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  • 1.
    Aghanavesi, Somayeh
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Fleyeh, Hasan
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Memedi, Mevludin
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Feasibility of using smartphones for quantification of Parkinson’s disease motor states during hand rotation tests2019Conference paper (Refereed)
  • 2.
    Aghanavesi, Somayeh
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Memedi, Mevludin
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Nyholm, Dag
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Verification of a method for measuring Parkinson’s disease related temporal irregularity in spiral drawings2017In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 10, article id 2341Article in journal (Refereed)
    Abstract [en]

    Parkinson's disease (PD) is a progressive movement disorder caused by the death of dopamine-producing cells in the midbrain. There is a need for frequent symptom assessment, since the treatment needs to be individualized as the disease progresses. The aim of this paper was to verify and further investigate the clinimetric properties of an entropy-based method for measuring PD-related upper limb temporal irregularities during spiral drawing tasks. More specifically, properties of a temporal irregularity score (TIS) for patients at different stages of PD, and medication time points were investigated. Nineteen PD patients and 22 healthy controls performed repeated spiral drawing tasks on a smartphone. Patients performed the tests before a single levodopa dose and at specific time intervals after the dose was given. Three movement disorder specialists rated videos of the patients based on the unified PD rating scale (UPDRS) and the Dyskinesia scale. Differences in mean TIS between the groups of patients and healthy subjects were assessed. Test-retest reliability of the TIS was measured. The ability of TIS to detect changes from baseline (before medication) to later time points was investigated. Correlations between TIS and clinical rating scores were assessed. The mean TIS was significantly different between healthy subjects and patients in advanced groups (p-value = 0.02). Test-retest reliability of TIS was good with Intra-class Correlation Coefficient of 0.81. When assessing changes in relation to treatment, TIS contained some information to capture changes from Off to On and wearing off effects. However, the correlations between TIS and clinical scores (UPDRS and Dyskinesia) were weak. TIS was able to differentiate spiral drawings drawn by patients in an advanced stage from those drawn by healthy subjects, and TIS had good test-retest reliability. TIS was somewhat responsive to single-dose levodopa treatment. Since TIS is an upper limb high-frequency-based measure, it cannot be detected during clinical assessment.

  • 3. Ahmed, Mobyen
    et al.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Groth, Torgny
    A fuzzy rule-based decision support system for Duodopa treatment in Parkinson2006In: 23rd annual workshop of the Swedish Artificial Intelligence Society, Umeå, 2006Conference paper (Refereed)
    Abstract [en]

    A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

  • 4.
    Askar, Kalid
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Roche, T.
    Agent Based System that support Reliability Transport Engineering2004In: 8th AATT 2004 Conference, Bejing, China, 2004Conference paper (Refereed)
  • 5. Askar, Kalid
    et al.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Passerelle- A plugin that connects Protégé to Sesame2005In: 8th International Protégé Conference, Madrid, Spain, 2005Conference paper (Other academic)
  • 6. Begum, Shahina
    et al.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Funk, Peter
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Induction of an Adaptive Neuro-Fuzzy Inference System for investing fluctuation in Parkinson’s disease2006In: 23rd annual workshop of the Swedish Artificial Intelligence Society, Umeå, 2006Conference paper (Refereed)
    Abstract [en]

    This paper presents a methodology to formulate natural language rules for an adaptive neuro-fuzzy system based on discovered knowledge, supported by prior knowledge and statistical modeling. Relationships between disease related variables and fluctuations in Parkinson’s disease is often complex. Experts have simplified but mostly reliable “fuzzy” rules based on experience. These rules could be improved using statistical methods and neural nets. This gives clinicians a valuable tool to explore the importance of different variables and their relations in a disease and could aid treatment selection. A prototype using the proposed methodology has been used to induce an Adaptive Neuro Fuzzy Inference Model that has been used to “discover” relationships between fluctuation, treatment and disease severity. More data is needed to confirm these findings. The project shows that artificial intelligence techniques and methods in combination with statistical methods offer medical research and applications valuable opportunities.

  • 7.
    Bäckström, Mattias
    et al.
    Örebro University, Department of Natural Sciences.
    Dario, Mårten
    Örebro University, Department of Natural Sciences.
    Allard, Bert
    Örebro University, Department of Natural Sciences.
    Karlsson, Stefan
    Örebro University, Department of Natural Sciences.
    Effects of a fulvic acid on the adsorption of mercury and cadmium on goethite2003In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 304, no 1-3, p. 257-268Article in journal (Refereed)
    Abstract [en]

    The effects of an aquatic fulvic acid on the pH-dependent adsorption of Hg(II) and Cd(II) to particulate goethite (a-FeOOH) were studied in batch systems. The ionic medium consisted of 0.01 M HClO and the total concentrations 4 of mercury and cadmium were maintained at 10y8 M with 203Hg and 109Cd as tracers. pH In the systems was varied in the range 3–10 by addition of HClO and NaOH.All commercial chemicals were of analytical grade or better. An 4 aquatic fulvic acid (20 ppm), previously isolated and characterised in detail, was used as a model for humic substances and its adsorption to goethite is included in this study. The adsorption of the fulvic acid (20 ppm) onto goethite decreased slowly from 90% at pH 3–7.5 to 10% at pH 10. In systems without fulvic acid the adsorption of mercury increased in a linear fashion from 10% at pH 3 to 70% at pH 10.In the presence of fulvic acid (20 ppm), the adsorption was almost quantitative in the intermediate pH range (pH 5–7), and exceeded 92% over the entire pH range. Thus, association between mercury and the fulvic acid enhanced adsorption in general although the largest impact was found at low pH.Adsorption of cadmium increased from nearly 0 to almost 100% at approximately pH 6. In the presence of fulvic acid, the adsorption increased below pH 7 and decreased above pH 7. The adsorption isotherm for mercury when the concentration was increased from 10y8 to 1.8=10y4 M showed a corresponding increase of K (lyg) up to a total concentration at 10y6 M.At higher mercury concentrations K was lowered. In the presence of fulvic acid the corresponding relationship of K was bi-modal, i.e. high values at low and intermediate concentrations of mercury. This behaviour suggests that in the absence of fulvic acid the adsorption follow the expected behaviour, i.e. adsorption sites with similar affinity for mercury. In the presence of fulvic acid, additional adsorption sites are available by the organic molecule (possibly sulfur groups) when it is associated to the goethite. The adsorption isotherm for cadmium indicates a lowering of K at 10y4 M. Cadmium had no competitive effect on mercury and vice versa. Zinc, however, affected the adsorption of cadmium but not the adsorption of mercury.

