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  • 1.
    Aagerup, Ulf
    et al.
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Frank, Anna-Sofia
    Halmstad University, School of Business, Engineering and Science.
    Hultqvist, Evelina
    Halmstad University, School of Business, Engineering and Science.
    The persuasive effects of emotional green packaging claims2019In: British Food Journal, ISSN 0007-070X, E-ISSN 1758-4108, Vol. 121, no 12, p. 3233-3246Article in journal (Refereed)
    Abstract [en]

    Purpose - The purpose of this paper is to investigate the effects of rational green packaging claims vs emotional green packaging claims on consumers' purchase propensity for organic coffee.

    Design/methodology/approach - Three within-subjects experiment were carried out (N=87, N=245, N=60). The experimental design encompasses packaging with rational green claims, emotional green claims, as well as a neutral (control) claim. Measured variables are introduced to assess participants' environmental commitment and information processing ability. A manipulated between-subjects variable is introduced to test how distraction interacts with preference for the claims.

    Findings - Overall, consumers prefer products with green claims over those with neutral (control) claims, and products with emotional green claims to those with rational green claims. The studies also reveal that this effect is moderated by participants' environmental commitment, information processing ability and by distraction. The findings were statistically significant (p<0.05).

    Research limitations/implications - As a lab experiment, the study provides limited generalizability and external validity. Practical implications - For most organic FMCG products, it is advisable to employ emotional packaging claims.

    Social implications - The presented findings provide marketers with tools to influence consumer behavior toward sustainable choices.

    Originality/value - The paper validates previous contributions on the effects of product claim types, and extends them by introducing comprehensive empirical data on all the Elaboration Likelihood Model's criteria for rational decision-making; motivation, opportunity and ability.

  • 2.
    Aagerup, Ulf
    et al.
    Högskolan i Halmstad, Centrum för innovations-, entreprenörskaps- och lärandeforskning (CIEL).
    Frank, Anna-Sofia
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap.
    Hultqvist, Evelina
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap.
    The persuasive effects of emotional green packaging claims2019In: British Food Journal, ISSN 0007-070X, E-ISSN 1758-4108, Vol. 121, no 12, p. 3233-3246Article in journal (Refereed)
    Abstract [en]

    Purpose - The purpose of this paper is to investigate the effects of rational green packaging claims vs emotional green packaging claims on consumers' purchase propensity for organic coffee.

    Design/methodology/approach - Three within-subjects experiment were carried out (N=87, N=245, N=60). The experimental design encompasses packaging with rational green claims, emotional green claims, as well as a neutral (control) claim. Measured variables are introduced to assess participants' environmental commitment and information processing ability. A manipulated between-subjects variable is introduced to test how distraction interacts with preference for the claims.

    Findings - Overall, consumers prefer products with green claims over those with neutral (control) claims, and products with emotional green claims to those with rational green claims. The studies also reveal that this effect is moderated by participants' environmental commitment, information processing ability and by distraction. The findings were statistically significant (p<0.05).

    Research limitations/implications - As a lab experiment, the study provides limited generalizability and external validity. Practical implications - For most organic FMCG products, it is advisable to employ emotional packaging claims.

    Social implications - The presented findings provide marketers with tools to influence consumer behavior toward sustainable choices.

    Originality/value - The paper validates previous contributions on the effects of product claim types, and extends them by introducing comprehensive empirical data on all the Elaboration Likelihood Model's criteria for rational decision-making; motivation, opportunity and ability.

  • 3.
    Aare, Magnus
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Evaluation of head response to ballistic helmet impacts, using FEM2003Conference paper (Refereed)
  • 4.
    Aare, Magnus
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Proposed global injury thresholds for oblique helmet impacts2003Conference paper (Refereed)
  • 5.
    Abbaspour, Sara
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Surface EMG signal processing: Removing ECG interferences and classifying hand movements2017In: Medicinteknikdagarna 2017 MTD 2017, Västerås, Sweden, 2017Conference paper (Refereed)
  • 6.
    Abbaspour, Sara
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Electromyography signal analysis: Electrocardiogram artifact removal and classifying hand movements2018In: World Congress on Medical Physics and Biomedical Engineering IUPESM, 2018Conference paper (Refereed)
  • 7.
    Abdelakram, Hafid
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Abdullah, Saad
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kristoffersson, Annica
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Impact of Activities in Daily Living on Electrical Bioimpedance Measurements for Bladder Monitoring2023Conference paper (Refereed)
    Abstract [en]

    Accurate bladder monitoring is critical in the management of conditions such as urinary incontinence, voiding dysfunction, and spinal cord injuries. Electrical bioimpedance (EBI) has emerged as a cost-effective and non-invasive approach to monitoring bladder activity in daily life, with particular relevance to patient groups who require measurement of bladder urine volume (BUV) to prevent urinary leakage. However, the impact of activities in daily living (ADLs) on EBI measurements remains incompletely characterized. In this study, we investigated the impact of normal ADLs such as sitting, standing, and walking on EBI measurements using the MAX30009evkit system with four electrodes placed on the lower abdominal area. We developed an algorithm to identify artifacts caused by the different activities from the EBI signals. Our findings demonstrate that various physical activities clearly affected the EBI measurements, indicating the necessity of considering them during bladder monitoring with EBI technology performed during physical activity (or normal ADLs). We also observed that several specific activities could be distinguished based on their impedance values and waveform shapes. Thus, our results provide a better understanding of the impact of physical activity on EBI measurements and highlight the importance of considering such physical activities during EBI measurements in order to enhance the reliability and effectiveness of EBI technology for bladder monitoring.

  • 8.
    Abdelakram, Hafid
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Difallah, Sabrina
    Laboratory of Instrumentation, University of Sciences and Technology Houari Boumediene, 16111 Algiers, Algeria.
    Alves, Camille
    Assistive Technology Lab (NTA), Faculty of Electrical Engineering, Federal University of Uberlandia, Uberlandia 38408-100, Brazil.
    Abdullah, Saad
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kristoffersson, Annica
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    State of the Art of Non-Invasive Technologies for Bladder Monitoring: A Scoping Review2023In: Sensors, E-ISSN 1424-8220, Vol. 23, no 5, article id 2758Article, review/survey (Refereed)
    Abstract [en]

    Bladder monitoring, including urinary incontinence management and bladder urinary volume monitoring, is a vital part of urological care. Urinary incontinence is a common medical condition affecting the quality of life of more than 420 million people worldwide, and bladder urinary volume is an important indicator to evaluate the function and health of the bladder. Previous studies on non-invasive techniques for urinary incontinence management technology, bladder activity and bladder urine volume monitoring have been conducted. This scoping review outlines the prevalence of bladder monitoring with a focus on recent developments in smart incontinence care wearable devices and the latest technologies for non-invasive bladder urine volume monitoring using ultrasound, optical and electrical bioimpedance techniques. The results found are promising and their application will improve the well-being of the population suffering from neurogenic dysfunction of the bladder and the management of urinary incontinence. The latest research advances in bladder urinary volume monitoring and urinary incontinence management have significantly improved existing market products and solutions and will enable the development of more effective future solutions.

