Vision Controlled Sensorized Prosthetic Hand
Md Abdul Baset Sarker, Juan Pablo S. Sola, Aaron Jones, Evan Laing,, Ernesto Sola-Thomas, Masudul H. Imtiaz

TL;DR
This paper introduces a sensorized, vision-enabled prosthetic hand that mimics natural hand functions, offering a user-friendly interface without the need for personalized training, and incorporates sensors for safe and effective object manipulation.
Contribution
The paper presents a novel prosthetic hand design that uses vision and embedded sensors to eliminate the need for personalized training, enhancing usability and safety.
Findings
Successful integration of camera and sensors for grasping
Safe object handling through pressure feedback
Gesture detection with accelerometer
Abstract
This paper presents a sensorized vision-enabled prosthetic hand aimed at replicating a natural hand's performance, functionality, appearance, and comfort. The design goal was to create an accessible substitution with a user-friendly interface requiring little to no training. Our mechanical hand uses a camera and embedded processors to perform most of these tasks. The interfaced pressure sensor is used to get pressure feedback and ensure a safe grasp of the object; an accelerometer is used to detect gestures and release the object. Unlike current EMG-based designs, the prototyped hand does not require personalized training. The details of the design, trade-offs, results, and informing the next iteration are presented in this paper.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRobot Manipulation and Learning · Hand Gesture Recognition Systems
