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    This summary is machine-generated.

    Optimal ultrasound transducer placement on the forearm enables accurate decoding of motor intent. A reduced number of ultrasound scanlines maintains high classification accuracy for muscle-computer interfaces (MCIs).

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Rehabilitation Technology

    Background:

    • Sonomyography utilizes ultrasound imaging of forearm muscles to decode volitional motor intent.
    • Muscle-computer interfaces (MCIs) offer potential for rehabilitation and gesture recognition.

    Purpose of the Study:

    • Determine optimal ultrasound transducer placement for maximum muscle deformation during hand motions.
    • Investigate the impact of sparse ultrasound scanlines on motion classification accuracy for MCIs.

    Main Methods:

    • Freehand 3D reconstructions identified optimal transducer placement (40%-50% forearm length).
    • Classification accuracy assessed using full (128) and sparse (4) scanlines.
    • Fisher criterion (FC) and mutual information (MI) evaluated scanline contribution.

    Main Results:

    • Optimal placement yielded maximum muscle deformation.
    • Average classification accuracy was 94% with full and sparse scanlines (±6% and ±5% respectively).
    • No significant accuracy improvement with optimal scanline selection using FC and MI.

    Conclusions:

    • A small subset of ultrasound scanlines is sufficient for high-accuracy motion classification with optimal transducer placement.
    • Reduced scanline usage simplifies instrumentation and lowers power consumption for wearable sonomyographic MCIs.