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Description
The use of electromyography (EMG) signals to characterize muscle fatigue has been widely accepted. Initial work on characterizing muscle fatigue during isometric contractions demonstrated that its frequency decreases while its amplitude increases with the onset of fatigue. More recent work concentrated on developing techniques to characterize dynamic contractions for use in clinical and training applications. Studies demonstrated that as fatigue progresses, the EMG signal undergoes a shift in frequency, and different physiological mechanisms on the possible cause of the shift were considered. Time-frequency processing, using the Wigner distribution or spectrogram, is one of the techniques used to estimate the instantaneous mean frequency and instantaneous median frequency of the EMG signal using a variety of techniques. However, these time-frequency methods suffer either from cross-term interference when processing signals with multiple components or time-frequency resolution due to the use of windowing. This study proposes the use of the matching pursuit decomposition (MPD) with a Gaussian dictionary to process EMG signals produced during both isometric and dynamic contractions. In particular, the MPD obtains unique time-frequency features that represent the EMG signal time-frequency dependence without suffering from cross-terms or loss in time-frequency resolution. As the MPD does not depend on an analysis window like the spectrogram, it is more robust in applying the timefrequency features to identify the spectral time-variation of the EGM signal.
ContributorsAustin, Hiroko (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Kovvali, Narayan (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2012
Description
Development of post-traumatic epilepsy (PTE) after traumatic brain injury (TBI) is a major health concern (5% - 50% of TBI cases). A significant problem in TBI management is the inability to predict which patients will develop PTE. Such prediction, followed by timely treatment, could be highly beneficial to TBI patients. Six male Sprague-Dawley rats were subjected to a controlled cortical impact (CCI). A 6mm piston was pneumatically driven 3mm into the right parietal cortex with velocity of 5.5m/s. The rats were subsequently implanted with 6 intracranial electroencephalographic (EEG) electrodes. Long-term (14-week) continuous EEG recordings were conducted. Using linear (coherence) and non-linear (Lyapunov exponents) measures of EEG dynamics in conjunction with measures of network connectivity, we studied the evolution over time of the functional connectivity between brain sites in order to identify early precursors of development of epilepsy. Four of the six TBI rats developed PTE 6 to 10 weeks after the initial insult to the brain. Analysis of the continuous EEG from these rats showed a gradual increase of the connectivity between critical brain sites in terms of their EEG dynamics, starting at least 2 weeks prior to their first spontaneous seizure. In contrast, for the rats that did not develop epilepsy, connectivity levels did not change, or decreased during the whole course of the experiment across pairs of brain sites. Consistent behavior of functional connectivity changes between brain sites and the "focus" (site of impact) over time was demonstrated for coherence in three out of the four epileptic and in both non-epileptic rats, while for STLmax in all four epileptic and in both non-epileptic rats. This study provided us with the opportunity to quantitatively investigate several aspects of epileptogenesis following traumatic brain injury. Our results strongly support a network pathology that worsens with time. It is conceivable that the observed changes in spatiotemporal dynamics after an initial brain insult, and long before the development of epilepsy, could constitute a basis for predictors of epileptogenesis in TBI patients.
ContributorsTobin, Edward (Author) / Iasemidis, Leonidas (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2012
Description
It is unknown which regions of the brain are most or least active for golfers during a peak performance state (Flow State or "The Zone") on the putting green. To address this issue, electroencephalographic (EEG) recordings were taken on 10 elite golfers while they performed a putting drill consisting of hitting nine putts spaced uniformly around a hole each five feet away. Data was collected at three time periods, before, during and after the putt. Galvanic Skin Response (GSR) measurements were also recorded on each subject. Three of the subjects performed a visualization of the same putting drill and their brain waves and GSR were recorded and then compared with their actual performance of the drill. EEG data in the Theta (4 \u2014 7 Hz) bandwidth and Alpha (7 \u2014 13 Hz) bandwidth in 11 different locations across the head were analyzed. Relative power spectrum was used to quantify the data. From the results, it was found that there is a higher magnitude of power in both the theta and alpha bandwidths for a missed putt in comparison to a made putt (p<0.05). It was also found that there is a higher average power in the right hemisphere for made putts. There was not a higher power in the occipital region of the brain nor was there a lower power level in the frontal cortical region during made putts. The hypothesis that there would be a difference between the means of the power level in performance compared to visualization techniques was also supported.
ContributorsCarpenter, Andrea (Co-author) / Hool, Nicholas (Co-author) / Muthuswamy, Jitendran (Thesis director) / Crews, Debbie (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
From time immemorial, epilepsy has persisted to be one of the greatest impediments to human life for those stricken by it. As the fourth most common neurological disorder, epilepsy causes paroxysmal electrical discharges in the brain that manifest as seizures. Seizures have the effect of debilitating patients on a physical and psychological level. Although not lethal by themselves, they can bring about total disruption in consciousness which can, in hazardous conditions, lead to fatality. Roughly 1\% of the world population suffer from epilepsy and another 30 to 50 new cases per 100,000 increase the number of affected annually. Controlling seizures in epileptic patients has therefore become a great medical and, in recent years, engineering challenge.