  • 8. Bäckström, Mattias
    et al.
    Dario, Mårten
    Örebro University, Department of Natural Sciences.
    Karlsson, Stefan
    Allard, Bert
    Örebro University, Department of Natural Sciences.
    Effects of a fulvic acid on the adsorption of mercury and cadmium on goethite2003In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 304, no 1-3, p. 257-268Article in journal (Refereed)
    Abstract [en]

    The effects of an aquatic fulvic acid on the pH-dependent adsorption of Hg(II) and Cd(II) to particulate goethite (alpha-FeOOH) were studied in batch systems. The ionic medium consisted of 0.01 M HClO(4) and the total concentrations of mercury and cadmium were maintained at 10(-8) M with 203Hg and 109Cd as tracers. pH In the systems was varied in the range 3-10 by addition of HClO(4) and NaOH. All commercial chemicals were of analytical grade or better. An aquatic fulvic acid (20 ppm), previously isolated and characterised in detail, was used as a model for humic substances and its adsorption to goethite is included in this study. The adsorption of the fulvic acid (20 ppm) onto goethite decreased slowly from 90% at pH 3-7.5 to 10% at pH 10. In systems without fulvic acid the adsorption of mercury increased in a linear fashion from 10% at pH 3 to 70% at pH 10. In the presence of fulvic acid (20 ppm), the adsorption was almost quantitative in the intermediate pH range (pH 5-7), and exceeded 92% over the entire pH range. Thus, association between mercury and the fulvic acid enhanced adsorption in general although the largest impact was found at low pH. Adsorption of cadmium increased from nearly 0 to almost 100% at approximately pH 6. In the presence of fulvic acid, the adsorption increased below pH 7 and decreased above pH 7. The adsorption isotherm for mercury when the concentration was increased from 10(-8) to 1.8 x 10(-4) M showed a corresponding increase of K(d) (l/g) up to a total concentration at 10(-6) M. At higher mercury concentrations K(d) was lowered. In the presence of fulvic acid the corresponding relationship of K(d) was bi-modal, i.e. high values at low and intermediate concentrations of mercury. This behaviour suggests that in the absence of fulvic acid the adsorption follow the expected behaviour, i.e. adsorption sites with similar affinity for mercury. In the presence of fulvic acid, additional adsorption sites are available by the organic molecule (possibly sulfur groups) when it is associated to the goethite. The adsorption isotherm for cadmium indicates a lowering of K(d) at 10(-4) M. Cadmium had no competitive effect on mercury and vice versa. Zinc, however, affected the adsorption of cadmium but not the adsorption of mercury.

  • 9.
    Dario, Mårten
    Örebro University, Department of Natural Sciences.
    Metal distribution and mobility under alkaline conditions2004Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The adsorption of an element, expressed as its distribution between liquid (aquatic) and solid phases in the biogeosphere, largely determines its mobility and transport properties. This is of fundamental importance in the assessment of the performance of e.g. geologic repositories for hazardous elements like radionuclides. Geologic repositories for low and intermediate level nuclear waste will most likely be based on concrete constructions in a suitable bedrock, leading to a local chemical environment with pH well above 12. At this pH metal adsorption is very high, and thus the mobility is hindered. Organic complexing agents, such as natural humic matter from the ground and in the groundwater, as well as components in the waste (cleaning agents, degradation products from ion exchange resins and cellulose, cement additives etc.) would affect the sorption properties of the various elements in the waste. Trace element migration from a cementitious repository through the pH- and salinity gradient created around the repository would be affected by the presence and creation of particulate matter (colloids) that may serve as carriers that enhance the mobility.

    The objective of this thesis was to describe and quantify the sorption of some selected elements representative of spent nuclear fuel (Eu, Am) and other heavy metals (Zn, Cd, Hg) in a clay/cement environment (pH 10-13) and in the pH-gradient outside this environment. The potential of organic complexing agents and colloids to enhance metal migration was also investigated. It was shown that many organic ligands are able to reduce trace metal sorption under these conditions. It was not possible to calculate the effect of well-defined organic ligands on the metal sorption in a cement environment by using stability constants from the literature. A simple method for comparing the effect of different complexing agents on metal sorption is, however, suggested.

    The stability in terms of the particle size of suspended colloidal matter (clays and an iron hydroxide) was measured by photon correlation spectroscopy. In the absence of large amounts of organic material, the present colloids will, in most cases, not enhance metal migration in a cementitious environment due to agglomeration of the colloidal phase at high pH and salinities.

