Gait analysis using a single wearable inertial measurement unit

Procedures for quantitative walking analysis include the assessment of body segment movements within defined gait cycles. Recently, methods to track human body motion using inertial measurement units have been suggested. It is not known if these techniques can be readily transferred to clinical measurement situations. This work investigates the aspects necessary for one inertial measurement unit mounted on the lower back to track orientation, and determine spatio-temporal features of gait outside the confines of a conventional gait laboratory. Apparent limitations of different inertial sensors can be overcome by fusing data using methods such as a Kalman filter. The benefits of optimizing such a filter for the type of motion are unknown. 3D accelerations and 3D angular velocities were collected for 18 healthy subjects while treadmill walking. Optimization of Kalman filter parameters improved pitch and roll angle estimates when compared to angles derived using stereophotogrammetry. A Weighted Fourier Linear Combiner method for estimating 3D orientation angles by constructing an analytical representation of angular velocities and allowing drift free integration is also presented. When tested this method provided accurate estimates of 3D orientation when compared to stereophotogrammetry. Methods to determine spatio-temporal features from lower trunk accelerations generally require knowledge of sensor alignment. A method was developed to estimate the instants of initial and final ground contact from accelerations measured by a waist mounted inertial device without rigorous alignment. A continuous wavelet transform method was used to filter and differentiate the signal and derive estimates of initial and final contact times. The technique was tested with data recorded for both healthy and pathologic (hemiplegia and Parkinson’s disease) subjects and validated using an instrumented mat. The results show that a single inertial measurement unit can assist whole body gait assessment however further investigation is required to understand altered gait timing in some pathological subjects.

Peak-to-Peak Output Current Ripple Analysis in Multiphase and Multilevel Inverters

Analysis of the peak-to-peak output current ripple amplitude for multiphase and multilevel inverters is presented in this PhD thesis. The current ripple is calculated on the basis of the alternating voltage component, and peak-to-peak value is defined by the current slopes and application times of the voltage levels in a switching period. Detailed analytical expressions of peak-to-peak current ripple distribution over a fundamental period are given as function of the modulation index. For all the cases, reference is made to centered and symmetrical switching patterns, generated either by carrier-based or space vector PWM. Starting from the definition and the analysis of the output current ripple in three-phase two-level inverters, the theoretical developments have been extended to the case of multiphase inverters, with emphasis on the five- and seven-phase inverters. The instantaneous current ripple is introduced for a generic balanced multiphase loads consisting of series RL impedance and ac back emf (RLE). Simplified and effective expressions to account for the maximum of the output current ripple have been defined. The peak-to-peak current ripple diagrams are presented and discussed. The analysis of the output current ripple has been extended also to multilevel inverters, specifically three-phase three-level inverters. Also in this case, the current ripple analysis is carried out for a balanced three-phase system consisting of series RL impedance and ac back emf (RLE), representing both motor loads and grid-connected applications. The peak-to-peak current ripple diagrams are presented and discussed. In addition, simulation and experimental results are carried out to prove the validity of the analytical developments in all the cases. The cases with different phase numbers and with different number of levels are compared among them, and some useful conclusions have been pointed out. Furthermore, some application examples are given.

Analysis of the pig genome for the identification of genomic regions affecting production traits

The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

Statistical analysis of the error associated with the simplification of the stratigraphy in geotechnical models

The uncertainties in the determination of the stratigraphic profile of natural soils is one of the main problems in geotechnics, in particular for landslide characterization and modeling. The study deals with a new approach in geotechnical modeling which relays on a stochastic generation of different soil layers distributions, following a boolean logic – the method has been thus called BoSG (Boolean Stochastic Generation). In this way, it is possible to randomize the presence of a specific material interdigitated in a uniform matrix. In the building of a geotechnical model it is generally common to discard some stratigraphic data in order to simplify the model itself, assuming that the significance of the results of the modeling procedure would not be affected. With the proposed technique it is possible to quantify the error associated with this simplification. Moreover, it could be used to determine the most significant zones where eventual further investigations and surveys would be more effective to build the geotechnical model of the slope. The commercial software FLAC was used for the 2D and 3D geotechnical model. The distribution of the materials was randomized through a specifically coded MatLab program that automatically generates text files, each of them representing a specific soil configuration. Besides, a routine was designed to automate the computation of FLAC with the different data files in order to maximize the sample number. The methodology is applied with reference to a simplified slope in 2D, a simplified slope in 3D and an actual landslide, namely the Mortisa mudslide (Cortina d’Ampezzo, BL, Italy). However, it could be extended to numerous different cases, especially for hydrogeological analysis and landslide stability assessment, in different geological and geomorphological contexts.

