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  • 101.
    Ahmadzadeh, Farzaneh
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ranking of Two Multi Criteria Decision Making Cases with Evidential Reasoning under Uncertainty2017In: Advances in Science, Technology and Engineering Systems Journal V2(3) ASTESJ-V2(3), ISSN 2415-6698, Vol. 2, no 3, p. 1059-1063Article in journal (Refereed)
    Abstract [en]

    Many decision problems have more than one objective that need to be dealt with simultaneously. Moreover, because of the qualitative nature of the most of real world problem it is an inevitable activity and very important to interpret and present the uncertain information for making effective decision. The Evidential Reasoning (ER) approach which is one of the latest development within multi criteria decision making (MCDM) seems to be the best fit to synthesize both qualitative and quantitative data under uncertainty. To support this claim, two case studies were tested to illustrate the application of ER for prioritization and ranking of decision alternative to support decision process even with uncertain information. The overall goal of the first case study is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. The result after applying ER shows “inadequate resources” and “weather /indoor climate,” respectively, are the highest and lowest average scores for creating maintenance-related waste. This prioritization methodology can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste. The aim of the second case study is to look at the possibility of having a new approach for sustainable design. So through a literature review six design strategies were taken into consideration in order to develop a new approach based on all advantages (sustainable factors) of the six approaches. For ranking and finding out about the most important factors the evidential reasoning (ER) approach is used. Based on ER all the important factors, apart from the one collected from interviews are a part of eco-design. So it means among all strategies eco-design is the most dominant strategy in term of environment. However two of the important factors are not found in any strategy but in interviews. These factors can be used as the building blocks for a new approach. The importance of having a better structured decision process is essential for the success of any organization, so it can be applied widely in most of real world problem dealing with making effective decision.

  • 102.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bengtsson, Marcus
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Classification of Maintenance-Related Waste Based on Human Factors2015In: 22nd International Annual EurOMA Conference EurOMA15, Neuchâtel, Switzerland, 2015Conference paper (Refereed)
    Abstract [en]

    The goal of this research is to identify and classify factors creating maintenance-related waste. A workshop study has been performed in order to identify root-causes for maintenance-related waste. In total, 16 categories were found in the analysis and it is concluded that these are heavily reliant on human factors as a root- or major contributory cause. These, together with factors based on a literature review have been incorporated into a classification model. The model can be used in creating awareness in, as well as provide a basic framework for decision making of, which waste to target for elimination.

  • 103.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bengtsson, Marcus
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Using evidential reasoning approach for prioritization of maintenance-related waste caused by human factors-a case study2017In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 90, no 9-12, p. 2761-2775Article in journal (Refereed)
    Abstract [en]

    The reduction and elimination of maintenance-related waste is receiving increasing attention because of the negative effect of such waste on production costs. The overall goal of this research is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. Five manufacturing companies participated in a workshop to identify root causes of maintenance-related waste; 16 categories were found. The identified factors were heavily reliant on human factors as a root or major contributory cause at different levels affecting performance and productivity. For prioritization, the evidential reasoning (ER) approach which is one of the latest developments in multi-criteria decision-making is applied. A basic tree structure necessary for ER assessment is developed based on the workshop results as well as literature on human factors. Then, a survey on basic attributes at the lowest level of this tree is designed and performed at one of the companies participating in the workshop. The application of ER shows that, on an overall level, "management condition" is in first order and "maintainer condition" and "working condition" are in second and third order respectively as the worst cases for creating maintenance-related waste. On the most delimited level "inadequate resources" and "weather/indoor climate" have the highest and lowest average scores respectively in ER ranking or prioritization. This methodology with its resulting ranking can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste.

  • 104.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Jederström, Kathrina
    Mälardalen University.
    Plahn, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Olsson, Anna
    Mälardalen University.
    Foyer, Isabell
    Mälardalen University.
    AN INVESTIGATION OF THE MOST IMPORTANT FACTORS FOR SUSTAINABLE PRODUCT DEVELOPMENT USING EVIDENTIAL REASONING2017In: Numerical Algebra, Control and Optimization, ISSN 2155-3289, E-ISSN 2155-3297, Vol. 7, no 4, p. 435-455Article in journal (Refereed)
    Abstract [en]

    Those working in product development need to consider sustain ability, being careful not to compromise the future generations ability to satisfy its needs. Several strategies guide companies towards sustainability. This paper studies six of these strategies: eco-design, green design, cradle-to-cradle, design for environment, zero waste, and life cycle approaches. Based on a literature review and semi-structured interviews, it identifies 22 factors of sustainability from the perspective of manufacturers. The purpose is to determine which are the most important and to use them as a foundation for a new design strategy. A survey based on the 22 factors was given to people working with product development; they graded each factor by importance. The resulting qualitative data were analyzed using evidential reasoning. The analysis found the factors minimize use of toxic substances, increase competitiveness, economic benefits, reduce material usage, material selection, reduce emissions, and increase product functionality are more important and should serve as the foundation for a new approach to sustainable product development.

  • 105.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Luleå University of Technology, Luleå, Sweden.
    Lundberg, Jan
    Luleå University of Technology, Luleå, Sweden.
    Remaining useful life estimation: Review2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 4, p. 461-474Article, book review (Other academic)
    Abstract [en]

    This paper reviews the recent modelling developments in estimating the remaining useful life (RUL) of industrial systems. The RUL estimation models are categorized into experimental, data driven, physics based and hybrid approaches. The paper reviews some typical approaches and discusses their advantages and disadvantages. According to the literature, the selection of the best model depends on the level of accuracy and availability of data. In cases of quick estimations which are less accurate, the data driven method is preferred, while the physics based approach is applied when the accuracy of estimation is important.

  • 106.
    Ahmed, Athar Nadeem
    Mälardalen University, School of Innovation, Design and Engineering.
    Wireless inertial measurement unit for industrial robotic arm2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
  • 107.
    Ahmed, B. S.
    et al.
    Istituto Dalle Molle di Studi Sull'Intelligenza Artificiale (IDSIA), Manno-Lugano, Switzerland.
    Sahib, M. A.
    Software and Informatics Engineering Department, Engineering College, Salahaddin University - Erbil, Iraq.
    Gambardella, L. M.
    Istituto Dalle Molle di Studi Sull'Intelligenza Artificiale (IDSIA), Manno-Lugano, Switzerland.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Zamli, K. Z.
    IBM Centre of Excellence, Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang Lebuhraya Tun Razak, Kuantan, Pahang Darul Makmur, Malaysia.
    Optimum design of PIλDμ controller for an automatic voltage regulator system using combinatorial test design2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 11, article id e0166150Article in journal (Refereed)
    Abstract [en]