  • 10.
    Dario, Mårten
    et al.
    Örebro University, Department of Natural Sciences.
    Allard, Bert
    Örebro University, Department of Natural Sciences.
    Sorption of europium onto titanium dioxide at high pH: influence of isosaccharinic and fulvic acidManuscript (preprint) (Other academic)
  • 11.
    Dario, Mårten
    et al.
    Örebro University, Department of Natural Sciences.
    Ledin, Anna
    Sorption of Cd to colloidal ferric hydroxides: impact of pH and organic acids1997In: Chemical speciation and bioavailability, ISSN 0954-2299, E-ISSN 2047-6523, Vol. 9, no 1, p. 3-14Article in journal (Refereed)
    Abstract [en]

    The sorption (both ad- and desorption) of Cd to or from colloidal ferric hydroxides as a function of pH, the concentration of organic acids (acetic acid (AA), EDTA, fulvic acid (FA) and malonic acid (MA)), the precipitation procedure for the ferric hydroxide as well as the contact time were investigated in the present study. The concentrations of Cd, colloids and organic acids were chosen to be representative of natural surface waters. The ferric hydroxide were either precipitated in presence of FA or the acid was mixed with the colloids after the purification steps. The presence of FA during the precipitation of ferric hydroxide, had an impact on the size distribution of the solid phase, but it did not have any influence on the sorption behaviour of Cd. The adsorption process was found to be relatively fast and largely pH-dependent. It was fully reversible when the pH was decreased, however, with somewhat slower kinetics. The addition of up to 1 mmol L-1 AA or MA did not cause any measurable desorption of Cd, probably due to the relatively weak complexes formed between Cd(II)-ions and the anions of the acids. Thermodynamic calculations of the distribution between different soluble Cd-species indicated that EDTA and FA would form stronger complexes with Cd. This was indicated in the experiments as enhanced adsorption at low pH-values due to the adsorption of Cd(II)-organic species, and an increase in the soluble fraction at high pH-values caused by competition for Cd(II)-ions between complex forming groups on the surfaces and the soluble organic ligands.

  • 12.
    Dario, Mårten
    et al.
    Örebro University, Department of Natural Sciences.
    Molera, Mireia
    Allard, Bert
    Effects of cement additives on radionuclide mobility2004In: Scientific basis for radioactive waste management XXVII: symposium held June 15-19, 2003, Kalmar, Sweden / [ed] Virginia M. Oversby, Lars O. Werme, Warrendale, Pa: Materials Research Society , 2004, p. 639-644Conference paper (Other academic)
  • 13.
    Dario, Mårten
    et al.
    Örebro University, Department of Natural Sciences.
    Molera, Mireia
    Allard, Bert
    Effects of technical adsorbents and cleaning agents in a cement matrix: a case study2004In: Scientific basis for nuclear waste management XXVII: symposium held June 15-19, 2003, Kalmar, Sweden / [ed] Virginia M. Oversby, Lars O. Werme, Warrendale, Pa: Materials Research Society , 2004, p. 371-376Conference paper (Other academic)
  • 14.
    Dario, Mårten
    et al.
    Örebro University, Department of Natural Sciences.
    Molera, Mireia
    Allard, Bert
    Örebro University, Department of Natural Sciences.
    Sorption of europium on TiO2 and cement at high pH in the presence of organic ligands2006In: Journal of Radioanalytical and Nuclear Chemistry, ISSN 0236-5731, E-ISSN 1588-2780, Vol. 270, no 3, p. 495-505Article in journal (Refereed)
    Abstract [en]

    Organic substances present in radioactive waste lower the sorption of metal ions at the high pH in cement matrices and, hence, enhance their possible migration. The aim of this study was to develop a method to compare organic substances or their degradation products with respect to what extent they affect metal sorption. Batch sorption studies were performed with cement or TiO2 as solid phase and Eu(III) as a model element for trivalent lanthanides and actinides at pH 12.5 (representative of a cement waste matrix during the first approximately 100,000 years). Different kinds of ligands were studied in a broad concentration range, e.g., organic acids, cement additives, cleaning agents and degradation products from ion-exchange resin.

  • 15.
    Dario, Mårten
    et al.
    Örebro University, Department of Natural Sciences.
    Strömberg, Jessica
    Ledin, Anna
    Sorption of europium to colloidal montmorillonite: impact of pH, an aquatic fulvic acid and calcium isosaccharinateManuscript (preprint) (Other academic)
  • 16. De Queiroz, I
    et al.
    Jaques, M
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Weigang, L
    Using neural networks for estimating saturation flow rates at signalized intersections.2006In: Proceedings of the EWGT 2006. Joint International Conferences., Bari : Euro Working Group in Transportation, 2006, p. 47-52Conference paper (Refereed)
  • 17.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A Peer Group Support Network for an International Masters Programme2005In: ISANA 2004 / [ed] Siril, Yella, Melbourne, 2005Conference paper (Other academic)
  • 18.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    International Master Programme: two intakes per year for a better peer group support2005In: LIEE: LMD Informatique en Europe et Emploi / [ed] Rebreyend, Pascal, Montpellier, 2005Conference paper (Refereed)
    Abstract [en]

    In 2001 Ho"gskolan Dalarna launched a masters programme in computer science. This programme hasattracted a large number of applications from international students. This has yielded many exciting opportunities, but also given rise to some problems, both practical and academic. A key element of thesuccess in solving some of these problems has been to make the programme highly modular in structure, allowing two intakes per year. This has been the key to developing a peer group support system that ismuch appreciated by the students. Another key element in the modular structure is that studies can be partly done in partner universities member of the INHEE network. INHEE is a International Network forHigher Education in Engineering and most partners are small european universities.