Studio dell'innesco di frane rapide in un'area campione dell'Appennino Bolognese

Il lavoro di tesi ha preso spunto da un fenomeno franoso avvenuto a Porretta Terme (provincia di Bologna), nell’autunno 2008, a causa di abbondanti precipitazioni, in tale occasione si innescò una colata rapida di detriti che invase la strada statale n. 64 e lambì la ferrovia che collega l’Emilia Romagna e la Toscana. I detriti colpirono anche un’abitazione, senza per fortuna causare perdite umane ne danni ingenti, ma l’evento riscosse numerose attenzioni da parte della popolazione locale, preoccupata che fenomeni del genere potessero ripetersi anche in altre zone e senza alcun preavviso. L’evento allertò anche la Protezione Civile regionale che da subito si interessò all’applicazione di metodi in grado di prevedere la suscettività areale da frane di questo tipo. Metodi previsionali per colate rapide sono stati sviluppati negli ultimi anni in diverse università sia in Europa sia negli Stati Uniti d’America. Lo scopo è quello di prevedere le possibili zone di innesco e individuare le soglie di precipitazione critica in modo da realizzare carte di suscettività a scopo di pianificazione territoriale e mitigazione del rischio. Il lavoro, durato diversi mesi, è passato attraverso diverse fasi. In primis si è proceduto a sopralluoghi di campo al fine di inquadrare l’area oggetto di studio dal punto di vista geologico e geomorfologico. Successivamente è stata svolta una fase di campionamento sul terreno; tramite una trivella manuale sono stati effettuati numerosi carotaggi (circa 60) sparsi sull’intero versante oggetto di studio, al fine di ricavare un dato relativo allo spessore del suolo. Inoltre sono stati raccolti dei campioni di terreno, analizzati successivamente in laboratorio al fine di ricavarne le curve granulometriche e alcuni dati caratterizzanti. Terminata la fase sul terreno, si è provveduto ad effettuare le prove di laboratorio (curve granulometriche, limiti di Attemberg, etc). Grazie ai dati raccolti, è stato possibile applicare un modello previsionale di stabilità superficiale, TRIGRS 2.0 basato sull’infiltrazione in un mezzo non saturo di una precipitazione di durata finita. Particolare attenzione è stata rivolta ai metodi per la previsione dello spessore del suolo (Z Model, S Model, Sexp Model) e alla loro influenza nella suscettività da frana superficiale.

Analisi della suscettività da frane rapide nell'Appennino Bolognese

Nel presente lavoro di tesi, partendo dall’Inventario del Dissesto della Regione Emilia – Romagna sono stati individuati i fenomeni di colata rapida di detrito che hanno interessato l’Appennino Bolognese negli ultimi anni. Si tratta di fenomeni rapidi, altamente pericolosi e ancora poco studiati. Ad ogni evento individuato è stata associata la precipitazione di innesco, caratterizzandola in termini di durata (D) e intensità (I) al fine di confrontarla con le soglie probabilistiche bayesiane proposte da Berti et al. (2012). Nella maggior parte dei casi è stato verificato che gli eventi considerati ricadono al di sopra delle soglie considerate come limite accettabile. Successivamente è stato applicato il metodo fisicamente basato SHALSTAB (SHALlow STABility model. Montgomery & Dietricht, 1994) al fine di valutarne la capacità previsionale al variare dei dati di input. Ne è emerso che tale metodo risulta fortemente influenzato dalla topografia. Dai dati esaminati, è stato dedotto che i fenomeni di colata rapida si sono innescati in seguito a eventi di pioggia fortemente transitori, pertanto l’applicazione del metodo SHALSTAB, che presuppone flusso allo stato stazionario mal si adatta a riprodurre questi casi.

Caratterizzazione geologico tecnica di terreni limoso sabbiosi soggetti a colate detritiche.

Le frane superficiali sono degli eventi franosi che si innescano nelle maggior parte dei casi a causa delle forti pioggie. Se la coltre di terreno è costituita prevalentemente da terreni granulari la frana può involvere in colata di detrito. Per conoscere il meccanismo bisogna conoscere le caratteristiche del terreno coinvolto. Sono state effettuate prove di taglio e prove triassiali su un materiale prelevato da un versante soggetto a colate detritiche per investigare il comportamento che provaca questi eventi franosi.

