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Theses/Dissertations

Biomedical Engineering and Bioengineering

EEG

Theses and Dissertations--Biomedical Engineering

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Full-Text Articles in Engineering

Voluntary Control Of Breathing According To The Breathing Pattern During Listening To Music And Non-Contact Measurement Of Heart Rate And Respiration, Dibyajyoti Biswal Jan 2022

Voluntary Control Of Breathing According To The Breathing Pattern During Listening To Music And Non-Contact Measurement Of Heart Rate And Respiration, Dibyajyoti Biswal

Theses and Dissertations--Biomedical Engineering

We investigated if listening to songs changes breathing pattern which changes autonomic responses such as heart rate (HR) and heart rate variability (HRV) or change in breathing pattern is a byproduct of listening to songs or change in breathing pattern as well as listening to songs causes changes in autonomic responses. Seven subjects (4 males and 3 females) participated in a pilot study where they listened to two types of songs and used a custom developed biofeedback program to control their breathing pattern to match the one recorded during listening to the songs.

Coherencies between EEG, breathing pattern and RR …


Characterization Of Modulation And Coherence In Sensorimotor Rhythms Using Different Electroencephalographic Signal Derivations, Stephen Dundon Jan 2021

Characterization Of Modulation And Coherence In Sensorimotor Rhythms Using Different Electroencephalographic Signal Derivations, Stephen Dundon

Theses and Dissertations--Biomedical Engineering

Electroencephalography (EEG) is a widely used technique for monitoring and analyzing brain activity in experimental, diagnostic, and therapeutic applications. Since EEG is sensitive to noise and artefact sources, referential signals at different locations can be combined in different ways to improve signal quality and better localize cortical activity. Four signal derivations were compared against referential EEG in terms of their ability to measure the alpha rhythm modulation (or reactivity) and spatial coherence associated with an eye closure task: a common average reference (CAR), a local average reference (LAR), a large Laplacian (LL), and a focal Laplacian (FL) estimated using a …


Analysis Of Graded Sensorimotor Rhythms For Brain-Computer Interface Applications, Chase Allen Haddix Jan 2021

Analysis Of Graded Sensorimotor Rhythms For Brain-Computer Interface Applications, Chase Allen Haddix

Theses and Dissertations--Biomedical Engineering

The emerging field of neural engineering is tasked with applying engineering principles towards understanding neuroscience. A by-product of such a venture has been the development of a class of assistive devices known as brain-computer interfaces (BCIs) which link brain activity to actions performed by external devices. One application of this technology is in the rehabilitative sector for individuals with neuromuscular diseases and disorders. Despite tremendous efforts in the last few decades, a reliable signal that reflects fine motor control has yet to be adequately investigated. This gap in knowledge has limited the potential of BCIs to restore movement and communication. …


Closed-Loop Afferent Nerve Electrical Stimulation For Rehabilitation Of Hand Function In Subjects With Incomplete Spinal Cord Injury, Christopher J. Schildt Jan 2016

Closed-Loop Afferent Nerve Electrical Stimulation For Rehabilitation Of Hand Function In Subjects With Incomplete Spinal Cord Injury, Christopher J. Schildt

Theses and Dissertations--Biomedical Engineering

Peripheral nerve stimulation (PNS) is commonly used to promote use-dependent cortical plasticity for rehabilitation of motor function in spinal cord injury. Pairing transcranial magnetic stimulation (TMS) with PNS has been shown to increase motor evoked potentials most when the two stimuli are timed to arrive in the cortex simultaneously. This suggests that a mechanism of timing-dependent plasticity (TDP) may be a more effective method of promoting motor rehabilitation. The following thesis is the result of applying a brain-computer interface to apply PNS in closed-loop simultaneously to movement intention onset as measured by EEG of the sensorimotor cortex to test whether …


Experimental-Computational Analysis Of Vigilance Dynamics For Applications In Sleep And Epilepsy, Farid Yaghouby Jan 2015

Experimental-Computational Analysis Of Vigilance Dynamics For Applications In Sleep And Epilepsy, Farid Yaghouby

Theses and Dissertations--Biomedical Engineering

Epilepsy is a neurological disorder characterized by recurrent seizures. Sleep problems can cooccur with epilepsy, and adversely affect seizure diagnosis and treatment. In fact, the relationship between sleep and seizures in individuals with epilepsy is a complex one. Seizures disturb sleep and sleep deprivation aggravates seizures. Antiepileptic drugs may also impair sleep quality at the cost of controlling seizures. In general, particular vigilance states may inhibit or facilitate seizure generation, and changes in vigilance state can affect the predictability of seizures. A clear understanding of sleep-seizure interactions will therefore benefit epilepsy care providers and improve quality of life in patients. …


Development Of An Eeg Brain-Machine Interface To Aid In Recovery Of Motor Function After Neurological Injury, Elizabeth Salmon Jan 2013

Development Of An Eeg Brain-Machine Interface To Aid In Recovery Of Motor Function After Neurological Injury, Elizabeth Salmon

Theses and Dissertations--Biomedical Engineering

Impaired motor function following neurological injury may be overcome through therapies that induce neuroplastic changes in the brain. Therapeutic methods include repetitive exercises that promote use-dependent plasticity (UDP), the benefit of which may be increased by first administering peripheral nerve stimulation (PNS) to activate afferent fibers, resulting in increased cortical excitability. We speculate that PNS delivered only in response to attempted movement would induce timing-dependent plasticity (TDP), a mechanism essential to normal motor learning. Here we develop a brain-machine interface (BMI) to detect movement intent and effort in healthy volunteers (n=5) from their electroencephalogram (EEG). This could be used in …