  • 19.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Something old, something new, something borrowed, something blue part 1: Alan turing, hypercomputation, adam smith and next generation intelligent systems2012In: Journal of Intelligent Systems, ISSN 0334-1860, Vol. 21, no 4, p. 325-330Article in journal (Refereed)
    Abstract [en]

    In this article intelligent systems are placed in the context of accelerated Turing machines. Although such machines are not currently a reality, the very real gains in computing power made over previous decades require us to continually reevaluate the potential of intelligent systems. The economic theories of Adam Smith provide us with a useful insight into this question. © de Gruyter 2012.

  • 20.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Something old, something new, something borrowed, something blue: Part 3 - An elephant never forgets2017In: Journal of Intelligent Systems, ISSN 0334-1860, E-ISSN 2191-026X, Vol. 26, no 3, p. 433-437Article in journal (Refereed)
    Abstract [en]

    Forgetting is an oft-forgotten art. Many artificial intelligence (AI) systems deliver good performance when first implemented; however, as the contextual environment changes, they become out of date and their performance degrades. Learning new knowledge is part of the solution, but forgetting outdated facts and information is a vital part of the process of renewal. However, forgetting proves to be a surprisingly difficult concept to either understand or implement. Much of AI is based on analogies with natural systems, and although all of us have plenty of experiences with having forgotten something, as yet we have only an incomplete picture of how this process occurs in the brain. A recent judgment by the European Court concerns the "right to be forgotten" by web index services such as Google. This has made debate and research into the concept of forgetting very urgent. Given the rapid growth in requests for pages to be forgotten, it is clear that the process will have to be automated and that intelligent systems of forgetting are required in order to meet this challenge.

  • 21.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    The affect of binocular vision disorders on cave survey accuracy.2006In: Cave and Karst Science, ISSN 1356-191X, Vol. 33, no 2, p. 53-56Article in journal (Refereed)
    Abstract [en]

    Binocular vision disorders such as heterophoria and hyperphoria are relatively common. This paper shows, that if a cave survey team does not take careful account of the possibility of one or more of its members suffering from such a disorder, very serious errors can occur. Both theoretical as well as empirical evidence is presented. The likely magnitude of these errors implies that BCRA grade 5 cannot be achieved unless surveyors check for, or if necessary correct for, binocular vision disorders. Various techniques to eliminate such errors are explained and compared. Finally a recommendation is made concerning an additional clause to the notes which accompany the BCRA cave surveying grade definitions. To achieve BCRA grade 5, the possibility of binocular vision disorders must be taken into account.

  • 22.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    What has literature to offer computer science?2004In: Human IT, ISSN 1402-1501, E-ISSN 1402-151X, Vol. 7, no 1Article in journal (Refereed)
  • 23.
    Dougherty, Mark
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Sofi H
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    The April Fool Turing Test2006In: tripleC (cognition, communication, co-operation): Journal for a Global Sustainable Information Society / Unified Theory of Information Research Group, ISSN 1726-670X, E-ISSN 1726-670X, Vol. 4, no 2Article in journal (Refereed)
    Abstract [en]

    This paper explores certain issues concerning the Turing test; non-termination, asymmetry and the need for a control experiment. A standard diagonalisation argument to show the non-computability of AI is extended to yields a socalled “April fool Turing test”, which bears some relationship to Wizard of Oz experiments and involves placing several experimental participants in a symmetrical paradox – the “April Fool Turing Test”. The fundamental question which is asked is whether escaping from this paradox is a sign of intelligence. An important ethical consideration with such an experiment is that in order to place humans in such a paradox it is necessary to fool them. Results from an actual April Fool Turing Test experiment are reported. It is concluded that the results clearly illustrate some of the difficulties and paradoxes which surround the classical Turing Test.

  • 24.
    Dougherty, Mark
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Slutrapport för projektet E-MOTIONS2013Report (Other academic)
  • 25. Düker, Anders
    et al.
    Dario, Mårten
    Örebro University, Department of Natural Sciences.
    Ledin, Anna
    Impact of some hydrochemical parameters on the size distribution of illite, kaolin and montmorilloniteManuscript (preprint) (Other academic)
  • 26.
    Elf, Marie
    et al.
    Chalmers Tekniska Högskola.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    The role for simulation in the design of new health care environments2003In: The 8th International Congress in Nursing Informatics - NI2003, Rio de Janeiro, Brazil, 2003Conference paper (Refereed)
  • 27.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Road and traffic sign detection and recognition2005In: 10th EWGT Meeting and 16th Mini-EURO Conference, Poznan, Poland, 2005Conference paper (Refereed)
    Abstract [en]

    This paper presents an overview of the road and traffic sign detection and recognition. It describes the characteristics of the road signs, the requirements and difficulties behind road signs detection and recognition, how to deal with outdoor images, and the different techniques used in the image segmentation based on the colour analysis, shape analysis. It shows also the techniques used for the recognition and classification of the road signs. Although image processing plays a central role in the road signs recognition, especially in colour analysis, but the paper points to many problems regarding the stability of the received information of colours, variations of these colours with respect to the daylight conditions, and absence of a colour model that can led to a good solution. This means that there is a lot of work to be done in the field, and a lot of improvement can be achieved. Neural networks were widely used in the detection and the recognition of the road signs. The majority of the authors used neural networks as a recognizer, and as classifier. Some other techniques such as template matching or classical classifiers were also used. New techniques should be involved to increase the robustness, and to get faster systems for real-time applications.

