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  • 251.
    Verikas, Antanas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Bacauskiene, Marija
    Kaunas University of Technology, Department of Electric Power Systems, Kaunas, Lithuania.
    Malmqvist, Kerstin
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Selecting features for neural network committees2002In: Proceedings of the International Joint Conference on Neural Networks, Piscataway: IEEE, 2002, p. 215-220Conference paper (Refereed)
    Abstract [en]

    We present a neural network based approach for identifying salient features for classification in neural network committees. Our approach involves neural network training with an augmented cross-entropy error function. The augmented error function forces the neural network to keep low derivatives of the transfer functions of neurons of the network when learning a classification task. Such an approach reduces output sensitivity to the input changes. Feature selection is based on the reaction of the cross-validation data set classification error due to the removal of the individual features. We compared the approach with two other neural network based feature selection methods. The algorithm developed outperformed the methods by achieving a higher classification accuracy on three real world problems tested. ©2002 IEEE

  • 252.
    Verikas, Antanas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Bacauskiene, Marija
    Department of Applied Electronics, Kaunas University of Technology, Studentu 50, LT-3031, Kaunas, Lithuania.
    Malmqvist, Kerstin
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Selecting salient features for classification committees2003In: Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003 / [ed] Kaynak, O Alpaydin, E Oja, E Xu, L, Heidelberg: Springer Berlin/Heidelberg, 2003, Vol. 2714, p. 35-42Conference paper (Refereed)
    Abstract [en]

    We present a neural network based approach for identifying salient features for classification in neural network committees. Our approach involves neural network training with an augmented cross-entropy error function. The augmented error function forces the neural network to keep low derivatives of the transfer functions of neurons of the network when learning a classification task. Feature selection is based on two criteria, namely the reaction of the cross-validation data set classification error due to the removal of the individual features and the diversity of neural networks comprising the committee. The algorithm developed removed a large number of features from the original data sets without reducing the classification accuracy of the committees. By contrast, the accuracy of the committees utilizing the reduced feature sets was higher than those exploiting all the original features. © Springer-Verlag Berlin Heidelberg 2003.

  • 253.
    Verikas, Antanas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Department of Electrical and Control Equipment, Kaunas University of Technology, Kaunas, Lithuania.
    Gelzinis, Adas
    Department of Electrical and Control Equipment, Kaunas University of Technology, Kaunas, Lithuania.
    Bacauskiene, Marija
    Department of Electrical and Control Equipment, Kaunas University of Technology, Kaunas, Lithuania.
    Olenina, Irina
    Department of Marine Research of the Environmental Protection Agency, Klaipeda, Lithuania & Marine Science and Technology Center, Klaipeda University, Klaipeda, Lithuania.
    Vaiciukynas, Evaldas
    Department of Electrical and Control Equipment, Kaunas University of Technology, Kaunas, Lithuania.
    An Integrated Approach to Analysis of Phytoplankton Images2015In: IEEE Journal of Oceanic Engineering, ISSN 0364-9059, E-ISSN 1558-1691, Vol. 40, no 2, p. 315-326Article in journal (Refereed)
    Abstract [en]

    The main objective of this paper is detection, recognition, and abundance estimation of objects representing the Prorocentrum minimum (Pavillard) Schiller (P. minimum) species in phytoplankton images. The species is known to cause harmful blooms in many estuarine and coastal environments. The proposed technique for solving the task exploits images of two types, namely, obtained using light and fluorescence microscopy. Various image preprocessing techniques are applied to extract a variety of features characterizing P. minimum cells and cell contours. Relevant feature subsets are then selected and used in support vector machine (SVM) as well as random forest (RF) classifiers to distinguish between P. minimum cells and other objects. To improve the cell abundance estimation accuracy, classification results are corrected based on probabilities of interclass misclassification. The developed algorithms were tested using 158 phytoplankton images. There were 920 P. minimum cells in the images in total. The algorithms detected 98.1% of P. minimum cells present in the images and correctly classified 98.09% of all detected objects. The classification accuracy of detected P. minimum cells was equal to 98.9%, yielding a 97.0% overall recognition rate of P. minimum cells. The feature set used in this work has shown considerable tolerance to out-of-focus distortions. Tests of the system by phytoplankton experts in the cell abundance estimation task of P. minimum species have shown that its performance is comparable or even better than performance of phytoplankton experts exhibited in manual counting of artificial microparticles, similar to P. minimum cells. The automated system detected and correctly recognized 308 (91.1%) of 338 P. minimum cells found by experts in 65 phytoplankton images taken from new phytoplankton samples and erroneously assigned to the P. minimum class 3% of other objects. Note that, due to large variations of texture and size of P. minimum cells as well as- background, the task performed by the system was more complex than that performed by the experts when counting artificial microparticles similar to P. minimum cells.