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  • 9.
    Abdelakram, Hafid
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kristoffersson, Annica
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Abdullah, Saad
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Edu-Mphy: A Low-Cost Multi-Physiological Recording System for Education and Research in Healthcare and Engineering2023In: Abstracts: Medicinteknikdagarna 2023, 2023, p. 117-117Conference paper (Other academic)
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  • 10.
    Abdi Yusuf Isse, Muna
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Identifying Patient Safety and The Healthcare Environment in Puntland, Somalia2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Independent on where in the world one is, patient safety is regarded as one of the most important aspects in the healthcare industry. On the contrary, depending on where you are, the patient safety will differ and is therefore location dependent. The patient safety in a developing country will therefore be evaluated in a different way compared to a developed country. This study, therefore aimed to identify the patient safety in Puntland, Somalia and with it, its healthcare environment in the hospitals. The goal was to identify the main factors that affected the patient safety.

    To investigate this, a field study to the region of interest was made and subsequently interviews with staff at the site were conducted as well as observations in the concerned hospitals. The obtained results were analysed using the method of Qualitative Content Analysis. At a later stage, the results could be thematized into four categories; “​Need​”, “​Device​”, “​Training​” and “​Knowledge​”, which pinpointed the main issues.

    The study show that there was a common transversal issue of a inherent lack of devices, training and knowledge which in turn could severely affect the patients and their safety in ways such as misdiagnosis, delayed treatment and in worst cases death. Furthermore, it was evident that rather than the lack of actual devices, the absence of knowledge was more prevalent. 

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  • 11.
    Abdollahi Sani, Negar
    et al.
    Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering.
    Mirbel, Deborah
    Univ Bordeaux, France.
    Fabiano, Simone
    Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering.
    Simon, Daniel
    Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering.
    Engquist, Isak
    Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering.
    Brochon, Cyril
    Univ Bordeaux, France.
    Cloutet, Eric
    Univ Bordeaux, France.
    Hadziioannou, Georges
    Univ Bordeaux, France.
    Berggren, Magnus
    Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering.
    A ferroelectric polymer introduces addressability in electrophoretic display cells2019In: FLEXIBLE AND PRINTED ELECTRONICS, ISSN 2058-8585, Vol. 4, no 3, article id 035004Article in journal (Refereed)
    Abstract [en]

    During the last decades, tremendous efforts have been carried out to develop flexible electronics for a vast array of applications. Among all different applications investigated in this area, flexible displays have gained significant attention, being a vital part of large-area devices, portable systems and electronic labels etc electrophoretic (EP) ink displays have outstanding properties such as a superior optical switch contrast and low power consumption, besides being compatible with flexible electronics. However, the EP ink technology requires an active matrix-addressing scheme to enable exclusive addressing of individual pixels. EP ink pixels cannot be incorporated in low cost and easily manufactured passive matrix circuits due to the lack of threshold voltage and nonlinearity, necessities to provide addressability. Here, we suggest a simple method to introduce nonlinearity and threshold voltage in EP ink display cells in order to make them passively addressable. Our method exploits the nonlinearity of an organic ferroelectric capacitor that introduces passive addressability in display cells. The organic ferroelectric material poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) is here chosen because of its simple manufacturing protocol and good polarizability. We demonstrate that a nonlinear EP cell with bistable states can be produced by depositing a P(VDF-TrFE) film on the bottom electrode of the display cell. The P(VDF-TrFE) capacitor and the EP ink cell are separately characterized in order to match the surface charge at their respective interfaces and to achieve and optimize bistable operation of display pixels.

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  • 12.
    Abdullah, Saad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Department of Biomedical Engineering, Riphah International University, Lahore, Pakistan.
    Abdelakram, Hafid
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kristoffersson, Annica
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bilal Saeed, Muhammad
    Biomedical Engineering Department, NED University of Engineering and Technology, Karachi, Pakistan..
    Saad, Samreen
    Department of Biochemistry, Karachi University, Karachi, Pakistan.
    Real-Time Portable Raspberry Pi-Based System for Sickle Cell Anemia Detection2023In: Abstracts: Medicinteknikdagarna 2023, 2023, p. 118-118Conference paper (Other academic)
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  • 13.
    Abdullah, Saad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Abdelakram, Hafid
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kristoffersson, Annica
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Machine Learning-Based Classification of Hypertension using CnD Features from Acceleration Photoplethysmography and Clinical Parameters2023In: Proceedings - IEEE Symposium on Computer-Based Medical Systems, Institute of Electrical and Electronics Engineers Inc. , 2023, p. 923-924Conference paper (Refereed)
    Abstract [en]

    Cardiovascular diseases (CVDs) are a leading cause of death worldwide, and hypertension is a major risk factor for acquiring CVDs. Early detection and treatment of hypertension can significantly reduce the risk of developing CVDs and related complications. In this study, a linear SVM machine learning model was used to classify subjects as normal or at different stages of hypertension. The features combined statistical parameters derived from the acceleration plethysmography waveforms and clinical parameters extracted from a publicly available dataset. The model achieved an overall accuracy of 87.50% on the validation dataset and 95.35% on the test dataset. The model's true positive rate and positive predictivity was high in all classes, indicating a high accuracy, and precision. This study represents the first attempt to classify cardiovascular conditions using a combination of acceleration photoplethysmogram (APG) features and clinical parameters The study demonstrates the potential of APG analysis as a valuable tool for early detection of hypertension.

  • 14.
    Abdullah, Saad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hafid, Abdelakram
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kristoffersson, Annica
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Novel Fiducial Point Extraction Algorithm to Detect C and D Points from the Acceleration Photoplethysmogram (CnD)2023In: Electronics, E-ISSN 2079-9292, Vol. 12, no 5, article id 1174Article in journal (Refereed)
    Abstract [en]

    The extraction of relevant features from the photoplethysmography signal for estimating certain physiological parameters is a challenging task. Various feature extraction methods have been proposed in the literature. In this study, we present a novel fiducial point extraction algorithm to detect c and d points from the acceleration photoplethysmogram (APG), namely “CnD”. The algorithm allows for the application of various pre-processing techniques, such as filtering, smoothing, and removing baseline drift; the possibility of calculating first, second, and third photoplethysmography derivatives; and the implementation of algorithms for detecting and highlighting APG fiducial points. An evaluation of the CnD indicated a high level of accuracy in the algorithm’s ability to identify fiducial points. Out of 438 APG fiducial c and d points, the algorithm accurately identified 434 points, resulting in an accuracy rate of 99%. This level of accuracy was consistent across all the test cases, with low error rates. These findings indicate that the algorithm has a high potential for use in practical applications as a reliable method for detecting fiducial points. Thereby, it provides a valuable new resource for researchers and healthcare professionals working in the analysis of photoplethysmography signals.

