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Updated: Aug 4, 2025

Harmonic Radar Tags for Insect Tracking: Lightweight, Low-cost, and Accessible
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tinyRadar for Fitness: A Contactless Framework for Edge Computing.

Satyapreet Singh Yadav, Radha Agarwal, Kola Bharath

    IEEE Transactions on Biomedical Circuits and Systems
    |April 6, 2023
    PubMed
    Summary
    This summary is machine-generated.

    tinyRadar, a novel millimeter wave (mmWave) radar fitness tracker, offers a comfortable and private solution for personalized healthcare. It accurately tracks exercises and repetitions using on-board processing, enhancing smart home fitness monitoring.

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    Area of Science:

    • Biomedical Engineering
    • Wearable Technology
    • Signal Processing

    Background:

    • Conventional fitness trackers face challenges like skin discomfort, inaccurate readings, and privacy risks due to prolonged wear and data transmission.
    • The shift towards personalized healthcare necessitates innovative solutions for continuous, reliable health monitoring.

    Purpose of the Study:

    • To introduce tinyRadar, an on-edge millimeter wave (mmWave) radar-based fitness tracker designed to overcome the limitations of current wearable devices.
    • To develop a compact, privacy-preserving fitness tracker suitable for smart home environments.

    Main Methods:

    • Utilized a Texas Instruments IWR1843 mmWave radar board for exercise recognition and repetition counting.
    • Implemented signal processing and a Convolutional Neural Network (CNN) on-board for real-time analysis.
    • Interfaced the radar board with ESP32 for data transfer to smartphones via Bluetooth Low Energy (BLE).

    Main Results:

    • Achieved 96% average accuracy in real-time repetition counting.
    • Demonstrated 97% subject-independent classification accuracy for exercise types.
    • The on-board CNN model exhibited low memory utilization (11.36 KB total, 1.46 KB for parameters).

    Conclusions:

    • tinyRadar effectively addresses discomfort and privacy concerns associated with traditional fitness trackers.
    • The mmWave radar-based approach provides accurate and efficient exercise tracking in a small form factor.
    • This technology is well-suited for personalized, real-time fitness monitoring within a smart home setting.