  • 254.
    Verikas, Antanas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab). Kaunas University of Technology, Kaunas, Lithuania.
    Gelzinis, Adas
    Kaunas University of Technology, Kaunas, Lithuania.
    Vaiciukynas, Evaldas
    Kaunas University of Technology, Kaunas, Lithuania.
    Bacauskiene, Marija
    Kaunas University of Technology, Kaunas, Lithuania.
    Minelga, Jonas
    Kaunas University of Technology, Kaunas, Lithuania.
    Hållander, Magnus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Uloza, Virgilijus
    Lithuanian University of Health Sciences, Kaunas, Lithuania.
    Padervinskis, Evaldas
    Lithuanian University of Health Sciences, Kaunas, Lithuania.
    Data dependent random forest applied to screening for laryngeal disorders through analysis of sustained phonation: Acoustic versus contact microphone2015In: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 37, no 2, p. 210-218Article in journal (Refereed)
    Abstract [en]

    Comprehensive evaluation of results obtained using acoustic and contact microphones in screening for laryngeal disorders through analysis of sustained phonation is the main objective of this study. Aiming to obtain a versatile characterization of voice samples recorded using microphones of both types, 14 different sets of features are extracted and used to build an accurate classifier to distinguish between normal and pathological cases. We propose a new, data dependent random forests-based, way to combine information available from the different feature sets. An approach to exploring data and decisions made by a random forest is also presented. Experimental investigations using a mixed gender database of 273 subjects have shown that the perceptual linear predictive cepstral coefficients (PLPCC) was the best feature set for both microphones. However, the linear predictive coefficients (LPC) and linear predictive cosine transform coefficients (LPCTC) exhibited good performance in the acoustic microphone case only. Models designed using the acoustic microphone data significantly outperformed the ones built using data recorded by the contact microphone. The contact microphone did not bring any additional information useful for the classification. The proposed data dependent random forest significantly outperformed the traditional random forest. (C) 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

  • 255.
    Verikas, Antanas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Lipnickas, Arunas
    Kaunas University of Technology, Department of Applied Electronics, Studentu 50, 3031, Kaunas, Lithuania.
    Malmqvist, Kerstin
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Selecting neural networks for making a committee decision2002In: ARTIFICIAL NEURAL NETWORKS - ICANN 2002 / [ed] Dorronsoro, J R, Berlin: Springer Berlin/Heidelberg, 2002, Vol. 2415, p. 420-425Conference paper (Refereed)
    Abstract [en]

    To improve recognition results, decisions of multiple neural networks can be aggregated into a committee decision. In contrast to the ordinary approach of utilizing all neural networks available to make a committee decision, we propose creating adaptive committees, which are specific for each input data point. A prediction network is used to identify classification neural networks to be fused for making a committee decision about a given input data point. The jth output value of the prediction network expresses the expectation level that the jth classification neural network will make a correct decision about the class label of a given input data point. The effectiveness of the approach is demonstrated on two artificial and three real data sets.

  • 256.
    Verikas, Antanas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Kaunas University of Technology, Kaunas, Lithuania.
    Parker, James
    Halmstad University, School of Business, Engineering and Science, The Rydberg Laboratory for Applied Sciences (RLAS).
    Bacauskiene, Marija
    Kaunas University of Technology, Kaunas, Lithuania.
    Olsson, M. Charlotte
    Halmstad University, School of Business, Engineering and Science, The Rydberg Laboratory for Applied Sciences (RLAS).
    Exploring relations between EMG and biomechanical data recorded during a golf swing2017In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 88, p. 109-117Article in journal (Refereed)
    Abstract [en]

