Engineering Commons^™

Brain Computer Interface-Based Drone Control Using Gyroscopic Data From Head Movements, Ikaia Cacha Melton

Honors College Theses

This research explores the potential of using gyroscopic data from a person’s head movement to control a DJI Tello quadcopter via a Brain-Computer Interface (BCI). In this study, over 100 gyroscopic recordings capturing the X, Y and Z columns (formally known as GyroX, GyroY, GyroZ) between 4 volunteers with the Emotiv Epoc X headset were collected. The Emotiv Epoc X data captured (left, right, still, and forward) head movements of each participant associated with the DJI Tello quadcopter navigation. The data underwent thorough processing and analysis, revealing distinctive patterns in charts using Microsoft Excel. A Python condition algorithm was then …

Implementation Of Self Diving Car To Assist Physically Challenged People By Analyzing Eeg Signals, Santhosh Kumar, Meghana S, Shobha Airaddi, Gagana P, Advithi M J

Manipal Journal of Science and Technology

The modern technology which is meant to provide communication between our brain and the car is BCI (Brain computer interface). Its goal is to help persons who are disabled or have trouble moving due to muscle cramps. It uses an EEG (Electroencephalogram) headset to record data, classifies and demonstrate the set of data on the hardware and attain required commands on the robotic car reached from the given order. The data is moved through a Zigbee module in that period Arduino will executes the commands. This interfacing techniques can be used to unravel brain activity into commands to control outer …

A Python-Based Brain-Computer Interface Package For Neural Data Analysis, Md Hasan Anowar

Theses and Dissertations

Anowar, Md Hasan, A Python-based Brain-Computer Interface Package for Neural Data Analysis. Master of Science (MS), December, 2020, 70 pp., 4 tables, 23 figures, 74 references.

Although a growing amount of research has been dedicated to neural engineering, only a handful of software packages are available for brain signal processing. Popular brain-computer interface packages depend on commercial software products such as MATLAB. Moreover, almost every brain-computer interface software is designed for a specific neuro-biological signal; there is no single Python-based package that supports motor imagery, sleep, and stimulated brain signal analysis. The necessity to introduce a brain-computer interface package that …

A Brain-Computer Interface For Closed-Loop Sensory Stimulation During Motor Training In Patients With Tetraplegia, Sarah Helen Thomas

Theses and Dissertations--Biomedical Engineering

Normal movement execution requires proper coupling of motor and sensory activation. An increasing body of literature supports the idea that incorporation of sensory stimulation into motor rehabilitation practices increases its effectiveness. Paired associative stimulation (PAS) studies, in which afferent and efferent pathways are activated in tandem, have brought attention to the importance of well-timed stimulation rather than non-associative (i.e., open-loop) activation. In patients with tetraplegia resulting from spinal cord injury (SCI), varying degrees of upper limb function may remain and could be harnessed for rehabilitation. Incorporating associative sensory stimulation coupled with self-paced motor training would be a means for supplementing …

Brain-Computer Interfaces Using Electrocorticography And Surface Stimulation, Jesse Wheeler

McKelvey School of Engineering Theses & Dissertations

The brain connects to, modulates, and receives information from every organ in the body. As such, brain-computer interfaces (BCIs) have vast potential for diagnostics, medical therapies, and even augmentation or enhancement of normal functions. BCIs provide a means to explore the furthest corners of what it means to think, to feel, and to act—to experience the world and to be who you are. This work focuses on the development of a chronic bi-directional BCI for sensorimotor restoration through the use of separable frequency bands for recording motor intent and providing sensory feedback via electrocortical stimulation. Epidural cortical surface electrodes are …

Human Ipsilateral Motor Physiology And Neuroprosthetic Applications In Chronic Stroke, David Thomas Bundy

McKelvey School of Engineering Theses & Dissertations

Improving the recovery of lost motor function in hemiplegic chronic stroke survivors is a critical need to improve the lives of these patients. Over the last several decades, neuroprosthetic systems have emerged as novel tools with the potential to restore function in a variety of patient populations. While traditional neuroprosthetics have focused on using neural activity contralateral to a moving limb for device control, an alternative control signal may be necessary to develop brain-computer interface (BCI) systems in stroke survivors that suffer damage to the cortical hemisphere contralateral to the affected limb. While movement-related neural activity also occurs in the …

Optimization Of Feature Selection In A Brain-Computer Interface Switch Based On Event-Related Desynchronization And Synchronization Detected By Eeg, Mason Montgomery

Theses and Dissertations

There are hundreds of thousands of people who could benefit from a Brain-Computer Interface. However, not all are willing to undergo surgery, so an EEG is the prime candidate for use as a BCI. The features of Event-Related Desynchronization and Synchronization could be used for a switch and have been in the past. A new method of feature selection was proposed to optimize classification of active motor movement vs a non-active idle state. The previous method had pre-selected which frequency and electrode to use as electrode C3 at the 20Hz bin. The new method used SPSS statistical software to determine …