Engineering Science - Theses, Dissertations, and other Required Graduate Degree Essays

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Grasp Detection with Force Myography for Upper-extremity Stroke Rehabilitation Applications

Date created: 
2016-11-25
Abstract: 

Grasp training is a key aspect of stroke rehabilitation. This thesis explores the suitability of Force Myography (FMG) classification for the two-class problem of grasping, regardless of grasp-type, versus a lack of grasping, for rehabilitation applications. FMG-based grasp detection in individuals with stroke was assessed with a protocol comprising of three grasp-and-move tasks, requiring a single grasp-type. Accuracy was lower, and required more training data for individuals with stroke when compared to healthy volunteers. Despite this, accuracy was above 90% in individuals with stroke. FMG-based grasp detection was further evaluated using a second protocol comprising of multiple grasp-types and upper-extremity movements, with healthy volunteers. The utility of classifying temporal features of the FMG signal was also assessed using Area under the Receiver Operator Curve (AUC). Accuracy with the raw FMG signal was 88.8%. At certain window configurations, model-based temporal features yielded up to a 6.1% relative increase in AUC over the raw FMG signal.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Carlo Menon
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) M.A.Sc.

Polymeric Pressure Cushions for Potential Applications on Forearm Robotic Orthoses

Date created: 
2016-11-18
Abstract: 

Robot devices for stroke rehabilitation measure the interaction forces between users and the structure of the orthosis through load cells. Although these load cells are well-suited for stationary robotic devices in hospitals, they do not easily allow for the development of affordable wearable orthoses that can assist in daily living. When load cells are attached onto a robotic orthosis, they neither conform to the shape of the user’s body nor directly measure the applied forces at the contact point between the user and the orthosis. A polymeric cushion containing atmospheric air was developed as an alternative technology for measuring forces. A finite element model (FEM) of the polymeric cushion was made to simulate air pressure changes inside the polymeric cushion from applied forces. The polymeric cushions were fabricated entirely of Poly(dimethylsiloxane) (PDMS), making them biocompatible, flexible, and free of electrically conductive materials. An air pressure sensor attached to the tube of the polymeric cushion measured the air pressure and converted it into an electrical signal to be processed by a data acquisition board (DAQ). A test bench setup was made to characterize the relationship between the air pressure and applied force from each polymeric cushion, where a linear stage applied a setpoint force onto the cushion with an aluminum flat plate and a spherical glass tube. The characterization results of the experimental test bench setup were compared to the FEM results. Six polymeric cushions were mounted onto a wrist brace exoskeleton, where a LabVIEW program was written to record specific combinations of pressure sensors and measure the pronation/supination torque of the forearm (rotation), flexion/extension force of the elbow (up/down), and the internal/external rotation of the shoulder (left/right) at the forearm. These measured force values from the polymeric cushions were compared to the measured values of a torque sensor and load cell. The potential suitability of polymeric cushions for the measurement of isometric forces on an orthoses, is compared to the abilities of exoskeleton devices which involve the motions tested in this study using the wrist brace exoskeleton.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Carlo Menon
Ash Parameswaran
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) M.A.Sc.

Development of a robust pipeline for mapping of subcortical structures

Date created: 
2017-01-04
Abstract: 

This project focuses on developing a tool which can perform registration between subcortical surfaces. Current MATLAB-based ‘Spherical Demons’ algorithm, although very useful for most cases, fails to successfully complete surface registration in some cases. Therefore, FreeSurfer has been incorporated with ‘spherical demons’ algorithm to improve the existing surface registration algorithm by utilizing FreeSurfer’s superior spherical parameterization algorithm to parameterize the surface. This significantly improved the quality (smoothness and uniformity) of the parameterization over the existing spherical mapping which led to successful surface registration between subcortical surfaces.

Document type: 
Graduating extended essay / Research project
File(s): 
Senior supervisor: 
Mirza Faisal Beg
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Project) M.Eng.

Plasmonics-Based Alignment Ruler for 3D Circuit Technology

Author: 
Date created: 
2017-12-05
Abstract: 

Metallic nanostructures can be engineered to manipulate light into a certain and unique fashion. One such example of these structures is the so-called plasmonic structures, which allows the coupling of an incident radiation with the surface electrons on the metal surface of the plasmonic nanostructure. This coupling has been utilized in a wide area of applications including structural coloring, which can be used in display, imaging, sensing and security applications. One such important area that can utilize these structures is the three-dimensional integrated circuit technology (3D ICs). 3D ICs technology is about the vertical stacking and integration of various technologies that can include electronics, biological systems, chemistry analysis, energy, etc. to form one complete autonomous system. Integrating these technologies altogether involve several steps, one of which is alignment to accuracies at the micro and nanoscale. Wafer-to-Wafer and Wafer-to-chip alignment is an inherited concept from the CMOS and MEMs technologies. However, using the plasmonic structures and their spectral responses to achieve the alignment in 3D IC technology is a very new concept. In this research, an optical technique for this alignment by incorporating nano-optical technology, known as ‘alignment ruler’, is proposed, implemented, and tested.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Bozena Kaminska
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) M.A.Sc.

