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- Creators: Arizona State University
Description
This study used exploratory data analysis (EDA) to examine the use of a biofeedback intervention in the treatment of anxiety for college students diagnosed with an Autism Spectrum Disorder (ASD) (n=10) and in a typical college population (n=37). The use of EDA allowed for trends to emerge from the data and provided a foundation for future research in the areas of biofeedback and accommodations for college students with ASD. Comparing the first five weeks of the study with the second five weeks of the 10 week study, both groups showed improvement in their control of heart rate variability, a physiological marker for anxiety used in biofeedback. The ASD group showed greater gains, more consistent gains, and less variability in raw scores than the typical group. EDA also revealed a pattern between participant attrition and a participant's biofeedback progress. Implications are discussed.
ContributorsWestlake, Garret (Author) / McCoy, Kathleen M. (Thesis advisor) / Brown, Jane T (Committee member) / DiGangi, Samuel A. (Committee member) / Caterino, Linda K (Committee member) / Arizona State University (Publisher)
Created2013
Description
Advances in miniaturized sensors and wireless technologies have enabled mobile health systems for efficient healthcare. A mobile health system assists the physician to monitor the patient's progress remotely and provide quick feedbacks and suggestions in case of emergencies, which reduces the cost of healthcare without the expense of hospitalization. This work involves development of an innovative mobile health system with adaptive biofeedback mechanism and demonstrates the importance of biofeedback in accurate measurements of physiological parameters to facilitate the diagnosis in mobile health systems. Resting Metabolic Rate (RMR) assessment, a key aspect in the treatment of diet related health problems is considered as a model to demonstrate the importance of adaptive biofeedback in mobile health. A breathing biofeedback mechanism has been implemented with digital signal processing techniques for real-time visual and musical guidance to accurately measure the RMR. The effects of adaptive biofeedback with musical and visual guidance were assessed on 22 healthy subjects (12 men, 10 women). Eight RMR measurements were taken for each subject on different days under same conditions. It was observed the subjects unconsciously followed breathing biofeedback, yielding consistent and accurate measurements for the diagnosis. The coefficient of variation of the measured metabolic parameters decreased significantly (p < 0.05) for 20 subjects out of 22 subjects.
ContributorsKrishnan, Ranganath (Author) / Tao, Nongjian (Thesis advisor) / Forzani, Erica (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2012
Description
Beneath the epidermis, the human body contains a vibrant and complex ecology of interwoven rhythms such the heartbeat, the breath, the division of cells, and complex brain activity. By repurposing emergent medical technology into real-time gestural sound controllers of electronic musical instruments, experimental musicians in the 1960s and 1970s – including David Rosenboom – began to realize the expressive potential of these biological sounds. Composers experimented with breath and heartbeat. They also used electroencephalography (EEG) sensors, which register various types of brain waves. Instead of using the sound of brain waves in fixed-media pieces, many composers took diverse approaches to the challenge of presenting this in live performance. Their performance practices suggest different notions of embodiment, a relationship in this music which has not been discussed in detail.
Rosenboom reflects extensively on this performance practice. He supports his EEG research with theory about the practice of biofeedback. Rosenboom’s work with EEG sensors spans several decades and continue today, which has allowed him to make use of advancing sensing and computing technologies. For instance, in his 1976 On Being Invisible, the culmination of his work with EEG, he makes use of analyzed EEG data to drive a co-improvising musical system.
In this thesis, I parse different notions of embodiment in the performance of EEG music. Through a critical analysis of examples from the discourse surrounding EEG music in its early years, I show that cultural perception of EEG sonification points to imaginative speculations about the practice’s potentials; these fantasies have fascinating ramifications on the role of the body in this music’s performance. Juxtaposing these with Rosenboom, I contend that he cultivated an embodied performance practice of the EEG. To show how this might be manifest in performance, I consider two recordings of On Being Invisible.
As few musicologists have investigated this particular strain of musical experimentalism, I hope to contextualize biofeedback musicianship by offering an embodied reading of this milestone work for EEG.
Rosenboom reflects extensively on this performance practice. He supports his EEG research with theory about the practice of biofeedback. Rosenboom’s work with EEG sensors spans several decades and continue today, which has allowed him to make use of advancing sensing and computing technologies. For instance, in his 1976 On Being Invisible, the culmination of his work with EEG, he makes use of analyzed EEG data to drive a co-improvising musical system.
In this thesis, I parse different notions of embodiment in the performance of EEG music. Through a critical analysis of examples from the discourse surrounding EEG music in its early years, I show that cultural perception of EEG sonification points to imaginative speculations about the practice’s potentials; these fantasies have fascinating ramifications on the role of the body in this music’s performance. Juxtaposing these with Rosenboom, I contend that he cultivated an embodied performance practice of the EEG. To show how this might be manifest in performance, I consider two recordings of On Being Invisible.
As few musicologists have investigated this particular strain of musical experimentalism, I hope to contextualize biofeedback musicianship by offering an embodied reading of this milestone work for EEG.
ContributorsJohnson, Garrett Laroy (Author) / Xin Wei, Sha (Thesis advisor) / Ingalls, Todd (Committee member) / Suzuki, Kotoka (Committee member) / Tobias, Evan (Committee member) / Arizona State University (Publisher)
Created2015