Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices.Mohamed Elgendi, Björn Eskofier, Socrates Dokos, Derek Abbot

Image enhancement techniques applied to solar feature detection

This dissertation presents the development of automatic image enhancement techniques for solar feature detection. The new method allows for detection and tracking of the evolution of filaments in solar images. Series of H-alpha full-disk images are taken in regular time intervals to observe the changes of the solar disk features. In each picture, the solar chromosphere filaments are identified for further evolution examination. The initial preprocessing step involves local thresholding to convert grayscale images into black-and-white pictures with chromosphere granularity enhanced. An alternative preprocessing method, based on image normalization and global thresholding is presented. The next step employs morphological closing operations with multi-directional linear structuring elements to extract elongated shapes in the image. After logical union of directional filtering results, the remaining noise is removed from the final outcome using morphological dilation and erosion with a circular structuring element. Experimental results show that the developed techniques can achieve excellent results in detecting large filaments and good detection rates for small filaments. The final chapter discusses proposed directions of the future research and applications to other areas of solar image processing, in particular to detection of solar flares, plages and sunspots

Development of collision avoidance system for useful UAV applications using image sensors with laser transmitter

The main goal of this study is to demonstrate the approach of achieving collision avoidance on Quadrotor Unmanned Aerial Vehicle (QUAV) using image sensors with colour-based tracking method. A pair of high definition (HD) stereo cameras were chosen as the stereo vision sensor to obtain depth data from flat object surfaces. Laser transmitter was utilized to project high contrast tracking spot for depth calculation using common triangulation. Stereo vision algorithm was developed to acquire the distance from tracked point to QUAV and the control algorithm was designed to manipulate QUAV's response based on depth calculated. Attitude and position controller were designed using the non-linear model with the help of Optitrack motion tracking system. A number of collision avoidance flight tests were carried out to validate the performance of the stereo vision and control algorithm based on image sensors. In the results, the UAV was able to hover with fairly good accuracy in both static and dynamic collision avoidance for short range collision avoidance. Collision avoidance performance of the UAV was better with obstacle of dull surfaces in comparison to shiny surfaces. The minimum collision avoidance distance achievable was 0.4 m. The approach was suitable to be applied in short range collision avoidance

Experimental and Numerical Investigations of Wettability of Positive Electrodes for Li−O2 Batteries

The objective of this dissertation is to characterize the positive electrode wettability and its effects on the performance (e.g., discharge capacity) of Li−O2 batteries. The investigations include an experimental study of discharging electrodes with various wettabilities, proposing and examining the intermittent discharge strategy, and the numerical simulation of the distribution of the electrolyte at various saturations and of the discharge performance of Li−O2 batteries at the pore scale. Future work will measure the structure of positive electrodes using advanced imaging technology such as transmission X-ray microscopy. First, I fabricated the electrodes and adjusted their wettability by mixing acetylene black carbon particles with various binders. The wettability was quantitatively characterized by the contact angle and ionic resistance. The customized electrodes were then discharged in Li−O2 batteries at 0.1 mA/cm2 through which the relationship between electrode wettability and discharge capacity was obtained. The discharge capacity of the electrode with 15% PVDF (36.5°) binder was 1665.8 mAh/g while the customized electrode with 15% PTFE (128.4°) binder had a discharge capacity of 4160.8 mAh/g. The effects of lyophobicity on O2 transfer in the porous electrode have been proved. A positive electrode with mixed wettability was designed and tested, which acquired the highest specific discharge capacity of 5149.5 mAh/g. The structure of this electrode included two lyophobic carbon coatings on top and bottom and one lyophilic carbon coating in the middle. Further design may focus on appropriately configuring the wettability to balance the gas paths for O2 diffusion and wetted area for reaction sites. A novel strategy for discharging Li−O2 batteries was then proposed and identified. The battery was periodically discharged and rested, which can enhance O2 availability and increase the discharge capacity. Periodically resting the battery increased the specific discharge capacity by at least 50% at various current densities (0.1 - 1.5 mA/cm2). Afterward, the investigation combined the electrode wettability and the intermittent strategy. Compared with the continuous strategy, the capacity of lyophobic electrodes increased by over 100% when the intermittent strategy was applied. Besides, a multi-step discharge strategy can provide greater capacity when the battery is discharged at decreasing current rates (2.0, 1.5, and 1.0 mA/cm2). The importance of O2 diffusion is emphasized and provide practical strategies are proposed to improve the deep discharge capacity of Li-O2 batteries, especially at high current rates (> 1.0 mA/cm2). Finally, a numerical study was conducted to investigate the electrode with different saturations of the electrolyte. The effects of electrolyte saturation levels and the distribution of electrolyte have been demonstrated by comparing the corresponding discharge performance of Li-O2 batteries. It was found that fully saturated electrodes (100% saturation) have high oxygen transfer resistance, which will result in the lowest discharge capacity of 7.41 Ah/g. On the contrary, over-dried battery (with 1.0 mA/cm2). Finally, a numerical study was conducted to investigate the electrode with different saturations of the electrolyte. The effects of electrolyte saturation levels and the distribution of electrolyte have been demonstrated by comparing the corresponding discharge performance of Li-O2 batteries. It was found that fully saturated electrodes (100% saturation) have high oxygen transfer resistance, which will result in the lowest discharge capacity of 7.41 Ah/g. On the contrary, over-dried battery (with 7 Ah/g) at high current (20 A/m2) similar to hydrophilic electrodes which are fully saturated by the electrolyte at low current (1 A/m2). The modeling study found that designing the electrode with a mixture of lyophilic and lyophobic pores is critical to significantly increasing (by orders of magnitude) the operating current and power of the Li–O2 battery. In the future, plans are to characterize the geometry of the positive electrode using the imaging techniques (e.g., transmission X-ray microscopy) and gas sorption method. Based on the characterization of the porous structure, the relationship between the porous structure and the mass transport phenomena will be clarified

