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  • 1.
    Eneling, Martin
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Wickström, M
    Linköping University, Department of Biomedical Engineering.
    Johansson, Anders
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Vätternrundan.  Fjärr-registrering av fysiologiska parametrar under idrottsutövning.2006Conference paper (Other academic)
  • 2.
    Jönsson, Björn
    et al.
    Linköping University, Department of Medicine and Care, Vascular surgery. Linköping University, Department of Medicine and Care, Anaesthesiology. Linköping University, Faculty of Health Sciences.
    Laurent, Claes
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Eneling, Martin
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Skau, Tommy
    Linköping University, Department of Medicine and Care, Vascular surgery. Linköping University, Faculty of Health Sciences.
    Lindberg, Lars-Göran
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Automatic ankle pressure measurements using PPG in ankle-brachial pressure index determination2005In: European Journal of Vascular and Endovascular Surgery, ISSN 1078-5884, E-ISSN 1532-2165, Vol. 30, no 4, p. 395-401Article in journal (Refereed)
    Abstract [en]

    Objective

    To evaluate a new technique using a photoplethysmographic (PPG) probe for automatic ankle pressure measurements.

    Design

    Comparative study on two techniques for ankle pressure measurement.

    Setting

    University hospital.

    Material

    Thirty-five patients with leg arterial disease and eight healthy volunteers. Ankle-brachial indices (ABPI) were measured using conventional CW Doppler technique and PPG-based prototype equipment for the ankle pressure recordings.

    Chief outcome measures

    ABPIs calculated from CW Doppler and PPG ankle pressure measurements. The PPG signals were analysed both by visual judgement and by a software based, automatic algorithm.

    Main results

    The mean difference between ABPIs calculated from CW Doppler recordings and PPG (visual analysis) was −0.01 (limits of agreement (±two standard deviations) +0.16 to −0.19). The correlation coefficient was 0.93. When the algorithm was used, the mean difference (CW Doppler−PPG) was 0.05 (limits of agreement 0.28 to −0.18, r=0.89).

    Conclusions

    The PPG method is a promising technique with an inherent potential for automatisation of the ankle pressure measurements, thereby reducing the observer-dependency in ABPI recordings.

  • 3.
    Laurent, Claes
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Jönsson, Björn
    Linköping University, Department of Medicine and Care, Vascular surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery. Linköping University, Faculty of Health Sciences.
    Vegfors, Magnus
    Linköping University, Department of Medicine and Care, Anaesthesiology. Linköping University, Faculty of Health Sciences.
    Eneling, Martin
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Lindberg, Lars-Göran
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Noninvasive monitoring of systolic blood pressure on the arm utilizing photoplethysmography (PPG): clinical report2004In: Proc. SPIE 5318, Advanced Biomedical and Clinical Diagnostic Systems II / [ed] Gerald E. Cohn; Warren S. Grundfest; David A. Benaron; Tuan Vo-Dinh, Bellingham WA, USA: SPIE , 2004, p. 99-Conference paper (Refereed)
    Abstract [en]

    A soft (silicone) probe, containing six light emitting diodes (880 nm) and three photo detectors, utilizes photoplethysmography (PPG) to monitor pulsations from the brachialis artery under an occluding cuff during deflation. When the arterial pulse returns, measured by PPG, the corresponding pressure in the cuff is determined. This pressure is assumed to equal the systolic pressure. An assessment trial was performed on 21 patients (9 women and 12 men, aged 27-69) at the Neuro-Intensive care unit. Since the patients were already provided with arterial needles, invasive blood pressure could be used as the reference. By choosing a threshold, for detecting pulses, as a fraction (4%) of the maximum amplitude, the systolic blood pressure was underestimated (-0.57 mmHg, SD 12.1). The range of systolic pressure for the patients was 95.5 - 199.0 mmHg, n=14. The method is promising, but improvements still have to be made in order to improve the technique.

  • 4.
    Nyström, Mikael
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Eneling, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Petersson, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Introduction to openEHR basic principles2008Conference paper (Refereed)
  • 5.
    Rattfält, Linda
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology. Biomedical Engineering, Örebro County Council, Örebro, Sweden.
    Ahlström, Christer
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology. Biomedical Engineering, Örebro County Council, Örebro, Sweden.
    Eneling, Martin
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Ragnemalm, Bengt
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements. Biomedical Engineering, Örebro County Council, Örebro, Sweden.
    Lindén, M.
    Intelligent Sensor Systems, Mälardalen University, Västerås, Sweden.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology. Biomedical Engineering, Örebro County Council, Örebro, Sweden.
    A platform for physiological signals including an intelligent stethoscope2009In: 4th European Conference of the International Federation for Medical and Biological Engineering: ECIFMBE 2008 23–27 November 2008 Antwerp, Belgium / [ed] Jos Sloten, Pascal Verdonck, Marc Nyssen, Jens Haueisen, Springer Berlin/Heidelberg, 2009, Vol. 22, p. 1038-1041Chapter in book (Refereed)
    Abstract [en]

    We have developed a physiological signal platform where presently phonocardiographic (PCG) and electrocardiographic (ECG) signals can be acquired and on which our signal analysis techniques can be implemented. The platform can also be used to store patient data, to enable comparison over time and invoke distance consultation if necessary. Our studies so far indicate that with our signal analysis techniques of heart sounds we are able to separate normal subject from those with aortic stenosis and mitral insufficiency. Further we are able to identify the third heart sound. The platform is being tested in a primary health care setting.

  • 6.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Eneling, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Chen, Rong
    Cambio Healthcare Systems.
    Örman, Håkan
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Applying representational state transfer (REST) architecture to archetype-based electronic health record systems2013In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 13, no 57Article in journal (Refereed)
    Abstract [en]

    Background

    The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content.

    The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored.

    Results

    The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored.

    A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping.

    Conclusions

    Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications.

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