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  • 15.
    Abdullah, Saad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hafid, Abdelakram
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kristoffersson, Annica
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points2023In: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 11, article id 1199604Article in journal (Refereed)
    Abstract [en]

    Photoplethysmography is a non-invasive technique used for measuring several vital signs and for the identification of individuals with an increased disease risk. Its principle of work is based on detecting changes in blood volume in the microvasculature of the skin through the absorption of light. The extraction of relevant features from the photoplethysmography signal for estimating certain physiological parameters is a challenging task, where various feature extraction methods have been proposed in the literature. In this work, we present PPGFeat, a novel MATLAB toolbox supporting the analysis of raw photoplethysmography waveform data. PPGFeat allows for the application of various preprocessing techniques, such as filtering, smoothing, and removal of baseline drift; the calculation of photoplethysmography derivatives; and the implementation of algorithms for detecting and highlighting photoplethysmography fiducial points. PPGFeat includes a graphical user interface allowing users to perform various operations on photoplethysmography signals and to identify, and if required also adjust, the fiducial points. Evaluating the PPGFeat’s performance in identifying the fiducial points present in the publicly available PPG-BP dataset, resulted in an overall accuracy of 99% and 3038/3066 fiducial points were correctly identified. PPGFeat significantly reduces the risk of errors in identifying inaccurate fiducial points. Thereby, it is providing a valuable new resource for researchers for the analysis of photoplethysmography signals.

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  • 16.
    Abdullah, Saad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hafid, Abdelakram
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Shahid, H.
    Coventry University, Research Centre for Intelligent Healthcare, Coventry, United Kingdom.
    Comparing the Effectiveness of EMG and Electrical Impedance myography Measurements for Controlling Prosthetics2023In: IEEE Int. Multidiscip. Conf. Eng. Technol., IMCET, Institute of Electrical and Electronics Engineers Inc. , 2023, p. 189-193Conference paper (Refereed)
    Abstract [en]

    In recent years, the field of prosthetics has made significant progress towards creating prosthetic devices that are more functional, comfortable, and user-friendly. However, achieving intuitive control over prosthetic hand movements remains a significant challenge, especially for individuals with limb loss who rely on prosthetics for independent daily activities. To address this challenge, researchers have explored the potential of non-invasive techniques as electromyography (EMG) for prosthetic control. This paper aims to investigate the potential of using EMG and the electrical impedance myography (EIMG) techniques jointly for the measurement of hand movements. The study involved recording and comparing EMG and EIMG signals from a cohort of healthy individuals. These signals were captured during four distinct hand gestures: opening and closing the hand, as well as extending and flexing it, under varying time conditions, allowing for categorization into low and high-intensity movements. Data collection employed the Open BCI and ZRPI devices. The analysis of these signal waveforms revealed compelling results. Brachioradialis activity in EMG 2 exhibited an increase during open hand (0.015mV) and extension hand (0.009mV in low and 0.013mV in high intensity) gestures, accompanied by increased EIMG activity (56mV and 52mV respectively). Additionally, close hand (0.0018mV in low and 0.05mV in high intensity) and flexion hand (0.0075 in low intensity and 0.002 in high intensity) gestures exhibited heightened flexor carpi ulnaris activity with raised EIMG activity (57mV and 45mV respectively). These results proved to be consistent, acceptable, and aligned with existing literature. The findings of this paper indicate that both EMG and EIMG techniques could be used together to control custom-made hand prosthetics, demonstrating a significant development that could lead to more intuitive and easier-to-control prosthetics. Also, the results obtained could be valuable to researchers and engineers working in the prosthetics field, as it provides insights into the potential of non-invasive techniques for prosthetic control.

  • 17.
    Abdullah, Saad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kristoffersson, Annica
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Machine learning approaches for cardiovascular hypertension stage estimation using photoplethysmography and clinical features2023In: Frontiers in Cardiovascular Medicine, E-ISSN 2297-055X, Vol. 10, article id 1285066Article in journal (Refereed)
    Abstract [en]

    Cardiovascular diseases (CVDs) are a leading cause of death worldwide, with hypertension emerging as a significant risk factor. Early detection and treatment of hypertension can significantly reduce the risk of developing CVDs and related complications. This work proposes a novel approach employing features extracted from the acceleration photoplethysmography (APG) waveform, alongside clinical parameters, to estimate different stages of hypertension. The current study used a publicly available dataset and a novel feature extraction algorithm to extract APG waveform features. Three distinct supervised machine learning algorithms were employed in the classification task, namely: Decision Tree (DT), Linear Discriminant Analysis (LDA), and Linear Support Vector Machine (LSVM). Results indicate that the DT model achieved exceptional training accuracy of 100% during cross-validation and maintained a high accuracy of 96.87% on the test dataset. The LDA model demonstrated competitive performance, yielding 85.02% accuracy during cross-validation and 84.37% on the test dataset. Meanwhile, the LSVM model exhibited robust accuracy, achieving 88.77% during cross-validation and 93.75% on the test dataset. These findings underscore the potential of APG analysis as a valuable tool for clinicians in estimating hypertension stages, supporting the need for early detection and intervention. This investigation not only advances hypertension risk assessment but also advocates for enhanced cardiovascular healthcare outcomes.

  • 18.
    Abed, Ala
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    eValuate - A Sports Analytics mHealth App: Featuring the Perceived Load and Fitness Scale for Overtraining Prevention and Intervention2020Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Health and fitness apps have become ubiquitous as smart devices become a major necessity in day-to-day life. However, an obvious issue with mobile health (mHealth) apps is that a substantial portion of them lack a scientific foundation and instead utilize  experiential  stratagems.  Hence,  the  acquired  data  becomes  unreliable.  In sports, where data collection is extensive, this becomes a vital factor for success due to  the  increasing  usage  of  mHealth.  Therefore,  the  Swedish  School  of  Sport  and Health Sciences has, in collaboration with other organizations, created the Perceived Load  and  Fitness  Scale  Questionnaire.  The  purpose  of  this  questionnaire  is  to function as a marker for overtraining, and thus injury prevention and intervention will become a simpler and more efficient task. A computer software was developed for the questionnaire; however, a mobile version was required, and thus requested. Consequently, the mHealth prototype app eValuate was developed. Research, in the form of literature studies, and dissection of other apps, for additional information, contributed  to  the  development  of  it.  The  prototype  was  developed  using  the programming language Java with Android Studio as the Integrated Development Environment  and  Cloud  Firebase  Firestore  as  a  database  solution.  The  finished prototype, eValuate, had to be trialled to ensure that it satisfies the criteria. Thus, the Mobile Application Rating Scale was employed as the most appropriate means of evaluation. A small-scale study was planned to trial the prototype by utilizing this scale.  However,  due  to  unforeseen  events,  only  four  respondents  could  provide feedback. The prototype performed admirably and scored 3.8 stars out of 5 stars. Nonetheless, the testing sample is too small to draw any real conclusions. 

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  • 19.
    Abedan Kondori, Farid
    et al.
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Yousefi, Shahrouz
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Li, Haibo
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Sonning, Samuel
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Sonning, Sabina
    3D Head Pose Estimation Using the Kinect2011Conference paper (Refereed)
    Abstract [en]

    Head pose estimation plays an essential role for bridging the information gap between humans and computers. Conventional head pose estimation methods are mostly done in images captured by cameras. However accurate and robust pose estimation is often problematic. In this paper we present an algorithm for recovering the six degrees of freedom (DOF) of motion of a head from a sequence of range images taken by the Microsoft Kinectfor Xbox 360. The proposed algorithm utilizes a least-squares minimization of the difference between themeasured rate of change of depth at a point and the rate predicted by the depth rate constraint equation. We segment the human head from its surroundings and background, and then we estimate the head motion. Our system has the capability to recover the six DOF of the head motion of multiple people in one image. Theproposed system is evaluated in our lab and presents superior results.