    Combinatorial test design is a plan of test that aims to reduce the amount of test cases systematically by choosing a subset of the test cases based on the combination of input variables. The subset covers all possible combinations of a given strength and hence tries to match the effectiveness of the exhaustive set. This mechanism of reduction has been used successfully in software testing research with t-way testing (where t indicates the interaction strength of combinations). Potentially, other systems may exhibit many similarities with this approach. Hence, it could form an emerging application in different areas of research due to its usefulness. To this end, more recently it has been applied in a few research areas successfully. In this paper, we explore the applicability of combinatorial test design technique for Fractional Order (FO), Proportional-Integral-Derivative (PID) parameter design controller, named as FOPID, for an automatic voltage regulator (AVR) system. Throughout the paper, we justify this new application theoretically and practically through simulations. In addition, we report on first experiments indicating its practical use in this field. We design different algorithms and adapted other strategies to cover all the combinations with an optimum and effective test set. Our findings indicate that combinatorial test design can find the combinations that lead to optimum design. Besides this, we also found that by increasing the strength of combination, we can approach to the optimum design in a way that with only 4-way combinatorial set, we can get the effectiveness of an exhaustive test set. This significantly reduced the number of tests needed and thus leads to an approach that optimizes design of parameters quickly. © 2016 Ahmed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • 108.
    Ahmed, Bestoun
    et al.
    Istituto Dalle Molle di Studi sullIntelligenza Artificiale (IDSIA), Switzerland.
    Gambardella, Luca
    Istituto Dalle Molle di Studi sullIntelligenza Artificiale (IDSIA), Switzerland.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Zamli, Kamal
    University Malaysia Pahang, Gambang, Malaysia.
    Handling Constraints in Combinatorial Interaction Testing in the Presence of Multi Objective Particle Swarm and Multithreading2017In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 86, no 01, p. 20-36Article in journal (Refereed)
    Abstract [en]

    Combinatorial strategies have received a lot of attention lately as a result of their diverse applications in areas of research, particularly in software engineering. In its simple form, a combinatorial strategy can reduce several input parameters (configurations) of a system into a small set of these parameters based on their interaction (combination). However, in practice, the input configurations of software systems are subjected to constraints, especially highly configurable systems. To implement this feature within a strategy, many difficulties arise for construction. While there are many combinatorial interaction testing strategies nowadays, few of them support constraints. This paper presents a new strategy, called Octopus to construct a combinatorial interaction test suites with the presence of constraints. The design and algorithms are provided in the paper in detail. The strategy is inspired by the behaviour of octopus to search for the optimal solution using multi-threading mechanism. To overcome the multi judgement criteria for an optimal solution, the multi-objective particle swarm optimisation is used. The strategy and its algorithms are evaluated extensively using different benchmarks and comparisons. The evaluation results showed the efficiency of each algorithm in the strategy. The benchmarking results also showed that Octopus can generate test suites efficiently as compared to state-of-the-art strategies.

  • 109.
    Ahmed, Bestoun
    et al.
    Czech Technical University, Czech Republic.
    Zamli, Kamal
    University Malaysia Pahang, Gambang, Malaysia..
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bures, Miroslav
    Czech Technical University, Czech Republic.
    Constrained Interaction Testing: A Systematic Literature Study2017In: IEEE Access, E-ISSN 2169-3536, IEEE Access, ISSN 2169-3536, Vol. PP, no 99Article, book review (Other academic)
    Abstract [en]

    Interaction testing can be used to effectively detect faults that are otherwise difficult to find by other testing techniques. However, in practice, the input configurations of software systems are subjected to constraints, especially in the case of highly configurable systems. Handling constraints effectively and efficiently in combinatorial interaction testing is a challenging problem. Nevertheless, researchers have attacked this challenge through different techniques, and much progress has been achieved in the past decade. Thus, it is useful to reflect on the current achievements and shortcomings and to identify potential areas of improvements. This paper presents the first comprehensive and systematic literature study to structure and categorize the research contributions for constrained interaction testing. Following the guidelines of conducting a literature study, the relevant data is extracted from a set of 103 research papers belonging to constrained interaction testing. The topics addressed in constrained interaction testing research are classified into four categories of constraint test generation, application, generation & application and model validation studies. The papers within each of these categories are extensively reviewed. Apart from answering several other research questions, this study also discusses the applications of constrained interaction testing in several domains such as software product lines, fault detection & characterization, test selection, security and GUI testing. The study ends with a discussion of limitations, challenges and future work in the area.

  • 110.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering.
    A case-based multi-modal clinical system for stress management2010Licentiate thesis, monograph (Other academic)
    Abstract [en]

    A difficult issue in stress management is to use biomedical sensor signal in the diagnosis and treatment of stress. Clinicians often make their diagnosis and decision based on manual inspection of physiological signals such as, ECG, heart rate, finger temperature etc. However, the complexity associated with manual analysis and interpretation of the signals makes it difficult even for experienced clinicians. Today the diagnosis and decision is largely dependent on how experienced the clinician is interpreting the measurements.  A computer-aided decision support system for diagnosis and treatment of stress would enable a more objective and consistent diagnosis and decisions.

    A challenge in the field of medicine is the accuracy of the system, it is essential that the clinician is able to judge the accuracy of the suggested solutions. Case-based reasoning systems for medical applications are increasingly multi-purpose and multi-modal, using a variety of different methods and techniques to meet the challenges of the medical domain. This research work covers the development of an intelligent clinical decision support system for diagnosis, classification and treatment in stress management. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques have been investigated to enable a more reliable and efficient diagnosis and treatment of stress such as case-based reasoning, textual information retrieval, rule-based reasoning, and fuzzy logic. Functionalities and the performance of the system have been validated by implementing a research prototype based on close collaboration with an expert in stress. The case base of the implemented system has been initiated with 53 reference cases classified by an experienced clinician. A case study also shows that the system provides results close to a human expert. The experimental results suggest that such a system is valuable both for less experienced clinicians and for experts where the system may function as a second option.

  • 111.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering.
    A Multimodal Approach for Clinical Diagnosis and Treatment2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    A computer-aided Clinical Decision Support System (CDSS) for diagnosis and treatment often plays a vital role and brings essential benefits for clinicians. Such a CDSS could function as an expert for a less experienced clinician or as a second option/opinion of an experienced clinician to their decision making task. Nevertheless, it has been a real challenge to design and develop such a functional system where accuracy of the system performance is an important issue.

    This research work focuses on development of intelligent CDSS based on a multimodal approach for diagnosis, classification and treatment in medical domains i.e. stress and post-operative pain management domains. Several Artificial Intelligence (AI) techniques such as Case-Based Reasoning (CBR), textual Information Retrieval (IR), Rule-Based Reasoning (RBR), Fuzzy Logic and clustering approaches have been investigated in this thesis work.

    Patient’s data i.e. their stress and pain related information are collected from complex data sources for instance, finger temperature measurements through sensor signals, pain measurements using a Numerical Visual Analogue Scale (NVAS), patient’s information from text and multiple choice questionnaires. The proposed approach considers multimedia data management to be able to use them in CDSSs for both the domains.

    The functionalities and performance of the systems have been evaluated based on close collaboration with experts and clinicians of the domains. In stress management, 68 measurements from 46 subjects and 1572 patients’ cases out of ≈4000 in post-operative pain have been used to design, develop and validate the systems. In the stress management domain, besides the 68 measurement cases, three trainees and one senior clinician also have been involved in order to conduct the experimental work. The result from the evaluation shows that the system reaches a level of performance close to the expert and better than the senior and trainee clinicians. Thus, the proposed CDSS could be used as an expert for a less experienced clinician (i.e. trainee) or as a second option/opinion for an experienced clinician (i.e. senior) to their decision making process in stress management. In post-operative pain treatment, the CDSS retrieves and presents most similar cases (e.g. both rare and regular) with their outcomes to assist physicians. Moreover, an automatic approach is presented in order to identify rare cases and 18% of cases from the whole cases library i.e. 276 out of 1572 are identified as rare cases by the approach. Again, among the rare cases (i.e. 276), around 57.25% of the cases are classified as ‘unusually bad’ i.e. the average pain outcome value is greater or equal to 5 on the NVAS scale 0 to 10. Identification of rear cases is an important part of the PAIN OUT project and can be used to improve the quality of individual pain treatment.

