A review of Parkinson’s disease cardinal and dyskinetic motor symptoms assessment methods using sensor systems

This paper is reviewing objective assessments of Parkinson’s disease(PD) motor symptoms, cardinal, and dyskinesia, using sensor systems. It surveys the manifestation of PD symptoms, sensors that were used for their detection, types of signals (measures) as well as their signal processing (data analysis) methods. A summary of this review’s finding is represented in a table including devices (sensors), measures and methods that were used in each reviewed motor symptom assessment study. In the gathered studies among sensors, accelerometers and touch screen devices are the most widely used to detect PD symptoms and among symptoms, bradykinesia and tremor were found to be mostly evaluated. In general, machine learning methods are potentially promising for this. PD is a complex disease that requires continuous monitoring and multidimensional symptom analysis. Combining existing technologies to develop new sensor platforms may assist in assessing the overall symptom profile more accurately to develop useful tools towards supporting better treatment process.

Development of a ESES Solar Thermal Lab on Full Scale System

The main aim of this project is to develop an ESES lab on a full scale system. The solar combisystem used is available most of the time and is only used twice a year to carry out some technical courses. At the moment, there are no other laboratories about combisystems. The experiments were designed in a way to use the system to the most in order to help the students apply the theoretical knowledge in the solar thermal course as well as make them more familiar with solar systems components. The method adopted to reach this aim is to carry out several test sequences on the system, in order to help formulating at the end some educating experiments. A few tests were carried out at the beginning of the project just for the sake of understanding the system and figuring out if any additional measuring equipment is required. The level of these tests sequences was varying from a simple energy draw off or collector loop controller respond tests to more complicated tests, such as the use of the ‘collector’ heater to simulate the solar collector effect on the system. The tests results were compared and verified with the theoretical data wherever relevant. The results of the experiment about the use of the ‘collector’ heater instead of the collector were positively acceptable. Finally, the Lab guide was developed based on the results of these experiments and also the experience gotten while conducting them. The lab work covers the theories related to solar systems in general and combisystems in particular. 

Multimodal Literacy as a form of Communication : What is the state of the students at Dalarna University multimodal literacy?

Literacy is an invaluable asset to have, and has allowed for communication, documentation and the spreading of ideas since the beginning of the written language. With technological advancements, and new possibilities to communicate, it is important to question the degree to which people’s abilities to utilise these new methods have developed in relation to these emerging technologies. The purpose of this bachelor’s thesis is to analyse the state of students’ at Dalarna University mulitimodal literacy, as well as their experience of multimodality in their education. This has led to the two main research questions: What is the state of the students at Dalarna University multimodal literacy? And: How have the students at Dalarna University experienced multimodality in education? The paper is based on a mixed-method study that incorporates both a quantitative and qualitative aspect to it. The main thrust of the research paper is, however, based on a quantitative study that was conducted online and emailed to students via their program coordinators. The scope of the research is in audio-visual modes, i.e. audio, video and images, while textual literacy is presumed and serves as an inspiration to the study. The purpose of the study is to analyse the state of the students’ multimodal literacy and their experience of multimodality in education. The study revealed that the students at Dalarna University have most skill in image editing, while not being very literate in audio or video editing. The students seem to have had mediocre experience creating meaning through multimodality both in private use and in their respective educational institutions. The study also reveals that students prefer learning by means of video (rather than text or audio), yet are not able to create meaning (communicate) through it.

Automatic and objective assessment of alternating tapping performance in Parkinson’s disease

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.

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.

Optimization of cable cycles : a trade-off between reliability and cost

This paper elaborates the routing of cable cycle through available routes in a building in order to link a set of devices, in a most reasonable way. Despite of the similarities to other NP-hard routing problems, the only goal is not only to minimize the cost (length of the cycle) but also to increase the reliability of the path (in case of a cable cut) which is assessed by a risk factor. Since there is often a trade-off between the risk and length factors, a criterion for ranking candidates and deciding the most reasonable solution is defined. A set of techniques is proposed to perform an efficient and exact search among candidates. A novel graph is introduced to reduce the search-space, and navigate the search toward feasible and desirable solutions. Moreover, admissible heuristic length estimation helps to early detection of partial cycles which lead to unreasonable solutions. The results show that the method provides solutions which are both technically and financially reasonable. Furthermore, it is proved that the proposed techniques are very efficient in reducing the computational time of the search to a reasonable amount.

Multiclass Adaboost Based on an Ensemble of Binary Adaboosts

This paper presents a multi-class AdaBoost based on incorporating an ensemble of binary AdaBoosts which is organized as Binary Decision Tree (BDT). It is proved that binary AdaBoost is extremely successful in producing accurate classification but it does not perform very well for multi-class problems. To avoid this performance degradation, the multi-class problem is divided into a number of binary problems and binary AdaBoost classifiers are invoked to solve these classification problems. This approach is tested with a dataset consisting of 6500 binary images of traffic signs. Haar-like features of these images are computed and the multi-class AdaBoost classifier is invoked to classify them. A classification rate of 96.7% and 95.7% is achieved for the traffic sign boarders and pictograms, respectively. The proposed approach is also evaluated using a number of standard datasets such as Iris, Wine, Yeast, etc. The performance of the proposed BDT classifier is quite high as compared with the state of the art and it converges very fast to a solution which indicates it as a reliable classifier.