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Design and Pilot Evaluation of a Prototype Sensorized Trunk Exoskeleton.

Dalton Hass, Benjamin A Miller, Boyi Dai

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 11, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a sensorized passive trunk exoskeleton to reduce physical strain. Pilot tests show its potential for improving wearer stability and guiding movement in demanding tasks.

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    Area of Science:

    • Biomechanics
    • Wearable Robotics
    • Human Augmentation

    Background:

    • Physically demanding tasks increase biomechanical loads on the trunk.
    • Wearable exoskeletons offer a solution to reduce these loads and enhance stability.
    • Sensor integration is crucial for understanding exoskeleton-wearer interaction.

    Purpose of the Study:

    • To present a prototype sensorized passive trunk exoskeleton.
    • To evaluate the feasibility of the sensorized exoskeleton in everyday tasks.
    • To explore potential applications for advanced exoskeleton designs.

    Main Methods:

    • Developed a passive trunk exoskeleton with integrated sensors: 5 motion processing units, 4 flex sensors, and 2 force sensors.
    • Conducted a pilot evaluation with two wearers performing various daily activities.
    • Collected sensor data during tasks such as sitting, standing, walking, and lifting.

    Main Results:

    • The sensorized trunk exoskeleton successfully captured biomechanical data during diverse tasks.
    • Illustrative graphs demonstrated the system's ability to measure wearer-exoskeleton interaction forces and motion.
    • The pilot study provided initial insights into the exoskeleton's performance and data acquisition capabilities.

    Conclusions:

    • The sensorized passive trunk exoskeleton is a viable prototype for biomechanical load reduction.
    • The integrated sensor system provides valuable data for understanding trunk movements and forces.
    • This technology can serve as a foundation for semi-active exoskeletons and advanced feedback systems.