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 …

Efficient Discovery And Utilization Of Radio Information In Ultra-Dense Heterogeneous 3d Wireless Networks, Mattaka Gamage Samantha Sriyananda

Electronic Thesis and Dissertation Repository

Emergence of new applications, industrial automation and the explosive boost of smart concepts have led to an environment with rapidly increasing device densification and service diversification. This revolutionary upward trend has led the upcoming 6th-Generation (6G) and beyond communication systems to be globally available communication, computing and intelligent systems seamlessly connecting devices, services and infrastructure facilities. In this kind of environment, scarcity of radio resources would be upshot to an unimaginably high level compelling them to be very efficiently utilized. In this case, timely action is taken to deviate from approximate site-specific 2-Dimensional (2D) network concepts in radio resource utilization …

The Development Of A Motion Sensing Device For Use In A Home Setting, Jaspreet K. Kalsi

Electronic Thesis and Dissertation Repository

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease, with over 10 million individuals diagnosed with PD world-wide. The most common symptom characterized by PD is tremor. Tremor is an involuntary oscillatory motion that most prominently occurs in upper limb, specifically in the hand and wrist that has a measurable frequency and amplitude. This thesis aims to evaluate the usability and functionality of a tremor sensing device designed to collect quantitative data on individuals with PD. The designed device uses 23 commercially-available inertial measuring units (IMUs) located between 21 joints: distal interphalangeal (DIP) joints, proximal interphalangeal (PIP) joints, Interphalangeal …

Multi-Device Data Analysis For Fault Localization In Electrical Distribution Grids, Jacob D L Hunte

Electronic Thesis and Dissertation Repository

The work presented in this dissertation represents work which addresses some of the main challenges of fault localization methods in electrical distribution grids. The methods developed largely assume access to sophisticated data sources that may not be available and that any data sets recorded by devices are synchronized. These issues have created a barrier to the adoption of many solutions by industry. The goal of the research presented in this dissertation is to address these challenges through the development of three elements. These elements are a synchronization protocol, a fault localization technique, and a sensor placement algorithm.

The synchronization protocol …

The Role Of Transient Vibration Of The Skull On Concussion, Rodrigo Dalvit Carvalho Da Silva

Electronic Thesis and Dissertation Repository

Concussion is a traumatic brain injury usually caused by a direct or indirect blow to the head that affects brain function. The maximum mechanical impedance of the brain tissue occurs at 450±50 Hz and may be affected by the skull resonant frequencies. After an impact to the head, vibration resonance of the skull damages the underlying cortex. The skull deforms and vibrates, like a bell for 3 to 5 milliseconds, bruising the cortex. Furthermore, the deceleration forces the frontal and temporal cortex against the skull, eliminating a layer of cerebrospinal fluid. When the skull vibrates, the force spreads directly to …

Effect Of Levodopa On Eeg Connectivity In Parkinson's Patients, Sepehr Torab Parhiz

Electronic Thesis and Dissertation Repository

Levodopa is a dopamine replacement medication administered to patients with Parkinson’s disease (PD) to alleviate their motor symptoms. However, its long-term use can cause adverse side effects, including involuntary motor movements. We studied 16 PD patients before and after taking Levodopa based on resting-state electroencephalography (EEG) recordings to determine how Levodopa affects the functional connectivity of their brain networks. We used several metrics from graph theory, in particular the minimum spanning tree (MST) metric, and analyzed how they change after subjects take Levodopa. We observed significant changes in the lower alpha band toward a more path-like and less globally efficient …

Data And Sensor Fusion Using Fmg, Semg And Imu Sensors For Upper Limb Prosthesis Control, Jason S. Gharibo

Electronic Thesis and Dissertation Repository

Whether someone is born with a missing limb or an amputation occurs later in life, living with this disability can be extremely challenging. The robotic prosthetic devices available today are capable of giving users more functionality, but the methods available to control these prostheses restrict their use to simple actions, and are part of the reason why users often reject prosthetic technologies. Using multiple myography modalities has been a promising approach to address these control limitations; however, only two myography modalities have been rigorously tested so far, and while the results have shown improvements, they have not been robust enough …