  • 28.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    SVM based traffic sign classification using legender moments2007In: Proceedings of the 3rd Indian International Conference on Artificial Intelligence, IICAI 2007, 2007, p. 957-968Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel approach to recognize traffic signs using Support Vector Machines (SVMs) and Legendre Moments. Images of traffic signs are collected by a digital camera mounted in a vehicle. They are color segmented and all objects which represent signs are extracted and normalized to 36×36 pixels images. Legendre moments of sign borders and speed-limit signs of 350 and 250 images are computed and the SVM classifier is trained with theses features. Two stages of SVM are trained; the first stage determines the class of the sign from the shape of its border and the second one determines the pictogram of the sign. Training and testing of both SVM classifiers are done offline by using still images. In the online mode, the system loads the SVM training model and performs recognition. Copyright © 2007 IICAI.

  • 29.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    SVM Based Traffic Sign Classification Using Legendre Moments2007In: Third Indian International Conference on Artificial Intelligence, Pune, India, 2007Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel approach to recognise traffic signs using Support Vector Machines (SVMs) and Legendre Moments. Images of traffic signs are collected by a digital camera mounted in a vehicle. They are colour segmented and all objects which represent signs are extracted and normalised to 36x36 pixels images. Legendre moments of sign borders and speed-limit signs of 350 and 250 images are computed and the SVM classifier is trained with theses features. Two stages of SVM are trained; the first stage determines the class of the sign from the shape of its border and the second one determines the pictogram of the sign. Training and testing of both SVM classifiers are done offline by using still images. In the online mode, the system loads the SVM training model and performs recognition.

  • 30.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Traffic sign classification using invariant features and support vector machines2008In: Intelligent Vehicles Symposium, 2008 IEEE, 2008, Vol. 1-3, p. 530-535Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel approach to recognize traffic signs using invariant features and support vector machines (SVM). Images of traffic signs are collected by a digital camera mounted in a vehicle. They are color segmented and all objects which represent signs are extracted and normalized to 36 x 36 pixels images. Invariant features of sign rims and speed-limit sign interiors of 350 and 250 images are computed and the SVM classifier is trained with these features. Two stages of SVM are trained; the first stage determines the shape of sign rim and the second determines the pictogram of the sign. Training and testing of both SVM classifiers are done using still images. The best performance achieved is 98% for sign rims and 93% for speed limit signs.

  • 31.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Aenugula, Dinesh
    Baddam, Sruthi
    Invariant road sign recognition with fuzzy ARTMAP and zernike moments2007In: 2007 IEEE Intelligent Vehicles Symposium, vols 1-3, 2007, Vol. 1-3, p. 1-6Conference paper (Refereed)
    Abstract [en]

    In this paper, a novel approach to recognize road signs is developed. Images of road signs are collected by a digital camera mounted in a vehicle. They are segmented using colour information and all objects which represent signs are extracted, normalized to 36x36 pixels, and used to train a Fuzzy ARTMAP neural network by calculating Zernike moments for these objects as features. Sign borders and pictograms are investigated in this study. Zernike moments of sign borders and speed-limit signs of 210 and 150 images are calculated as features. A fuzzy ARTMAP is trained directly with features, or by using PCA for dimension reduction, or by using LDA algorithm as dimension reduction and data separation algorithm. Two Fuzzy ARTMAP Neural Networks are trained. The first NN determines the class of the sign from the shape of its border and the second one determines the sign itself from its pictogram. Training and testing of both NNs is done offline by using still images. In the online mode, the system loads the Fuzzy ARTMAP Neural Networks, and performs recognition process. An accuracy of about 99% is achieved in sign border recognition and 96% for Speed-Limit recognition.

  • 32.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Gilani, Syed
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Road sign detection and recognition using fuzzy artmap: a case study Swedish speed-limit signs2006In: The 10th IASTED International Conference on Artificial Intelligence and Soft Computing, Palma de Mallorca, Spain, 2006Conference paper (Refereed)
    Abstract [en]

    In this paper, a novel approach is developed using Fuzzy ARTMAP Neural Networks to recognize and classify Swedish road and traffic signs. The Swedish Speed-Limit signs are selected as a case study, but the system can be applied to other signs. A new color detection and segmentation algorithm is presented in which the effects of shadows and highlights are eliminated. Images are taken by a digital camera mounted in a car. Segmented images are created by converting RGB images into HSV color space and applying the shadow-highlight invariant method. The method is tested on hundreds of outdoor images under shadow and highlight conditions, and it shows high robustness; in 95% of cases of correct segmentation is achieved. Classification is carried out by two stages of Fuzzy ARTMAP which are trained by 210 and 150 images, respectively. The first stage determines the border of the sign and the second stage determines the pictogram. Training and testing of both stages are made offline, using still images. In online mode, the system loads the Fuzzy ARTMAP and performs recognition process. An accuracy of 96.7% is achieved in Speed-Limit recognition and more than 90% as whole accuracy.

  • 33.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Jomaa, Diala
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Segmentation of low quality fingerprint images2010Conference paper (Refereed)
    Abstract [en]

    This paper presents a new algorithm to segment fingerprint images. The algorithm uses four features, the global mean, the local mean, variance and coherence of the image to achieve the fingerprint segmentation. Based on these features, a rule based system is built to segment the image. The proposed algorithm is implemented in three stages; pre-processing, segmentation, and post-processing. Gaussian filter and histogram equalization are applied in the pre-processing stage. Segmentation is applied using the local features. Finally, fill the gaps algorithm and a modified version of Otsu thresholding are invoked in the post-processing stage. In order to evaluate the performance of this method, experiments are performed on FVC2000 DB1. Segmentation of 100 images is performed and compared with manual examinations of human experts. It shows that the proposed algorithm achieves a correct segmentation of 82% of images under test.