  • 20.
    Abedan Kondori, Farid
    et al.
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Yousefi, Shahrouz
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Liu, Li
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Active human gesture capture for diagnosing and treating movement disorders2013Conference paper (Other academic)
    Abstract [en]

    Movement disorders prevent many people fromenjoying their daily lives. As with other diseases, diagnosisand analysis are key issues in treating such disorders.Computer vision-based motion capture systems are helpfultools for accomplishing this task. However Classical motiontracking systems suffer from several limitations. First theyare not cost effective. Second these systems cannot detectminute motions accurately. Finally they are spatially limitedto the lab environment where the system is installed. In thisproject, we propose an innovative solution to solve the abovementionedissues. Mounting the camera on human body, webuild a convenient, low cost motion capture system that canbe used by the patient in daily-life activities. We refer tothis system as active motion capture, which is not confinedto the lab environment. Real-time experiments in our labrevealed the robustness and accuracy of the system.

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    Active Human Gesture Capture for Diagnosing and Treating Movement Disorders
  • 21.
    Abou-Hamad, Eliana
    Luleå University of Technology, Department of Social Sciences, Technology and Arts.
    A design solution for prevention of pressure ulcers: A sensor driven bedding for hospital beds that detect pressure2021Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This report is about preventing pressure ulcers (bedsores). The master thesis was carried outby an Industrial Design Engineering master student at Luleå University of Technology, in thespring of 2021. Pressure ulcers are a difficult and troublesome problem that exists everywherein healthcare. They occur on people who lie or sit in the same position for a long time, wherethe weight of the body creates pressure on the surface. That contributes to reduced bloodflow in the skin and subcutaneous tissues, which leads to pressure ulcers.

    Interest in the work came after getting in touch with Per Söderberg, he described the projecthe used to work on and could not let go of, after retiring. The project was about healing andpreventing pressure ulcers through a bed cradle, CUNIDORM, that Per created. Per gotstuck with his idea due to a design flaw and continued to look for someone who could seethe assignment from a new perspective. The purpose of the project was to find a solution thatprevents pressure ulcers from occurring.

    To solve the problem, an iterative design process PCDIO (Planning, Conceive, Design,Implement & Operate) was used, which was performed with HCD (Human-Centered design)as the way of thinking, because the solution is intended for humans. At the beginning of theprocess, the context phase was carried out. There, the needs were determined throughinterviews and research about the current state. The greatest need identified was the need toreduce patient turnarounds and examinations. Examination is the main method of preventingpressure ulcers. The need for good materials was identified as well, due to moisture and heatbeing a cause of pressure ulcers. After the user needs were established, different methods wereused within the industrial design engineering framework to create ideas and concepts.

    It resulted in three concepts, the air mattress, the foam mattress with mechanical arms andthe mattress with sensors. The concepts were evaluated on the basis of a design specificationwhere they were scored. The concept that met the criteria best with the highest score becamethe winning concept.

    The result was SENSAI, the mattress that senses the patient's weight over a period of time,using sensors. It detects where the pressure is immense and how harmful it is. By detectingpressure and weight, potential pressure ulcers can be detected earlier. The product has notbeen tested using prototypes or similarly, due to the pandemic and lack of access to materials.The conclusion of this project is therefore to perform more tests and investigations.Hopefully, this will happen as continued work after the master thesis is done

  • 22.
    Abouzayed, Ayman
    et al.
    Uppsala Univ, Dept Med Chem, S-75183 Uppsala, Sweden..
    Borin, Jesper
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Lundmark, Fanny
    Uppsala Univ, Dept Med Chem, S-75183 Uppsala, Sweden..
    Rybina, Anastasiya
    Russian Acad Sci, Canc Res Inst, Tomsk Natl Res Med Ctr, Dept Nucl Med, Tomsk 634009, Russia.;Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia..
    Hober, Sophia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Zelchan, Roman
    Russian Acad Sci, Canc Res Inst, Tomsk Natl Res Med Ctr, Dept Nucl Med, Tomsk 634009, Russia.;Tomsk Polytech Univ, Res Sch Chem & Appl Biomed Sci, Res Ctr Oncotheranost, Tomsk 634050, Russia..
    Tolmachev, Vladimir
    Uppsala Univ, Dept Immunol Genet & Pathol, S-75237 Uppsala, Sweden..
    Chernov, Vladimir
    Russian Acad Sci, Canc Res Inst, Tomsk Natl Res Med Ctr, Dept Nucl Med, Tomsk 634009, Russia..
    Orlova, Anna
    Uppsala Univ, Dept Med Chem, S-75183 Uppsala, Sweden.;Uppsala Univ, Sci Life Lab, S-75237 Uppsala, Sweden..
    The GRPR Antagonist [Tc-99m]Tc-maSSS-PEG(2)-RM26 towards Phase I Clinical Trial: Kit Preparation, Characterization and Toxicity2023In: Diagnostics, ISSN 2075-4418, Vol. 13, no 9, p. 1611-, article id 1611Article in journal (Refereed)
    Abstract [en]

    Gastrin-releasing peptide receptors (GRPRs) are overexpressed in the majority of primary prostate tumors and in prostatic lymph node and bone metastases. Several GRPR antagonists were developed for SPECT and PET imaging of prostate cancer. We previously reported a preclinical evaluation of the GRPR antagonist [Tc-99m]Tc-maSSS-PEG2-RM26 (based on [D-Phe(6), Sta(13), Leu(14)-NH2]BBN(6-14)) which bound to GRPR with high affinity and had a favorable biodistribution profile in tumor-bearing animal models. In this study, we aimed to prepare and test kits for prospective use in an early-phase clinical study. The kits were prepared to allow for a one-pot single-step radiolabeling with technetium-99m pertechnetate. The kit vials were tested for sterility and labeling efficacy. The radiolabeled by using the kit GRPR antagonist was evaluated in vitro for binding specificity to GRPR on PC-3 cells (GRPR-positive). In vivo, the toxicity of the kit constituents was evaluated in rats. The labeling efficacy of the kits stored at 4 degrees C was monitored for 18 months. The biological properties of [Tc-99m]Tc-maSSS-PEG2-RM26, which were obtained after this period, were examined both in vitro and in vivo. The one-pot (gluconic acid, ethylenediaminetetraacetic acid, stannous chloride, and maSSS-PEG(2)-RM26) single-step radiolabeling with technetium-99m was successful with high radiochemical yields (>97%) and high molar activities (16-24 MBq/nmol). The radiolabeled peptide maintained its binding properties to GRPR. The kit constituents were sterile and non-toxic when tested in living subjects. In conclusion, the prepared kit is considered safe in animal models and can be further evaluated for use in clinics.

