Motion Cues Analysis for Parkinson Gait Recognition

Background: Previous assessment methods for PG recognition used sensor mechanisms for PG that may cause discomfort. In order to avoid stress of applying wearable sensors, computer vision (CV) based diagnostic systems for PG recognition have been proposed. Main constraints in these methods are the laboratory setup procedures: Novel colored dresses for the patients were specifically designed to segment the test body from a specific colored background. Objective: To develop an image processing tool for home-assessment of Parkinson Gait(PG) by analyzing motion cues extracted during the gait cycles. Methods: The system is based on the idea that a normal body attains equilibrium during the gait by aligning the body posture with the axis of gravity. Due to the rigidity in muscular tone, persons with PD fail to align their bodies with the axis of gravity. The leaned posture of PD patients appears to fall forward. Whereas a normal posture exhibits a constant erect posture throughout the gait. Patients with PD walk with shortened stride angle (less than 15 degrees on average) with high variability in the stride frequency. Whereas a normal gait exhibits a constant stride frequency with an average stride angle of 45 degrees. In order to analyze PG, levodopa-responsive patients and normal controls were videotaped with several gait cycles. First, the test body is segmented in each frame of the gait video based on the pixel contrast from the background to form a silhouette. Next, the center of gravity of this silhouette is calculated. This silhouette is further skeletonized from the video frames to extract the motion cues. Two motion cues were stride frequency based on the cyclic leg motion and the lean frequency based on the angle between the leaned torso tangent and the axis of gravity. The differences in the peaks in stride and lean frequencies between PG and normal gait are calculated using Cosine Similarity measurements. Results: High cosine dissimilarity was observed in the stride and lean frequencies between PG and normal gait. High variations are found in the stride intervals of PG whereas constant stride intervals are found in the normal gait. Conclusions: We propose an algorithm as a source to eliminate laboratory constraints and discomfort during PG analysis. Installing this tool in a home computer with a webcam allows assessment of gait in the home environment.

What affects recognition most – wrong wordstress or wrong word accent?

In an attempt to find out which of the two Swedish prosodic contrasts of 1) wordstress pattern and 2) tonal word accent category has the greatest communicative weight, a lexical decision experiment was conducted: in one part word stress pattern was changed from trochaic to iambic, and in the other part trochaic accentII words were changed to accent I.Native Swedish listeners were asked to decide whether the distorted words werereal words or ‘non-words’. A clear tendency is that listeners preferred to give more‘non-word’ responses when the stress pattern was shifted, compared to when wordaccent category was shifted. This could have implications for priority of phonological features when teaching Swedish as a second language.

Children's Vocabulary Development : The role of parental input, vocabulary composition and early communicative skills

The aim of this thesis is to examine the early vocabulary development of a sample of Swedish children in relation to parental input and early communicative skills. Three studies are situated in an overall description of early language development in children. The data analyzed in the thesis was collected within a larger project at Stockholm University (SPRINT- “Effects of enhanced parental input on young children’s vocabulary development and subsequent literacy development” [VR 2008-5094]). Data analysis was based on parental report via SECDI, the Swedish version of the MacArthur-Bates Communicative Development Inventories, and audio recordings. One study examined parental verbal interaction characteristics in three groups of children with varying vocabulary size at 18 months. The stability of vocabulary development at 18 and 24 months was investigated in a larger study, with focus on children’s vocabulary composition and grammatical abilities. The third study examined interrelations among early gestures, receptive and productive vocabulary, and grammar measured with M3L, i.e. three longest utterances, from 12 to 30 months. Overall results of the thesis highlight the importance of early language development. Variability in different characteristics in parental input is associated with variability in child vocabulary size. Children with large early vocabularies exhibit the most stability in vocabulary composition and the earliest grammatical development. Children’s vocabulary composition may reflect individual stylistic variation. Use of early gestures is associated differentially with receptive and productive vocabulary. Results of the thesis have implications for parents, child- and healthcare personnel, as well as researchers and educational practitioners. The results underscore the importance of high quality in adult-child interaction, with rich input fine-tuned to children’s developmental levels and age, together with high awareness of early language development.

Traffic and Road Sign Recognition

This thesis presents a system to recognise and classify road and traffic signs for the purpose of developing an inventory of them which could assist the highway engineers’ tasks of updating and maintaining them. It uses images taken by a camera from a moving vehicle. The system is based on three major stages: colour segmentation, recognition, and classification. Four colour segmentation algorithms are developed and tested. They are a shadow and highlight invariant, a dynamic threshold, a modification of de la Escalera’s algorithm and a Fuzzy colour segmentation algorithm. All algorithms are tested using hundreds of images and the shadow-highlight invariant algorithm is eventually chosen as the best performer. This is because it is immune to shadows and highlights. It is also robust as it was tested in different lighting conditions, weather conditions, and times of the day. Approximately 97% successful segmentation rate was achieved using this algorithm.Recognition of traffic signs is carried out using a fuzzy shape recogniser. Based on four shape measures - the rectangularity, triangularity, ellipticity, and octagonality, fuzzy rules were developed to determine the shape of the sign. Among these shape measures octangonality has been introduced in this research. The final decision of the recogniser is based on the combination of both the colour and shape of the sign. The recogniser was tested in a variety of testing conditions giving an overall performance of approximately 88%.Classification was undertaken using a Support Vector Machine (SVM) classifier. The classification is carried out in two stages: rim’s shape classification followed by the classification of interior of the sign. The classifier was trained and tested using binary images in addition to five different types of moments which are Geometric moments, Zernike moments, Legendre moments, Orthogonal Fourier-Mellin Moments, and Binary Haar features. The performance of the SVM was tested using different features, kernels, SVM types, SVM parameters, and moment’s orders. The average classification rate achieved is about 97%. Binary images show the best testing results followed by Legendre moments. Linear kernel gives the best testing results followed by RBF. C-SVM shows very good performance, but ?-SVM gives better results in some case.

