A low-cost prosthetic arm with real-time haptic feedback and gesture control for enhanced user autonomy

In daily life, manipulating and feeling objects is essential for autonomy and engagement in various activities. However, individuals relying on prosthetic limbs often encounter barriers such as high costs, ineffective feedback, and limited design adaptability. Unlike conventional prosthetic limbs, which frequently struggle to integrate seamlessly and provide intuitive control, the robotic arm outlined in this study represents a leap in functionality and user experience. At the core of its design lies a specialized glove outfitted with a calibrated array of flex-sensing resistors capable of precisely detecting and interpreting the wearer's movements. These sensors input to the robotic arm, translating the user's gestures into motions that follow human hands. The fingertips are equipped with force-sensing resistors to discern the magnitude of force applied during gripping actions. This real-time sensory feedback is conveyed to the user through a haptic system integrated into the glove. By modulating the intensity and pattern of vibrations, users can gauge their grip strength and manipulate their grasp of the object accordingly. Comprehensive experiments were conducted across various scenarios to assess its performance, agility, strength, and sensory accuracy. Through refinement, the author aims to optimize functionality and reliability, enhancing practicality for users. This project has broader implications for the prosthetics community. By utilizing the scalability and cost-effectiveness of this model, the author envisions tailored solutions that empower individuals with limb differences to live more independently.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2024-10-19
DOI
https://doi.org/10.30574/wjarr.2024.24.1.3050
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
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article

A low-cost prosthetic arm with real-time haptic feedback and gesture control for enhanced user autonomy

Nikhil Sakthirajan
World Journal of Advanced Research and Reviews
Muscle activation and electromyography studies
article

A low-cost prosthetic arm with real-time haptic feedback and gesture control for enhanced user autonomy

Nikhil Sakthirajan
article en

Abstract

In daily life, manipulating and feeling objects is essential for autonomy and engagement in various activities. However, individuals relying on prosthetic limbs often encounter barriers such as high costs, ineffective feedback, and limited design adaptability. Unlike conventional prosthetic limbs, which frequently struggle to integrate seamlessly and provide intuitive control, the robotic arm outlined in this study represents a leap in functionality and user experience. At the core of its design lies a specialized glove outfitted with a calibrated array of flex-sensing resistors capable of precisely detecting and interpreting the wearer's movements. These sensors input to the robotic arm, translating the user's gestures into motions that follow human hands. The fingertips are equipped with force-sensing resistors to discern the magnitude of force applied during gripping actions. This real-time sensory feedback is conveyed to the user through a haptic system integrated into the glove. By modulating the intensity and pattern of vibrations, users can gauge their grip strength and manipulate their grasp of the object accordingly. Comprehensive experiments were conducted across various scenarios to assess its performance, agility, strength, and sensory accuracy. Through refinement, the author aims to optimize functionality and reliability, enhancing practicality for users. This project has broader implications for the prosthetics community. By utilizing the scalability and cost-effectiveness of this model, the author envisions tailored solutions that empower individuals with limb differences to live more independently.

World Journal of Advanced Research and ReviewsVol. 24(1)
Openalex Percentile: Top 83%
Muscle activation and electromyography studies
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