333 research outputs found

    Comparing the effectiveness of music therapy and alpha-theta neuro-feedback training on anxiety and depression among patients with chronic irritable bowel syndrome

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    BACKGROUND: Non-pharmaceutical interventions are a promising area of research in psychiatry. Traditional treatment of Irritable Bowel Syndrome (IBS) lacked notable efficacy. The aim of this study was to examine the effectiveness of music therapy (MT) and alpha-theta neurofeedback training (NFT) on anxiety and depression symptoms among patients with IBS.METHODS: Patients with IBS, based on ROME III criteria, and high level of anxiety or depression symptoms were randomly assigned into three groups: (A) music, (B) alpha-theta training, and (C) control. In intervention groups, participants received ten 30-minute sessions of either music or alpha-theta NFT. The Hospital Anxiety and Depression Scale (HADS) was administered for all patients before and after the training period. Thirty-three patients completed the study. Data were analyzed using analysis of covariance (ANCOVA) to compare changes in HADS scores among the three study groups.RESULTS: There was a significant main effect of HADS scores (F1,18 = 17.79, P < 0.001) in the responses of MT group. Significant decreases were observed in HADS scores from pre-intervention to post-intervention tests in MT group comparing to control group. The MT accounted for 49 percent of variance in HADS scores. There was also a significant main effect of HADS scores (F1,20 = 17.79, P < 0.010) in the responses of NFT group. HADS scores from pre-intervention to post-intervention tests in alpha-theta NFT group comparing to control group showed significant decreases, too. In addition, MT and alpha-theta NFT did not show any significant difference in somatic symptoms scores between pretest and posttest among patients with IBS.CONCLUSION: This study showed that MT and alpha-theta NFT significantly alleviated anxiety and depression level among patients with IBS

    The Human Auditory System

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    This book presents the latest findings in clinical audiology with a strong emphasis on new emerging technologies that facilitate and optimize a better assessment of the patient. The book has been edited with a strong educational perspective (all chapters include an introduction to their corresponding topic and a glossary of terms). The book contains material suitable for graduate students in audiology, ENT, hearing science and neuroscience

    Effects of theta-frequency binaural beats on post-exercise recovery and stress responsivity

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    Binaural beats are an auditory illusion perceived when two or more pure tones of similar frequencies are presented dichotically through stereo headphones. This phenomenon is thought to have the potential to facilitate changes in arousal. The present study investigated the effects of 7 Hz binaural beating on post-exercise recovery and stress responsivity in college-aged students (n = 21; 18-29 years old).Theta binaural beats failed to outperform placebo in altering post-exercise recovery or stress responsivity. However, after listening to binaural beats, participants reported feeling more relaxed (6.4% change) and less stressed (11.5% change). Findings from the present study suggest that listening to binaural beats may have subtle psychological effects

    BRAIN-COMPUTER MUSIC INTERFACING: DESIGNING PRACTICAL SYSTEMS FOR CREATIVE APPLICATIONS

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    Brain-computer music interfacing (BCMI) presents a novel approach to music making, as it requires only the brainwaves of a user to control musical parameters. This presents immediate benefits for users with motor disabilities that may otherwise prevent them from engaging in traditional musical activities such as composition, performance or collaboration with other musicians. BCMI systems with active control, where a user can make cognitive choices that are detected within brain signals, provide a platform for developing new approaches towards accomplishing these activities. BCMI systems that use passive control present an interesting alternate to active control, where control over music is accomplished by harnessing brainwave patterns that are associated with subconscious mental states. Recent developments in brainwave measuring technologies, in particular electroencephalography (EEG), have made brainwave interaction with computer systems more affordable and accessible and the time is ripe for research into the potential such technologies can offer for creative applications for users of all abilities. This thesis presents an account of BCMI development that investigates methods of active, passive and hybrid (multiple control methods) control that include control over electronic music, acoustic instrumental music, multi-brain systems and combining methods of brainwave control. In practice there are many obstacles associated with detecting useful brainwave signals, in particular when scaling systems otherwise designed for medical studies for use outside of laboratory settings. Two key areas are addressed throughout this thesis. Firstly, improving the accuracy of meaningful brain signal detection in BCMI, and secondly, exploring the creativity available in user control through ways in which brainwaves can be mapped to musical features. Six BCMIs are presented in this thesis, each with the objective of exploring a unique aspect of user control. Four of these systems are designed for live BCMI concert performance, one evaluates a proof-of-concept through end-user testing and one is designed as a musical composition tool. The thesis begins by exploring the field of brainwave detection and control and identifies the steady-state visually evoked potential (SSVEP) method of eliciting brainwave control as a suitable technique for use in BCMI. In an attempt to improve signal accuracy of the SSVEP technique a new modular hardware unit is presented that provides accurate SSVEP stimuli, suitable for live music performance. Experimental data confirms the performance of the unit in tests across three different EEG hardware platforms. Results across 11 users indicate that a mean accuracy of 96% and an average response time of 3.88 seconds are attainable with the system. These results contribute to the development of the BCMI for Activating Memory, a multi-user system. Once a stable SSVEP platform is developed, control is extended through the integration of two more brainwave control techniques: affective (emotional) state detection and motor imagery response. In order to ascertain the suitability of the former an experiment confirms the accuracy of EEG when measuring affective states in response to music in a pilot study. This thesis demonstrates how a range of brainwave detection methods can be used for creative control in musical applications. Video and audio excerpts of BCMI pieces are also included in the Appendices

