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Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next sampling...

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Related Experiment Video

Updated: Jul 15, 2026

Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories
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Towards Natural Prosthetic Hand Gestures: A Common-Rig and Diffusion Inpainting Pipeline.

Seungyup Ka, Taemoon Jeong, Sunwoo Kim

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    Summary

    This study introduces a new method for generating realistic prosthetic hand movements from body motion using Common-Rig and diffusion inpainting. The approach improves accuracy and diversity, enabling more natural prosthetic hand control.

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    Area of Science:

    • Robotics
    • Computer Graphics
    • Biomechanics

    Background:

    • Current prosthetic hands prioritize dexterity for functional tasks.
    • Generating natural hand movements, like finger pointing, remains an underexplored research area.
    • Existing methods lack robust solutions for synthesizing hand motion from body dynamics.

    Purpose of the Study:

    • To develop a novel pipeline for generating prosthetic hand motion from body motion.
    • To leverage advanced techniques like Common-Rig and diffusion inpainting for motion synthesis.
    • To enable more intuitive and realistic control of prosthetic hands.

    Main Methods:

    • Utilized the Common-Rig, a kinematic representation, for effective motion encoding.
    • Employed a diffusion-based inpainting technique for stable and generalized motion generation.
    • Applied the pipeline to a motion capture dataset, conditioning hand motion on body motion.

    Main Results:

    • The proposed method achieved lower fingertip positional errors compared to baseline approaches.
    • Generated hand motion diversity closely matched ground truth data.
    • The synthesized motions were successfully implemented and evaluated on a robotic prosthetic hand system.

    Conclusions:

    • The developed pipeline effectively generates realistic hand motions from body dynamics.
    • This work advances the field of prosthetic hand control by addressing the synthesis of natural movement.
    • The findings have implications for improving the naturalness and usability of prosthetic devices.