  • 23.
    Abrahamsson, Josefine
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Materials Science and Engineering.
    Biomarkers and age-related diseases: An overview of how biomarkers can be used to prevent age-related diseases2022Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Medical devices are becoming more and more implemented for use at home and in parallel, the interest from humans in their own health is increasing. Age-related diseases such as diabetes, cancer, and dementia, to name a few, are examples of diseases that with an early diagnosis could be prevented. To find out if there are early indications of the disease in the body, it is necessary to measure biomarkers. These can be measured either invasive or non-invasive and today they are often measurable only clinically at a hospital, but how can people measure these at home by themselves?

    To investigate this, a literature study has been done with focus on age-related diseases. A total of 49 abstracts were read through to determine relevance to the questions of inquiry and three articles were mainly used in the literature study. It was found that there is research focusing on the use of biomarkers to identify and do earlier diagnosing of age-related diseases. Methodology and technology for measuring glucose to identify diabetes are implemented, and a change in lifestyle can prevent a person from being affected by type 2 diabetes. With this knowledge, it is easier to see opportunities for other diseases by using the same type of method and technology further on. A previously conducted study regarding diabetes focus on dietary variations and physical activity for non-diabetic people. Meanwhile in the cancer and dementia area, where the developments are not as successful, the focus is on earlier diagnosing by combining technologies.

    In the future, the technology should be developed so that biomarkers can be used as indicators of the diseases cancer and dementia, and not just as a complement to already applied technology such as imaging techniques that are available today.

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  • 24. Abrahamsson, S.
    et al.
    Blom, Hans
    KTH, School of Engineering Sciences (SCI), Applied Physics.
    Agostinho, A.
    Jans, Daniel
    KTH, School of Engineering Sciences (SCI), Applied Physics.
    Jost, A.
    Müller, M.
    Nilsson, Linnea
    KTH, School of Engineering Sciences (SCI), Applied Physics.
    Bernhem, K.
    Lambert, T. J.
    Heintzmann, R.
    Brismar, Hjalmar
    KTH, School of Engineering Sciences (SCI), Applied Physics.
    Multifocus structured illumination microscopy for fast volumetric super-resolution imaging2017In: Biomedical Optics Express, E-ISSN 2156-7085, Vol. 8, no 9, p. 4135-4140, article id #294866Article in journal (Refereed)
    Abstract [en]

    We here report for the first time the synergistic implementation of structured illumination microscopy (SIM) and multifocus microscopy (MFM). This imaging modality is designed to alleviate the problem of insufficient volumetric acquisition speed in superresolution biological imaging. SIM is a wide-field super-resolution technique that allows imaging with visible light beyond the classical diffraction limit. Employing multifocus diffractive optics we obtain simultaneous wide-field 3D imaging capability in the SIM acquisition sequence, improving volumetric acquisition speed by an order of magnitude. Imaging performance is demonstrated on biological specimens.

  • 25.
    Abramian, David
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Modern multimodal methods in brain MRI2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Magnetic resonance imaging (MRI) is one of the pillars of modern medical imaging, providing a non-invasive means to generate 3D images of the body with high soft-tissue contrast. Furthermore, the possibilities afforded by the design of MRI sequences enable the signal to be sensitized to a multitude of physiological tissue properties, resulting in a wide variety of distinct MRI modalities for clinical and research use. 

    This thesis presents a number of advanced brain MRI applications, which fulfill, to differing extents, two complementary aims. On the one hand, they explore the benefits of a multimodal approach to MRI, combining structural, functional and diffusion MRI, in a variety of contexts. On the other, they emphasize the use of advanced mathematical and computational tools in the analysis of MRI data, such as deep learning, Bayesian statistics, and graph signal processing. 

    Paper I introduces an anatomically-adapted extension to previous work in Bayesian spatial priors for functional MRI data, where anatomical information is introduced from a T1-weighted image to compensate for the low anatomical contrast of functional MRI data. 

    It has been observed that the spatial correlation structure of the BOLD signal in brain white matter follows the orientation of the underlying axonal fibers. Paper II argues about the implications of this fact on the ideal shape of spatial filters for the analysis of white matter functional MRI data. By using axonal orientation information extracted from diffusion MRI, and leveraging the possibilities afforded by graph signal processing, a graph-based description of the white matter structure is introduced, which, in turn, enables the definition of spatial filters whose shape is adapted to the underlying axonal structure, and demonstrates the increased detection power resulting from their use. 

    One of the main clinical applications of functional MRI is functional localization of the eloquent areas of the brain prior to brain surgery. This practice is widespread for various invasive surgeries, but is less common for stereotactic radiosurgery (SRS), a non-invasive surgical procedure wherein tissue is ablated by concentrating several beams of high-energy radiation. Paper III describes an analysis and processing pipeline for functional MRI data that enables its use for functional localization and delineation of organs-at-risk for Elekta GammaKnife SRS procedures. 

    Paper IV presents a deep learning model for super-resolution of diffusion MRI fiber ODFs, which outperforms standard interpolation methods in estimating local axonal fiber orientations in white matter. Finally, Paper V demonstrates that some popular methods for anonymizing facial data in structural MRI volumes can be partially reversed by applying generative deep learning models, highlighting one way in which the enormous power of deep learning models can potentially be put to use for harmful purposes. 

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  • 26.
    Abramian, David
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Larsson, Martin
    Centre of Mathematical Sciences, Lund University, Lund, Sweden.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
    Aganj, Iman
    Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA; Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, USA.
    Westin, Carl-Fredrik
    Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA.
    Behjat, Hamid
    Department of Biomedical Engineering, Lund University, Lund, Sweden; Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
    Diffusion-Informed Spatial Smoothing of fMRI Data in White Matter Using Spectral Graph Filters2021In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 237, article id 118095Article in journal (Refereed)
    Abstract [en]

    Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detachability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject’s unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project’s 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.

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  • 27.
    Abramian, David
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Larsson, Martin
    Centre for Mathematical Sciences, Lund University, Sweden.
    Eklund, Anders
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
    Behjat, Hamid
    Department of Biomedical Engineering, Lund University, Sweden.
    Improved Functional MRI Activation Mapping in White Matter Through Diffusion-Adapted Spatial Filtering2020In: ISBI 2020: IEEE International Symposium on Biomedical Imaging, IEEE, 2020Conference paper (Refereed)
    Abstract [en]

    Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD contrast in white matter having been generally disregarded. Recent results have provided evidence of the functional significance of the white matter BOLD signal, showing at the same time that its correlation structure is highly anisotropic, and related to the diffusion tensor in shape and orientation. This evidence suggests that conventional isotropic Gaussian filters are inadequate for denoising white matter fMRI data, since they are incapable of adapting to the complex anisotropic domain of white matter axonal connections. In this paper we explore a graph-based description of the white matter developed from diffusion MRI data, which is capable of encoding the anisotropy of the domain. Based on this representation we design localized spatial filters that adapt to white matter structure by leveraging graph signal processing principles. The performance of the proposed filtering technique is evaluated on semi-synthetic data, where it shows potential for greater sensitivity and specificity in white matter activation mapping, compared to isotropic filtering.