Design and implementation of an image based portable ELISA analyzer using EIPA and 4PLR

Author: 
Date created: 
2017-10-12
Abstract: 

This thesis presents an implementation of predictive analytics on ELISA Imaging Systems in the absence of the standard laboratory equipment for field diagnostics. To that aim I developed a custom built optical setup with image processing and machine learning techniques. Using the light absorbance and transmittance properties of chemical compounds involved in hormone assays, I was able to estimate the hormone levels across reproductive stages. This work would allow for the eventual development of compact and economical closed systems which can be used for diagnostic advisory purposes in remote areas. This line of applied research, is expected to yield data that can be used to monitor health related outcomes. To test this use I focus the development of this tool on the monitoring of women’s ovarian function. Experimental results demonstrate that our proposed model predicts hormone levels comparable to currently used commercial and laboratory methods.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Dr. Ash M Parameswaran
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) M.A.Sc.

Exploring the feasibility of ion beam gyroscope based on corona discharge

Author: 
Date created: 
2017-09-01
Abstract: 

An ion beam gyroscope has been proposed to measure the speed of rotating, which is potentially inexpensive and free of the mechanical stress. The characteristics of the low-pressure corona gas discharge in a compact discharge tube are studied to obtain a sufficient and stable ion beam source for ion beam gyroscopes. Ions moving to the cathode by the effect of an electric field can produce a current signal. If a dual-cathode discharge device is used, currents going to the two cathodes are denoted by I1and I2 respectively. If the device is placed on a rotating platform, ions will be deflected by the Coriolis effect. Thus, I1 and I2 change accordingly with rotating speeds. Consequently, the differential current between the variation of each cathode is a function of the Coriolis acceleration rate. Since a magnetic field can deflect ions in the same way as the Coriolis effect, a magnetic field is used to simulate the Coriolis effect to avoid the rotating platform in the early exploring stage. This replacement allows us to have a simpler experimental setup, and the magnetic field is also easier to control. A theoretical model has been derived to describe the motion of ions in the discharge tube. Emulation experiments were conducted to explore the correlation between speed of rotating and differential current, relevant variables and their impacts on the sensitivity of ion beam gyroscopes. These experiments demonstrate the ion beam gyroscope is feasible, although the device's sensitivity is limited by 1.6 pA/rpm.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Albert Leung
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) M.A.Sc.

Precision and reliability of application specific designs on FPGA

Date created: 
2017-04-20
Abstract: 

Application-specific designs can use hardware, such as Field Programmable Gate Array(FPGA)s, to have complete freedom. This includes defining data types as opposed to usingthe predefined standard data types supported in software that are restricted by the architectureof the target processor. Moreover FPGAs are extremely popular for computationallyintensive applications that use either integer or fixed-point calculations and have a limitedpower budget. Static Random-Access Memory (SRAM)-based FPGAs also have the potentialfor a high level of reliability by leveraging their ability to be reconfigured at runtime.In this thesis, we have selected two case studies for hardware acceleration: 1) a biomedicalimaging system for our investigations on precision and reliability Fourier Domain OpticalCoherence Tomography (FD-OCT), and 2) and a Synthetic Aperture Radar (SAR) systemfor our investigations on reliability.Fixed-point arithmetic provides faster and smaller hardware implementations for DigitalSignal Processing (DSP) applications at the expense of accuracy. Especially, when a FastFourier Transform (FFT)-Inverse Fast Fourier Transform (IFFT) pair are required as partof the calculation, the error introduced into the calculations can be significant. This errormostly affects the phase information of the processing signal. Thus, for phase sensitiveapplications, such as FD-OCT, this degradation is unacceptable. For example, a 32-bitfixed-point implementation of FD-OCT on an FPGA could result in a 78% of error comparedto double precision calculations. In order to retain the accuracy of both SAR andFD-OCT implementations, we numerically analyzed the algorithm versus fixed-point, integerand floating point numbers and introduced the adaptability of integer transforms forsuch applications, specially FD-OCT. Then, by using our custom designed Integer SplitRadix Fast Fourier Transform (Int-SRFFT) and Integer Radix-22 FFT, we decreased themaximum peak error from 78% to less than 1 percent. Moreover, a mathematical reliabilitymodel has been developed for an on-board SAR processor that informs the appropriatetechniques for increasing the reliability of the final SAR processor implementation. Variousupset mitigation strategies are introduced and two customized strategies are proposed forthis specific application. The proposed methods are based on truth vectoring and scheduledscrubbing that achieved an increase of robustness of the system by the factor of 3.8 and 4.8respectively.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Lesley Shannon
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) Ph.D.