Motion cue analysis for parkinsonian gait recognition

This paper presents a computer-vision based marker-free method for gait-impairment detection in Patients with Parkinson's disease (PWP). The system is based upon the idea that a normal human body attains equilibrium during the gait by aligning the body posture with Axis-of-Gravity (AOG) using feet as the base of support. In contrast, PWP appear to be falling forward as they are less-able to align their body with AOG due to rigid muscular tone. A normal gait exhibits periodic stride-cycles with stride-angle around 45o between the legs, whereas PWP walk with shortened stride-angle with high variability between the stride-cycles. In order to analyze Parkinsonian-gait (PG), subjects were videotaped with several gait-cycles. The subject's body was segmented using a color-segmentation method to form a silhouette. The silhouette was skeletonized for motion cues extraction. The motion cues analyzed were stride-cycles (based on the cyclic leg motion of skeleton) and posture lean (based on the angle between leaned torso of skeleton and AOG). Cosine similarity between an imaginary perfect gait pattern and the subject gait patterns produced 100% recognition rate of PG for 4 normal-controls and 3 PWP. Results suggested that the method is a promising tool to be used for PG assessment in home-environment.

Análise de ecossistemas aquáticos através do método input-output : estudo de caso lagoa Itapeva (sistema lagunar costeiro do Rio Grande do Sul)

A enorme complexidade dos sistemas ecológicos tem sido uma grande barreira para a compreensão e o gerenciamento da problemática ambiental. Neste sentido a modelagem matemática é uma valiosa ferramenta, devido a sua capacidade de organizar as informações disponíveis sobre estes sistemas e de fazer previsões a seu respeito para diferentes condições. Desta forma a análise de sistemas naturais vem sendo abordada de diferentes maneiras, sendo que nas últimas décadas a teoria de ecossistemas expandiu-se e ramos específicos, que permitem seguir e predizer a evolução de ecossistemas, foram formulados. Um destes enfoques, conhecido como análise do fluxo de insumo-produto, pode ser utilizado para explicar o funcionamento e estrutura dos subsistemas de um ecossistema através da descrição dos fluxos de matéria ou energia. A análise do fluxo de insumo-produto pode ser representada através de dois modelos: o modelo determinístico ou o modelo estocástico, tendo sua origem em estudos de caso com o objetivo de analisar a econômica norte-americana, sendo uma extensão prática da teoria clássica de interdependência geral. Este trabalho faz uma abordagem sintética da evolução desta análise, avaliando dados teóricos e principalmente dados referentes à Lagoa Itapeva. A análise de input-output (determinística e estocástica) com o propósito de obter informações no que diz respeito aos fluxos (matéria e energia), é bastante simples; sendo que os modelos determinísticos se prestam melhor para traçar um panorama global e para obter projeções para as variáveis já os modelos estocásticos são mais complexos, mas provêem uma descrição mais acurada. Na Lagoa Itapeva os processos determinísticos demonstraram um baixo índice de ciclagem do carbono entre os três compartimentos em estudo e o fluxo preferencial na normalização corresponde ao compartimento dos produtores primários, isto decorre de não existir loop nos compartimentos em estudo e também não existir fluxos em dois sentidos. Em relação à avaliação estocástica foram observadas uma baixa relação no sentido espacial superfície-meio-fundo da lagoa, e uma boa distribuição espacial norte-centro-sul. Quanto à distribuição temporal, foi constatada uma baixa concordância entre os dados analisados e os dados reais quanto das análises realizadas em intervalos de tempo pequeno (horas) e uma boa concordância nas medidas feitas quando o intervalo foi significativo (meses). Também em relação à Lagoa Itapeva, foi verificado nas análises estocásticas, utilizando-se operadores espaciais, que como a dinâmica biológica nem sempre é linear, os organismos não podem acompanhar imediatamente e perfeitamente as mudanças do ambiente, resultando em tempos de residência de matéria significativamente baixo. Além da análise dos fluxos ligados a este ecossistema lagunar, foram desenvolvidas técnicas de correção e adaptação de dados referentes à amostragem ocorrida na Lagoa durante um ano de campanha. Assim, propõe-se uma nova perspectiva no uso desta metodologia de forma simples e de fácil manipulação matemática.

March 4th, 1999 : the recognition-primed decision hypothesis

On March 4, 1999, the newly appointed President of the Brazilian Central Bank, Mr Armínio Fraga, raised interest rates to a staggering 45% per annum. The objective of that decision was to keep foreign investors assets in Brazil, and prevent the country from default. At the time, Brazil suffered frem an enormously intense crisis of confidence, and fears of such default were widespread. Mr Fraga was walking a very fine line when making that decision, for it could bring forth unintended effects: the market, already concerned about Brazil's sustainability, could perceive the increased rate as an irreversible step towards the abyss inevitable default. Economic theory postulates the rational actor model as the driving force behind economic decision-making. The objective of this thesis is to present and discuss the hypothesis that this particular decision, and by extension many others, are better explained threugh the recognition-primed decision mode!.