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  • 28.
    Abramian, David
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering.
    Sidén, Per
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences.
    Knutsson, Hans
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Villani, Mattias
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Department of Statistics, Stockholm University.
    Eklund, Anders
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Anatomically Informed Bayesian Spatial Priors for FMRI Analysis2020In: ISBI 2020: IEEE International Symposium on Biomedical Imaging / [ed] IEEE, IEEE, 2020Conference paper (Refereed)
    Abstract [en]

    Existing Bayesian spatial priors for functional magnetic resonance imaging (fMRI) data correspond to stationary isotropic smoothing filters that may oversmooth at anatomical boundaries. We propose two anatomically informed Bayesian spatial models for fMRI data with local smoothing in each voxel based on a tensor field estimated from a T1-weighted anatomical image. We show that our anatomically informed Bayesian spatial models results in posterior probability maps that follow the anatomical structure.

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  • 29.
    Abtahi, Farhad
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Aspects of Electrical Bioimpedance Spectrum Estimation2014Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Electrical bioimpedance spectroscopy (EBIS) has been used to assess the status or composition of various types of tissue, and examples of EBIS include body composition analysis (BCA) and tissue characterisation for skin cancer detection. EBIS is a non-invasive method that has the potential to provide a large amount of information for diagnosis or monitoring purposes, such as the monitoring of pulmonary oedema, i.e., fluid accumulation in the lungs. However, in many cases, systems based on EBIS have not become generally accepted in clinical practice. Possible reasons behind the low acceptance of EBIS could involve inaccurate models; artefacts, such as those from movements; measurement errors; and estimation errors. Previous thoracic EBIS measurements aimed at pulmonary oedema have shown some uncertainties in their results, making it difficult to produce trustworthy monitoring methods. The current research hypothesis was that these uncertainties mostly originate from estimation errors. In particular, time-varying behaviours of the thorax, e.g., respiratory and cardiac activity, can cause estimation errors, which make it tricky to detect the slowly varying behaviour of this system, i.e., pulmonary oedema.

    The aim of this thesis is to investigate potential sources of estimation error in transthoracic impedance spectroscopy (TIS) for pulmonary oedema detection and to propose methods to prevent or compensate for these errors.   This work is mainly focused on two aspects of impedance spectrum estimation: first, the problems associated with the delay between estimations of spectrum samples in the frequency-sweep technique and second, the influence of undersampling (a result of impedance estimation times) when estimating an EBIS spectrum. The delay between frequency sweeps can produce huge errors when analysing EBIS spectra, but its effect decreases with averaging or low-pass filtering, which is a common and simple method for monitoring the time-invariant behaviour of a system. The results show the importance of the undersampling effect as the main estimation error that can cause uncertainty in TIS measurements.  The best time for dealing with this error is during the design process, when the system can be designed to avoid this error or with the possibility to compensate for the error during analysis. A case study of monitoring pulmonary oedema is used to assess the effect of these two estimation errors. However, the results can be generalised to any case for identifying the slowly varying behaviour of physiological systems that also display higher frequency variations.  Finally, some suggestions for designing an EBIS measurement system and analysis methods to avoid or compensate for these estimation errors are discussed.

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    Thesis
  • 30.
    Abtahi, Farhad
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Towards Heart Rate Variability Tools in P-Health: Pervasive, Preventive, Predictive and Personalized2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Heart rate variability (HRV) has received much attention lately. It has been shown that HRV can be used to monitor the autonomic nervous system and to detect autonomic dysfunction, especially vagal dysfunction. Reduced HRV is associated with several diseases and has also been suggested as a predictor of poor outcomes and sudden cardiac death. HRV is, however, not yet widely accepted as a clinical tool and is mostly used for research. Advances in neuroimmunity with an improved understanding of the link between the nervous and immune systems have opened a new potential arena for HRV applications. An example is when systemic inflammation and autoimmune disease are primarily caused by low vagal activity; it can be detected and prognosticated by reduced HRV. This thesis is the result of several technical development steps and exploratory research where HRV is applied as a prognostic diagnostic tool with preventive potential. The main objectives were 1) to develop an affordable tool for the effective analysis of HRV, 2) to study the correlation between HRV and pro-inflammatory markers and the potential degree of activity in the cholinergic anti-inflammatory pathway, and 3) to develop a biofeedback application intended for support of personal capability to increase the vagal activity as reflected in increased HRV. Written as a compilation thesis, the methodology and the results of each study are presented in each appended paper. In the thesis frame/summary chapter, a summary of each of the included papers is presented, grouped by topic and with their connections. The summary of the results shows that the developed tools may accurately register and properly analyse and potentially influence HRV through the designed biofeedback game. HRV can be used as a prognostic tool, not just in traditional healthcare with a focus on illness but also in wellness. By using these tools for the early detection of decreased HRV, prompt intervention may be possible, enabling the prevention of disease. Gamification and serious gaming is a potential platform to motivate people to follow a routine of exercise that might, through biofeedback, improve HRV and thereby health.

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  • 31.
    Abtahi, Farhad
    et al.
    Karolinska Institutet.
    Anund, Anna
    Fors, Carina
    Seoane, Fernando
    University of Borås, Faculty of Textiles, Engineering and Business. University of Borås, Faculty of Caring Science, Work Life and Social Welfare. Karolinska Institutet.
    Lindecrantz, Kaj
    University of Borås, Faculty of Textiles, Engineering and Business. Karolinska Institutet.
    Association of Drivers’ sleepiness with heart rate variability. A Pilot Study with Drivers on Real Road2017Conference paper (Other academic)
  • 32. Abtahi, Farhad
    et al.
    Forsman, Mikael
    Diaz-Olivares, Jose A.
    KTH, School of Technology and Health (STH). KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Yang, Liyun
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Lu, Ke
    KTH, School of Technology and Health (STH).
    Eklund, Jörgen
    KTH, School of Technology and Health (STH).
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH).
    Seoane, Fernando
    Teriö, Heikki
    Mediavilla Martinez, Cesar
    Aso, Santiago
    Tiemann, Christian
    Big Data & Wearable Sensors Ensuring Safety and Health @Work2017In: GLOBAL HEALTH 2017, The Sixth International Conference on Global Health Challenges, 2017Conference paper (Refereed)
    Abstract [en]

    —Work-related injuries and disorders constitute a major burden and cost for employers, society in general and workers in particular. We@Work is a project that aims to develop an integrated solution for promoting and supporting a safe and healthy working life by combining wearable technologies, Big Data analytics, ergonomics, and information and communication technologies. The We@Work solution aims to support the worker and employer to ensure a healthy working life through pervasive monitoring for early warnings, prompt detection of capacity-loss and accurate risk assessments at workplace as well as self-management of a healthy working life. A multiservice platform will allow unobtrusive data collection at workplaces. Big Data analytics will provide real-time information useful to prevent work injuries and support healthy working life

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  • 33.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Karolinska Institutet, Sweden.
    Hilderman, Marie
    Bruchfeld, Annette
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. University of Borås, Sweden.
    Janerot-Sjöberg, Birgitta
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Imaging. Karolinska Institutet, Sweden.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Karolinska Institutet, Sweden.
    Pro-inflammatory Blood Markers and Heart Rate Variability in Apnoea as a Reflection of Basal Vagal ToneManuscript (preprint) (Other academic)
    Abstract [en]

