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Mobile Brain and Body Imaging during Walking Motor Tasks

dc.contributor.authorHanada, Grant
dc.date.accessioned2019-02-07T17:56:30Z
dc.date.availableNO_RESTRICTION
dc.date.available2019-02-07T17:56:30Z
dc.date.issued2018
dc.date.submitted
dc.identifier.urihttps://hdl.handle.net/2027.42/147691
dc.description.abstractMobile brain and body imaging (MoBI) presents new and promising methods for moving traditional research studies out of a controlled laboratory and into the real world. Most current neuroimaging techniques require subjects to be stationary in laboratory settings because of both hardware and software limitations. Recent developments in mobile brain imaging have utilized Electroencephalography (EEG) in conjunction with advanced signal processing techniques such as Independent Component Analysis (ICA) to overcome these obstacles and study humans doing complex tasks in non-traditional environments. In my first study, I used high density EEG to examine the cortical dynamics of subjects walking on a split-belt treadmill with legs moving independently of each other at different speeds to investigate how humans adapt to novel perturbations. I found significantly increased low and high frequency spectral power across all sensorimotor and parietal neural sources during split-belt adaptation compared to normal walking, which provides insight into the brain areas and patterns used to accommodate locomotor adaptation. In my second study I combined multi-modal sensing and biometric devices including EEG, eye tracking, heart rate, accelerometers, and salivary cortisol into a portable setup that subjects wore indoors on a treadmill using virtual reality as well as outdoors in a public arboretum. Subjects walked for 1 hour each indoors and outdoors while completing a free viewing visual search oddball task in virtual reality and in real life. I reported on the methods for how to set this experiment up, synchronize all data, and standardize the data in order to make it usable as an open access dataset that has been made available to the public online. My third study used this data set to examine the P300 event-related potential response during both indoors in virtual reality and outdoors in the arboretum. I found a significantly increased amplitude response between 250 to 400 ms across the centro-parietal electrodes that distinguished target flags from distractor flags during visual search for both indoor and outdoor environments. And finally, for my fourth study I used the same data set to look at the behavioral and neural correlates associated with gait dynamics when subjects walked indoors on a treadmill vs outdoors in variable terrain while also doing the visual search task. I found significant EEG power differences across multiple neural sources that showed increased spectral fluctuations throughout the gait cycle when subjects walked outdoors compared to indoors on a treadmill. The collective studies in this dissertation present new ways of using mobile brain and body imaging devices to expand our knowledge of the neural dynamics involved in humans moving in complex ways and in variable environments outside of traditional laboratories.
dc.language.isoen_US
dc.subjectEEG
dc.subjectMoBI
dc.subjectMobile brain body imaging
dc.subjectBiomechanics
dc.subjectVisual search
dc.subjectERP
dc.titleMobile Brain and Body Imaging during Walking Motor Tasks
dc.typeThesisen_US
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineBiomedical Engineering
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studies
dc.contributor.committeememberChestek, Cynthia Anne
dc.contributor.committeememberFerris, Daniel P
dc.contributor.committeememberMeehan, Sean
dc.contributor.committeememberStacey, William Charles
dc.subject.hlbsecondlevelBiomedical Engineering
dc.subject.hlbtoplevelEngineering
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/147691/1/ghanada_1.pdf
dc.identifier.orcid0000-0002-0878-6939
dc.identifier.name-orcidHanada, Grant; 0000-0002-0878-6939en_US
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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