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Related Experiment Video

Updated: Jun 6, 2026

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

Remote tactile sensing glove-based system.

Martin O Culjat¹, Ji Son, Richard E Fan

¹UCLA Departments of Bioengineering and Surgery, UCSB Department of Electrical and Computer Engineering, and the UCLA Center for Advanced Surgical and Interventional Technology (CASIT), Los Angeles, CA 90095, USA. mculjat@mednet.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|November 25, 2010

Summary

This summary is machine-generated.

Researchers developed a glove system for remote touch sensation. This tactile feedback system accurately conveyed finger stimuli, enabling applications in virtual reality and remote surgery.

Related Experiment Videos

Last Updated: Jun 6, 2026

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

Area of Science:

Robotics and Human-Computer Interaction
Haptics and Sensory Feedback

Background:

Remote interaction often lacks tactile feedback, limiting immersion and precision.
Existing systems struggle to replicate nuanced touch sensations effectively.

Purpose of the Study:

To develop and evaluate a glove-based master-slave system for remote tactile feedback.
To enable users to perceive touch stimuli transmitted from a remote location.

Main Methods:

A master glove with piezoresistive force sensors and a slave glove with pneumatic actuators were developed.
A control system translated detected forces into discrete pressure levels for the slave glove.

Main Results:

Users could accurately identify the stimulated finger with 99.3% accuracy.
Users detected three simultaneous finger stimuli with 90.2% accuracy in separate rooms.

Conclusions:

The developed glove-based tactile feedback system effectively transmits touch information remotely.
Potential applications include virtual reality, rehabilitation, remote surgery, and robotics.