Real-Time Parkinsonian Tremor Signal Identifier Based On Internal Model Principle, Jian Dong

Electronic Thesis and Dissertation Repository

Parkinsonian tremor is one of the clinical hallmarks of Parkinson's disease. Since the traditional medical treatments are not effective, many wearable devices are developed to help suppress the tremor. In order to suppress the tremor, a well-designed tremor estimator is needed. Previous tremor estimators treat a 3-D tremor signal as three independent 1-D signals. Moreover, they did not consider the real-life characteristics of tremor signals. For instance, the tremor does not always exist in the postural tremor signal, and the patient's voluntary motion can be included in the kinetic tremor signal. This paper presents a real-time adaptive parkinsonian tremor signal …

Snapshot Three-Dimensional Surface Imaging With Multispectral Fringe Projection Profilometry, Parsa Omidi

Electronic Thesis and Dissertation Repository

Fringe Projection Profilometry (FPP) is a popular method for non-contact optical surface measurements, including motion tracking. The technique derives 3D surface maps from phase maps estimated from the distortions of fringe patterns projected onto the surface of an object. Estimation of phase maps is commonly performed with spatial phase retrieval algorithms that use a series of complex data processing stages. Researchers must have advanced data analysis skills to process FPP data due to a lack of availability of simple research-oriented software tools. Chapter 2 describes a comprehensive FPP software tool called PhaseWare^TM that allows novice to experienced users to …

Development Of A Wearable Haptic Feedback Device For Upper Limb Prosthetics Through Sensory Substitution, Marco B.S. Gallone

Electronic Thesis and Dissertation Repository

Haptics can enable a direct communication pipeline between the artificial limb and the brain; adding haptic sensory feedback for prosthesis wearers is believed to improve operation without drawing too much of the user's attention. Through neuroplasticity, the brain can become more cognizant of the information delivered through the skin and may eventually interpret it as inherently as other natural senses. In this thesis, a wearable haptic feedback device (WHFD) is developed to communicate prosthesis sensory information. A 14-week, 6-stage, between subjects study was created to investigate the learning trajectory as participants were stimulated with haptic patterns conveying joint proprioception. 37 …

Radiometric Correction Of Multispectral Cameras Using Photosensor Irradiance For Agronomy Applications, Nicholas S. Mitchell

Electronic Thesis and Dissertation Repository

Cloud coverage has a significant impact on the reflectance maps generated by multispectral cameras mounted on UAV's in small farm settings. The current approach is to calibrate the camera once before every flight and use the radiometric calibration map for the entire flight. In this work we have designed and built a downwelling and upwelling photosensor to work in sync with our custom multispectral camera. A dual reflectance panel implementation for the time dependent radiometric calibration of the multispectral camera is completed. The solar spectral irradiance curve is approximated using the current measurements from the downwelling photosensor and the ground …

Longitudinal Partitioning Waveform Relaxation Methods For The Analysis Of Transmission Line Circuits, Tarik Menkad

Electronic Thesis and Dissertation Repository

Three research projects are presented in this manuscript. Projects one and two describe two waveform relaxation algorithms (WR) with longitudinal partitioning for the time-domain analysis of transmission line circuits. Project three presents theoretical results about the convergence of WR for chains of general circuits.

The first WR algorithm uses a assignment-partition procedure that relies on inserting external series combinations of positive and negative resistances into the circuit to control the speed of convergence of the algorithm. The convergence of the subsequent WR method is examined, and fast convergence is cast as a generic optimization problem in the frequency-domain. An automatic …

Advanced Hardware And Software Approach To Seismic Site Response Investigations, Aleksandar Dimitrov Mihaylov