    Exploring relations between patterns of peak rotational speed of thorax, pelvis and arm, and patterns of EMG signals recorded from eight muscle regions of forearms and shoulders during the golf swing is the main objective of this article. The linear canonical correlation analysis, allowing studying relations between sets of variables, was the main technique applied. To get deeper insights, linear and nonlinear random forests-based prediction models relating a single output variable, e.g. a thorax peak rotational speed, with a set of input variables, e.g. an average intensity of EMG signals were used. The experimental investigations using data from 16 golfers revealed statistically significant relations between sets of input and output variables. A strong direct linear relation was observed between lin- ear combinations of EMG averages and peak rotational speeds. The coefficient of determination values R2 = 0 . 958 and R2 = 0 . 943 obtained on unseen data by the random forest models designed to predict peak rotational speed of thorax and pelvis , indicate high modelling accuracy. However, predictions of peak rotational speed of arm were less accurate. This was expected, since peak rotational speed of arm played a minor role in the linear combination of peak speeds. The most important muscles to predict peak rotational speed of the body parts were identified. The investigations have shown that the canon- ical correlation analysis is a promising tool for studying relations between sets of biomechanical and EMG data. Better understanding of these relations will lead to guidelines concerning muscle engagement and coordination of thorax, pelvis and arms during a golf swing and will help golf coaches in providing substantiated advices. ©2017 Elsevier Ltd. All rights reserved.

  • 257.
    Verikas, Antanas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Kaunas University of Technology, Kaunas, Lithuania.
    Vaiciukynas, Evaldas
    Kaunas University of Technology, Kaunas, Lithuania.
    Gelzinis, Adas
    Kaunas University of Technology, Kaunas, Lithuania.
    Parker, James
    Halmstad University, School of Business, Engineering and Science, Biological and Environmental Systems (BLESS).
    Olsson, M. Charlotte
    Halmstad University, School of Business, Engineering and Science, Biological and Environmental Systems (BLESS).
    Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness2016In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 16, no 4, article id 592Article in journal (Refereed)
    Abstract [en]

    This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features derived from the properties of two highest peaks as important predictors of personal shot effectiveness. Activation sequence profiles helped in analyzing muscle orchestration during golf shot, exposing a specific avalanche pattern, but data from more players are needed for stronger conclusions. Results demonstrate that information arising from an EMG signal stream is useful for predicting golf shot success, in terms of club head speed and ball carry distance, with acceptable accuracy. Surface EMG data, collected with a goal to automatically evaluate golf player’s performance, enables wearable computing in the field of ambient intelligence and has potential to enhance exercising of a long carry distance drive.

  • 258.
    Viteckova, Slavka
    et al.
    Faculty of Biomedical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
    Khandelwal, Siddhartha
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Kutilek, Patrik
    Faculty of Biomedical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
    Krupicka, Radim
    Faculty of Biomedical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
    Szabo, Zoltan
    Faculty of Biomedical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
    Gait symmetry methods: Comparison of waveform-based Methods and recommendation for use2020In: Biomedical Signal Processing and Control, ISSN 1746-8094, E-ISSN 1746-8108, Vol. 55, article id 101643Article in journal (Refereed)
    Abstract [en]

    Gait symmetry has been shown to be a relevant measure for differentiating between normal and pathological gait. Although a number of symmetry methods exist, it is not clear which of these methods should be used as they have been developed using data collected from varying experimental protocols. This paper presents a comparison of state-of-the-art waveform-based symmetry methods and tests them on walking data collected from different environments. Acceleration signals collected from the ankle are used to analyse symmetry methods under different signal circumstances, such as phase shift, waveform shape difference, signal length (i.e. number of gait cycles) and gait initiation phase. The cyclogram based method is invariant to signal phase shifts, signal length and the gait initiation phase. The trend symmetry method is not affected by signal scaling and the gait initiation phase but is affected by signal length depending on the environment. Similar to the trend method, the cross-correlation symmetry method is not responsive to signal scaling and the gait initiation phase. The results of the symbolic method are not influenced by signal scaling, gait initiation and depending on the environment by the signal phase shift. From the results of the performed analysis, we recommend the trend method to gait symmetry assessment. The comparison of waveform-based symmetry methods brings new knowledge that will help in selecting an appropriate method for gait symmetry assessment under different experimental protocols. © 2019 Elsevier Ltd. All rights reserved.