    Comparing the effectiveness of music therapy and alpha-theta neuro-feedback training on anxiety and depression among patients with chronic irritable bowel syndrome

    Get PDF
    BACKGROUND: Non-pharmaceutical interventions are a promising area of research in psychiatry. Traditional treatment of Irritable Bowel Syndrome (IBS) lacked notable efficacy. The aim of this study was to examine the effectiveness of music therapy (MT) and alpha-theta neurofeedback training (NFT) on anxiety and depression symptoms among patients with IBS. METHODS: Patients with IBS, based on ROME III criteria, and high level of anxiety or depression symptoms were randomly assigned into three groups: (A) music, (B) alpha-theta training, and (C) control. In intervention groups, participants received ten 30-minute sessions of either music or alpha-theta NFT. The Hospital Anxiety and Depression Scale (HADS) was administered for all patients before and after the training period. Thirty-three patients completed the study. Data were analyzed using analysis of covariance (ANCOVA) to compare changes in HADS scores among the three study groups. RESULTS: There was a significant main effect of HADS scores (F1,18 = 17.79, P < 0.001) in the responses of MT group. Significant decreases were observed in HADS scores from pre-intervention to post-intervention tests in MT group comparing to control group. The MT accounted for 49 percent of variance in HADS scores. There was also a significant main effect of HADS scores (F1,20 = 17.79, P < 0.010) in the responses of NFT group. HADS scores from pre-intervention to post-intervention tests in alpha-theta NFT group comparing to control group showed significant decreases, too. In addition, MT and alpha-theta NFT did not show any significant difference in somatic symptoms scores between pretest and posttest among patients with IBS. CONCLUSION: This study showed that MT and alpha-theta NFT significantly alleviated anxiety and depression level among patients with IBS

    Recent Applications in Graph Theory

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    Graph theory, being a rigorously investigated field of combinatorial mathematics, is adopted by a wide variety of disciplines addressing a plethora of real-world applications. Advances in graph algorithms and software implementations have made graph theory accessible to a larger community of interest. Ever-increasing interest in machine learning and model deployments for network data demands a coherent selection of topics rewarding a fresh, up-to-date summary of the theory and fruitful applications to probe further. This volume is a small yet unique contribution to graph theory applications and modeling with graphs. The subjects discussed include information hiding using graphs, dynamic graph-based systems to model and control cyber-physical systems, graph reconstruction, average distance neighborhood graphs, and pure and mixed-integer linear programming formulations to cluster networks

    Brain-Computer Interface

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    Brain-computer interfacing (BCI) with the use of advanced artificial intelligence identification is a rapidly growing new technology that allows a silently commanding brain to manipulate devices ranging from smartphones to advanced articulated robotic arms when physical control is not possible. BCI can be viewed as a collaboration between the brain and a device via the direct passage of electrical signals from neurons to an external system. The book provides a comprehensive summary of conventional and novel methods for processing brain signals. The chapters cover a range of topics including noninvasive and invasive signal acquisition, signal processing methods, deep learning approaches, and implementation of BCI in experimental problems
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