Electronic Thesis and Dissertation Repository

Vibration measurement is an essential aspect of modern geotechnical engineering. It is particularly vital task for measuring the dynamic soil parameters, estimating seismic hazards and evaluating influence of industrial, traffic and construction vibrations on the surrounding buildings, structures and their elements. Meanwhile, commercial exploration seismic stations and data acquisition systems require significant professional knowledge and training in geophysics or vibration measurement, as well as practical skills and experience in adjusting data acquisition parameters. Furthermore, available seismological investigation and vibrometry sensors are not universally suitable for field applications in geophysical studies, soil-structure interaction investigations or structural vibrations. The frequency range suitable …

Objective Estimation Of Tracheoesophageal Speech Quality, Yousef S Ettomi Ali

Electronic Thesis and Dissertation Repository

Speech quality estimation for pathological voices is becoming an increasingly important research topic. The assessment of the quality and the degree of severity of a disordered speech is important to the clinical treatment and rehabilitation of patients. In particular, patients who have undergone total laryngectomy (larynx removal) produce Tracheoesophageal (TE) speech. In this thesis, we study the problem of TE speech quality estimation using advanced signal processing approaches. Since it is not possible to have a reference (clean) signal corresponding to a given TE speech (disordered) signal, we investigate in particular the non-intrusive techniques (also called single-ended or blind approaches) …

A Wearable Mechatronic Device For Hand Tremor Monitoring And Suppression: Development And Evaluation, Yue Zhou

Electronic Thesis and Dissertation Repository

Tremor, one of the most disabling symptoms of Parkinson's disease (PD), significantly affects the quality of life of the individuals who suffer from it. These people live with difficulties with fine motor tasks, such as eating and writing, and suffer from social embarrassment. Traditional medicines are often ineffective, and surgery is highly invasive and risky. The emergence of wearable technology facilitates an externally worn mechatronic tremor suppression device as a potential alternative approach for tremor management. However, no device has been developed for the suppression of finger tremor that has been validated on a human.

It has been reported in …

Exploitation Of Robust Aoa Estimation And Low Overhead Beamforming In Mmwave Mimo System, Yuyan Zhao

Electronic Thesis and Dissertation Repository

The limited spectral resource for wireless communications and dramatic proliferation of new applications and services directly necessitate the exploitation of millimeter wave (mmWave) communications. One critical enabling technology for mmWave communications is multi-input multi-output (MIMO), which enables other important physical layer techniques, specifically beamforming and antenna array based angle of arrival (AoA) estimation. Deployment of beamforming and AoA estimation has many challenges. Significant training and feedback overhead is required for beamforming, while conventional AoA estimation methods are not fast or robust. Thus, in this thesis, new algorithms are designed for low overhead beamforming, and robust AoA estimation with significantly reduced …

Schrödinger Filtering: A Novel Technique For Removing Gradient Artifact From Electroencephalography Data Acquired During Functional Magnetic Resonance Imaging, Gabriel Bruno Benigno

Electronic Thesis and Dissertation Repository

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are complementary modalities commonly acquired simultaneously to study brain function with high spatial and temporal resolution. The time-varying gradient fields from fMRI induce massive-amplitude artifacts (GRAs) that overlap in time and frequency with EEG, making GRA removal a challenge for which no satisfactory solution yet exists. We present a new GRA removal method termed Schrödinger filtering (SF). SF is based on semi-classical signal analysis in which a signal is decomposed into a series of energy-based components using the discrete spectrum of the Schrödinger operator. Using a publicly available dataset, we compared our …

Classifying Appliances Operation Modes Using Dynamic Time Warping (Dtw) And K Nearest Neighbors (Knn), Abdelkareem M. Jaradat

Electronic Thesis and Dissertation Repository

In the Smart Grid environment, the advent of intelligent measuring devices facilitates monitoring appliance electricity consumption. This data can be used in applying Demand Response (DR) in residential houses through data analytics, and developing data mining techniques. In this research, we introduce a smart system approach that is applied to user's disaggregated power consumption data. This system encourages the users to apply DR by changing their behaviour of using heavier operation modes to lighter modes, and by encouraging users to shift their usages to off-peak hours. First, we apply Cross Correlation to detect times of the occurrences when an appliance …

