Set of mobile applications for fitness

Mobile applications have been implemented that work in pair and allow the trainer to create a training program, as well as to track the schedule and results of their clients. For clients of a fitness trainer, a mobile application has also been implemented, which is a personal profile, where statistics and results for the entire time of training are displayed.

  • Analytics
  • Mobile
  • Testing
[a]Set of[/a] mobile applications for fitness

Goal And Tasks

The purpose of the app is to provide a clients personal training diary to their trainer

[a]Set of[/a] mobile applications for fitness
  • 01Gathering requirements
  • 02Market analysis
  • 03Development of requirement specification
  • 04Architecture
  • 05Designing integrations between AQ Trainer and AQ Client applications
  • 06Designing integrations with calorie counting and pedometer apps


In the Athletic Quotient application, the client has access to: - training statistics. - determination of the effectiveness of the training process using AQ points that are gained during classes with a personal trainer. - implemented integration with Apple Health to collect calories burned per day, which are summed up with calories burned for training. Information about calories consumed is also collected. Due to this, the program calculates the balance of calories (surplus or deficit) for the selected period (week/month/year).



AQ Trainer is an electronic training diary that a trainer keeps for each client. The scoring system for the physical activities allows you to involve the client in the training process and analyze the results. The application also allows you to connect a heart rate sensor via Bluetooth and monitor the client's pulse during the session. The collected training data is sent to the AQ Client app. Also, the application maintains personal statistics of the trainer on the number of training sessions and visits for each client.



  • 01Statistics after each workout
  • 02GoogleFit and Apple Health integrations
  • 03Calculation of the metabolic rate based on personal indicators
  • 04Getting heart rate data from sensors
  • 05Interaction language: Russian, English and Arabic

Technologies used

  • Python
  • Postgresql
  • Docker
  • Firebase
  • Flutter
  • Dart
  • BLoC
  • Dio
  • Django
  • Docker-Compose
  • Hive
  • BLE


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