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  • 1.
    Andersson, Matilda
    Halmstad University, School of Business, Engineering and Science.
    Analysis of Changes in Running Technique Between a Shod and Barefoot Running Condition.2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Background: Lately, barefoot running has become popular and there is a debate on the pros and cons of barefoot running with regards to running injuries. Many factors are causing injuries and one of the factors discussed is the fact that we run in shoes. When we run in shoes the biomechanics of the running technique may and therefore be a possible cause to injury. Aim: The aim of the study was to assess how the foot strike pattern, angle of the knee and ankle joint at time of initial contact, as well as the step length changes between a shod and barefoot running condition in habitually shod runners when running in a pace equivalent to their running pace over ten kilometers. Method: Twenty-seven healthy runners (18 male, 9 female) were included in the study. The study took place at the fitness center of Halmstad University. Subjects ran on a treadmill, in an individual pace equivalent to their running pace over ten km, both in a shod and barefoot running condition. Two-dimensional analysis of the sagittal plane kinematics of the knee joint, ankle joint and foot position to horizontal, foot strike pattern and step length was done. Participants ran for ten minutes with shoes and for five minutes barefoot. Running technique was videotaped using an Iphone 6 camera and landmarks were marked with white tape to ease the analysis. Results: Changes in foot strike pattern was observed. When running barefoot 63% of the subjects adopted a non-heel strike pattern compared to 18.5% when shod (p=0.001). Knee flexion was increased at IC for the barefoot condition, with 164°±6 relative knee angle compared to 167°±6 when shod (p=0.001). Ankle angle at IC did not show a statistical significant difference between conditions (p=0.657). When barefoot the angle was 117°±8 compared to 115°±8 when shod. Foot angle to horizontal showed a flatter foot placement at IC with a less dorsiflexed foot for the barefoot condition (-4°±8) compared to shod (-12°±8), (p=0.001). Step length was decreased for the barefoot condition (0.82m ±0.15)   compared to shod (0.85m ±0.13), (p=0.008). Conclusion: Results are consistent with previous findings that barefoot running in some cases change the running technique with a flatter foot placement, an increased knee flexion at IC and a decreased step length. However, caution must be taken when habitually shod runners transition to barefoot running in regards to the biomechanical changes that may occur. To benefit from barefoot running a non-heel strike pattern is required. Further, the running technique may be the more important factor, regardless of wearing shoes or not.

  • 2.
    Ashfaq, Awais
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Halland Hospital, Region Halland, Halmstad, Sweden.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Machine learning in healthcare - a system’s perspective2019In: Proceedings of the ACM SIGKDD Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK) / [ed] B. Aditya Prakash, Anil Vullikanti, Shweta Bansal, Adam Sadelik, Arlington, 2019, p. 14-17Conference paper (Refereed)
    Abstract [en]

    A consequence of the fragmented and siloed healthcare landscape is that patient care (and data) is split along multitude of different facilities and computer systems and enabling interoperability between these systems is hard. The lack interoperability not only hinders continuity of care and burdens providers, but also hinders effective application of Machine Learning (ML) algorithms. Thus, most current ML algorithms, designed to understand patient care and facilitate clinical decision-support, are trained on limited datasets. This approach is analogous to the Newtonian paradigm of Reductionism in which a system is broken down into elementary components and a description of the whole is formed by understanding those components individually. A key limitation of the reductionist approach is that it ignores the component-component interactions and dynamics within the system which are often of prime significance in understanding the overall behaviour of complex adaptive systems (CAS). Healthcare is a CAS.

    Though the application of ML on health data have shown incremental improvements for clinical decision support, ML has a much a broader potential to restructure care delivery as a whole and maximize care value. However, this ML potential remains largely untapped: primarily due to functional limitations of Electronic Health Records (EHR) and the inability to see the healthcare system as a whole. This viewpoint (i) articulates the healthcare as a complex system which has a biological and an organizational perspective, (ii) motivates with examples, the need of a system's approach when addressing healthcare challenges via ML and, (iii) emphasizes to unleash EHR functionality - while duly respecting all ethical and legal concerns - to reap full benefits of ML.