  • 34.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Jomaa, Diala
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Davami, Erfan
    Segmentation of fingerprint images based on bi-level combination of global and local processing2012In: Journal of Intelligent Systems, ISSN 2191-026X, Vol. 21, no 2, p. 97-120Article in journal (Refereed)
    Abstract [en]

    This paper presents a new approach to segment low quality fingerprint imageswhich are collected by low quality fingerprint readers. Images collected using such readersare easy to collect but difficult to segment. The proposed approach is based on combiningglobal and local processing to achieve segmentation of fingerprint images. On the globallevel, the fingerprint is located and extracted from the rest of the image by using a globalthresholding followed by dilation and edge detection of the largest object in the image.On the local level, fingerprint’s foreground and its border image are treated using differentfuzzy rules. These rules are based on the mean and variance of the block under consideration.The approach is implemented in three stages: pre-processing, segmentation, andpost-processing.Segmentation of 100 images was performed and compared with manual examinationsby human experts. The experiments showed that 96% of images under test are correctlysegmented. The results from the quality of segmentation test revealed that the averageerror in block segmentation was 2.84% and the false positive and false negatives wereapproximately 1.4%. This indicates the high robustness of the proposed approach.

  • 35.
    Grek, Åsa
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Hartwig, Fredrik
    Dalarna University, School of Technology and Business Studies, Business Administration and Management.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Auxiliary variables for nonresponse adjustment in business surveysManuscript (preprint) (Other academic)
  • 36.
    Grek, Åsa
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Hartwig, Fredrik
    Dalarna University, School of Technology and Business Studies, Business Administration and Management.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Determinants of debt leverage ratios in Swedish listed companiesManuscript (preprint) (Other academic)
  • 37.
    Hansson, Karl
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Fleyeh, Hasan
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Machine Learning Algorithms in Heavy Process Manufacturing2016In: American Journal of Intelligent Systems, ISSN 2165-8978, E-ISSN 2165-8994, Vol. 6, no 1, p. 1-13Article in journal (Refereed)
    Abstract [en]

    In a global economy, manufacturers mainly compete with cost efficiency of production, as the price of raw materials are similar worldwide. Heavy industry has two big issues to deal with. On the one hand there is lots of data which needs to be analyzed in an effective manner, and on the other hand making big improvements via investments in cooperate structure or new machinery is neither economically nor physically viable. Machine learning offers a promising way for manufacturers to address both these problems as they are in an excellent position to employ learning techniques with their massive resource of historical production data. However, choosing modelling a strategy in this setting is far from trivial and this is the objective of this article. The article investigates characteristics of the most popular classifiers used in industry today. Support Vector Machines, Multilayer Perceptron, Decision Trees, Random Forests, and the meta-algorithms Bagging and Boosting are mainly investigated in this work. Lessons from real-world implementations of these learners are also provided together with future directions when different learners are expected to perform well. The importance of feature selection and relevant selection methods in an industrial setting are further investigated. Performance metrics have also been discussed for the sake of completion.

  • 38.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Triggering Radar Speed Warning signs using Association Rules and Clustering Techniques2012Conference paper (Refereed)
    Abstract [en]

    Radar speed warning signs (RSWS) have been used in recent years across Sweden and elsewhere in the world. Such signs measure vehicle speed using radar and are designed to display a message when the driver exceeds a pre-set threshold speed, which is often relative to the speed limit on a particular road segment. RSWS are typically placed on locations which are perceived to be problematic by relevant authorities. Excessive speeding or road accidents are examples of such perceived problems.  Deploying RSWS in many relevant locations is often impractical due to the lack of necessary power supply needed for operation. Battery driven RSWS are an alternative but are less attractive because of limited running time and frequent maintenance (changing batteries etc). Therefore, solar powered RSWS are more desirable. However, these signs are also dependent on batteries that need to be charged. The duration of operation of solar powered RSWS largely depend on how often the sign is triggered. Constant activation of the sign drains the battery. It is desirable to trigger the sign only when necessary. Hence, the main goal of this research is to design a model that optimises the performance of RSWS depending on prevailing conditions i.e traffic flows during different times of the day and so on.  Vehicle speed data had been collected at a test site in Sweden all hours of the day. This paper attempts to use a hybrid system based on Apriori and K-means clustering algorithm. Apriori algorithm is simple and efficient to determine associations’ rules among attributes in particular to discover the most common combination that can occur within the data set.  K-means clustering is basically used to quantize the input variables into smaller clusters that can easily derive the trigger threshold value. The proposed hybrid system indicated that the system was able to trigger solar RWWS efficiently.

  • 39.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Edvardsson, Karin
    Dalarna University, School of Technology and Business Studies, Construction.
    Effectiveness of trigger speed of vehicle-activated signs on mean and standard deviation of speed2016In: Journal of Transportation Safety and Security, ISSN 1943-9962, Vol. 8, no 4, p. 293-309Article in journal (Refereed)
    Abstract [en]

    Excessive or inappropriate speeds are a key factor in traffic fatalities and crashes. Vehicle-activated signs (VASs) are therefore being extensively used to reduce speeding to increase traffic safety. A VAS is triggered by an individual vehicle when the driver exceeds a speed threshold, otherwise known as trigger speed (TS). The TS is usually set to a constant, normally proportional to the speed limit on the particular segment of road. Decisions concerning the TS largely depend on the local traffic authorities. The primary objective of this article is to help authorities determine the TS that gives an optimal effect on the Mean and Standard Deviation of speed. The data were systematically collected using radar technology whilst varying the TS. The results show that when the applied TS was set near the speed limit, the standard deviation was high. However, the Standard Deviation decreased substantially when the threshold was set to the 85th percentile. This decrease occurred without a significant increase in the mean speed. It is concluded that the optimal threshold speed should approximate the 85th percentile, though VASs should ideally be individually calibrated to the traffic conditions at each site.

