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UW-Madison BME 400 - EEG Biofeedback System

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EEG Biofeedback System Final Report Team Members Andrew Eley Joseph Hippensteel Prakash Rao Cullen Rotroff BME 400 Department of Biomedical Engineering University of Wisconsin – Madison December 13, 2006 Client Daniel Muller, M.D., Ph.D Dept. of Medicine - Rheumatology UW Hospital & Clinics Advisor Willis Tompkins, Ph.D Department of Biomedical Engineering1Abstract The physiological effects of meditation have been an active area of research in recent decades and are widely accepted to be highly beneficial for stress reduction and overall well-being. As a result, many physicians have become increasingly intrigued by meditation’s clinical potential; developing a device to enhance one’s ability to reach a meditative state through biofeedback could prove to be a clinically significant tool. A compact, affordable device was designed and fabricated to acquire clean, human electroencephalogram (EEG) signals and provide auditory feedback upon detection of alpha and theta waves. These rhythms are believed to be strongly linked to the “bliss” state of meditation. Computer simulations have verified the theoretical functionality of the device. Human testing will be conducted to determine its true effectiveness.2Fig. 2 – Commercially available EEG monitor; built-in theta/alpha differentiation display. This unit costs $1500. Fig. 1 – Overview of specific brainwave types and their associated state of consciousness that are commonly seen in EEG recordings. Background Electroencephalography The EEG is a particularly powerful clinical tool and has been the gold standard for neurology and psychology research for decades. It is a relatively simple, inexpensive and completely harmless method for analyzing brain activity. The EEG has inherent disadvantages when compared to more invasive or expensive techniques such as decreased spatial and temporal resolution. The EEG allows for a glance into the global organization of the brain by recording the mass action potential activity of neurons in the brain and is sufficient for a wide variety of applications. Typically EEG data is acquired using a high end bioamplifier connected to an array of up to 128 electrodes. The amplifier quality is necessitated by the 10-100μV amplitude of an EEG signal. The data that is collected is then fed into a digital computer where it can be analyzed in real time or off-line. Such methodology has led to the classification of four specific categories of brain activity commonly discussed in EEG literature: alpha, beta, theta, and delta waves (Fig. 1).3Due to the niche market of EEG, commercially available equipment is all but non-existent. Technology that allows for the detection and delineation of an EEG signal typically costs upward of $1,500 (fig. 2) [2]. Due to the expertise required for use of such devices and their high price tag, private utilization of such technology is rare. Meditation Meditation has been practiced for thousands of years as a means to reach spiritual enlightenment. The pop culture cliché that is most commonly associated with the end result of meditation is the phenomenon of finding “inner-peace.” It is a belief in many religions that by achieving a pure meditative state (nirvana, enlightenment, ‘inner-peace’, etc.) an individual can attain selflessness and a seemingly complete understanding of the universe [13]. The inherent imagery that is associated with the metaphysical aspects of meditation have resulted in a cross-cultural scientific curiosity with regards to the physical manifestations of meditation; especially intriguing are changes observed in the neural patterns during attainment of such an extraordinary state of mind. Specifically, it has been shown that individuals extensively trained in meditation exhibit alpha wave neural activity while approaching meditation and theta wave activity (4-7 Hz) upon reaching a meditative state [3, 4]. Other signs of meditation include decreased heart rate, oxygen consumption, and metabolism as well as increased skin resistance and peripheral blood flow. Beyond the physiological characteristics, it is widely accepted that regular practice of meditation can lead to significant health benefits that are directly related to a reduction in stress [4, 8, 9]. In particular, decreased blood pressure, anxiety, and stress hormone levels have been observed. Because of this, more physicians have been advocating the benefits of meditation. If a device that allowed for easier attainment of a meditative state via biofeedback were to be developed, it could have a significant clinical impact. Physiological modalities that could be4directly measured as a strategy for meditation training include muscle activity, skin moisture and brain activity. Project History The EEG Biofeedback project has been open for approximately six years, and considerable progress has been made. The product can be broken into three essential stages: signal acquisition, signal conditioning, and biofeedback. Past groups have tended to focus on a single stage, rather than pursuing all portions concurrently. It was our intention to address all portions of the design in the fall of 2006 in order to create a foundation for developing a functioning prototype by May of 2007. Previous groups’ work has been reviewed to accelerate and improve the efficiency of the design process. The first stage, signal acquisition, requires consideration of electrode type, quantity, and position. All former groups that approached this issue attempted to create their own electrode and final assembly. The first system designed consisted of a dual strap headband with variable electrode positioning. This was accomplished by including small slits in the headband straps for insertion of electrodes, allowing for sufficient electrode position flexibility [10]. Another approach was direct contact of custom-made silver probe electrodes with the scalp as the acquisition device, inserted in an earplug for comfort [6]. To date, no commercial electrodes have been considered by previous groups. Electrode quantity has varied significantly as a direct result of circuit design dictating the number required. Signal conditioning has been based upon two particular designs. One focused on the amplifier described in “Amplifier Design with a Minimal Number of Parts” [10]. This design is a low-power device that includes a high common mode rejection ratio (CMRR) and a low part count. The second design is


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