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    Wearable devices generate vast biometric data but have limited resources. This study introduces energy-efficient codebook-based (CB) compression algorithms to optimize data storage and transmission for wearables.

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    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Computer Science

    Background:

    • Wearable devices collect extensive biometric data for healthcare and fitness.
    • Constraints in memory, transmission, and energy necessitate efficient data management algorithms.
    • Existing methods require optimization for resource-limited wearable technology.

    Purpose of the Study:

    • To analyze and quantify the complexity and performance of selected lossy data compression techniques for biometric signals.
    • To propose a novel class of energy-efficient, online codebook-based (CB) compression algorithms for signals with recurrent patterns.
    • To assess the advantages of CB schemes in memory savings and their impact on classification algorithms.

    Main Methods:

    • Evaluation of selected lossy data compression techniques for biometric signals.
    • Development and proposal of a new class of codebook-based (CB) compression algorithms.
    • Performance assessment comparing CB schemes against selected techniques, focusing on energy efficiency and compression performance.

    Main Results:

    • Analysis quantified the complexity and compression performance of various techniques.
    • The proposed codebook-based (CB) algorithms demonstrated energy efficiency and suitability for online processing.
    • CB schemes showed significant advantages in memory savings and improved classification algorithm performance.

    Conclusions:

    • Lightweight, effective algorithms are crucial for managing the massive data from wearables.
    • Codebook-based (CB) compression offers a promising solution for energy-efficient data management in wearables.
    • The proposed CB algorithms enhance memory efficiency and support effective data analysis for personalized healthcare and fitness applications.