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  • 1.
    Abbaspour, Sara
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fallah, Ali
    Amirkabir University of Technology, Tehran, Iran.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gholamhosseini, Hamid
    Auckland University of Technology, Auckland, New Zealand.
    A Novel Approach for Removing ECG Interferences from Surface EMG signals Using a Combined ANFIS and Wavelet2015In: Journal of Electromyography & Kinesiology, ISSN 1050-6411, E-ISSN 1873-5711, Vol. 26, p. 52-59Article in journal (Refereed)
    Abstract [en]

    In recent years, the removal of electrocardiogram (ECG) interferences from electromyogram (EMG) signals has been given large consideration. Where the quality of EMG signal is of interest, it is important to remove ECG interferences from EMG signals. In this paper, an efficient method based on a combination of adaptive neuro-fuzzy inference system (ANFIS) and wavelet transform is proposed to effectively eliminate ECG interferences from surface EMG signals. The proposed approach is compared with other common methods such as high-pass filter, artificial neural network, adaptive noise canceller, wavelet transform, subtraction method and ANFIS. It is found that the performance of the proposed ANFIS-wavelet method is superior to the other methods with the signal to noise ratio and relative error of 14.97 dB and 0.02 respectively and a significantly higher correlation coefficient (p < 0.05).

  • 2.
    Abbaspour, Sara
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gholamhosseini, H.
    School of Engineering, Auckland University of TechnologyAuckland, New Zealand .
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Evaluation of wavelet based methods in removing motion artifact from ECG signal2015In: IFMBE Proceedings, 2015, p. 1-4Conference paper (Refereed)
    Abstract [en]

    Accurate recording and precise analysis of the electrocardiogram (ECG) signals are crucial in the pathophysiological study and clinical treatment. These recordings are often corrupted by different artifacts. The aim of this study is to propose two different methods, wavelet transform based on nonlinear thresholding and a combination method using wavelet and independent component analysis (ICA), to remove motion artifact from ECG signals. To evaluate the performance of the proposed methods, the developed techniques are applied to the real and simulated ECG data. The results of this evaluation are presented using quantitative and qualitative criteria. The results show that the proposed methods are able to reduce motion artifacts in ECG signals. Signal to noise ratio (SNR) of the wavelet technique is equal to 13.85. The wavelet-ICA method performed better with SNR of 14.23.

  • 3.
    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)
  • 4.
    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.
    Gholamhosseini, Hamid
    Auckland University of Technology, New Zealand.
    ECG Artifact Removal from Surface EMG Signal Using an Automated Method Based on Wavelet-ICA2015In: Studies in Health Technology and Informatics, Volume 211, 2015, p. 91-97Conference paper (Refereed)
    Abstract [en]

    This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact components from the original EMG signal. Components that correspond to the ECG artifact are then identified by an automated detection algorithm and are subsequently removed using a conventional high pass filter. Finally, the results of the proposed method are compared with wavelet transform, ICA, adaptive filter and empirical mode decomposition-ICA methods. The automated artifact removal method proposed in this study successfully removes the ECG artifacts from EMG signals with a signal to noise ratio value of 9.38 while keeping the distortion of original EMG to a minimum.

  • 5. Abdul-Ahad, Amir Stefan
    et al.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Larsson, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Mahmoud, Waleed A.
    Robust Distance-Based Watermarking for Digital Video2008In: Proceedings of The Annual SIGRAD Conference, Stockholm, 2008Conference paper (Refereed)
  • 6.
    Abdul-Ahad, Amir Stefan
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Çürüklü, Baran
    Mälardalen University, School of Innovation, Design and Engineering.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Indirect Wavelet-Based Cardio Arrhythmia Detection Algorithm2008In: Medicinteknikdagarna, Gothenburg, Sweden, 2008, p. 14-15Conference paper (Refereed)
  • 7.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering.
    Intelligent Stress Management System2009In: Medicinteknikdagarna 2009, 2009Conference paper (Refereed)
    Abstract [en]

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

  • 8.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Causevic, Aida
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    An Overview on the Internet of Things for Health Monitoring Systems2015In: 2nd EAI International Conference on IoT Technologies for HealthCare HealthyIoT2015, 2015Conference paper (Refereed)
    Abstract [en]

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

  • 9.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Generic System-level Framework for Self-Serve Health Monitoring System through Internet of Things(IoT)2015In: Studies in Health Technology and Informatics, Volume 211: Proceedings of the 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 2–4 June 2015, Västerås, Sweden, 2015, Vol. 211, p. 305-307Conference paper (Refereed)
    Abstract [en]