  • 112.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Personalized Health-Monitoring System for Elderly by Combining Rules and Case-based Reasoning2015In: Studies in Health Technology and Informatics, Volume 21: Proceedings of the 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 2–4 June 2015, Västerås, Sweden, 2015, p. 249-254Conference paper (Refereed)
    Abstract [en]

    Health-monitoring system for elderly in home environment is a promising solution to provide efficient medical services that increasingly interest by the researchers within this area. It is often more challenging when the system is self-served and functioning as personalized provision. This paper proposed a personalized self-served health-monitoring system for elderly in home environment by combining general rules with a case-based reasoning approach. Here, the system generates feedback, recommendation and alarm in a personalized manner based on elderly’s medical information and health parameters such as blood pressure, blood glucose, weight, activity, pulse, etc. A set of general rules has used to classify individual health parameters. The case-based reasoning approach is used to combine all different health parameters, which generates an overall classification of health condition. According to the evaluation result considering 323 cases and k=2 i.e., top 2 most similar retrieved cases, the sensitivity, specificity and overall accuracy are achieved as 90%, 97% and 96% respectively. The preliminary result of the system is acceptable since the feedback; recommendation and alarm messages are personalized and differ from the general messages. Thus, this approach could be possibly adapted for other situations in personalized elderly monitoring.

  • 113.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    An Intelligent Healthcare Service to Monitor Vital Signs in Daily Life – A Case Study on Health-IoT2017In: International Journal of Engineering Research and Applications, ISSN 2248-9622, E-ISSN 2248-9622, Vol. 7, no 3, p. 43-55Article in journal (Refereed)
    Abstract [en]

    Vital signs monitoring for elderly in daily life environment is a promising concept that efficiently can provide medical services to people at home. However, make the system self-served and functioning as personalized provision makes the challenge even larger. This paper presents a case study on a Health-IoT system where an intelligent healthcare service is developed to monitor vital signs in daily life. Here, a generic Health-IoT framework with a Clinical Decision Support System (CDSS) is presented. The generic framework is mainly focused on the supporting sensors, communication media, secure and safe data communication, cloud-based storage, and remote accesses of the data. The CDSS is used to provide a personalized report on persons’ health condition based on daily basis observation on vital signs. Six participants, from Spain (n=3) and Slovenia (n=3) have been using the proposed healthcare system for eight weeks (e.g. 300+ health measurements) in their home environments to monitor their health. The sensitivity, specificity and overall accuracy of the DSS’s classification are achieved as 90%, 97% and 96% respectively while k=2 i.e., top 2 most similar retrieved cases are considered. The initial user evaluation result demonstrates the feasibility and performance of the implemented system through the proposed framework.

  • 114.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Banaee, Hadi
    Loutfi, Amy
    Rafael-Palou, Xavier
    Intelligent Healthcare Services to Support Health Monitoring of Elderly2014In: International Conference on IoT Technologies for HealthCare HealthyIoT, Rome, Italy, 2014Conference paper (Refereed)
    Abstract [en]

    This paper proposed an approach of intelligent healthcare services to support health monitoring of old people through the project named SAAPHO. Here, definition and architecture of the proposed healthcare services are presented considering six different health parameters such as: 1) physical activity, 2) blood pressure, 3) glucose, 4) medication compliance, 5) pulse monitoring and 6) weight monitoring. The outcome of the proposed services is evaluated in a case study where total 201 subjects from Spain and Slovenia are involved for user requirements analysis considering 1) end users, 2) clinicians, and 3) field study analysis perspectives. The result shows the potentiality and competence of the proposed healthcare services for the users.

  • 115.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Bibliometric Profiling of a Group: A Discussion on Different Indicators2011Report (Other academic)
    Abstract [en]

    Now-a-days in some advanced countries bibliometric profiling plays a vital role when making decision on promotion, fund allocation and award prizes. Accurate identification of this is important since it is becoming important to assess scientific output for a researcher or a group of researcher. This paper presents and discusses several most common indicators of bibliometric profiling together with h- and g-indexes. A case study has been conducted on 101 scientific articles with three most well known search engines. The study results using several indicators are presented in this report.

  • 116.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    Big Data Analytics in Health Monitoring at Home2017In: Medicinteknikdagarna 2017 MTD 2017, 2017Conference paper (Refereed)
    Abstract [en]

    This paper proposed a big data analytics approach applied in the projects ESS-H and E-care@home in the context of biomedical and health informatics with the advancement of information fusion, data abstraction, data mining, knowledge discovery, learning, and reasoning [1][2]. Data are collected through the projects, considering both the health parameters, e.g. temperature, bio-impedance, skin conductance, heart sound, blood pressure, pulse, respiration, weight, BMI, BFP, movement, activity, oxygen saturation, blood glucose, heart rate, medication compliance, ECG, EMG, and EEG, and the environmental parameters e.g. force/pressure, infrared (IR), light/luminosity, photoelectric, room-temperature, room-humidity, electrical usage, water usage, RFID localization and accelerometers. They are collected as semi-structured/unstructured, continuous/periodic, digital/paper record, single/multiple patients, once/several-times, etc. and stored in a central could server [5]. Thus, with the help of embedded system, digital technologies, wireless communication, Internet of Things (IoT) and smart sensors, massive quantities of data (so called ‘Big Data’) with value, volume, velocity, variety, veracity and variability are achieved [2]. The data analysis work in the following three steps. In Step1, pre-processing, future extraction and selection are performed based on a combination of statistical, machine learning and signal processing techniques. A novel strategy to fuse the data at feature level and as well as at data level considers a defined fusion mechanism [3]. In Step2, a combination of potential sequences in the learning and search procedure is investigated. Data mining and knowledge discovery, using the refined data from the above for rule extraction and knowledge mining, with support for anomaly detection, pattern recognition and regression are also explored here [4]. In Step3, adaptation of knowledge representation approaches is achieved by combining different artificial intelligence methods [3] [4]. To provide decision support a hybrid approach is applied utilizing different machine learning algorithms, e.g. case-based reasoning, and clustering [4]. The approach offers several data analytics tasks, e.g. information fusion, anomaly detection, rules and knowledge extraction, clustering, pattern identification, correlation analysis, linear regression, logic regression, decision trees, etc. Thus, the approach assist in decision support, early detection of symptoms, context awareness and patient’s health status in a personal environment.

  • 117.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Catalina, Carlos Alberto
    ITCL Polígono Industrial Villalonquéjar c/López Bravo, 70. 09001 BURGOS, Spain.
    Limonad, Lior
    Smart Wearable and IoT Solutions, IBM Research, Haifa, Israil.
    Hök, Bertil
    Hök Instrument AB, Sweden.
    Flumeri, Gianluca Di
    Cognitive States in Operative Environment, BrainSigns, Italy.
    Cloud-based Data Analytics on Human Factor Measurement to Improve Safer Transport2018In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, p. 101-106Conference paper (Refereed)
    Abstract [en]

    Improving safer transport includes individual and collective behavioural aspects and their interaction. A system that can monitor and evaluate the human cognitive and physical capacities based on human factor measurement is often beneficial to improve safety in driving condition. However, analysis and evaluation of human factor measurement i.e. Demographics, Behavioural and Physiological in real-time is challenging. This paper presents a methodology for cloud-based data analysis, categorization and metrics correlation in real-time through a H2020 project called SimuSafe. Initial implementation of this methodology shows a step-by-step approach which can handle huge amount of data with variation and verity in the cloud.