    Pro-inflammatory cytokines play a crucial role in inflammatory response, which istightly regulated by the nervous system to avoid the damage caused by inflammation. There isevidence for a cholinergic anti-inflammatory pathway that includes afferent and efferent vagalnerves that sense the inflammation and stimulate the anti-inflammatory response. Non-functionalanti-inflammatory response might lead to excessive and chronic inflammation e.g., rheumatoidarthritis (RA), inflammatory bowel disease (IBD), and poor outcome. Heart rate variability(HRV) has been proposed as a potential tool to monitor the level of anti-inflammatory activitythrough the monitoring of vagal activity. In this paper, the association of pro-inflammatorymarkers with HRV indices is evaluated. We used a database called “Heart Biomarker Evaluationin Apnea Treatment (HeartBEAT)” that consists of 6±2 hours of Electrocardiogram (ECG)recordings during nocturnal sleep from 318 patients at baseline and 301of them at 3 monthsfollow-up. HRV indices are calculated from ECG recordings of 5-360 minutes. The results showa statistically significant correlation between heart rate (HR) and pro-inflammatory cytokines,independent of duration of ECG analysis. HRV indices e.g., standard deviation of all RRintervals (SDNN) show an inverse relation to the pro-inflammatory cytokines. Longer ECGrecordings show a higher potential to reflect the level of anti-inflammatory response. In light oftheories for the cholinergic anti-inflammatory pathway, a combination of HR and HRV as areflection of basal vagal activity might be a potential prognostic tool for interventional guidance.

  • 34.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Ji, Guangchao
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Rodby, Kristian
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    A knitted garment using intarsia technique for Heart Rate Variability biofeedback: Evaluation of initial prototype2015In: Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, IEEE , 2015, Vol. 2015, p. 3121-3124Conference paper (Refereed)
    Abstract [en]

    Heart rate variability (HRV) biofeedback is a method based on paced breathing at specific rate called resonance frequency by giving online feedbacks from user respiration and its effect on HRV. Since the HRV is also influence by different factors like stress and emotions, stress related to an unfamiliar measurement device, cables and skin electrodes may cover the underling effect of such kind of intervention. Wearable systems are usually considered as intuitive solutions which are more familiar to the end-user and can help to improve usability and hence reducing the stress. In this work, a prototype of a knitted garment using intarsia technique is developed and evaluated. Results show the satisfactory level of quality for Electrocardiogram and thoracic electrical bioimpedance i.e. for respiration monitoring as a part of HRV biofeedback system. Using intarsia technique and conductive yarn for making the connection instead of cables will reduce the complexity of fabrication in textile production and hence reduce the final costs in a final commercial product. Further development of garment and Android application is ongoing and usability and efficiency of final prototype will be evaluated in detail.

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  • 35.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Ji, Guangchao
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Rödby, Kristian
    University of Borås, Faculty of Textiles, Engineering and Business.
    Björlin, Anders
    Kiwok AB.
    Östlund, Anders
    Kiwok AB.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lindecrantz, Kaj
    KTH-School of Technology and Health.
    Textile-Electronic Integration in Wearable Measurement Garments for Pervasive Healthcare Monitoring2015Conference paper (Other academic)
  • 36.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Ji, Guangchao
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Rödby, Kristian
    Högskolan i Borås, Akademin för textil, teknik och ekonomi.
    Björlin, Anders
    Kiwok AB.
    Östlund, Anders
    Kiwok AB.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås, Akademin för vård, arbetsliv och välfärd.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Textile-Electronic Integration in Wearable Measurement Garments for Pervasive Healthcare Monitoring2015Conference paper (Other academic)
  • 37.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Ji, Guangchao
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Rödby, Kristian
    University of Borås, Faculty of Textiles, Engineering and Business.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    A knitted garment using intarsia technique for Heart Rate Variability biofeedback: Evaluation of initial prototype2015In: Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015, p. 3121-3124Conference paper (Refereed)
  • 38.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Aslamy, Benjamin
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Boujabir, Imaneh
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    An Affordable ECG and Respiration Monitoring System Based on Raspberry PI and ADAS1000: First Step towards Homecare Applications2015In: 16th Nordic-Baltic Conference on Biomedical Engineering: 16. NBC & 10. MTD 2014 joint conferences. October 14-16, 2014, Gothenburg, Sweden, Springer, 2015, p. 5-8Conference paper (Refereed)
    Abstract [en]

    Homecare is a potential solution for problems associated with an aging population. This may involve several physiological measurements, and hence a flexible but affordable measurement device is needed. In this work, we have designed an ADAS1000-based four-lead electrocardiogram (ECG) and respiration monitoring system. It has been implemented using Raspberry PI as a platform for homecare applications. ADuM chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 and IEC 60950 for patient safety. The result proved the potential of Raspberry PI for the design of a compact, affordable, and medically safe measurement device. Further work involves developing a more flexible software for collecting measurements from different devices (measuring, e.g., blood pressure, weight, impedance spectroscopy, blood glucose) through Bluetooth or user input and integrating them into a cloud-based homecare system.

  • 39.
    Abtahi, Farhad
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics. Karolinska Inst, Inst Environm Med, S-17165 Stockholm, Sweden..
    Lu, Ke
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Diaz-Olivares, Jose A.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Ergonomics.
    Forsman, Mikael
    Karolinska Inst, Inst Environm Med, S-17165 Stockholm, Sweden..
    Seoane, Fernando
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Halsovagen 7, S-14157 Stockholm, Sweden.;Univ Boras, Swedish Sch Text, Allegatan 1, S-50190 Boras, Sweden.;Karolinska Univ Hosp, Dept Biomed Engn, S-17176 Solna, Sweden..
    Lindecrantz, Kaj
    Karolinska Inst, Inst Environm Med, S-17165 Stockholm, Sweden.;Univ Boras, Sci Pk,Allegatan 1, S-50190 Boras, Sweden..
    Wearable Sensors Enabling Personalized Occupational Healthcare2018In: INTELLIGENT ENVIRONMENTS 2018 / [ed] Chatzigiannakis, I Tobe, Y Novais, P Amft, O, IOS PRESS , 2018, p. 371-376Conference paper (Refereed)
    Abstract [en]

    This paper presents needs and potentials for wearable sensors in occupational healthcare. In addition, it presents ongoing European and Swedish projects for developing personalized, and pervasive wearable systems for assessing risks of developing musculoskeletal disorders and cardiovascular diseases at work. Occupational healthcare should benefit in preventing diseases and disorders by providing the right feedback at the right time to the right person. Collected data from workers can provide evidence supporting the ergonomic and industrial tasks of redesigning the working environment to reduce the risks.