  • 259.
    Voronov, Alexey
    et al.
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Viktoria Swedish ICT, Gothenburg, Sweden.
    Bengtsson, Hoai
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Chen, Lei
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Ploeg, Jeroen
    TNO, Helmond, The Netherlands.
    de Jongh, Jan
    TNO, Helmond, The Netherlands.
    van de Sluis, Jacco
    TNO, Helmond, The Netherlands.
    Interactive test tool for interoperable C-ITS development2015In: 2015 IEEE 18th International Conference on Intelligent Transportation Systems / [ed] Lisa O’Conner, Los Alamitos: IEEE, 2015, p. 1713-1718, article id 7313370Conference paper (Refereed)
    Abstract [en]

    This paper presents the architecture of an Interactive Test Tool (ITT) for interoperability testing of Cooperative Intelligent Transport Systems (C-ITS). Cooperative systems are developed by different manufacturers at different locations, which makes interoperability testing a tedious task. Up until now, interoperability testing is performed during physical meetings where the C-ITS devices are placed within range of wireless communication, and messages are exchanged. The ITT allows distributed (e.g. over the Internet) interoperability testing starting from the network Transport Layer and all the way up to the Application Layer, e.g. to platooning. ITT clients can be implemented as Hardware-in-the-Loop, thus allowing to combine physical and virtual vehicles. Since the ITT considers each client as a black box, manufacturers can test together without revealing internal implementations to each other. The architecture of the ITT allows users to easily switch between physical wireless networking and virtual ITT networking. Therefore, only one implementation of the ITS communication stack is required for both development and testing. This reduces the work overhead and ensures that the stack that is used during the testing is the one deployed in the real world. © 2015 IEEE.

  • 260.
    Weckstén, Mattias
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Frick, Jan
    Halmstad University.
    Sjostrom, Andreas
    Halmstad University.
    Järpe, Eric
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A Novel Method for Recovery from Crypto Ransomware Infections2016In: 2016 2nd IEEE International Conference on Computer and Communications, ICCC 2016 - Proceedings, New York: IEEE, 2016, p. 1354-1358Conference paper (Refereed)
    Abstract [en]

    Extortion using digital platforms is an increasing form of crime. A commonly seen problem is extortion in the form of an infection of a Crypto Ransomware that encrypts the files of the target and demands a ransom to recover the locked data. By analyzing the four most common Crypto Ransomwares, at writing, a clear vulnerability is identified; all infections rely on tools available on the target system to be able to prevent a simple recovery after the attack has been detected. By renaming the system tool that handles shadow copies it is possible to recover from infections from all four of the most common Crypto Ransomwares. The solution is packaged in a single, easy to use script. © 2016 IEEE.

  • 261.
    Weman Josefsson, Karin
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Ebbesson, Esbjörn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Sport Health and Physical activity.
    Lund, Jesper
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Application of self-determination theory in the e-health industry – promoting sustainable exercise motivation2015In: Proceeding: 14th European Congress of Sport Psychology: Sport Psychology: Theories and Applications for Performance, Health and Humanity: 14-19 July 2015, Bern, Switzerland / [ed] Olivier Schmid & Roland Seiler, Bern: University of Bern , 2015, p. 372-372Conference paper (Refereed)
    Abstract [en]

    Developing tailored digital interventions for exercise motivation by applying behavioral theory into existing web services in cooperation with the e-health industry could create a mutual base for experience exchange and practical implications. It could also add higher standards to e-health business by providing a scientifically sound and trustworthy foundation for digital solutions. This project aims to design an interactive tool grounded in sport and exercise psychology and combined with the latest expertise from information technology and innovation science, considering e-health industrial requirements and user needs. A main objective is to test the efficacy of using Self-Determination Theory (SDT) in designing, constructing and evaluating an exercise intervention. The digital intervention is based on a literature review mapping exercise motivation related to self-determination theory, complemented by qualitative cross-disciplinary interaction design methodologies, such as qualitative analysis of interviews and contextual observation capturing participant goals, behaviour, preferences, attitudes and frustrations. Intervention contents are essentially autonomy supportive structures, goal-setting support and relapse prevention, self-regulation structures, health information and web links. In February 2015 the intervention prototype will be pilot tested in a randomized controlled trial (RCT), involving existing members and clients (N > 10 000) of two health service companies. Outcomes relate to self-determined exercise motivation (The Basic Psychological Needs in Exercise Scale and The Behavioral Regulation in Exercise Questionnaire-2) and exercise behaviour, measured both by self-report measures (Godin Leisure-Time Exercise Questionnaire) and step counters. The RCT contains three measure points in order to allow advanced analyses of change and mechanisms based on the SDT-process model and motivational profiles. Latent growth curve and structural equation models will primarily be used to analyse data. This pilot study will create a baseline for elaboration into a second phase, were the digital tool will be further developed and longitudinally tested and evaluated over a nine months period. © 2015 University of Bern, Institut of Sport Science 