  • 118.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    A Hybrid Case-Based System in Stress Diagnosis and Treatment2012Manuscript (preprint) (Other academic)
    Abstract [en]

    Computer-aided decision support systems play anincreasingly important role in clinical diagnosis and treatment.However, they are difficult to build for domains where thedomain theory is weak and where different experts differ indiagnosis. Stress diagnosis and treatment is an example of such adomain. This paper explores several artificial intelligencemethods and techniques and in particular case-based reasoning,textual information retrieval, rule-based reasoning, and fuzzylogic to enable a more reliable diagnosis and treatment of stress.The proposed hybrid case-based approach has been validated byimplementing a prototype in close collaboration with leadingexperts in stress diagnosis. The obtained sensitivity, specificityand overall accuracy compared to an expert are 92%, 86% and88% respectively.

  • 119.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    A Multi-Modal Case-Based System for Clinical Diagnosis and Treatment in Stress Management2009In: / [ed] Delany, S.J., 2009, p. 215-224Conference paper (Refereed)
    Abstract [en]

    A difficult issue in stress management is to use biomedical sensor signal in the diagnosis and treatment of stress. Clinicians often base their diagnosis and decision on manual inspection of signals such as, ECG, heart rate, finger temperature etc. However, the complexity associated with the manual analysis and interpretation of the signals makes it difficult even for experienced clinicians. A computer system, classifying the sensor signals is one valuable property assisting a clinician. This paper presents a case-based system that assist a clinician in diagnosis and treatment of stress. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques such as textual information retrieval, rule-based reasoning, and fuzzy logic have been combined together with case-based reasoning to enable more reliable and efficient diagnosis and treatment of stress. The performance has been validated implementing a research prototype and close collaboration with the experts. The experimental results suggest that such a system is valuable both for the less experienced clinicians and for experts where the system may be seen as a second option.

  • 120.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    An Overview of three Medical Applications Using Hybrid Case-Based Reasoning2012Conference paper (Refereed)
    Abstract [en]

    Today more and more patient journals are stored electronically but they are rarely used for more than statistical purpose. In this paper we present an approach where clinical patient journals are used for improved clinical decision making on an individual level. The underlying assumption is that medical staff benefit from comparing a specific patient with similar patient. By comparing symptoms, diagnosis, medication and outcome in an individual level they are able to make more informed decisions at the point of care. This paper presents some parts of our more than ten years research efforts in the area and some of the projects and their underlying hybrid approaches. As a foundation for all our projects we use case-based reasoning (CBR) research in combination with techniques from artificial intelligence, data mining, statistics and search techniques. Three systems are presented in two medical domains 1) decision support for stress diagnosis 2) decision support for stress treatment and 3) decision support for post-operative pain treatment and discuss results and lessons learned.

  • 121.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Case studies on the clinical applications using case-based reasoning2012In: 2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012, 2012, p. 3-10Conference paper (Refereed)
    Abstract [en]

    Case-Based Reasoning (CBR) is a promising Artificial Intelligence (AI) method that is applied for problem solving tasks. This approach is widely used in order to develop Clinical Decision Support System (CDSS). A CDSS for diagnosis and treatment often plays a vital role and brings essential benefits for clinicians. Such a CDSS could function as an expert for a less experienced clinician or as a second option/opinion of an experienced clinician to their decision making task. This paper presents the case studies on 3 clinical Decision Support Systems as an overview of CBR research and development. Two medical domains are used here for the case studies: case-study-1) CDSS for stress diagnosis case-study-2) CDSS for stress treatment and case-study-3) CDSS for postoperative pain treatment. The observation shows the current developments, future directions and pros and cons of the CBR approach. Moreover, the paper shares the experiences of developing 3CDSS in medical domain in terms of case study.

  • 122.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    System Overview on a Clinical Decision Support System for Stress Management2012In: Proceedings of the ICCBR 2012 Workshops, 2012, p. 111-116Conference paper (Refereed)
    Abstract [en]

    There is an increased need for Clinical Decision Support Systems (CDSS) in the medical community as ICT technology is increasingly used in hospitals as more and more patient data is stored in computers. A CDSS has the potential to play a vital role and bring essential information and knowledge to the clinicians and function as a second opinion in their decision-making tasks. In this paper, a CDSS in stress management is presented where the CDSS can help the clinicians in order to diagnosis and treat stress related disorders. As a foundation for the CDSS, the Case-Based Reasoning (CBR) approach has been used as a core method of the system. The systems also combine other techniques from artificial intelligence in a multimodal manner, such as fuzzy logic, rule-based reasoning and textual information retrieval. In this paper we review our experiences and research efforts while developing the CDSS. The performance of the CDSS shows that the system can be useful both for trainee clinicians as an expert and as well as for senior clinicians as a second option. Moreover, the observation shows the current developments, and pros and cons of the CBR approach.

  • 123.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    The 3 CDSSs: An Overview and Application in Case-Based Reasoning2012In: The 27th annual workshop of the Swedish Artificial Intelligence Society (SAIS), Linköping: Linköping University Electronic Press, 2012, p. 25-32Conference paper (Refereed)
    Abstract [en]

    A computer-aided Clinical Decision SupportSystem (CDSS) for diagnosis and treatment often plays a vital role and brings essential benefits for clinicians. Such a CDSScould function as an expert for a less experienced clinician oras a second option/opinion of an experienced clinician to their decision making task. This paper presents 3 clinical DecisionSupport Systems as an overview of case-based reasoning (CBR) research and development. Two medical domains are used here for the case study 1) CDSS for stress diagnosis 2) CDSS for stress treatment and 3) CDSS for post-operative pain treatment.The observation shows the current developments, future direction and pros and cons of the CBR approach. Moreover,the paper shares the experiences of developing 3CDSS in medical domain.

  • 124.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    FUZZY RULE-BASED CLASSIFICATION TO BUILD INITIAL CASE LIBRARY FOR CASE-BASED STRESS DIAGNOSIS2009In: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2009 / [ed] M.H. Hamza, 2009, p. 225-230Conference paper (Refereed)
    Abstract [en]

    Case-Based Reasoning (CBR) is receiving increasedinterest for applications in medical decision support.Clinicians appreciate the fact that the system reasons withfull medical cases, symptoms, diagnosis, actions takenand outcomes. Also for experts it is often appreciated toget a second opinion. In the initial phase of a CBR systemthere are often a limited number of cases available whichreduces the performance of the system. If past cases aremissing or very sparse in some areas the accuracy isreduced. This paper presents a fuzzy rule-basedclassification scheme which is introduced into the CBRsystem to initiate the case library, providing improvedperformance in the stress diagnosis task. Theexperimental results showed that the CBR system usingthe enhanced case library can correctly classify 83% ofthe cases, whereas previously the correctness of theclassification was 61%. Consequently the proposedsystem has an improved performance with 22% in termsof accuracy. In terms of the discrepancy in classificationcompared to the expert, the goodness-of-fit value of thetest results is on average 87%. Thus by employing thefuzzy rule-based classification, the new hybrid system cangenerate artificial cases to enhance the case library.Furthermore, it can classify new problem cases previouslynot classified by the system.

