HIGH PERFORMANCE, LOW COST SUBSPACE DECOMPOSITION AND POLYNOMIAL ROOTING FOR REAL TIME DIRECTION OF ARRIVAL ESTIMATION: ANALYSIS AND IMPLEMENTATION

This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

Validation of a new method for determination of cup orientation in THA

Our goal was to validate accuracy, consistency, and reproducibility/reliability of a new method for determining cup orientation in total hip arthroplasty (THA). This method allows matching the 3D-model from CT images or slices with the projected pelvis on an anteroposterior pelvic radiograph using a fully automated registration procedure. Cup orientation (inclination and anteversion) is calculated relative to the anterior pelvic plane, corrected for individual malposition of the pelvis during radiograph acquisition. Measurements on blinded and randomized radiographs of 80 cadaver and 327 patient hips were investigated. The method showed a mean accuracy of 0.7 +/- 1.7 degrees (-3.7 degrees to 4.0 degrees) for inclination and 1.2 +/- 2.4 degrees (-5.3 degrees to 5.6 degrees) for anteversion in the cadaver trials and 1.7 +/- 1.7 degrees (-4.6 degrees to 5.5 degrees) for inclination and 0.9 +/- 2.8 degrees (-5.2 degrees to 5.7 degrees) for anteversion in the clinical data when compared to CT-based measurements. No systematic errors in accuracy were detected with the Bland-Altman analysis. The software consistency and the reproducibility/reliability were very good. This software is an accurate, consistent, reliable, and reproducible method to measure cup orientation in THA using a sophisticated 2D/3D-matching technique. Its robust and accurate matching algorithm can be expanded to statistical models.

Comparison of calcium analysis, longitudinal microradiography and profilometry for the quantitative assessment of erosion in dentine

Erosion of dentine causes mineral dissolution, while the organic compounds remain at the surface. Therefore, a determination of tissue loss is complicated. Established quantitative methods for the evaluation of enamel have also been used for dentine, but the suitability of these techniques in this field has not been systematically determined. Therefore, this study aimed to compare longitudinal microradiography (LMR), contacting (cPM) and non-contacting profilometry (ncPM), and analysis of dissolved calcium (Ca analysis) in the erosion solution. Results are discussed in the light of the histology of dentine erosion. Erosion was performed with 0.05 M citric acid (pH 2.5) for 30, 60, 90 or 120 min, and erosive loss was determined by each method. LMR, cPM and ncPM were performed before and after collagenase digestion of the demineralised organic surface layer, with an emphasis on moisture control. Scanning electron microscopy was performed on randomly selected specimens. All measurements were converted into micrometres. Profilometry was not suitable to adequately quantify mineral loss prior to collagenase digestion. After 120 min of erosion, values of 5.4 +/- 1.9 microm (ncPM) and 27.8 +/- 4.6 microm (cPM) were determined. Ca analysis revealed a mineral loss of 55.4 +/- 11.5 microm. The values for profilometry after matrix digestion were 43.0 +/- 5.5 microm (ncPM) and 46.9 +/- 6.2 (cPM). Relative and proportional biases were detected for all method comparisons. The mineral loss values were below the detection limit for LMR. The study revealed gross differences between methods, particularly when demineralised organic surface tissue was present. These results indicate that the choice of method is critical and depends on the parameter under study.

Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials

A system for screening of nutritional risk is described. It is based on the concept that nutritional support is indicated in patients who are severely ill with increased nutritional requirements, or who are severely undernourished, or who have certain degrees of severity of disease in combination with certain degrees of undernutrition. Degrees of severity of disease and undernutrition were defined as absent, mild, moderate or severe from data sets in a selected number of randomized controlled trials (RCTs) and converted to a numeric score. After completion, the screening system was validated against all published RCTs known to us of nutritional support vs spontaneous intake to investigate whether the screening system could distinguish between trials with a positive outcome and trials with no effect on outcome.

Investigating Research Streams of Conjoint Analysis: A Bibliometric Study

Conjoint analysis (CA) is one of the most important methods for preference elicitation. In this paper we investigate the intellectual structure within the conjoint analytical research community. Analyses based on single papers provide a method-based overview of streams of conjoint research. By using novel bibliometric techniques in this field we complement findings of existing reviews. We use co-citation and factor analysis of the most cited articles in SSCI to identify the most important articles and research streams. Seven research streams are revealed which are visualized by means of multidimensional scaling. Tables and graphics reveal the disciplinary affiliations of contributors to CA, the special structure within the classes as well as links between them.

The silent loss of neuronavigation accuracy: a systematic retrospective analysis of factors influencing the mismatch of frameless stereotactic systems in cranial neurosurgery

BACKGROUND Neuronavigation has become an intrinsic part of preoperative surgical planning and surgical procedures. However, many surgeons have the impression that accuracy decreases during surgery. OBJECTIVE To quantify the decrease of neuronavigation accuracy and identify possible origins, we performed a retrospective quality-control study. METHODS Between April and July 2011, a neuronavigation system was used in conjunction with a specially prepared head holder in 55 consecutive patients. Two different neuronavigation systems were investigated separately. Coregistration was performed with laser-surface matching, paired-point matching using skin fiducials, anatomic landmarks, or bone screws. The initial target registration error (TRE1) was measured using the nasion as the anatomic landmark. Then, after draping and during surgery, the accuracy was checked at predefined procedural landmark steps (Mayfield measurement point and bone measurement point), and deviations were recorded. RESULTS After initial coregistration, the mean (SD) TRE1 was 2.9 (3.3) mm. The TRE1 was significantly dependent on patient positioning, lesion localization, type of neuroimaging, and coregistration method. The following procedures decreased neuronavigation accuracy: attachment of surgical drapes (DTRE2 = 2.7 [1.7] mm), skin retractor attachment (DTRE3 = 1.2 [1.0] mm), craniotomy (DTRE3 = 1.0 [1.4] mm), and Halo ring installation (DTRE3 = 0.5 [0.5] mm). Surgery duration was a significant factor also; the overall DTRE was 1.3 [1.5] mm after 30 minutes and increased to 4.4 [1.8] mm after 5.5 hours of surgery. CONCLUSION After registration, there is an ongoing loss of neuronavigation accuracy. The major factors were draping, attachment of skin retractors, and duration of surgery. Surgeons should be aware of this silent loss of accuracy when using neuronavigation.

Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics

We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.