Document Type
Dissertation
Degree
Doctor of Philosophy (PhD)
Major/Program
Electrical and Computer Engineering
First Advisor's Name
Ou Bai
First Advisor's Committee Title
Committee chair
Second Advisor's Name
Corneliu C Luca
Second Advisor's Committee Title
Committee member
Third Advisor's Name
Elias Alwan
Third Advisor's Committee Title
Committee member
Fourth Advisor's Name
Armando Barreto
Fourth Advisor's Committee Title
Committee member
Fifth Advisor's Name
Wei-Chiang Lin
Fifth Advisor's Committee Title
Committee member
Keywords
Parkinson's Disease (PD), Freezing of Gait (FoG), Biomarker, Electrophysiology, Wearables, Electroencephalography
Date of Defense
11-12-2020
Abstract
Parkinson's Disease (PD) affects over 1% of the population over 60 years of age and is expected to reach 1 million in the USA by the year 2020, growing by 60 thousand each year. It is well understood that PD is characterized by dopaminergic loss, leading to decreased executive function causing motor symptoms such as tremors, bradykinesia, dyskinesia, and freezing of gait (FoG) as well as non-motor symptoms such as loss of smell, depression, and sleep abnormalities. A PD diagnosis is difficult to make since there is no worldwide approved test and difficult to manage since its manifestations are widely heterogeneous among subjects. Thus, understanding the patient subsets and the neural biomarkers that set them apart will lead to improved personalized care. To explore the physiological alternations caused by PD on neurological pathways and their effect on motor control, it is necessary to detect the neural activity and its dissociation with healthy physiological function. To this effect, this study presents a custom ultra-wearable sensor solution, consisting of electroencephalograph, electromyograph, ground reaction force, and symptom measurement sensors for the exploration of neural biomarkers during active gait paradigms. Additionally, this study employed novel de-noising techniques for dealing with the motion artifacts associated with active gait EEG recordings and compared time-frequency features between a group of PD with FoG and a group of age-matched controls and found significant differences between several EEG frequency bands during start and end of normal walking (with a p<0.05).
Identifier
FIDC009227
ORCID
0000-0002-6054-0549
Previously Published In
- J. Sebastian Marquez, et al., Neural correlates of Freezing of Gait in Parkinson’s disease: An Electrophysiology Mini-Review. Front. Neurol.
- CPS pressure-based sensing system for symmetry measurement, Patent number: 10,555,689
- Marquez, J Sebastian, et al. “5th World Parkinson Congress.” A wearable sensor device with internet connectivity for accurate movement assessment in Parkinson's patients, 2019, cdn.ymaws.com/www.worldpdcoalition.org/resource/resmgr/finalprogram_may2019_lr.pdf.
Recommended Citation
Marquez Jaramillo, Juan Sebastian, "Sensor Approach for Brain Pathophysiology of Freezing of Gait in Parkinson's Disease Patients" (2020). FIU Electronic Theses and Dissertations. 4560.
https://digitalcommons.fiu.edu/etd/4560
Rights Statement
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).