  • 125.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Multi-Modal and Multi-Purpose Case-based Reasoning in the Health Sciences2009In: PROCEEDINGS OF THE 8TH WSEAS INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, KNOWLEDGE ENGINEERING AND DATA BASES / [ed] Leon Trilling et al, Cambridge, UK: WSEAS press , 2009, p. 378-383Conference paper (Refereed)
    Abstract [en]

    Case-based reasoning systems for medical application are increasingly multi-purpose systems and also multi-modal, using a variety of different methods and techniques to meet the challenges from the medical domain. It this paper, some of the recent medical case-based reasoning systems are classified according to their functionality and development properties. It shows how a particular multi-purpose and multi-modal case-based reasoning system solved these challenges. For this a medical case-based reasoning system in the domain of psychophysiology is used. 

  • 126.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    A Multi-Module Case Based Biofeedback System for Stress Treatment2011In: Artificial Intelligence in Medicine, ISSN 0933-3657, E-ISSN 1873-2860, Vol. 51, no 2, p. 107-115Article in journal (Refereed)
    Abstract [en]

    Biofeedback is today a recognized treatment method for a number of physical and psychological problems. Experienced clinicians often achieve good results in these areas and their success largely builds on many years of experience and often thousands of treated patients. Unfortunately many of the areas where biofeedback is used are very complex, e.g. diagnosis and treatment of stress. Less experienced clinicians may even have difficulties to initially classify the patient correctly. Often there are only a few experts available to assist less experienced clinicians. To reduce this problem we propose a computer assisted biofeedback system helping in classification, parameter setting and biofeedback training. By adopting a case based approach in a computer-based biofeedback system, decision support can be offered to less experienced clinicians and provide a second opinion to experts. We explore how such a system may be designed and validate the approach in the area of stress where the system assists in the classification, parameter setting and finally in the training. In a case study we show that the case based biofeedback system outperforms novice clinicians based on a case library of cases authorized by an expert.

  • 127.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    A Three Phase Computer Assisted Biofeedback Training System Using Case-Based Reasoning2008In: Proc. 9th European Conference on Case-based Reasoning, 2008, p. 57-68Conference paper (Refereed)
    Abstract [en]

    Biofeedback is a method gaining increased interest and showing good results for a number of physical and psychological problems. Biofeedback training is mostly guided by an experienced clinician and the results largely rely on the clinician's competence. In this paper we propose a three phase computer assisted sensor-based biofeedback decision support system assisting less experienced clinicians, acting as second opinion for experienced clinicians. The three phase CBR framework is deployed to classify a patient, estimate initial parameters and to make recommendations for biofeedback training by retrieving and comparing with previous similar cases in terms of features extracted. The three phases work independently from each other. Moreover, fuzzy techniques are incorporated into our CBR system to better accommodate uncertainty in clinicians reasoning as well as decision analysis. All parts in the proposed framework have been implemented and primarily validated in a prototypical system. The initial result shows how the three phases functioned with CBR technique to assist biofeedback training. Eventually the system enables the clinicians to allow a patient to train himself/herself unsupervised.

  • 128.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    Case-based Reasoning for Diagnosis of Stress using Enhanced Cosine and Fuzzy Similarity2008In: Case-based Reasoning for Diagnosis of Stress using Enhanced Cosine and Fuzzy Similarity, ISSN 1867-366X, Vol. 1, p. 3-19Article in journal (Refereed)
    Abstract [en]

    Intelligent analysis of heterogeneous data and information sources for efficient decision support presents an interesting yet challenging task in clinical envi-ronments. This is particularly the case in stress medicine where digital patient re-cords are becoming popular which contain not only lengthy time series measurements but also unstructured textual documents expressed in form of natural languages. This paper develops a hybrid case-based reasoning system for stress di-agnosis which is capable of coping with both numerical signals and textual data at the same time. The total case index consists of two sub-parts corresponding to signal and textual data respectively. For matching of cases on the signal aspect we present a fuzzy similarity matching metric to accommodate and tackle the imprecision and uncertainty in sensor measurements. Preliminary evaluations have revealed that this fuzzy matching algorithm leads to more accurate similarity estimates for improved case ranking and retrieval compared with traditional distance-based matching crite-ria. For evaluation of similarity on the textual dimension we propose an enhanced cosine matching function augmented with related domain knowledge. This is im-plemented by incorporating Wordnet and domain specific ontology into the textual case-based reasoning process for refining weights of terms according to available knowledge encoded therein. Such knowledge-based reasoning for matching of tex-tual cases has empirically shown its merit in improving both precision and recall of retrieved cases with our initial medical databases. Experts in the domain are very positive to our system and they deem that it will be a valuable tool to foster wide-spread experience reuse and transfer in the area of stress diagnosis and treatment.

  • 129.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    Case-based Reasoning for Diagnosis of Stress using Enhanced Cosine and Fuzzy Similarity2008In: Transactions on Case-Based Reasoning on Multimedia Data, ISSN 1867-366X, Vol. 1, no 1, p. 3-19Article in journal (Refereed)
    Abstract [en]

    Intelligent analysis of heterogeneous data and information sources for efficient decision support presents an interesting yet challenging task in clinical environments. This is particularly the case in stress medicine where digital patient records are becoming popular which contain not only lengthy time series measurements but also unstructured textual documents expressed in form of natural languages. This paper develops a hybrid case-based reasoning system for stress diagnosis which is capable of coping with both numerical signals and textual data at the same time. The total case index consists of two sub-parts corresponding to signal and textual data respectively. For matching of cases on the signal aspect we present a fuzzy similarity matching metric to accommodate and tackle the imprecision and uncertainty in sensor measurements. Preliminary evaluations have revealed that this fuzzy matching algorithm leads to more accurate similarity estimates for improved case ranking and retrieval compared with traditional distance-based matching criteria. For evaluation of similarity on the textual dimension we propose an enhanced cosine matching function augmented with related domain knowledge. This is implemented by incorporating Wordnet and domain specific ontology into the textual case-based reasoning process for refining weights of terms according to available knowledge encoded therein. Such knowledge-based reasoning for matching of textual cases has empirically shown its merit in improving both precision and recall of retrieved cases with our initial medical databases. Experts in the domain are very positive to our system and they deem that it will be a valuable tool to foster widespread experience reuse and transfer in the area of stress diagnosis and treatment.

  • 130.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering.
    Intelligent Stress Management System2009In: Medicinteknikdagarna 2009, 2009Conference paper (Refereed)
    Abstract [en]

    Today, in our daily life we are subjected to a wide range of pressures. When the pressures exceed the extent that we are able to deal with then stress is trigged. High level of stress may cause serious health problems i.e. it reduces awareness of bodily symptoms. So, people may first notice it weeks or months later meanwhile the stress could cause more serious effect in the body and health. A difficult issue in stress management is to use biomedical sensor signals in the diagnosis and treatment of stress. This paper presents a case-based system that assists a clinician in diagnosis and treatment of stress. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques such as textual information retrieval, rule-based reasoning (RBR), and fuzzy logic have been combined together with case-based reasoning to enable more reliable and efficient diagnosis and treatment of stress. The performance has been validated implementing a research prototype and close collaboration with experts.

