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This is a Experimental Study study.

October 11, 2025Journal of biomimetics, biomaterials and biomedical engineering

A 3D Printing Soft Prosthesis and an IoT Architecture for Controlling Gestures

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The prosthesis achieved a precision of 91.25% in gesture recognition, enhancing user control.
Integrating soft 3D printing materials improves grasping abilities, adapting to various object shapes effectively.
The system uses a neural network for efficient gesture control, demonstrating advancements in prosthetic technology.
Myoelectric sensors enable users to perform three distinct hand gestures, promoting greater usability.

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Implication

This work demonstrates a low-cost active prosthesis using a myoelectric sensor for three gestures, suggesting new advancements in upper limb prosthetics.

Cite This Study

Ordóñez-Ávila et al. (2025) studied this question.

synapsesocial.com/papers/68e9b1c9ba7d64b6fc1325d2 https://doi.org/10.4028/p-y0nyin

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Implication

This work demonstrates a low-cost active prosthesis using a myoelectric sensor for three gestures, suggesting new advancements in upper limb prosthetics.

A 3D Printing Soft Prosthesis and an IoT Architecture for Controlling Gestures

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Implication

Cite This Study

A 3D Printing Soft Prosthesis and an IoT Architecture for Controlling Gestures

Key Points

Discussion

Implication

Cite This Study

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