Date of Award

4-23-2025

Document Type

Thesis

Degree Name

Master of Science in Mechanical Engineering (MSME)

Department

Mechanical Engineering

First Advisor

Joel Canino

Second Advisor

Rebecca Bercich

Third Advisor

Cheuk Ming Lui

Abstract

Robotic rehabilitation systems are increasingly used to restore sensorimotor functions for individuals with disabilities. However, many assistive devices lack sensory feedback, which is essential information for user control and embodiment. Haptic feedback is a simple and non-invasive solution to provide sensory feedback through tactile stimulation. Errors in haptic feedback can reduce the device’s effectiveness. This study aims to investigate whether error-related potentials can be detected when evoked through errors in haptic feedback during elbow flexion and extension. Electroencephalography recordings showed statistically significant decreases in power spectral density under the conditions of 12.5 Hz, 2.8 and 4.0 seconds after the onset of an error. These findings support that error-related potentials can be evoked through tactile stimulation. The detection of error-related potentials can assist robotic rehabilitation 3 systems, with possible real-time error classification, advanced control strategies, and automated training.

Download

Share

COinS