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Articles 1 - 3 of 3
Full-Text Articles in Signal Processing
Exploring The Use Of Audible Sound In Bone Density Diagnostic Devices, Evan J. Bess
Exploring The Use Of Audible Sound In Bone Density Diagnostic Devices, Evan J. Bess
Electronic Theses and Dissertations
Osteoporosis is a medical condition in which there is a progressive degradation of bone tissue that correlates with a characteristic decrease in bone density (BD). It is estimated that osteoporosis affects over 200 million people globally and is responsible for 8.9 million fractures annually. Populations at risk for developing osteoporosis include post-menopausal women, diabetic patients, and the elderly, representing a large population within the state of Maine. Current densitometric and sonometric devices used to monitor BD include quantitative computed tomography (QCT), dual-energy x-ray absorption (DXA), and ultrasound (QUS). All methods are expensive and, in the cases of QCT and DXA, …
Evaluating Eeg–Emg Fusion-Based Classification As A Method For Improving Control Of Wearable Robotic Devices For Upper-Limb Rehabilitation, Jacob G. Tryon
Evaluating Eeg–Emg Fusion-Based Classification As A Method For Improving Control Of Wearable Robotic Devices For Upper-Limb Rehabilitation, Jacob G. Tryon
Electronic Thesis and Dissertation Repository
Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Developments often focus on model-dependent nonlinear control theory, which is challenging to implement for wearable devices.
One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor …
A Novel Brain Computer Interface Design, Steven Vogan
A Novel Brain Computer Interface Design, Steven Vogan
Senior Honors Theses
A brain computer interface (BCI) is a system which connects neural signals to a computer system. They have been used for controlling systems including robotics, on-screen computer control such as mouse movement, typing, and synthesizing audio signals. Invasive, or implanted, systems are often long-term medical solutions, or used for research where very clear signal is required. Non-invasive systems usually rely on exterior signals gathered through a headset using one or more electrode sensors. These signals are composed of sums of neuron activation potentials from brain activity and can be used to determine particular aspects of brain function. All BCIs rely …