  • 3.
    Ekelund, Gustaf
    et al.
    Halmstad University, School of Business, Engineering and Science.
    Andersson, Sebastian
    Halmstad University, School of Business, Engineering and Science.
    Jack The Gripper: Fixationsplatta för typ 3-frakturer på scapula2017Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Reverse Total Shoulder Arthroplasty (rTSA) is an increasingly common approach to treating different shoulder injuries. The rTSA results in increased force from m. deltoideus which originates from acromion. However, postoperative fractures on the scapula have occurred in some cases. These fractures are divided into 3 different types depending on where the fracture occurs. There is no recommended treatment for type 3 fractures. This project is a product development project with the purpose to find a solution to the fixation problem of type 3 fractures.To reach the project goal, the group has used well-known and proven product development methods, calculations, FEM analyzes and a model assembly analysis. The concept development was performed by interviewing orthopedics who have a lot of experience with rTSA and osteosynthesis related to these fractures. A prototype, which shows the features of the fixation plate, was made using 3D printers.The result of this project has provided a fixation plate that meets the groups requirements and has features that a modern fixation plate has today. In addition, two types of extra plates mounted on the fixation plate to the thin structure of spina scapula, was developed to counteract the axial force. The fixation plate shows excellent results on the FEM analyzes and assembly analysis performed on a scapula model. The prototype has also been given good testimonials from the orthopedics who participated in the project.

  • 4.
    Khandelwal, Siddhartha
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Gait Event Detection in the Real World2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Healthy gait requires a balance between various neuro-physiological systems and is considered an important indicator of a subject's physical and cognitive health status. As such, health-related applications would immensely benefit by performing long-term or continuous monitoring of subjects' gait in their natural environment and everyday lives. In contrast to stationary sensors such as motion capture systems and force plates, inertial sensors provide a good alternative for such gait analysis applications as they are miniature, cheap, mobile and can be easily integrated into wearable systems.

    This thesis focuses on improving overall gait analysis using inertial sensors by providing a methodology for detecting gait events in real-world settings. Although the experimental protocols for such analysis have been restricted to only highly-controlled lab-like indoor settings; this thesis presents a new gait database that consists of data from gait activities carried out in both, indoor and outdoor environments. The thesis shows how domain knowledge about gait could be formulated and utilized to develop methods that are robust and can tackle real-world challenges. It also shows how the proposed approach can be generalized to estimate gait events from multiple body locations. Another aspect of this thesis is to demonstrate that the traditionally used temporal error metrics are not enough for presenting the overall performance of gait event detection methods. The thesis introduces how non-parametric tests can be used to complement them and provide a better overview.

    The results of comparing the proposed methodology to state-of-the-art methods showed that the approach of incorporating domain knowledge into the time-frequency analysis of the signal was robust across different real-world scenarios and outperformed other methods, especially for the scenario involving variable gait speeds in outdoor settings. The methodology was also benchmarked on publicly available gait databases yielding good performance for estimating events from different body locations. To conclude, this thesis presents a road map for the development of gait analysis systems in real-world settings.

  • 5.
    Khandelwal, Siddhartha
    et al.
    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.
    Wickström, Nicholas
    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.
    Identification of Gait Events using Expert Knowledge and Continuous Wavelet Transform Analysis2014In: BIOSIGNALS 2014: Proceedings of the International Conference on Bio-inspired Systems and Signal Processing / [ed] Harald Loose, Guy Plantier, Tanja Schultz, Ana Fred & Hugo Gamboa, [S.l.]: SciTePress, 2014, p. 197-204Conference paper (Refereed)
    Abstract [en]

    Many gait analysis applications involve long-term or continuous monitoring which require gait measurements to be taken outdoors. Wearable inertial sensors like accelerometers have become popular for such applications as they are miniature, low-powered and inexpensive but with the drawback that they are prone to noise and require robust algorithms for precise identification of gait events. However, most gait event detection algorithms have been developed by simulating physical world environments inside controlled laboratories. In this paper, we propose a novel algorithm that robustly and efficiently identifies gait events from accelerometer signals collected during both, indoor and outdoor walking of healthy subjects. The proposed method makes adept use of prior knowledge of walking gait characteristics, referred to as expert knowledge, in conjunction with continuous wavelet transform analysis to detect gait events of heel strike and toe off. It was observed that in comparison to indoor, the outdoor walking acceleration signals were of poorer quality and highly corrupted with noise. The proposed algorithm presents an automated way to effectively analyze such noisy signals in order to identify gait events.