  • 262.
    Weman Josefsson, Karin
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI). University of Gothenburg, Gothenburg, Sweden.
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Lindwall, Magnus
    University of Gothenburg, Gothenburg, Sweden.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Digital innovations and self-determined exercise motivation: a person-centred perspective2014In: Vitalis – Nordens ledande eHälsomöte 2014: Vetenskapliga papers presenterade vid Vitalis konferens, Svenska Mässan, Göteborg, 8-10 april 2014, Göteborg: Vitalis & Sahlgrenska akademin, Göteborgs universitet , 2014, p. 22-25Conference paper (Refereed)
    Abstract [en]

    Health care costs are increasing twice as fast as wealth, making health promotion and development of cost-effective care increasingly important in order to generate sustainable health care solutions. E-health, applications and interactive tools for exercise promotion flourish; but despite this and an overflow of information regarding health benefits of regular physical activity, exercise adherence has proven to be a significant challenge. This article concerns a project aimed to design an interactive tool based on comprehensive knowledge from the field of psychology combined with expertise from information technology and innovation, based on e-health industrial requirements and user needs. The research group will, together with the expertise and infrastructure of the collaborating companies Health Profile Institute AB and Tappa Service AB, support and progress an existing PhD-project on digital interventions in exercise motivation. This will be done by designing; applying and evaluating a person-centred digital intervention prototype for exercise motivation and adherence enhancement based on Self-Determination Theory.

  • 263.
    Weman Josefsson, Karin
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Sport Health and Physical activity.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Digital interventions in self-determined exercise motivation – interdisciplinary innovations2015In: ISBNPA 2015: Advancing Behavior Change Science : 3rd – 6th June 2015: Abstract Book, 2015, p. 592-592Conference paper (Refereed)
    Abstract [en]

    Purpose:There is a need for scientifically sound and theory based tools and services in e-health. In this project knowledge from the field of psychology will be complemented by expertise in information technology and innovation science in designing a digital intervention based on Self-determination theory (SDT) aiming to facilitate exercise motivation.

    Methods:The intervention will be tested by a three wave RCT design in a population of e-health clients (n = 200) in a web based exercise service. Sensors (step counters) and self-reports (Godin Leisure-Time Exercise Questionnaire) will be used to measure objective and subjective exercise behavior while instruments based on SDT (Basic Psychological Needs in Exercise Scale and Behavioral Regulation in Exercise Questionnaire-2 ) will measure factors related to motivation.  Advanced mediation variable analyses (MVA) and latent growth curve models (LGCM) will be used to explore motivational processes, changes and profiles in relation to exercise behavior.

    Expected Results:Based on the SDT process model, it is hypothesized that a (digital) environment supporting basic psychological need satisfaction will facilitate internalization and enhanced self-determined motivation, which in turn will have a positive effect on exercise behavior.

    Conclusions:Clarifying mechanisms and indirect effects provide knowledge of how intervention effects could be interpreted and understood. Combining high level research design like RCT and advanced analyses as MVA provides valuable contributions to the understanding of theoretical mechanisms of motivation that could inform the tailoring of effective interventions promoting healthy exercise behaviours.  In addition, the project might form a prosperous interdisciplinary fusion generating innovative and theory based digital solutions for e-health.