Parkinsonian Speech And Voice Quality: Assessment And Improvement, Amr Gaballah

Electronic Thesis and Dissertation Repository

Parkinson’s disease (PD) is the second most common neurodegenerative disease. Statistics show that nearly 90% of people impaired with PD develop voice and speech disorders. Speech production impairments in PD subjects typically result in hypophonia and consequently, poor speech signal-to-noise ratio (SNR) in noisy environments and inferior speech intelligibility and quality. Assessment, monitoring, and improvement of the perceived quality and intelligibility of Parkinsonian voice and speech are, therefore, paramount. In the first study of this thesis, the perceived quality of sustained vowels produced by PD patients was assessed through objective predictors. Subjective quality ratings of sustained vowels were collected from …

Objective And Subjective Evaluation Of Binaural Beamformers In Hearing Aids, Scott Aker

Electronic Thesis and Dissertation Repository

Hearing aids use a variety of noise reduction techniques to enhance the experience of hearing impaired listeners. One of these techniques is beamforming, which typically aims to preserve sounds coming from the front of the user and suppresses those from the sides and back. Recently, hearing aids have begun employing a wireless connection between the left and right hearing aids in order to augment the directionality of the beamformers, called binaural beamformers. However, the effect of these binaural beamformers on perceived quality and intelligibility has not been thoroughly tested. This thesis investigated the benchmarking of hearing aids which utilize binaural …

Intraoperative Localization Of Subthalamic Nucleus During Deep Brain Stimulation Surgery Using Machine Learning Algorithms, Mahsa Khosravi

Electronic Thesis and Dissertation Repository

This thesis presents a novel technique for localizing the Subthalamic Nucleus (STN) during Deep Brain Stimulation (DBS) surgery. DBS is an accepted treatment for individuals living with Parkinson's Disease (PD). This surgery involves implantation of a permanent electrode inside the STN to deliver electrical current. The STN is a small grey matter structure within the brain, which makes accurate placement a challenging task for the surgical team. Prior to placement of the permanent electrode, intraoperative microelectrode recordings (MERs) of neural activity are used to localize the STN. The placement of the permanent electrode and the success of the stimulation therapy …

Development And Assessment Of Signal Processing Algorithms For Assistive Hearing Devices, Farid Moshgelani

Electronic Thesis and Dissertation Repository

Speech identification in the presence of background noise is difficult for children with auditory processing disorder and adults with sensorineural hearing loss. The listening difficulty arises from deficits in their temporal, spectral, binaural, and/ or cognitive processing. Given the lack of improvement with conventional assistive hearing devices, alternate speech processing methodologies, which exaggerate the temporal and spectral cues, need to be developed to improve speech intelligibility for individuals who have poor temporal and/ or spectral processing.

This thesis first, reports results from a series of experiments on subjective and objective assessments of two different schemes of envelope enhancement algorithms (dynamic …

Electroacoustic Assessment Of Hearing Aids And Psaps, Manan Sheel

Electronic Thesis and Dissertation Repository

Hearing aids and personal sound amplification products (PSAPs) are commonly used assistive devices for treating hearing loss. Due to the diversity in the hardware and signal processing algorithms in these devices, comprehensive verification of their performance is essential. Existing standards for assistive hearing devices are primarily used for quality control purposes and do not quantify their performance in a perceptually-relevant manner. This thesis developed a comprehensive electroacoustic testing toolbox for hearing devices that encompasses both quality control and perceptually-relevant measures. In particular, a test sequence was developed to assess the effectiveness of noise reduction feature in assistive hearing devices. Several …

Objective Assessment Of Machine Learning Algorithms For Speech Enhancement In Hearing Aids, Krishnan Parameswaran

Electronic Thesis and Dissertation Repository

Speech enhancement in assistive hearing devices has been an area of research for many decades. Noise reduction is particularly challenging because of the wide variety of noise sources and the non-stationarity of speech and noise. Digital signal processing (DSP) algorithms deployed in modern hearing aids for noise reduction rely on certain assumptions on the statistical properties of undesired signals. This could be disadvantageous in accurate estimation of different noise types, which subsequently leads to suboptimal noise reduction. In this research, a relatively unexplored technique based on deep learning, i.e. Recurrent Neural Network (RNN), is used to perform noise reduction and …