Reports on computer graphics testbed to simulate and test vision systems for space applications

Three reports are presented on computer graphics testbed to simulate and test vision systems for space applications

Evaluation of yarn characteristics using computer vision and image processing

Irregularity, hairiness and twist are among the most important characteristics that define yarn quality. This thesis describes computer vision and image processing techniques developed to evaluate these characteristics. The optical and electronic aspects such as the illumination, lens parameters and aberrations play crucial role on the quality of yam images and on the overall performance of image processing. The depth of field limitation being the most important restraint in yam imaging as well as image distortion in line scan cameras arising from digitisation and yam movement are modelled mathematically and verified through experiments both for front-lit and back-lit illuminations. Various light sources and arrangements are tested and relative advantages and disadvantages are discussed based on the image quality. Known problems in defining the hair-core boundaries and determining the total hairiness from yam images are addressed and image enhancement and processing algorithms developed to overcome these problems are explained. A method to simulate various yam scanning resolution conditions is described. Using this method, the minimum scanning resolution limits to measure the hairiness and irregularity are investigated. [Continues.

Application of Machine Vision in UAVs for Autonomous Target Tracking

This research presents experimental results for the application of Machine Vision (MV) techniques to address the problem of target detection and tracking. The main objective is the design of a prototype UAV surveillance environment to emulate real-life conditions. The model environment for this experiment consists of a target simulated by a small electric train system, located at ground level, and a MV camera mounted on a motion-based apparatus located directly above the model setup. This system is meant to be a non-flying mockup of an aerial robot retrofitted with a MV sensor. Therefore, the final design is a two degree-of-freedom gantry simulating aircraft motions above the ground level at a constant altitude. On the ground level, the design of the landscape is an attempt to achieve a realistic natural landscape within a laboratory setting. Therefore, the scenery consists of small scale trees, bushes, a mountain, and a tunnel system within a 914 mm by 1066 mm boundary. To detect and track the moving train, MV algorithms are implemented in a Matlab/SimulinkRTM based simulation environment. Specifically, image pre-processing techniques and circle detection algorithms are implemented to detect and identify the chimney stack on the train engine. The circle detection algorithms analyzed in this research effort consists of a least squares based method and the Hough transform (HT) method for circle detection. The experimental results will show that the solution to the target detection problem could produce a positive detection rate of 90% during each simulation while utilizing only 56% of the input image. Tracking and timing data also shows that the least squares based target detection method performs substantially better then the HT method. This is evident from the result of using a 1--2 Hz frequency update rate for the SimulinkRTM scheme which is acceptable, in some cases, for use in navigation for a UAV performing scouting and reconnaissance missions. The development of vision-based control strategies, similar to the approach presented in this research, allows UAVs to participate in complex missions involving autonomous target tracking