Test-retest reliability of the nociceptive withdrawal reflex and electrical pain thresholds after single and repeated stimulation in patients with chronic low back pain

Recent studies have shown that the nociceptive withdrawal reflex threshold (NWR-T) and the electrical pain threshold (EP-T) are reliable measures in pain-free populations. However, it is necessary to investigate the reliability of these measures in patients with chronic pain in order to translate these techniques from laboratory to clinic. The aims of this study were to determine the test-retest reliability of the NWR-T and EP-T after single and repeated (temporal summation) electrical stimulation in a group of patients with chronic low back pain, and to investigate the association between the NWR-T and the EP-T. To this end, 25 patients with chronic pain participated in three identical sessions, separated by 1 week in average, in which the NWR-T and the EP-T to single and repeated stimulation were measured. Test-retest reliability was assessed using intra-class correlation coefficient (ICC), coefficient of variation (CV), and Bland-Altman analysis. The association between the thresholds was assessed using the coefficient of determination (r (2)). The results showed good-to-excellent reliability for both NWR-T and EP-T in all cases, with average ICC values ranging 0.76-0.90 and average CV values ranging 12.0-17.7%. The association between thresholds was better after repeated stimulation than after single stimulation, with average r (2) values of 0.83 and 0.56, respectively. In conclusion, the NWR-T and the EP-T are reliable assessment tools for assessing the sensitivity of spinal nociceptive pathways in patients with chronic pain.

The course of chronic and recurrent low back pain in the general population

Using latent class analysis (LCA), a previous study on patients attending primary care identified four courses of low back pain (LBP) over the subsequent 6 months. To date, no studies have used longitudinal pain recordings to examine the "natural" course of recurrent and chronic LBP in a population-based sample of individuals. This study examines the course of LBP in the general population and elaborates on the stability and criterion-related validity of the clusters derived. A random sample of 400 individuals reporting LBP in a population-based study was asked to complete a comprehensive questionnaire at the start and end of the year's survey, and 52 weekly pain diaries in between. The latter were analyzed using LCA. 305 individuals returned more than 50% of the diaries. Four clusters were identified (severe persistent, moderate persistent, mild persistent, and fluctuating). The clusters differed significantly with regards to pain and disability. Assessment of cluster stability showed that a considerable proportion of patients in the "fluctuating" group changed their classification over time. Three of the four clusters describing the typical course of pain matched the clusters described previously for patients in primary care. Due to the population-based design, this study achieves, for the first time, a close insight into the "natural" course of chronic and recurrent low back pain, including individuals that did not necessarily visit the general practitioner. The findings will help to understand better the nature of this pain in the general population.

Perceived functional ability assessed with the spinal function sort: is it valid for European rehabilitation settings in patients with non-specific non-acute low back pain?

The aim of this study involving 170 patients suffering from non-specific low back pain was to test the validity of the spinal function sort (SFS) in a European rehabilitation setting. The SFS, a picture-based questionnaire, assesses perceived functional ability of work tasks involving the spine. All measurements were taken by a blinded research assistant; work status was assessed with questionnaires. Our study demonstrated a high internal consistency shown by a Cronbach's alpha of 0.98, reasonable evidence for unidimensionality, spearman correlations of >0.6 with work activities, and discriminating power for work status at 3 and 12 months by ROC curve analysis (area under curve = 0.760 (95% CI 0.689-0.822), respectively, 0.801 (95% CI 0.731-0.859). The standardised response mean within the two treatment groups was 0.18 and -0.31. As a result, we conclude that the perceived functional ability for work tasks can be validly assessed with the SFS in a European rehabilitation setting in patients with non-specific low back pain, and is predictive for future work status.

A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.

Effect of intravenous tropisetron on modulation of pain and central hypersensitivity in chronic low back pain patients