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

  • 10.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Köckemann, Uwe
    Örebro University, Sweden.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomasic, Ivan
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tsiftes, Nicolas
    RISE SICS, Stockholm, Sweden.
    Voigt, Thiemo
    RISE SICS, Stockholm, Sweden.
    Run-Time Assurance for the E-care@home System2018In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, p. 107-110Conference paper (Refereed)
    Abstract [en]

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

  • 11.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Healthcare Service at Home: An Intelligent Health Monitoring System for Elderly2015In: Medicinteknikdagarna 2015 MFT 2015, 2015Conference paper (Refereed)
    Abstract [en]

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

  • 12.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Multi-parameter Sensing Platform in ESS-H and E-care@home2017In: Joint conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) EMBEC & NBC’17, 2017Conference paper (Refereed)
    Abstract [en]

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

  • 13.
    Ask, P.
    et al.
    Department of Biomedical Engineering, Linköping University, Sweden.
    Ekstrand, K.
    ?.
    Hult, P.
    Department of Biomedical Engineering, Linköping University, Sweden.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Pettersson, N. -E
    Örebro County Council, Sweden.
    NovaMedTech - A regional program for supporting new medical technologies in personalized health care2012In: Studies in Health Technology and Informatics, 2012, p. 71-75Conference paper (Refereed)
    Abstract [en]

    NovaMedTech is an initiative funded from EU structural funds for supporting new medical technologies for personalized health care. It aims at bringing these technologies into clinical use and to the health care market. The program has participants from health care, industry and academia in East middle Sweden. The first three year period of the program was successful in terms of product concepts tried clinically, and number of products brought to a commercialization phase. Further, the program has led to a large number of scientific publications. Among projects supported, we can mention: Intelligent sensor networks; A digital pen to collect medical information about health status from patients; A web-based intelligent stethoscope; Methodologies to measure local blood flow and nutrition using optical techniques; Blood flow assessment from ankle pressure measurements; Technologies for pressure ulcer prevention; An IR thermometer for improved accuracy; A technique that identifies individuals prone to commit suicide among depressed patients; Detection of infectious disease using an electronic nose; Identification of the lactate threshold from breath; Obesity measurements using special software and MR camera; and An optical probe guided tumor resection. During the present three years period emphasis will be on entrepreneurial activities supporting the commercialization and bringing products to the market.

  • 14. Ask, Per
    et al.
    Ekstrand, Kristina
    Hult, Peter
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Pettersson, Nils-Erik
    A regional program for supporting new medical technologies in personalized health care2012In: PHealth 2012, 2012, p. 71-75Conference paper (Refereed)
  • 15.
    Ask, Per
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Hult, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Pettersson, Nils-Erik
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekstrand, Kristina
    Mälardalen University, School of Innovation, Design and Engineering.
    NovaMedTechs satsning pa medicinsk teknik for individualiserad vard2011In: Svenska Lakaresallskapets riksstamma 2011, 30 Nov-2 Dec, Stockholm, Sweden, 2011Conference paper (Refereed)
  • 16.
    Baig, M. M.
    et al.
    Auckland University of Technology, Auckland, New Zealand.
    Gholamhosseini, H.
    Auckland University of Technology, Auckland, New Zealand.
    Connolly, M. J.
    University of Auckland, New Zealand.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Advanced decision support system for older adults2015In: Studies in Health Technology and Informatics, vol. 211, 2015, p. 235-240Conference paper (Refereed)
    Abstract [en]

    Decision support systems are rapidly becoming part of today's healthcare delivery. The paradigm has shifted from traditional and manual recording to computer-based electronic records and, further, to handheld devices as versatile and innovative healthcare monitoring systems. The current study focuses on interpreting multiple physical signs and early warning for hospitalized older adults so that severe consequences can be minimized. Data from a total of 30 patients have been collated in New Zealand Hospitals under local and national ethics approvals. The system records blood pressure, heart rate (pulse), oxygen saturation (SpO2), ear temperature and blood glucose levels from hospitalized patients and transfers this information to a web-based software application for remote monitoring and further interpretation. Ultimately, this system is aimed to achieve a high level of agreement with clinicians' interpretation when assessing specific physical signs such as bradycardia, tachycardia, hypertension, hypotension, hypoxemia, fever and hypothermia and to generate early warnings. 