  • 40.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Edvardsson, Karin
    Dalarna University, School of Technology and Business Studies, Construction.
    Effectiveness of vehicle activated signs on mean speed and standard deviation of vehicle speed2014Report (Other academic)
  • 41.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    A comparative study between vehicle activated signs and speed indicator devices2017In: Transportation Research Procedia, ISSN 2324-9935, E-ISSN 2352-1465, Vol. 22, p. 115-123Article in journal (Refereed)
    Abstract [en]

    Vehicle activated signs and Speed indicator devices are safety signs used to warn and remind drivers that they are exceeding the speed limit on a particular road segment. This article has analysed and compared such signs with the aim of reporting the most suitable sign for relevant situations. Vehicle speeds were recorded at different test sites and the effects of the signs were studied by analyzing the mean and standard deviation. Preliminary results from the work indicate that both types of signs have variable effects on the mean and standard deviation of speed on a given road segment. Speed indicator devices were relatively more effective than vehicle activated signs on local roads; in contrast their effectivity was only comparable when tested on highways.

  • 42.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Review of the effectiveness of vehicle activated signs2013In: Journal of Transportation Technologies, ISSN 2160-0481, Vol. 3, no 2, p. 123-130Article in journal (Refereed)
    Abstract [en]

    This paper reviews the effectiveness of vehicle activated signs. Vehicle activated signs are being reportedly used in recent years to display dynamic information to road users on an individual basis in order to give a warning or inform about a specific event. Vehicle activated signs are triggered individually by vehicles when a certain criteria is met. An example of such criteria is to trigger a speed limit sign when the driver exceeds a pre-set threshold speed. The preset threshold is usually set to a constant value which is often equal, or relative, to the speed limit on a particular road segment.

    This review examines in detail the basis for the configuration of the existing sign types in previous studies and explores the relation between the configuration of the sign and their impact on driver behavior and sign efficiency. Most of previous studies showed that these signs have significant impact on driver behavior, traffic safety and traffic efficiency. In most cases the signs deployed have yielded reductions in mean speeds, in speed variation and in longer headways. However most experiments reported within the area were performed with the signs set to a certain static configuration within applicable conditions. Since some of the aforementioned factors are dynamic in nature, it is felt that the configurations of these signs were thus not carefully considered by previous researchers and there is no clear statement in the previous studies describing the relationship between the trigger value and its consequences under different conditions. Bearing in mind that different designs of vehicle activated signs can give a different impact under certain conditions of road, traffic and weather conditions the current work suggests that variable speed thresholds should be considered instead.

  • 43.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Speed prediction for triggering vehicle activated signs2016Report (Other academic)
    Abstract [en]

    Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

  • 44.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means2014Conference paper (Refereed)
    Abstract [en]

    Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

  • 45.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Edvardsson, Karin
    Dalarna University, School of Technology and Business Studies, Construction.
    Data based Calibration System for Radar used by Vehicle Activated Signs2014In: Journal of Data Analysis and Information Processing, ISSN 2327-7203, no 2, p. 11p. 106-116Article in journal (Refereed)
    Abstract [en]

    The accurate measurement of a vehicle’s velocity is an essential feature in adaptive vehicle activated sign systems. Since the velocities of the vehicles are acquired from a continuous wave Doppler radar, the data collection becomes challenging. Data accuracy is sensitive to the calibration of the radar on the road. However, clear methodologies for in-field calibration have not been carefully established. The signs are often installed by subjective judgment which results in measurement errors. This paper develops a calibration method based on mining the data collected and matching individual vehicles travelling between two radars. The data was cleaned and prepared in two ways: cleaning and reconstructing. The results showed that the proposed correction factor derived from the cleaned data corresponded well with the experimental factor done on site. In addition, this proposed factor showed superior performance to the one derived from the reconstructed data.

  • 46.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University, Vasteras 72123, Sweden.
    Nyholm, Dag
    Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A Computer Vision Framework For Finger-Tapping Evaluation In Parkinson's Disease2013In: Movement Disorders: Supplement: Abstracts of the Seventeenth International Congress of Parkinson's Disease and Movement Disorders, Movement Disorder Society , 2013, p. 110-111Conference paper (Refereed)
    Abstract [en]

    Objective:

    To define and evaluate a Computer-Vision (CV) method for scoring Paced Finger-Tapping (PFT) in Parkinson's disease (PD) using quantitative motion analysis of index-fingers and to compare the obtained scores to the UPDRS (Unified Parkinson's Disease Rating Scale) finger-taps (FT).

    Background:

    The naked-eye evaluation of PFT in clinical practice results in coarse resolution to determine PD status. Besides, sensor mechanisms for PFT evaluation may cause patients discomfort. In order to avoid cost and effort of applying wearable sensors, a CV system for non-invasive PFT evaluation is introduced.

    Methods:

    A database of 221 PFT videos from 6 PD patients was processed. The subjects were instructed to position their hands above their shoulders besides the face and tap the index-finger against the thumb consistently with speed. They were facing towards a pivoted camera during recording. The videos were rated by two clinicians between symptom levels 0-to-3 using UPDRS-FT.

    The CV method incorporates a motion analyzer and a face detector. The method detects the face of testee in each video-frame. The frame is split into two images from face-rectangle center. Two regions of interest are located in each image to detect index-finger motion of left and right hands respectively. The tracking of opening and closing phases of dominant hand index-finger produces a tapping time-series. This time-series is normalized by the face height. The normalization calibrates the amplitude in tapping signal which is affected by the varying distance between camera and subject (farther the camera, lesser the amplitude). A total of 15 features were classified using K-nearest neighbor (KNN) classifier to characterize the symptoms levels in UPDRS-FT. The target ratings provided by the raters were averaged.

