fig.1 - L-R A pathway from the Registration screen to the Detail Page that covers the usage of the application.

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