  • 131.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Islam, Mohd. Siblee
    Mälardalen University, School of Innovation, Design and Engineering.
    Heart Rate and Inter-beat Interval Computation to Diagnose Stress2010Report (Other academic)
    Abstract [en]

    Problem in diagnosing of stress is an important issue. The variations in beat-to-beat alteration in the heart rate (HR) can provide an identification of stress. HR can be determined from the Electrocardiogram (ECG) signal. However, accurate detection of HR and inter-beat interval (IBI) values from the ECG waveform is important. This report presents a way of measuring the ECG signal together with the ECG component analysis such as QRS peak detection and HR calculation to use it in a computer-based stress diagnosis system.

  • 132.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kerstis, Birgitta
    Mälardalen University, School of Health, Care and Social Welfare, Health and Welfare.
    Petrovic, Nikola
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Sandborgh, Maria
    Mälardalen University, School of Health, Care and Social Welfare, Health and Welfare.
    Third Eye: An Intelligent Assisting Aid for Visual Impairment Elderly2016In: Medicinteknikdagarna 2016 MTF, 2016Conference paper (Refereed)
    Abstract [en]

    Background Visually impaired older persons need support in daily activities, e.g. moving around inside the house; making and eating food and taking medicine independently. A system that simulates the environment based on both dynamic and static objects, identify obstacles, navigates and translates sensory information in voice would be valuable to support their daily activities. Today several sensors and camera-based systems are popular as ambient-assisted living tools for older adults. However, intelligent assisting aid (IAA) to support older individuals with a recently acquired visual impairment is limited. The proposed system ‘Third Eye’ focuses on the advanced research and development of an IAA to support older individuals with a recently acquired visual impairment. The main goal in this system is to provide a usable, feasible and cost-effective solution for older persons to support their daily activities using intelligent sensor based system. Method The system consists of the following five phases to meet several central challenges in developing IAA in such domain. • User-perspective, focuses on user-driven technical development, investigating needs of potential users. The study will have a participatory design with focus group interviews of lead users. • Sensor-based system, focuses on the identification obstacles based on ultrasounds and/or radio frequencies embedded in white-cane or weaker. • Camera-based system, focuses on image based information translation into voice embedded in white-cane or weaker or glasses. • System of systems, focuses on integration of above systems where knowledge is engineered and suitable representations are learned and reasoning for decisions are made [9]. • Experimental, focuses on usability and feasibility of the IAA, with idiographic and group studies Results The initial results have shown the necessity of the proposed AAI systems for older individuals with a recently acquired visual impairment. However, more extension work e.g., process and analyze the information and synthesize it with existing literature for developing the system is ongoing.

  • 133.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Olsson, Erik
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Case-Based Reasoning for Medical and Industrial Decision Support Systems2010In: Successful Case-based Reasoning Applications, Springer, 2010, p. 7-52Chapter in book (Other academic)
    Abstract [en]

    The amount of medical and industrial experience and knowledge is rapidly growing and it is almost impossible to be up to date with everything. The demand of decision support system (DSS) is especially important in domains where experience and knowledge grow rapidly. However, traditional approaches to DSS are not always easy to adapt to a flow of new experience and knowledge and may also show a limitation in areas with a weak domain theory. This chapter explores the functionalities of Case-Based Reasoning (CBR) to facilitate experience reuse both in clinical and in industrial decision making tasks. Examples from the field of stress medicine and condition monitoring in industrial robots are presented here to demonstrate that the same approach assists both for clinical applications as well as for decision support for engineers. In the both domains, DSS deals with sensor signal data and integrate other artificial intelligence techniques into the CBR system to enhance the performance in a number of different aspects. Textual information retrieval, Rule-based Reasoning (RBR), and fuzzy logic are combined together with CBR to offer decision support to clinicians for a more reliable and efficient management of stress. Agent technology and wavelet transformations are applied with CBR to diagnose audible faults on industrial robots and to package such a system. The performance of the CBR systems have been validated and have shown to be useful in solving such problems in both of these domains.

  • 134.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, ShahinaMälardalen University, School of Innovation, Design and Engineering, Embedded Systems.Raad, WasimKing Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
    Internet of Things Technologies for HealthCare: Third International Conference, HealthyIoT 2016, Västerås, Sweden, October 18-19, 2016, Revised Selected Papers2016Conference proceedings (editor) (Other academic)
    Abstract [en]

    This book constitutes the proceedings of the Third International Conference on Internet of Things (IoT) Technologies for HealthCare, HealthyIoT 2016, held in Västerås, Sweden, October 18-19, 2016. The conference also included the First Workshop on Emerging eHealth through Internet of Things (EHIoT 2016). IoT as a set of existing and emerging technologies, notions and services provides many solutions to delivery of electronic healthcare, patient care, and medical data management. The 31 revised full papers presented along with 9 short papers were carefully reviewed and selected from 43 submissions in total. The papers cover topics such as healthcare support for the elderly, real-time monitoring systems, security, safety and communication, smart homes and smart caring environments, intelligent data processing and predictive algorithms in e-Health, emerging eHealth IoT applications, signal processing and analysis, and smartphones as a healthy thing.

  • 135.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Causevic, Aida
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    An Overview on the Internet of Things for Health Monitoring Systems2015In: 2nd EAI International Conference on IoT Technologies for HealthCare HealthyIoT2015, 2015Conference paper (Refereed)
    Abstract [en]

    The aging population and the increasing healthcare cost in hospitals are spurring the advent of remote health monitoring systems. Advances in physiological sensing devices and the emergence of reliable low-power wireless network technologies have enabled the design of remote health monitoring systems. The next generation Internet, commonly referred to as Internet of Things (IoT), depicts a world populated by devices that are able to sense, process and react via the Internet. Thus, we envision health monitoring systems that support Internet connection and use this connectivity to enable better and more reliable services. This paper presents an overview on existing health monitoring systems, considering the IoT vision. We focus on recent trends and the development of health monitoring systems in terms of: (1) health parameters, (2) frameworks, (3) wireless communication, and (4) security issues. We also identify the main limitations, requirements and advantages within these systems.

  • 136.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Generic System-level Framework for Self-Serve Health Monitoring System through Internet of Things(IoT)2015In: Studies in Health Technology and Informatics, Volume 211: Proceedings of the 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 2–4 June 2015, Västerås, Sweden, 2015, Vol. 211, p. 305-307Conference paper (Refereed)
    Abstract [en]

    Sensor data are traveling from sensors to a remote server, data is analysed remotely in a distributed manner, and health status of a user is presented in real-time. This paper presents a generic system-level framework for a self-served health monitoring system through the Internet of Things (IoT) to facilities an efficient sensor data management.

  • 137.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Köckemann, Uwe
    Örebro University, Sweden.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomasic, Ivan
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tsiftes, Nicolas
    RISE SICS, Stockholm, Sweden.
    Voigt, Thiemo
    RISE SICS, Stockholm, Sweden.
    Run-Time Assurance for the E-care@home System2018In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, p. 107-110Conference paper (Refereed)
    Abstract [en]

    This paper presents the design and implementation of the software for a run-time assurance infrastructure in the E-care@home system. An experimental evaluation is conducted to verify that the run-time assurance infrastructure is functioning correctly, and to enable detecting performance degradation in experimental IoT network deployments within the context of E-care@home.