Detecting upper extremity activity with force myography

Author: 
Date created: 
2017-09-12
Abstract: 

A novel technique named force myography (FMG) is shown to be able to detect some upper extremity (UE) status. It holds the potential to be a cost-effective solution to detect complex UE movements, which can be used for UE status monitoring and human-machine interface applications. In this thesis, a novel FMG system to capture the forearm muscle movement information was proposed. The system’s capability to detect complex UE postures was investigated. Also, its feasibility to be used in real-time UE posture detection applications, and its applicability to be utilized in a non-real-time UE activity tracking scenario were examined. Specifically, the capability of using FMG to predict the elbow, forearm, and wrist positions was investigated by studying the corresponding FMG signal patterns and classification performances. This study also used the more established surface electromyography (sEMG) method to identify the strength and weakness of FMG. Elbow, forearm, and wrist position predictions using FMG achieved 84%, 82%, and 71% accuracies respectively. The sEMG method yielded 75%, 83% and 92% accuracies for predicting the same respective positions. The feasibility of using FMG to predict a set of complex UE postures in real-time was investigated using a custom designed classification system. An experiment which required volunteers to perform a sequence of UE postures simulating a functional action, i.e., drinking from a cup, was conducted to examine the classification performance. An average accuracy of 92% with standard deviation of 3% was obtained from 6 volunteers. Also, the same system was used for controlling a robotic device that assists the forearm rotation. A 96% accuracy for predicting five forearm positions for controlling the device was obtained. Finally, the applicability of using FMG to count grasping actions during a pick-and-place (PAP) exercise was investigated. Two wireless FMG straps were prototyped to enable the capturing of FMG signal during the arm movement. A median percentage error of 1% with an interquartile range of 5% was achieved for counting 120 PAP actions with ten volunteers.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Carlo Menon
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) Ph.D.

Improving EEG Classification Accuracy of Single Limb Imaginary Movements by Leveraging an Established EMG Pattern Recognition Scheme

Author: 
Date created: 
2017-09-27
Abstract: 

Brain-computer interfaces may enable the collaboration between human and machines. They can in fact potentially translate the electrical activity of the brain to understandable commands to operate a machine or a device.In this thesis, a method is proposed to improve the accuracy of a BCI by leveraging an established electromyography (EMG) pattern recognition scheme. Such a pattern recognition scheme extracts time-domain features, which include autoregressive (AR) model coefficients, root mean square (RMS), waveform length (WL) and classifies them using an optimized support vector machine (SVM) with a radial basis kernel function (RBF).Upon validating that such a method can indeed process EMG signals to classify different fifteen movements of the arm with high accuracy (> 90%), this thesis investigates the possibility of implementing it for the design of a BCI based on electroencephalographic (EEG) signals. The discrimination of rest, imaginary grasp and imaginary elbow movement of the same limb was selected as test case to validate the designed BCI. This classification task is particularly challenging because imaginary movements within the same limb have close spatial representations on the motor cortex area.The use of the proposed method was demonstrated to be suitable for identifying imaginary movements using EEG signal. In fact, the investigated method achieved an average accuracy of 91.8 % and 90 % for identifying the user intention corresponding to imaginary grasps and imaginary elbow movements (2-class BCI). An average classification accuracy of 74.2 % was achieved for classification of rest versus imaginary grasps versus imaginary elbow movements (3-class BCI).The investigated method outperformed methods that are widely used in the BCI literature such as common spatial patterns (CSP), filter bank CSP (FBCSP), and band power methods. These results are encouraging and the proposed method could potentially be used in the future in BCI-driven robotic devices to assist individuals with impaired upper extremity functions in performing daily tasks.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Carlo Menon
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) Ph.D.

USB 3.0 machine vision camera hardware design and FPGA implementation

Author: 
Date created: 
2017-05-31
Abstract: 

Machine vision camera is becoming more popular in the industry. USB 3.0 interface support 5Gbps transmission, and is a low-cost and fast way to transmit video signals from sensors to computers. However, most image sensors are incompatible with USB 3.0 protocol, and cannot directly connect to USB 3.0. In this report, we present the development of the hardware design of a USB 3.0 multi-purpose camera using the Cypress microprocessor. Our camera also has a FPGA module as an adaptive part to provide protocol translation, voltage level conversion, serial to parallel conversion, multi-channel data collection, and clock synthesis. We also discuss some important principles of system and schematic design, and emphasize a few critical PCB routing rules for assurance of PCB integrity. Some testing outcomes are provided to illustrate the hardware functionality and algorithm running results, which verify the success of the design and the performance of the camera.

Document type: 
Graduating extended essay / Research project
File(s): 
Senior supervisor: 
Jie Liang
Marinko Sarunic Jianbing Wu
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Project) M.Eng.