    Results:

    A 10-fold cross validation in KNN classified 221 videos between 3 symptom levels with 75% accuracy. An area under the receiver operating characteristic curves of 82.6% supports feasibility of the obtained features to replicate clinical assessments.

    Conclusions:

    The system is able to track index-finger motion to estimate tapping symptoms in PD. It has certain advantages compared to other technologies (e.g. magnetic sensors, accelerometers etc.) for PFT evaluation to improve and automate the ratings

  • 47.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University, Vasteras 72123, Sweden.
    Nyholm, Dag
    Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A computer vision framework for finger-tapping evaluation in Parkinson’s disease2014In: Artificial Intelligence in Medicine, ISSN 0933-3657, E-ISSN 1873-2860, Vol. 60, no 1, p. 27-40Article in journal (Refereed)
    Abstract [en]

    Objectives: The rapid finger-tapping test (RFT) is an important method for clinical evaluation of movementdisorders, including Parkinson’s disease (PD). In clinical practice, the naked-eye evaluation of RFT results in a coarse judgment of symptom scores. We introduce a novel computer-vision (CV) method forquantification of tapping symptoms through motion analysis of index fingers. The method is unique asit utilizes facial features to calibrate tapping amplitude for normalization of distance variation betweenthe camera and subject.

    Methods: The study involved 387 video footages of RFT recorded from 13 patients diagnosed with advanced PD. Tapping performance in these videos was rated by two clinicians between the symptom severity levels (‘0: normal’ to ‘3: severe’) using the unified Parkinson’s disease rating scale motor examination of finger-tapping (UPDRS-FT). Another set of recordings in this study consisted of 84 videos of RFT recorded from 6 healthy controls. These videos were processed by a CV algorithm that tracks the index-finger motion between the video-frames to produce a tapping time-series. Different features were computed from this time series to estimate speed, amplitude, rhythm and fatigue in tapping. The features were trained in a support vector machine (1) to categorize the patient group between UPDRS-FT symptom severity levels, and (2) to discriminate between PD patients and healthy controls.

    Results: A new representative feature of tapping rhythm, ‘cross-correlation between the normalized peaks’ showed strong Guttman correlation (u2 =−0.80) with the clinical ratings. The classification oftapping features using the support vector machine classifier and 10-fold cross validation categorized the patient samples between UPDRS-FT levels with an accuracy of 88%. The same classification scheme discriminated between RFT samples of healthy controls and PD patients with an accuracy of 95%.

    Conclusion: The work supports the feasibility of the approach, which is presumed suitable for PD monitoringin the home environment. The system offers advantages over other technologies (e.g. magneticsensors, accelerometers, etc.) previously developed for objective assessment of tapping symptoms.

  • 48.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Cepstral separation difference: a novel approach for speech impairment quantification in Parkinson’s disease2014In: Biocybernetics and Biomedical Engineering, ISSN 0208-5216, Vol. 34, no 1, p. 25-34Article in journal (Refereed)
    Abstract [en]

    This paper introduces a novel approach, Cepstral Separation Difference (CSD), for quantification of speech impairment in Parkinson’s disease (PD). CSD represents a ratio between the magnitudes of glottal (source) and supra-glottal (filter) log-spectrums acquired using the source-filter speech model. The CSD-based features were tested on a database consisting of 240 clinically rated running speech samples acquired from 60 PD patients and 20 healthy controls. The Guttmann (µ2) monotonic correlations between the CSD features and the speech symptom severity ratings were strong (up to 0.78). This correlation increased with the increasing textual difficulty in different speech tests. CSD was compared with some non-CSD speech features (harmonic ratio, harmonic-to-noise ratio and Mel-frequency cepstral coefficients) for speech symptom characterization in terms of consistency and reproducibility. The high intra-class correlation coefficient (>0.9) and analysis of variance indicates that CSD features can be used reliably to distinguish between severity levels of speech impairment. Results motivate the use of CSD in monitoring speech symptoms in PD.

  • 49.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University, Vasteras 72123, Sweden.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Classification of speech intelligibility in Parkinson's disease: Speech Impairment Classification2014In: Biocybernetics and Biomedical Engineering, ISSN 0208-5216, Vol. 34, no 1, p. 35-45Article in journal (Refereed)
    Abstract [en]

    A problem in the clinical assessment of running speech in Parkinson's disease (PD) is to track underlying deficits in a number of speech components including respiration, phonation, articulation and prosody, each of which disturbs the speech intelligibility. A set of 13 features, including the cepstral separation difference and Mel-frequency cepstral coefficients were computed to represent deficits in each individual speech component. These features were then used in training a support vector machine (SVM) using n-fold cross validation. The dataset used for method development and evaluation consisted of 240 running speech samples recorded from 60 PD patients and 20 healthy controls. These speech samples were clinically rated using the Unified Parkinson's Disease Rating Scale Motor Examination of Speech (UPDRS-S). The classification accuracy of SVM was 85% in 3 levels of UPDRS-S scale and 92% in 2 levels with the average area under the ROC (receiver operating characteristic) curves of around 91%. The strong classification ability of selected features and the SVM model supports suitability of this scheme to monitor speech symptoms in PD

  • 50.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Motion cue analysis for parkinsonian gait recognition2013In: The open biomedical engineering journal, ISSN 1874-1207, Vol. 7, p. 1-8Article in journal (Refereed)
    Abstract [en]

    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.

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