  • 40.
    Abtahi, Farhad
    et al.
    Institute of Environmental Medicine, Karolinska Institutet, 171 65 Stockholm, Sweden; School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden.
    Lu, Ke
    School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden.
    Diaz-Olivares, Jose A
    School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden.
    Forsman, Mikael
    Institute of Environmental Medicine, Karolinska Institutet, 171 65 Stockholm, Sweden.
    Seoane, Fernando
    University of Borås, Faculty of Textiles, Engineering and Business. University of Borås, Faculty of Caring Science, Work Life and Social Welfare. Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Hälsovägen 7, 141 57 Stockholm, Sweden; Department of Biomedical Engineering, Karolinska University Hospital, 171 76 Solna, Sweden .
    Lindecrantz, Kaj
    University of Borås, Science Park Borås. Institute of Environmental Medicine, Karolinska Institutet, 171 65 Stockholm, Sweden .
    Wearable Sensors Enabling Personalized Occupational Healthcare2018In: Intelligent Environments 2018 / [ed] Ioannis Chatzigiannakis, Yoshito Tobe, Paulo Novais, Oliver Amft, Amsterdam: IOS Press, 2018, p. 371-376Chapter in book (Other academic)
    Abstract [en]

    This paper presents needs and potentials for wearable sensors inoccupational healthcare. In addition, it presents ongoing European and Swedishprojects for developing personalized, and pervasive wearable systems for assessingrisks of developing musculoskeletal disorders and cardiovascular diseases at work.Occupational healthcare should benefit in preventing diseases and disorders byproviding the right feedback at the right time to the right person. Collected datafrom workers can provide evidence supporting the ergonomic and industrial tasksof redesigning the working environment to reduce the risks.

    Download full text (pdf)
    fulltext
  • 41.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Dizon, M
    KTH-School of Technology and Health.
    Johansson, M
    KTH-School of Technology and Health.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lindecrantz, Kaj
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Evaluating Atrial Fibrillation Detection Algorithm based on Heart Rate Variability analysis2015In: Medicinteknikdagarna, Uppsala: Svensk förening för medicinsk teknik och fysik , 2015Conference paper (Refereed)
  • 42.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Dizon, M
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Johansson, M
    KTH-School of Technology and Health.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Computer and Electronic Engineering. Högskolan i Borås, Akademin för vård, arbetsliv och välfärd.
    Evaluating Atrial Fibrillation Detection Algorithm based on Heart Rate Variability analysis2015In: Medicinteknikdagarna, Uppsala: Svensk förening för medicinsk teknik och fysik , 2015Conference paper (Refereed)
  • 43.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Dizon, M
    KTH-School of Technology and Health.
    Johansson, M
    KTH-School of Technology and Health.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lindecrantz, Kaj
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Evaluation of Atrial Fibrillation Detection by using Heart Rate Variability analysis2015Conference paper (Other academic)
  • 44.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Dizon, M
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Johansson, M
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås, Akademin för vård, arbetsliv och välfärd.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Evaluation of Atrial Fibrillation Detection by using Heart Rate Variability analysis2015Conference paper (Other academic)
  • 45.
    Abtahi, Farhad
    et al.
    KTH-School of Technology and Health.
    Lu, Ke
    KTH-School of Technology and Health.
    Guangchao, Li
    KTH-School of Technology and Health.
    Rödby, Kristian
    University of Borås, Faculty of Textiles, Engineering and Business.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    A Knitted Garment using Intarsia Technique for Heart Rate Variability Biofeedback: Evaluation of Initial Prototype.2015Conference paper (Other academic)
  • 46.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lu, Ke
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Guangchao, Li
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Rödby, Kristian
    Högskolan i Borås, Akademin för textil, teknik och ekonomi.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Högskolan i Borås.
    A Knitted Garment using Intarsia Technique for Heart Rate Variability Biofeedback: Evaluation of Initial Prototype.2015Conference paper (Other academic)
  • 47.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Electrical bioimpedance spectroscopy in time-variant systems: Is undersampling always a problem?2014In: Journal of Electrical Bioimpedance, E-ISSN 1891-5469, Vol. 5, no 1, p. 28-33Article in journal (Refereed)
    Abstract [en]

    During the last decades, Electrical Bioimpedance Spectroscopy (EBIS) has been applied mainly by using the frequency-sweep technique, across a range of many different applications. Traditionally, the tissue under study is considered to be time-invariant and dynamic changes of tissue activity are ignored by treating the changes as a noise source. A new trend in EBIS is simultaneous electrical stimulation with several frequencies, through the application of a multi-sine, rectangular or other waveform. This method can provide measurements fast enough to sample dynamic changes of different tissues, such as cardiac muscle. This high sampling rate comes at a price of reduction in SNR and the increase in complexity of devices. Although the frequency-sweep technique is often inadequate for monitoring the dynamic changes in a variant system, it can be used successfully in applications focused on the time-invariant or slowly-variant part of a system. However, in order to successfully use frequency-sweep EBIS for monitoring time-variant systems, it is paramount to consider the effects of aliasing and especially the folding of higher frequencies, on the desired frequency e.g. DC level. This paper discusses sub-Nyquist sampling of thoracic EBIS measurements and its application in the case of monitoring pulmonary oedema. It is concluded that by considering aliasing, and with proper implementation of smoothing filters, as well as by using random sampling, frequency-sweep EBIS can be used for assessing time-invariant or slowly-variant properties of time-variant biological systems, even in the presence of aliasing. In general, undersampling is not always a problem, but does always require proper consideration.

  • 48.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Löfgren, Nils
    Elimination of ECG Artefacts in Foetal EEG Using Ensemble Average Subtraction and Wavelet Denoising Methods: A Simulation2014In: XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013, Springer, 2014, p. 551-554Conference paper (Refereed)
    Abstract [en]

    Biological signals recorded from surface electrodes contain interference from other signals which are not desired and should be considered as noise. Heart activity is especially present in EEG and EMG recordings as a noise. In this work, two ECG elimination methods are implemented; ensemble average subtraction (EAS) and wavelet denoising methods. Comparison of these methods has been done by use of simulated signals achieved by adding ECG to neonates EEG. The result shows successful elimination of ECG artifacts by using both methods. In general EAS method which remove estimate of all ECG components from signal is more trustable but it is also harder for implementation due to sensitivity to noise. It is also concluded that EAS behaves like a high-pass filter while wavelet denoising method acts as low-pass filter and hence the choice of one method depends on application.

  • 49.
    Abtahi, Farhad
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems.
    Snäll, Jonatan
    KTH, School of Technology and Health (STH).
    Aslamy, Benjamin
    KTH, School of Technology and Health (STH).
    Abtahi, Shirin
    KTH, School of Technology and Health (STH).
    Seoane, Fernando
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. University of Boras, Sweden.
    Lindecrantz, Kaj
    KTH, School of Technology and Health (STH), Medical Engineering, Medical sensors, signals and systems. Karolinska Institute, Sweden.
    Biosignal PI, an Affordable Open-Source ECG and Respiration Measurement System2014In: Sensors, E-ISSN 1424-8220, Vol. 15, no 1, p. 93-109Article in journal (Refereed)
    Abstract [en]

    Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org.

    Download full text (pdf)
    fulltext
  • 50. Abtahi, Farhad
    et al.
    Snäll, Jonathan
    Aslamy, Benjamin
    Abtahi, Shirin
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lindecrantz, Kaj
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Biosignal PI, an Affordable Open-Source ECG and Respiration Measurement System2015In: Sensors, E-ISSN 1424-8220, Vol. 15, no 1, p. 93-109Article in journal (Refereed)
    Abstract [en]

    Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org.

1234567 1 - 50 of 5219
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