  • 264.
    Weman-Josefsson, Karin Anna
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Sport Health and Physical activity. University of Gothenburg, Gothenburg, Sweden.
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Sport Health and Physical activity.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Digital Innovations and Self-determined exercise motivation: an interdisciplinary approach2015In: Proceedings of The 6th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC March 2015. Orlando, Florida., 2015Conference paper (Refereed)
    Abstract [en]

    In face of escalating health care costs, new technology holds great promise for innovative solutions and new, more sustainable health care models. Technology centers around the individual, allowing for greater autonomy and control in health issues and access to tailored information and customized health behavior interventions. While this offers good opportunities for both public health impact and improved well-being at individual levels, it also emphasizes the need for properly designed e-health models firmly based on scientific principles and adequate theoretical frameworks. Consequently, this project aims to design an interactive tool utilizing an interdisciplinary approach combining motivational theory with the fields of information technology and business model innovation. In collaboration with two companies from the e-health industry, the purpose is to design, apply and evaluate a person-centered interactive prototype for maintainable and self-determined exercise motivation.

  • 265.
    Weman-Josefsson, Karin
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    An interdisciplinary project plan on Digital Innovations and Self-determined Exercise Motivation2013Conference paper (Other academic)
  • 266.
    Yu, Tianyi
    et al.
    Halmstad University, School of Information Technology.
    Edén, Jenny
    Halmstad University, School of Information Technology.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Viktoria Swedish ICT, Gothenburg, Sweden.
    Larsson, Tony
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Traffic Situation Estimator for Adaptive Cruise Control2016In: 2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), Piscataway, NJ: IEEE, 2016, article id 7523567Conference paper (Refereed)
    Abstract [en]

    A traffic situation estimator capable of analyzing driving behavior utilizing an image analysis-based tracking module is presented. The behavior is analyzed by using a state machine driven counter to estimate the traffic rhythm and determine if the detected vehicles are approaching, getting away, have been overtaken or have overtaken the ego-vehicle. Depending on the result, the traffic situation estimator suggest different reactions, either to drive faster, slower or optionally suggest to overtake vehicles ahead to help the driver to follow the traffic rhythm which in turn will improve safety and energy efficiency. The proposed approach is implemented in a smart-phone and has shown good performance while testing the application on a two-lane highway. © 2016 IEEE.

  • 267.
    Zeng, Yingfu
    et al.
    Rice University, Houston, USA.
    Chad, Rose
    Rice University, Houston, USA.
    Taha, Walid
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). Rice University, Houston, USA.
    Duracz, Adam
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Atkinson, Kevin
    Rice University, Houston, USA.
    Philippsen, Roland
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Cartwright, Robert
    Rice University, Houston, USA.
    O'Malley, Marcia
    Rice University, Houston, USA.
    Modeling Electromechanical Aspects of Cyber-Physical Systems2016In: Journal of Software Engineering for Robotics, ISSN 2035-3928, E-ISSN 2035-3928, Vol. 7, no 1, p. 100-119Article in journal (Refereed)
    Abstract [en]

    Model-based tools have the potential to significantly improve the process of developing novel cyber-physical systems (CPS). In this paper, we consider the question of what language features are needed to model such systems. We use a small, experimental hybrid systems modeling language to show how a number of basic and pervasive aspects of cyber-physical systems can be modeled concisely using the small set of language constructs. We then consider four, more complex, case studies from the domain of robotics. The first, a quadcopter, illustrates that these constructs can support the modeling of interesting systems. The second, a serial robot, provides a concrete example of why it is important to support static partial derivatives, namely, that it significantly improves the way models of rigid body dynamics can be expressed. The third, a linear solenoid actuator, illustrates the language’s ability to integrate multiphysics subsystems. The fourth and final, a compass gait biped, shows how a hybrid system with non-trivial dynamics is modeled. Through this analysis, the work establishes a strong connection between the engineering needs of the CPS domain and the language features that can address these needs. The study builds the case for why modeling languages can be improved by integrating several features, most notably, partial derivatives, differentiation without duplication, and support for equations. These features do not appear to be addressed in a satisfactory manner in mainstream modeling and simulation tools.