Signal Identification In Discrete-Time Based On Internal-Model-Principle, Jie Chen

Electronic Thesis and Dissertation Repository

This work presents an implementation of a signal identification algorithm which is based on the internal model principle. By using several internal models in feedback with a tuning function, this algorithm can decompose a signal into narrow-band signals and identify the frequencies, amplitudes and relative phases. A desired band-pass filter response can be achieved by selecting appropriate coefficients of the controllers and tuning functions, which can reject the noise and improve the performance. To achieve a result with fast transient characteristics, this system is then modified by adding a low-pass filter. This work is based on the previous work in …

Learning-Based Reference-Free Speech Quality Assessment For Normal Hearing And Hearing Impaired Applications, Haniyeh Salehi

Electronic Thesis and Dissertation Repository

Accurate speech quality measures are highly attractive and beneficial in the design, fine-tuning, and benchmarking of speech processing algorithms, devices, and communication systems. Switching from narrowband telecommunication to wideband telephony is a change within the telecommunication industry which provides users with better speech quality experience but introduces a number of challenges in speech processing. Noise is the most common distortion on audio signals and as a result there have been a lot of studies on developing high performance noise reduction algorithms. Assistive hearing devices are designed to decrease communication difficulties for people with loss of hearing. As the algorithms within …

Realtime Implementation Of An Internal-Model-Principle Signal Identifier, Edris Saleh Mohsen

Electronic Thesis and Dissertation Repository

This thesis presents a new means approach of tuning an adaptive internal model principle based signal identification algorithm whose computational costs are low enough to allow a realtime implementation. The algorithm allows an instantaneous Fourier decomposition of nonstationary signals that have a strongly predictable component. The algorithm is implemented as a feedback loop resulting in a closed loop system with a frequency response of a bandpass filter with notches at the frequencies of the Fourier decomposition. This is achieved through real time selection of the coefficients of the transfer functions in the feedback loop. Previous work showed how the dynamics …

Predictive Shutdown Systems For Nuclear Power Plants, Drew J. Rankin

Electronic Thesis and Dissertation Repository

This dissertation investigates the use of a Kalman filter (KF) to predict, within the shutdown system (SDS) of a nuclear power plant (NPP), whether a safety parameter measurement will reach a corresponding trip set-point (TSP). The proposed predictive SDS (PSDS) designs aim to initiate shutdown actions at a time which is earlier than conventional shutdown initiation. These early detections are, in turn, expected to improve safety and productivity margins within the NPP. The KF-based point-PSDS design utilizes a linear time-varying (LTV) system model to predict mean safety parameter measurements for comparison against the TSP. The KF considers noise covariances that …

Basic Science To Clinical Research: Segmentation Of Ultrasound And Modelling In Clinical Informatics, Ali K. Hamou

Electronic Thesis and Dissertation Repository

The world of basic science is a world of minutia; it boils down to improving even a fraction of a percent over the baseline standard. It is a domain of peer reviewed fractions of seconds and the world of squeezing every last ounce of efficiency from a processor, a storage medium, or an algorithm. The field of health data is based on extracting knowledge from segments of data that may improve some clinical process or practice guideline to improve the time and quality of care. Clinical informatics and knowledge translation provide this information in order to reveal insights to …

Controlling And Processing Core For Wireless Implantable Telemetry System, Naeeme Modir

Electronic Thesis and Dissertation Repository

Wireless implantable telemetry systems are suitable choices for monitoring various physiological parameters such as blood pressure and volume. These systems typically compose of an internal device implanted into a living body captures the physiological data and sends them to an external base station located outside of the body for further processing. The internal device usually consists of a sensor interface to convert the collected data to electrical signals; a digital core to digitize the analog signals, process them and prepare them for transmission; an RF front-end to transmit the data outside the body and to receive the required commands from …