  • 6. Lavesson, Tilde
    Schysst Diabetes: Ett smart webbverktyg för diabetstekniska hjälpmedel.2016Independent thesis Basic level (degree of Bachelor), 180 HE creditsStudent thesis
  • 7.
    Norell Pejner, Margaretha
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Lundström, Jens
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Ourique de Morais, Wagner
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Laurell, Hélène
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL), Centre for International Marketing and Entrepreneurship Research (CIMER).
    Isaksson, Anna
    Halmstad University, School of Education, Humanities and Social Science, Centrum för lärande, kultur och samhälle (CLKS), Språk, kultur och samhälle.
    Stranne, Frida
    Halmstad University, School of Education, Humanities and Social Science, Centrum för lärande, kultur och samhälle (CLKS).
    Skärsäter, Ingela
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Smart medication organizer – one way to promote self-management and safety in drug administration in elderly people2017Conference paper (Refereed)
  • 8.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Eklund, Helene
    Center for Person-Centered Care, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Tranberg, Roy
    Department of Orthopedics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    A wearable gait analysis system using inertial sensors Part II: Evaluation in a clinical setting2012In: BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing, [S. l.]: SciTePress, 2012, p. 5-14Conference paper (Refereed)
    Abstract [en]

    The gold standard for gait analysis, in-lab 3D motion capture, is not routinely used for clinical assessment due to limitations in availability, cost and required training. Inexpensive alternatives to quantitative gait analysis are needed to increase the its adoption. Inertial sensors such as accelerometers and gyroscopes are promising tools for the development of wearable gait analysis (WGA) systems. The present study evaluates the use of a WGA system on hip-arthroplasty patients in a real clinical setting. The system provides information about gait symmetry and normality. Results show that the normality measurements are well correlated with various quantitative and qualitative measures of recovery and health status.

  • 9.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Zügner, Roland
    Department of Orthopedics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Tranberg, Roy
    Department of Orthopedics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    A wearable gait analysis system using inertial sensors Part I: Evaluation of measures of gait symmetry and normality against 3D kinematic data2012In: BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing, [S. l.]: SciTePress, 2012, p. 180-188Conference paper (Refereed)
    Abstract [en]

    Gait analysis (GA) is an important tool in the assessment of several physical and cognitive conditions. The lack of simple and economically viable quantitative GA systems has hindered the routine clinical use of GA in many areas. As a result, patients may be receiving sub-optimal treatment. The present study introduces and evaluates measures of gait symmetry and gait normality calculated from inertial sensor data. These indices support the creation of mobile, cheap and easy to use quantitative GA systems. The proposed method was compared to measures of symmetry and normality derived from 3D kinematic data. Results show that the proposed method is well correlated to the kinematic analysis in both symmetry (r=0.84, p<0.0001) and normality (r=0.81, p<0.0001). In addition, the proposed indices can be used to classify normal from abnormal gait.

  • 10.
    Teng, Xudong
    et al.
    Shanghai University of Engineering Science, Shanghai, China & Nanjing University, Nanjing, China.
    Fan, Yuantao
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Evaluation of Micro-flaws in Metallic Material Based on A Self-Organized Data-driven Approach2016In: 2016 IEEE International Conference on Prognostics and Health Management (ICPHM), IEEE conference proceedings, 2016Conference paper (Refereed)
    Abstract [en]

    Evaluating the health condition of a material that could potentially contain micro-flaws is a common and important application within the field of non-destructive testing. Examples of such micro-defects include dislocation, fatigue cracks or impurities and are often hard to detect. The ability to precisely measure their type, size and position is a prerequisite for estimating the remaining useful life of the component. One technique that was shown successful in the past is based on traditional ultrasonic testing methods. In most cases, inner micro-flaws induce slight changes of acoustic wave spectrum components. However, these changes are often difficult to detect directly, as they tend to exhibit features that are most naturally analyzed using statistical and probabilistic methods. In this paper we apply Consensus Self-Organizing Models (COSMO) method to detect micro-flaws in metallic material. This approach is essentially an unsupervised deviation detection method based on the concept of "wisdom of the crowd". This method is used to analyze the spectrum of acoustic waves received by the transducer attached on the surface of material being analyzed. We have modeled a steel board with micro-cracks and collected time-series of acoustic echo response, at different positions on material's surface. The experimental results show that the COSMO method is able to detect and locate micro-flaws. © 2016 IEEE

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