The activation of 5-hydroxytryptamine-3 (5-HT-3) receptors in spinal cord can enhance intrinsic spinal mechanisms of central hypersensitivity, possibly leading to exaggerated pain responses. Clinical studies suggest that 5-HT-3 receptor antagonists may have an analgesic effect. This randomized, double-blind, placebo-controlled crossover study tested the hypothesis that the 5-HT-3 receptor antagonist tropisetron attenuates pain and central hypersensitivity in patients with chronic low back pain. Thirty patients with chronic low back pain, 15 of whom were women (aged 53 ± 14 years) and 15 men (aged 48 ± 14 years), were studied. A single intravenous injection of 0.9% saline solution, tropisetron 2mg, and tropisetron 5mg was administrated in 3 different sessions, in a double-blind crossover manner. The main outcome was the visual analogue scale (VAS) score of spontaneous low back pain before, and 15, 30, 60, and 90 minutes after drug administration. Secondary outcomes were nociceptive withdrawal reflexes to single and repeated electrical stimulation, area of reflex receptive fields, pressure pain detection and tolerance thresholds, conditioned pain modulation, and area of clinical pain. The data were analyzed by analysis of variance and panel multiple regressions. All 3 treatments reduced VAS scores. However, there was no statistically significant difference between tropisetron and placebo in VAS scores. Compared to placebo, tropisetron produced a statistically significant increase in pain threshold after single electrical stimulation, but no difference in all other secondary outcomes was found. A single-dose intravenous administration of tropisetron in patients with chronic low back pain had no significant specific effect on intensity of pain and most parameters of central hypersensitivity.

Geochemical Modeling and Analysis of the Frac Water Used in the Hydraulic Fracturing of the Marcellus Formation, Pennsylvania

The hydraulic fracturing of the Marcellus Formation creates a byproduct known as frac water. Five frac water samples were collected in Bradford County, PA. Inorganic chemical analysis, field parameters analysis, alkalinity titrations, total dissolved solids(TDS), total suspended solids (TSS), biological oxygen demand (BOD), and chemical oxygen demand (COD) were conducted on each sample to characterize frac water. A database of frac water chemistry results from across the state of Pennsylvania from multiple sources was compiled in order to provide the public and research communitywith an accurate characterization of frac water. Four geochemical models were created to model the reactions between frac water and the Marcellus Formation, Purcell Limestone, and the oil field brines presumed present in the formations. The average concentrations of chloride and TDS in the five frac water samples were 1.1 �± 0.5 x 105 mg/L (5.5X average seawater) and 140,000 mg/L (4X average seawater). BOD values for frac water immediately upon flow back were over 10X greater than the BOD of typical wastewater, but decreased into the range of typical wastewater after a short period of time. The COD of frac water decreases dramatically with an increase in elapsed time from flow back, but remain considerably higher than typicalwastewater. Different alkalinity calculation methods produced a range of alkalinity values for frac water: this result is most likely due to high concentrations of aliphatic acid anions present in the samples. Laboratory analyses indicate that the frac watercomposition is quite variable depending on the companies from which the water was collected, the geology of the local area, and number of fracturing jobs in which the frac water was used, but will require more treatment than typical wastewater regardless of theprecise composition of each sample. The geochemical models created suggest that the presence of organic complexes in an oil field brine and Marcellus Formation aid in the dissolution of ions such as bariumand strontium into the solution. Although equilibration reactions between the Marcellus Formation and the slickwater account for some of the final frac water composition, the predominant control of frac water composition appears to be the ratio of the mixture between the oil field brine and slickwater. The high concentration of barium in the frac water is likely due to the abundance of barite nodules in the Purcell Limestone, and the lack of sulfate in the frac water samples is due to the reducing, anoxic conditions in the earth's subsurface that allow for the degassing of H2S(g).

Predictors of sickness absence in patients with a new episode of low back pain in primary care

This study examines predictors of sickness absence in patients presenting to a health practitioner with acute/ subacute low back pain (LBP). Aims of this study were to identify baseline-variables that detect patients with a new LBP episode at risk of sickness absence and to identify prognostic models for sickness absence at different time points after initial presentation. Prospective cohort study investigating 310 patients presenting to a health practitioner with a new episode of LBP at baseline, three-, six-, twelve-week and six-month follow-up, addressing work-related, psychological and biomedical factors. Multivariate logistic regression analysis was performed to identify baseline-predictors of sickness absence at different time points. Prognostic models comprised 'job control', 'depression' and 'functional limitation' as predictive baseline-factors of sickness absence at three and six-week follow-up with 'job control' being the best single predictor (OR 0.47; 95%CI 0.26-0.87). The six-week model explained 47% of variance of sickness absence at six-week follow-up (p<0.001). The prediction of sickness absence beyond six-weeks is limited, and health practitioners should re-assess patients at six weeks, especially if they have previously been identified as at risk of sickness absence. This would allow timely intervention with measures designed to reduce the likelihood of prolonged sickness absence.

A survey of MRI-based medical image analysis for brain tumor studies

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.