  • 138.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    A Case-Based Retrieval System for Post-Operative Pain Treatment2011In: / [ed] Petra Perner and Georg Rub, Germany: IBaI , 2011, p. 30-41Conference paper (Refereed)
    Abstract [en]

    This paper presents a clinical decision support system based on case-basedretrieval approach to assist physicians in post-operative pain treatment. Here,the cases are formulated by combining regular features and features using anumerical visual analogue scale (NVAS) through a questionnaire. Featureabstraction is done both in problem and outcome description of a case in order toreduce the number of attributes. The system retrieves most similar cases with theiroutcomes. The outcome of each case brings benefits for physicians since it presentsboth severity and fast recovery by the applied treatment in post-operative patients.Therefore, we have introduced a two-layer case structure i.e., solution is the firstlayer and outcome is the second layer that better suits this medical application. Inthe system, the solution presents the treatment and the outcome contains recoveryinformation of a patient, something physicians are interested in, especially the riskof side effects and complications.

  • 139.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    A Computer Aided System for Post-operative Pain Treatment Combining Knowledge Discovery and Case-Based Reasoning2012In: Lecture Notes in Computer Science, vol. 7466, Springer, 2012, p. 3-16Chapter in book (Refereed)
    Abstract [en]

    The quality improvement for individual postoperative-pain treatment is an important issue. This paper presents a computer aided system for physicians in their decision making tasks in post-operative pain treatment. Here, the system combines a Case-Based Reasoning (CBR) approach with knowledge discovery. Knowledge discovery is applied in terms of clustering in order to identify the unusual cases. We applied a two layered case structure for case solutions i.e. the treatment is in the first layer and outcome after treatment (i.e. recovery of the patient) is in the second layer. Moreover, a 2nd order retrieval approach is applied in the CBR retrieval step in order to retrieve the most similar cases. The system enables physicians to make more informed decisions since they are able to explore similar both regular and rare cases of post-operative patients. The two layered case structure is moving the focus from diagnosis to outcome i.e. the recovery of the patient, something a physician is especially interested in, including the risk of complications and side effects.

  • 140.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Mining Rare Cases in Post-Operative Pain by Means of Outlier Detection2011In: IEEE Symposium on Signal Processing and Information Technology (ISSPIT) 2011, IEEE , 2011, p. 35-41Conference paper (Refereed)
    Abstract [en]

    Rare cases are often interesting for health professionals, physicians, researchers and clinicians in order to reuse and disseminate experiences in healthcare. However, mining, i.e. identification of rare cases in electronic patient records, is non-trivial for information technology. This paper investigates a number of well-known clustering algorithms and finally applies a 2 nd order clustering approach by combining the Fuzzy C-means algorithm with the Hierarchical one. The approach was used to identify rare cases from 1572 patient cases in the domain of post-operative pain treatment. The results show that the approach enables the identification of rare cases in the domain of post-operative pain treatment and 18% of cases were identified as rare

  • 141.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Mining Rare Cases in Post-Operative Pain by Means of Outlier Detection2011Manuscript (preprint) (Other academic)
    Abstract [en]

    Rare cases are often interesting for healthprofessionals, physicians, researchers and clinicians in order toreuse and disseminate experiences in healthcare. However,mining, i.e. identification of rare cases in electronic patientrecords, is non-trivial for information technology. This paperinvestigates a number of well-known clustering algorithms andfinally applies a 2nd order clustering approach by combining theFuzzy C-means algorithm with the Hierarchical one. Theapproach is used in order to identify rare cases from 1572patient cases in the domain of post-operative pain management.The results show that the approach enables identification of rarecases in the domain of post-operative pain management and 18%of cases are identified as rare case.

  • 142.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Healthcare Service at Home: An Intelligent Health Monitoring System for Elderly2015In: Medicinteknikdagarna 2015 MFT 2015, 2015Conference paper (Refereed)
    Abstract [en]

    This paper presents an intelligent healthcare service to support active ageing by assisting seniors to participate in regular monitoring of elderly’s health condition. The proposed system is applicable to use in home environment and offers a self-service approach to monitor elderly’s health condition. According to the evaluation, the proposed system shows its necessity, competence and usefulness.

  • 143.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Multi-parameter Sensing Platform in ESS-H and E-care@home2017In: Joint conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) EMBEC & NBC’17, 2017Conference paper (Refereed)
    Abstract [en]

    Considering the population of ageing, health monitoring of elderly at home have the possibility for a person to keep track on his/her health status, e.g. decreased mobility in a personal environment. This also shows the potential of real-time decision support, early detection of symptoms, following of health trends and context awareness [1]. The ongoing projects Embedded Sensor for Health (ESS-H)1 and E-care@home2 are focusing on health monitoring of elderly at home. This paper presents the implementation of multi-parameter sensing on an Android platform. The objectives are, both to follow health trends and to enabling real time monitoring.

  • 144.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rahman, Hamidur
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Quality index analysis on camera- A sed R-eak identification considering movements and light illumination2018In: Studies in Health Technology and Informatics, vol 249, IOS Press , 2018, p. 84-92Conference paper (Refereed)
    Abstract [en]

    This paper presents a quality index (QI) analysis on R-peak extracted by a camera system considering movements and light illumination. Here, the proposed camera system is compared with a reference system named Shimmer PPG sensor. The study considers five test subjects with a 15 minutes measurement protocol, where the protocol consists of several conditions. The conditions are: Normal sittings, head movements i.e., up/down/left/right/forward/backword, with light on/off and with moving flash on/off. A percentage of corrected R-peaks are calculated based on time difference in milliseconds (MS) between the R-peaks extracted both from camera-based and sensor-based systems. A comparison results between normal, movements, and lighting condition is presented as individual and group wise. Furthermore, the comparison is extended considering gender and origin of the subjects. According to the results, more than 90% R-peaks are correctly identified by the camera system with ±200 MS time differences, however, it decreases with while there is no light than when it is on. At the same time, the camera system shows more 95% accuracy for European than Asian men. 

  • 145.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rahman, Hamidur
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Quality Index Analysis on Camera-based R-peak Identification Considering Movements and Light Illumination2018In: 15th International Conference on Wearable, Micro & Nano technologies for Personalized Health pHealth2018, 2018Conference paper (Refereed)
    Abstract [en]

    This paper presents a quality index (QI) analysis on R-peak extracted by a camera system considering movements and light illumination. Here, the proposed camera system is compared with a reference system named Shimmer PPG sensor. The study considers five test subjects with a 15 minutes measurement protocol, where the protocol consists of several conditions. The conditions are: normal sittings, head movements i.e., up/down/left/right/forward/backword, with light on/off and with moving flash on/off. A percentage of corrected R-peaks are calculated based on time difference in milliseconds (MS) between the R-peaks extracted both from camera-based and sensor-based systems. A comparison results between normal, movements, and lighting condition is presented as individual and group wise. Furthermore, the comparison is extended considering gender and origin of the subjects. According to the results, more than 90% R-peaks are correctly identified by the camera system with ?200 MS time differences, however, it decreases with while there is no light than when it is on. At the same time, the camera system shows more 95% accuracy for European than Asian men.

