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Wireless Pressure Sensor Array Module for Sensorized Object.

Guan Ming Lim, Prayook Jatesiktat, Christopher Wee Keong Kuah

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 12, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a sensorized object module that maps hand grasp pressure distribution. This technology enhances rehabilitation by providing therapists with detailed grasping data beyond visual observation.

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    Area of Science:

    • Biomedical Engineering
    • Rehabilitation Technology
    • Sensor Systems

    Background:

    • Rehabilitation assessments often lack detailed hand-object interaction data.
    • Grasping parameters are crucial for effective hand function evaluation.
    • Existing methods may not capture subtle pressure variations during object manipulation.

    Purpose of the Study:

    • To develop and evaluate a novel sensorized object module for capturing pressure distribution maps during hand-object interaction.
    • To enhance the quantitative assessment of grasping parameters in rehabilitation.
    • To provide therapists with objective data to complement visual assessments.

    Main Methods:

    • A pressure sensor array module was integrated into objects (cylindrical and cuboid) with up to 1024 sensing elements.
    • Wireless data transfer at over 30 Hz was implemented for real-time monitoring.
    • The module's sensitivity, object shape depiction, and performance in object pose estimation and hand grasp classification were assessed.

    Main Results:

    • The sensorized module accurately generates pressure distribution maps, sensitive to subtle pressure changes.
    • It demonstrated reasonable detail in depicting object shapes, with small errors in pose estimation.
    • High accuracy scores were achieved for hand grasp classification.
    • The system supports efficient wireless data transfer.

    Conclusions:

    • The developed sensorized object module provides a valuable tool for quantitative analysis of grasping parameters in rehabilitation.
    • Its modular design and wireless capabilities facilitate integration into various objects, creating smart sensing surfaces.
    • This technology offers clinical relevance by enabling therapists to analyze critical grasping data not visible through observation alone.