D.Ing. (Electrical and Electronic Engineering) / Please refer to full text to view abstract

This thesis presents novel techniques for the reduction of audio recordings and signal processing techniques as part of cough recognition. Evidence collected shows the reduction technique to be effective and the recognition techniques to give consistent performance across different patients. Cough is one of the commonest symptoms reported by patients to GPs. Despite this, it remains a significantly unmet medical need. At present, there exists no practical and validated technique for assessing the efficacy of therapies to treat cough on a large enough scale. Research that is presently undertaken requires fitting a patient with a recording system which will record their coughing and all other sound for a predefined period, usually 24 hours or less. This audio is then counted manually by trained cough counters to produce counts for each record which can be used as data for cough studies. Research in this field is relatively new, but a number of attempts have been made to automate this process. None so far have shown sufficient reliability or precision to be of sufficient use. The aim of this research is to analyse from the ground up signal processing techniques which can aid cough research. Specifically, the research will look into data minimisation techniques to improve the efficiency of manual counting techniques and recognition algorithmsThe research has produced a published record reduction system which can reduce 24 hour cough records down to around 10% of their original size without compromising the statistics of subsequent manual counts. Additionally, a review of signal processing techniques for cough recognition has produced a robust event detection technique and measurement techniques which have shown remarkable consistency between patients and conditions. Throughout the research a clear understanding of the limitations and possible solutions are pursued and reported on to aid further progress on what is a young and developing research field.

This thesis investigates the possibility of detecting weak vital signs, such as heartbeat and respiration rate, through the implementation of quadrature demodulation and frequency spectrum algorithms on a high performance digital signal processor. This thesis has been part of an ongoing research project at Linkoping University, with the aim to develop a sensor platform for wireless measurements of these vital signs. This sensor platform has been expected to consist of two major physical devices, a RF-radar front-end including a quadrature multi-port and a processing back-end which holds the implementation of the algorithms to detect the vital signs. The back-end consists of a data acquisition- and a processing-part which together forms the digital signal processor. The results show that the implemented algorithms works in terms of being able to find artificial vital signs from quadrature signals. This result also confirms that the hardware solution proposed during this thesis, has been considered as viable for the aim of the project.

This master thesis was completed at Limes Audio in Umeå. Limes Audio are specialized in speech enhancement software which is mostly used in conference phones. Their software is used to reduce noise, echo cancellation as well as reduction of distortion. When a conference phone is malfunctioning it can be troublesome to find the cause of the problem. Common issues that lead to perceived poor audio quality are rattling plastics, loose parts and an environment with demanding acoustics. There is a need for automatic tests to run on conference phone which can diagnose audio quality and the acoustics of the environment where the conference phone is located in. A previous master thesis by Wilhelmsson called "Estimating Loudspeaker Distortion and Room Reverberation Time Using a Speakerphone" focused on evaluating several tests run in MATLAB for analyzing acoustic characteristics of a room. The goal of this thesis was to continue the work of the master thesis by Wilhelmsson. Previous tests served as a basis for this thesis. The tests where modified and rewritten in C and run on a Linux computer connected to a specific conference phone model. In the extended test made in this thesis using sine sweep signals, the reverberation time as well as the distortion for the conference phone setup was determined. The calculated reverberation time was compared to the results using Room EQ Wizard and gave almost identical results. Total harmonic distortion was not easy to relate to the perceived audio quality. There is a need to further develop methods to take into account other types of distortion than the total harmonic distortion. Rub & buzz is one kind of distortion that could be of interest. To investigate pass or fail thresholds for reverberation time as well as distortion is central for further development of this test software.

This master’s thesis is focused on sensory systems and analysis of such signals. In the frst part, a theoretical analysis of each sensory system is conducted. Followingly, appropriate flters were used to process these signals. The last part of this thesis deals with the analysis of measured data.

This master’s thesis is focused on sensory systems and analysis of such signals. In the frst part, a theoretical analysis of each sensory system is conducted. Followingly, appropriate flters were used to process these signals. The last part of this thesis deals with the analysis of measured data.

This master thesis deals with implementation of the radar sensor for adaptive cruise control system. It discusses used technologies and processes and documents implementation of signal processing serving for the purpose of adaptive cruise control. It also describes the testing on the real data gathered in traffic. Texas Instrument's AWR1843 radar module was used as the sensor. This sensor represents currently very popular milimeter wave technology radars. Result of this master thesis are two implemented systems processing digital signal. One of them is a prototype application of the adaptive cruise control system, which also visualises the data. The other is implemented firmware of radar module doing real-time on-chip signal processing according to adaptive cruise control logic.

The utilisation of personal computers for a conditioning of audio devices has shown a significant increase, since the digital signal processing (DSP) was introduced. The expansion of the DSP has allowed implementing analyses to obtain frequency and linear characteristics, distortion parameters (THD, THD+N, WHD, SINAD), a rate of crosstalk or a signal-to-noise ratio. In this work a software analyser is developed, which is able to obtain qualitative parameters of hardware audio devices that are connected with a sound card. For an efficient communication between the sound card and the personal computer the ASIO driver is used. The application is capable to measure audio effects that are implemented in VST plug-ins. The software is developed in C++ language and the implemented analyses are based on the AES17 recommendation.

In digital image correlation, an optical full-field analysis method that can determine displacements of an object under load, high-resolution images are preferable. One way to improve the resolution is to improve the camera hardware. This can be expensive, hence another way to enhance the image is by various image processing techniques increase the resolution of the image. There are several ways of doing this and these techniques are called super-resolution. In this thesisthe theory behind several different approaches to super-resolution is presented and discussed. The goal of this Thesis has been to investigate if super-resolutionis possible in a scene with moving objects as well as movement of the camera. It became clear early on that image registration, a step in many super-resolution methods that will be explained in this thesis, was of utmost importance, and a major part of the work became comparing image registration methods. Data has been recorded and then two different super-resolution algorithms have been evaluated on a data set showing that super-resolution is possible.

As an extension of previous work done by Luke Newmeyer in his master's thesis \cite{newmeyer2018efficient}, this report presents an improved signal processing chain for efficient, real-time processing of radar data for small-scale UAV traffic control systems. The HDL design described is for a 16-channel, 2-dimensional phased array feed processing chain and includes mean subtraction, windowing, FIR filtering, decimation, spectral estimation via FFT, cross-correlation, and averaging, as well as a significant amount of control and configuration logic. The design runs near the the max allowable memory bus frequency at 300MHz, and using AXI DMA engines can achieve throughput of 38.3 Gb/s (~0.25% below theoretical 38.4 Gb/s), transferring 2MB of correlation data in about 440us. This allows for a pulse repetition frequency of nearly 2kHz, in contrast to 454Hz from the previous design. The design targets the Avnet UltraZed-EV MPSoC board, which boots custom PetaLinux images. API code and post-processing algorithms run in this environment to interface with the FPGA control registers and further process frames of data. Primary configuration options include variable sample rate, window coefficients, FIR filter coefficients, chirp length, pulse repetition interval, decimation factor, number of averaged frames, error monitoring, three DMA sampling points, and DMA ring buffer transfers. The result is a dynamic, high-speed, small-scale design which can process 16 parallel channels of data in real time for 3-dimensional detection of local UAV traffic at a range of 1000m.