First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

On processing GPS tracking data of car-movements in Borlänge, Sweden

The advancement of GPS technology enables GPS devices not only to be used as orientation and navigation tools, but also to track travelled routes. GPS tracking data provides essential information for a broad range of urban planning applications such as transportation routing and planning, traffic management and environmental control. This paper describes on processing the data that was collected by tracking the cars of 316 volunteers over a seven-week period. The detailed information is extracted. The processed data is further connected to the underlying road network by means of maps. Geographical maps are applied to check how the car-movements match the road network. The maps capture the complexity of the car-movements in the urban area. The results show that 90% of the trips on the plane match the road network within a tolerance.

Image processing technique to count the number of logs in a timber truck

This paper summarises the results of using image processing technique to get information about the load of timber trucks before their arrival using digital images or geo tagged images. Once the images are captured and sent to sawmill by drivers from forest, we can predict their arrival time using geo tagged coordinates, count the number of (timber) logs piled up in a truck, identify their type and calculate their diameter. With this information we can schedule and prioritise the inflow and unloading of trucks in the light of production schedules and raw material stocks available at the sawmill yard. It is important to keep all the actors in a supply chain integrated coordinated, so that optimal working routines can be reached in the sawmill yard.   

Learning by Reading : A literature study on the use of authentic texts in the EFL upper elementary classroom

The English language is widely used throughout the world and has become a core subject in many countries, especially for students in the upper elementary classroom. While textbooks have been the preferred EFL teaching method for a long time, this belief has seemingly changed within the last few years. Therefore, this study looks at what prior research says about the use of authentic texts in the EFL upper elementary classroom with an aim to answer research questions on how teachers can work with authentic texts, what the potential benefits of using authentic texts are and what teachers and students say about the use of authentic texts in the EFL classroom. While this thesis is written from a Swedish perspective, it is recognized that many countries teach EFL. Therefore, international results have also been taken into consideration and seven previous research studies have been analyzed in order to gain a better understanding of the use of authentic texts in the EFL classroom. Results indicate that the use of authentic texts is beneficial in teaching EFL. However, many teachers are still reluctant to use these, mainly because of time constraints and the belief that such texts are too difficult for their students. Since these findings are mainly focused on areas outside of Sweden, additional research is needed before conclusions can be drawn on the use of authentic texts in the Swedish upper elementary EFL classroom.

Professional and Non-Professional Written Travel Texts – Do They Have Common Features? : A Comparative Investigation on Travel Texts on Trysil, Norway

This study aims to investigate possible distinctions between professional and non-professional written travel texts all treating the same destination: the Norwegian ski resort Trysil. The study will investigate to what extent the different texts correlate with the genre of travel texts, as the travel texts are treated as personal narratives, and how they conform to a given structure for narratives and with guidelines for professional writers. Furthermore, the investigation aims to explore to what extent there are similarities and differences between the texts regarding the given structure. The texts will first be analysed and organized separately by macrorules and a news schema that are constructed specifically for these sorts of texts, in order to reveal their discourse structure, and then compared to each other. As the discourse structure of the different texts is revealed, it is seen that there are certain differences between the two different text types. Finally, seen that the text types differ in their structure, this study will show that despite the fact that journalists write stories, and that non-professional written stories are narratives, they do not share the same structure, and are constructed in different ways.

Authentic Texts in English Language Teaching : An empirical study on the use of and attitudes towards authentic texts in the Swedish EFL upper elementary classroom

International assessments indicate that Swedish students achieve high results in reading, writing and understanding English. However, this does not mean that the students display oral proficiency, despite an emphasis on functional and communicative language skills in the current English Syllabus. While a previous literature study by this researcher has shown that authentic texts are a way to increase these skills, most of the results shown are from an international viewpoint. Thus an empirical study was conducted within Sweden with the aim to examine the use of authentic texts in the Swedish EFL upper elementary classroom. Twelve teachers have answered a questionnaire on how they use authentic texts in their language teaching, as well as their opinions about these as a teaching tool. Additionally, 37 students have answered a questionnaire on their attitudes about authentic texts. Results indicate that all of the teachers surveyed see authentic texts as an effective way to increase students’ communicative competence and English language skills; however, only a few use them with any frequency in language teaching. Furthermore, this seems to affect the students’ attitudes, since many say that they read authentic texts in their free time, but prefer to learn English out of a textbook at school. These findings are based on a small area of Sweden. Therefore, further research is needed to learn if these opinions hold true for the entire country or vary dependent upon region or other factors not taken into consideration in this study.

Convex Hulls in Image Processing : A Scoping Review

The demands of image processing related systems are robustness, high recognition rates, capability to handle incomplete digital information, and magnanimous flexibility in capturing shape of an object in an image. It is exactly here that, the role of convex hulls comes to play. The objective of this paper is twofold. First, we summarize the state of the art in computational convex hull development for researchers interested in using convex hull image processing to build their intuition, or generate nontrivial models. Secondly, we present several applications involving convex hulls in image processing related tasks. By this, we have striven to show researchers the rich and varied set of applications they can contribute to. This paper also makes a humble effort to enthuse prospective researchers in this area. We hope that the resulting awareness will result in new advances for specific image recognition applications.

The Effects of Eating Behaviors and Exercise Patterns on the Processing of Food and Exercise Related Stimuli

The effectiveness of Cognitive Behavioral Therapy (CBT) for eating disorders has established a link between cognitive processes and unhealthy eating behaviors. However, the relationship between individual differences in unhealthy eating behaviors that are not related to clinical eating disorders, such as overeating and restrained eating, and the processing of food related verbal stimuli remains undetermined. Furthermore, the cognitive processes that promote unhealthy and healthy exercise patterns remain virtually unexplored by previous research. The present study compared individual differences in attitudes and behaviors around eating and exercise to responses to food and exercise-related words using a Lexical Decision Task (LDT). Participants were recruited from Colby (n = 61) and the greater Waterville community (n = 16). The results indicate the following trends in the data: Individuals who scored high in “thin ideal” responded faster to food-related words than individuals with low “thin Ideal” scores did. Regarding the exercise-related data, individuals who engage in more “low intensity exercise” responded faster to exercise-related words than individuals who engage in less “low intensity exercise” did. These findings suggest that cognitive schemata about food and exercise might mediate individual’s eating and exercise patterns.