  • 268.
    Zeng, Yingfu
    et al.
    Rice University, Houston, USA.
    Rose, Chad
    Rice University, Houston, USA.
    Brauner, Paul
    Rice University, Houston, USA.
    Taha, Walid
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). Rice University, Houston, USA.
    Masood, Jawad
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Philippsen, Roland
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    O’Malley, Marcia
    Rice University, Houston, USA.
    Cartwright, Robert
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS). Rice University, Houston, USA.
    Modeling Basic Aspects of Cyber-Physical Systems, Part II2013In: Proceedings DSLRob 2013 / [ed] Christian Schlegel, Ulrik Pagh Schultz, Serge Stinckwich, 2013Conference paper (Refereed)
    Abstract [en]

    We consider the question of what language features are needed to effectively model cyber-physical systems (CPS). In previous work, we proposed a core language called Acumen as a way to study this question, and showed how several basic aspects of CPS can be modeled clearly in a language with a small set of constructs. This paper reports on the result of our analysis of two more complex case studies from the domain of rigid body dynamics. The first one, a quadcopter, illustrates that Acumen can support larger, more interesting systems than previously shown. The second one, a serial robot, provides a concrete example of why explicit support for static partial derivatives can significantly improve the expressivity of a CPS modeling language.

  • 269.
    Zeng, Yingfu
    et al.
    Rice University, Houston, TX, USA.
    Rose, Chad
    Rice University, Houston, TX, USA.
    Brauner, Paul
    Rice University, Houston, TX, USA.
    Taha, Walid
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). Rice University, Houston, TX, USA.
    Masood, Jawad
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Philippsen, Roland
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    O'Malley, Marcia
    Rice University, Houston, TX, USA.
    Cartwright, Robert
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). Rice University, Houston, TX, USA.
    Modeling Basic Aspects of Cyber-Physical Systems, Part II (Extended Abstract)2014In: 2014 IEEE International Conference on High Performance Computing and Communications, 2014 IEEE 6th International Symposium on Cyberspace Safety and Security, 2014 IEEE 11th International Conference on Embedded Software and Systems (HPCC, CSS, ICESS) / [ed] Randall Bilof, Piscataway, NJ: IEEE Computer Society, 2014, p. 550-557Conference paper (Refereed)
    Abstract [en]

    We continue to consider the question of what language features are needed to effectively model cyber-physical systems (CPS). In previous work, we proposed using a core language as a way to study this question, and showed how several basic aspects of CPS can be modeled clearly in a language with a small set of constructs. This paper reports on the result of our analysis of two, more complex, case studies from the domain of rigid body dynamics. The first one, a quadcopter, illustrates that previously proposed core language can support larger, more interesting systems than previously shown. The second one, a serial robot, provides a concrete example of why we should add language support for static partial derivatives, namely that it would significantly improve the way models of rigid body dynamics can be expressed. © 2014 IEEE.

  • 270.
    Zhang, Man
    et al.
    Institute of Automation Chinese Academy of Sciences, China.
    Liu, Jing
    University of Science and Technology of China, China.
    Sun, Zhenan
    Institute of Automation Chinese Academy of Sciences, China.
    Tan, Tieniu
    Institute of Automation Chinese Academy of Sciences, China.
    Su, Wu
    Zhuhai YiSheng Electronics Technology Co, Ltd, China.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Némesin, Valérian
    Aix-Marseilles University, Centrale Marseille, CNRS, Institut Fresnel, France.
    Othman, Nadia
    Institut Mines-Telecom, Télécom SudParis, France.
    Noda, Koichi
    Nihon System Laboratory, Ltd, Japan.
    Li, Peihua
    Dalian University of Technology, China.
    Hoyle, Edmundo
    University Federal of Rio de Janeiro, Brasil.
    Joshi, Akanksha
    Centre for Development of Advanced Computing, India.
    The First ICB Competition on Iris Recognition2014In: 2014 IEEE International Joint Conference on Biometrics (IJCB), Piscataway, NJ: IEEE Press, 2014, article id 6996292Conference paper (Refereed)
    Abstract [en]

    Iris recognition becomes an important technology in our society. Visual patterns of human iris provide rich texture information for personal identification. However, it is greatly challenging to match intra-class iris images with large variations in unconstrained environments because of noises, illumination variation, heterogeneity and so on. To track current state-of-the-art algorithms in iris recognition, we organized the first ICB∗ Competition on Iris Recognition in 2013 (or ICIR2013 shortly). In this competition, 8 participants from 6 countries submitted 13 algorithms totally. All the algorithms were trained on a public database (e.g. CASIA-Iris-Thousand [3]) and evaluated on an unpublished database. The testing results in terms of False Non-match Rate (FNMR) when False Match Rate (FMR) is 0.0001 are taken to rank the submitted algorithms. © 2014 IEEE.

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