Bioelectrical and Neuroengineering Commons^™

The Effect Of Spinal Cord Stimulation And Video Games Training On Body-Machine Interface Control, Jie Fei

McKelvey School of Engineering Graduate Student Theses & Dissertations

Damage to the spinal cord causes long-lasting loss of motor and sensory function, and currently, there is no ‘cure’ for paralysis. However, even people with severe spinal cord injuries (SCI) have some residual mobility. Studies have shown that transcutaneous electrical spinal cord stimulation (tSCS) combined with functional training targeting residual mobility can further improve the motor function of individuals with SCI. In this study, we present a technical framework that aims to enhance rehabilitation outcomes by targeting residual mobility through a motor training-based approach. Our technical framework centers around a non-invasive body-machine interface (BoMI) that relies on the use of …

Advancing Prosthetic Design Using Neural And Mechanical Dynamics, Kacie E. Hanna

Graduate Theses, Dissertations, and Problem Reports (ETD)

Limb loss poses a significant challenge to mobility and the performance of daily activities. Currently, nearly half of the amputees using powered prosthetics abandon their device due to inadequate limb coordination and movement control abilities. In the healthy system, passive and neural dynamics facilitate the synchronized activation of muscles necessary for coordinated movement. However, in the amputee, the system is disrupted. The goal of this research is to use neural and mechanical dynamics to inform the design of prosthetic devices in order to restore intuitive control and coordinated limb movement.

The first aim of this research is to investigate neural …

Finding A Viable Neural Network Architecture For Use With Upper Limb Prosthetics, Maxwell Lavin

Master of Science in Computer Science Theses

This paper attempts to answer the question of if it’s possible to produce a simple, quick, and accurate neural network for the use in upper-limb prosthetics. Through the implementation of convolutional and artificial neural networks and feature extraction on electromyographic data different possible architectures are examined with regards to processing time, complexity, and accuracy. It is found that the most accurate architecture is a multi-entry categorical cross entropy convolutional neural network with 100% accuracy. The issue is that it is also the slowest method requiring 9 minutes to run. The next best method found was a single-entry binary cross entropy …

Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler

Master's Theses

Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems …

Eeg And Emg Sensorimotor Measurements To Assess Proprioception Following Acl Reconstruction, Teagan Frances Northrup

Honors Theses and Capstones

The Anterior Cruciate Ligament (ACL) is the primary source of rotational stability in the knee by preventing the tibia from sliding in front of the femur. When the ACL is torn, it typically must be repaired through reconstructive surgery which results in proprioceptive deficiencies in the knee. Proprioception plays an important role in understanding where one’s knee is in space, sensing movement and reacting accordingly. This study examines an alternative method of measuring proprioceptive responses to a stimulus (motion) by using electromyogram (EMG) and electroencephalogram (EEG) signals to observe muscle and brain activity. Two participants (one with an ACL reconstruction …