In this study, the conditions of human seizures are recreated in an animal model of temporal lobe epilepsy. The rodents used in this study are chemically induced to become chronically epileptic. Their Electroencephalogram (EEG) data is then recorded and analyzed to detect and predict seizures; with the ultimate goal being the control and complete suppression of seizures.
Two methods, the maximum Lyapunov exponent and the Generalized Partial Directed Coherence (GPDC), are applied on EEG data to extract meaningful information. Their effectiveness have been reported in the literature for the purpose of prediction of seizures and seizure focus localization. This study integrates these measures, through some modifications, to robustly detect seizures and separately find precursors to them and in consequence provide stimulation to the epileptic brain of rats in order to suppress seizures. Additionally open-loop stimulation with biphasic currents of various pairs of sites in differing lengths of time have helped us create control efficacy maps. While GPDC tells us about the possible location of the focus, control efficacy maps tells us how effective stimulating a certain pair of sites will be.
The results from computations performed on the data are presented and the feasibility of the control problem is discussed. The results show a new reliable means of seizure detection even in the presence of artifacts in the data. The seizure precursors provide a means of prediction, in the order of tens of minutes, prior to seizures. Closed loop stimulation experiments based on these precursors and control efficacy maps on the epileptic animals show a maximum reduction of seizure frequency by 24.26\% in one animal and reduction of length of seizures by 51.77\% in another. Thus, through this study it was shown that the implementation of the methods can ameliorate seizures in an epileptic patient. It is expected that the new knowledge and experimental techniques will provide a guide for future research in an effort to ultimately eliminate seizures in epileptic patients.
In this study, the conditions of human seizures are recreated in an animal model of temporal lobe epilepsy. The rodents used in this study are chemically induced to become chronically epileptic. Their Electroencephalogram (EEG) data is then recorded and analyzed to detect and predict seizures; with the ultimate goal being the control and complete suppression of seizures.
Two methods, the maximum Lyapunov exponent and the Generalized Partial Directed Coherence (GPDC), are applied on EEG data to extract meaningful information. Their effectiveness have been reported in the literature for the purpose of prediction of seizures and seizure focus localization. This study integrates these measures, through some modifications, to robustly detect seizures and separately find precursors to them and in consequence provide stimulation to the epileptic brain of rats in order to suppress seizures. Additionally open-loop stimulation with biphasic currents of various pairs of sites in differing lengths of time have helped us create control efficacy maps. While GPDC tells us about the possible location of the focus, control efficacy maps tells us how effective stimulating a certain pair of sites will be.
The results from computations performed on the data are presented and the feasibility of the control problem is discussed. The results show a new reliable means of seizure detection even in the presence of artifacts in the data. The seizure precursors provide a means of prediction, in the order of tens of minutes, prior to seizures. Closed loop stimulation experiments based on these precursors and control efficacy maps on the epileptic animals show a maximum reduction of seizure frequency by 24.26\% in one animal and reduction of length of seizures by 51.77\% in another. Thus, through this study it was shown that the implementation of the methods can ameliorate seizures in an epileptic patient. It is expected that the new knowledge and experimental techniques will provide a guide for future research in an effort to ultimately eliminate seizures in epileptic patients.
ContributorsShafique, Md Ashfaque Bin (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Muthuswamy, Jitendran (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2016
Description
Piloerection (known as goosebumps) is mediated by activation of alpha-adrenergic receptors within the sympathetic branch of the autonomic nervous system. The study of piloerection is important in multiple fields, from emotion studies to nervous system pathology. This makes piloerection particularly relevant to emotions research. Despite wide-ranging applications, current methods for measuring piloerection are laborious and qualitative. The goal of this study is to build a wearable piloerection sensor through the use of straight-line lasers and photoresistors. The study analyzed methods of detecting and measuring goosebumps, and applied the method of laser scattering as a detection method. This device was designed and tested against a population of seven Arizona State University students. Goosebumps were elicited through conditions of cold, and video clips meant to elicit emotions of awe and sadness. Piloerection was then quantified through two controls of self-identification and camera recording, as well as the new detection method. These were then compared together, and it was found that subjective methods of determining goosebumps did not correlate well with objective measurements, but that the two objective measurements correlated well with one another. This shows that the technique of laser scattering can be used to detect goosebumps and further developments on this new detection method will be made. Moreover, the presence of uncorrelated subjective measurements further shows the need for an objective measurement of piloerection, while also bringing into question other factors that may be confused with the feeling of piloerection, such as chills or shivers. This study further reaffirmed previous studies showing a positive correlation between intense emotions.
ContributorsHemesath, Angela (Author) / Muthuswamy, Jitendran (Thesis director) / Shiota, Michelle (Lani) (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05