  • 146.
    Ahrén, Christina
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nyblad, Ida
    Mälardalen University, School of Innovation, Design and Engineering.
    Investigating DRAM bank partitioning2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    We have investigated the page coloring technique bank partitioning and if it can be applied on commercial hardware platforms to reduce execution time jitter for specific tasks. We have also investigated how to alter execution times using bank partitioning. Unpredictable latency created by execution time jitter is a problem in real-time computing on commercial hardware platforms. We have run experiments that try to prove that the bank partitioning method we use alters the execution time and that thrashing occurs in the main memory if we run multiple instances of a workload. We receive significant changes in execution times when using bank partitioning and we can determine that thrashing occurs. However, due to the lack of the ability to measure the hardware performance counter for row buffer misses, we cannot determine if thrashing occurs in the main memory level. Since we cannot determine when, or if thrashing occurs in the main memory we find that we cannot reduce execution time jitter on the two systems that we have tested using bank partitioning on. We also find that execution times of specific tasks can be altered by reducing the number of bank bins associated with the specific task. The execution time of the task is increased if we reduce the number of bins associated with it.

  • 147.
    Ahvenlampi Svensson, Amanda
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Exploring challenges in a verification process - when adapting production processes to new environmental requirements2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The requirements on the products and production processes within the manufacturing industry are continuously increasing according to environmental standards. The new requirements are coming from a growing awareness of what our planet can provide for example by the global challenge of climate change. The industry needs to reduce energy consumption and waste to meet the upcoming requirements.

    One of the processes with high environmental impact in a discrete manufacturing industry is the paint shop. Surface treatment is also of great importance to maintain a high quality product. In scientific literature, technological risk is one of the barriers in implementing environmental conscious manufacturing. Therefore the area of sustainable operations management needs building bridges with other functions and disciplines such as economics, strategies and behavioral sciences in order to manage the transitions. The supply of competence around paint shops today is usually provided by suppliers and other sources within the industry and to make the collaboration to work is essential. In this process of collaboration with external sources, substantial measurements are required to maintain the desirable quality. In order to ensure the competence of testing the quality eventuate when switching technology at a pre-treatment line, this report sets out to explore what the challenges to be taken into consideration are when to assure the product- and- process quality. To respond to this question, a multiple case study is conducted during spring 2016 where the phenomenon to study is the change process and the unit of analysis is the challenges that can be faced during the verification process. The case studied is automotive companies located in Sweden which are producing components for heavy duty vehicles. Data collection is performed by studying documents, participatory observations and semi-structured interviews. The results will give insights to academia on what challenges that are occurring during the verification process of implementing new and cleaner technologies. The conclusions are drawn upon the literature and the empirical results. The managerial implications are to increase the awareness of any potential barriers in the verification process in order to be prepared for managing the technological change process.

  • 148.
    Aisa, J.
    et al.
    Universidad de Zaragoza, Zaragoza, Spain .
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Villarroel, J. L.
    Universidad de Zaragoza, Zaragoza, Spain .
    Almeida, L.
    University of Porto, Porto, Portugal.
    Soft real-time traffic communication in loaded Wireless Mesh Networks2016In: IEEE International Workshop on Factory Communication Systems - Proceedings, WFCS, 2016, article id Article number 7496503Conference paper (Refereed)
    Abstract [en]

    Industrial applications have been shifting towards wireless multi-hop networks in recent years due to their lower cost of deployment and reconfiguration compared with their wired counterparts. These wireless networks usually must support real-time communication to meet the application requirements. For this reason, Wireless Mesh Networks (WMNs) are potential candidates for industrial applications as they support a fixed infrastructure of static nodes for relaying packets. To meet the application demands, we modify the wireless chain network protocol (WICKPro) to support soft real-time traffic in WMNs with chain topologies over IEEE 802.11. We employ tele-operation of mobile robots as our case study, and perform extensive simulation and laboratory experiments. We show that the data delivery ratio is increased up to 42% in a scenario with 7 nodes, when the maximum end-to-end delay tolerated by the application is doubled. This is particularly suited to soft real-time applications that can trade longer delays by higher reliability. Moreover, when compared with a distributed priority-based token-passing protocol (RT-WMP), the lower overhead of WICKPro allows, in an error-free scenario, obtaining a throughput improvement of 33.42% on average.

  • 149.
    Aisa, Jesus
    et al.
    Universidad de Zaragoza, Zaragoza, Spain.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Almeida, Luis
    University of Porto, Portugal.
    Villarroel, José Luis
    Universidad de Zaragoza, Zaragoza, Spain.
    DoTHa - A Double-threshold Hand-off Algorithm for Managing Mobility in Wireless Mesh Networks2016In: 21st IEEE Conference on Emerging Technologies and Factory Automation ETFA'16, 2016, article id 7733511Conference paper (Refereed)
    Abstract [en]

    Wireless communication will play an increasingly important role in future factory automation and process control, where the presence of mobile autonomous devices is expected to grow. However, wireless links are prone to errors due to shadowing and multi-path fading, which is even more severe in dynamic environments. These problems can be attenuated by using a mesh backbone to which mobile node connect to, using a hand-off algorithm. This solution is particularly important under real-time requirements typically found in factory automation. In this paper, we devise the Double-Threshold Hand-off (DoTHa) algorithm, a novel hand-off mechanism that triggers a hand-off in various environmental conditions. As a case study, we carry out the tele-operation of a mobile robot through a wireless mesh network in an indoor setting, using a wireless chain network protocol (WICKPro-SRT) that supports soft real-time traffic. We empirically compared DoTHa with two existing hand-off algorithms based on single and double hysteresis margin. The results revealed that DoTHa achieves Data Delivery Ratio (DDR) close to 100% whereas the single hysteresis-based hand-off suffers from frequent disconnections, dropping DDR to 88%. The double hysteresis-based hand-off shows higher ping-pong effect than DoTHa, doubling the number of hand-offs in some scenarios.

  • 150.
    Akan, Batu
    Mälardalen University, School of Innovation, Design and Engineering.
    Human Robot Interaction Solutions for Intuitive Industrial Robot Programming2012Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Over the past few decades the use of industrial robots has increased the efficiency as well as competitiveness of many companies. Despite this fact, in many cases, robot automation investments are considered to be technically challenging. In addition, for most small and medium sized enterprises (SME) this process is associated with high costs. Due to their continuously changing product lines, reprogramming costs are likely to exceed installation costs by a large margin. Furthermore, traditional programming methods for industrial robots are too complex for an inexperienced robot programmer, thus assistance from a robot programming expert is often needed.  We hypothesize that in order to make industrial robots more common within the SME sector, the robots should be reprogrammable by technicians or manufacturing engineers rather than robot programming experts. In this thesis we propose a high-level natural language framework for interacting with industrial robots through an instructional programming environment for the user.  The ultimate goal of this thesis is to bring robot programming to a stage where it is as easy as working together with a colleague.In this thesis we mainly address two issues. The first issue is to make interaction with a robot easier and more natural through a multimodal framework. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high level commands. Interaction with simple voice commands and gestures enables the manufacturing engineer to focus on the task itself, rather than programming issues of the robot. This approach shifts the focus of industrial robot programming from the coordinate based programming paradigm, which currently dominates the field, to an object based programming scheme.The second issue addressed is a general framework for implementing multimodal interfaces. There have been numerous efforts to implement multimodal interfaces for computers and robots, but there is no general standard framework for developing them. The general framework proposed in this thesis is designed to perform natural language understanding, multimodal integration and semantic analysis with an incremental pipeline and includes a novel multimodal grammar language, which is used for multimodal presentation and semantic meaning generation.

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