Wearable Fitness Tracker

athlete_wearing_a_fitness_tracker | IoT Solutions Provider

The primary objective of this innovative project was the development of a state-of- the-art fitness tracker. This device not only showcases power efficiency but also excels in detecting intricate velocity curves and distances associated with specific movements, marking a milestone in wearable fitness technology.


Core Components:


  • NRF52 Microcontroller:

    • Serves as the central unit, orchestrating computations and managing wireless communications with finesse.

  • Digital Pressure Sensor:

    • Accurately gauges environmental pressure, providing critical data for altitude variation measurements.

  • 6 Degrees of Freedom (DoF) Inertial Measurement Unit (IMU):

    • Captures comprehensive data on the tracker's spatial orientation and movement, ensuring precise activity tracking.

  • Battery Management IC:

    • Guarantees optimal power management, a pivotal feature for the device's operational longevity.


Structural Design:


  • PCB Layout:

    • The device is engineered with a sophisticated 4-layer Printed Circuit Board (PCB).

  • Compact Form Factor:

    • A strategic arrangement of components reduces the device's dimensions to an impressive 15mm by 25mm, ensuring portability without compromising functionality.


Data Processing and Connectivity:


  • Advanced Data Processing:

    • The integration of sensor fusion algorithms and digital signal processing techniques plays a critical role in mitigating sensor noise. This approach ensures the computation of highly accurate relative altitudes and orientation angles.

  • Efficient Communication:

    • Processed data is adeptly relayed to a mobile application via Bluetooth Low Energy (BLE), offering users real-time access to their fitness metrics.


Algorithm Development and Optimization:


  • Feature Extraction and Classification Algorithms:

    • The tracker is equipped with sophisticated algorithms designed to identify specific movement types during physical activities. This feature adds a layer of depth to activity tracking, catering to diverse user needs.

  • MATLAB Simulations:

    • Initial stages of mathematical modeling and algorithm development were conducted using MATLAB simulations. This phase was crucial for establishing a strong theoretical foundation for the device's functionality.

  • C++ Implementation:

    • Subsequent to the simulations, these algorithms were meticulously implemented in C++ and optimized to ensure their efficient


Project