  • 17.
    Baig, M. M.
    et al.
    Auckland University of Technology, New Zealand.
    GholamHosseini, H.
    Auckland University of Technology, New Zealand.
    Moqeem, A. A.
    Auckland University of Technology, New Zealand.
    Mirza, F.
    Auckland University of Technology, New Zealand.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Systematic Review of Wearable Patient Monitoring Systems – Current Challenges and Opportunities for Clinical Adoption2017In: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 41, no 7, article id 115Article in journal (Refereed)
    Abstract [en]

    The aim of this review is to investigate barriers and challenges of wearable patient monitoring (WPM) solutions adopted by clinicians in acute, as well as in community, care settings. Currently, healthcare providers are coping with ever-growing healthcare challenges including an ageing population, chronic diseases, the cost of hospitalization, and the risk of medical errors. WPM systems are a potential solution for addressing some of these challenges by enabling advanced sensors, wearable technology, and secure and effective communication platforms between the clinicians and patients. A total of 791 articles were screened and 20 were selected for this review. The most common publication venue was conference proceedings (13, 54%). This review only considered recent studies published between 2015 and 2017. The identified studies involved chronic conditions (6, 30%), rehabilitation (7, 35%), cardiovascular diseases (4, 20%), falls (2, 10%) and mental health (1, 5%). Most studies focussed on the system aspects of WPM solutions including advanced sensors, wireless data collection, communication platform and clinical usability based on a specific area or disease. The current studies are progressing with localized sensor-software integration to solve a specific use-case/health area using non-scalable and ‘silo’ solutions. There is further work required regarding interoperability and clinical acceptance challenges. The advancement of wearable technology and possibilities of using machine learning and artificial intelligence in healthcare is a concept that has been investigated by many studies. We believe future patient monitoring and medical treatments will build upon efficient and affordable solutions of wearable technology. 

  • 18.
    Baig, M. M.
    et al.
    Auckland University of Technology, Auckland, New Zealand.
    Hosseini, H. G.
    Auckland University of Technology, Auckland, New Zealand.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Machine learning-based clinical decision support system for early diagnosis from real-time physiological data2017In: Proceedings/TENCON, Institute of Electrical and Electronics Engineers Inc. , 2017, p. 2943-2946, article id 7848584Conference paper (Refereed)
    Abstract [en]

    This research aims to design a self-organizing decision support system for early diagnosis of key physiological events. The proposed system consists of pre-processing, clustering and diagnostic system, based on self-organizing fuzzy logic modeling. The clustering technique was employed with empirical pattern analysis, particularly when the information available is incomplete or the data model is affected by vagueness, which is mostly the case with medical/clinical data. Clustering module can be viewed as unsupervised learning from a given dataset. This module partitions the patient vital signs to identify the key relationships, patterns and clusters among the medical data. Secondly, it uses self-organizing fuzzy logic modeling for early symptom and event detection. Based on the clustering outcome, when detecting abnormal signs, a high level of agreement was observed between system interpretation and human expert diagnosis of the physiological events and signs. © 2016 IEEE.

  • 19.
    Baig, M.M.
    et al.
    Auckland University of Technology.
    GholamHosseini, H.
    Auckland University of Technology.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tablet-based Patient Monitoring and Decision Support Systems in Hospital Care2015In: 2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2015, p. 1215-1218Conference paper (Refereed)
    Abstract [en]

    Remote patient monitoring with evidence-based decision support is revolutionizing healthcare. This novel approach could enable both patients and healthcare providers to improve quality of care and reduce costs. Clinicians can also view patients' data within the hospital network on tablet computers as well as other ubiquitous devices. Today, a wide range of applications are available on tablet computers which are increasingly integrating into the healthcare mainstream as clinical decision support systems. Despite the benefits of table-based healthcare applications, there are concerns around the accuracy, security and stability of such applications. In this study, we developed five tablet-based application screens for remote patient monitoring at hospital care settings and identified related issues and challenges. The ultimate aim of this research is to integrate decision support algorithms into the monitoring system in order to improve inpatient care and the effectiveness of such applications.

  • 20.
    Begum, Shahina
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering.
    Diagnosis and Biofeedback System for Stress2009In: Proceedings of the 6th International Workshop on Wearable, Micro, and Nano Technologies for Personalized Health: "Facing Future Healthcare Needs", pHealth 2009, 2009, p. 17-20Conference paper (Refereed)
    Abstract [en]

    Today, everyday life for many people contain many situations that may trigger stress or result in an individual living on an increased stress level under long time. High level of stress may cause serious health problems. It is known that respiratory rate is an important factor and can be used in diagnosis and biofeedback training, but available measurement of respiratory rate are not especially suitable for home and office use. The aim of this project is to develop a portable sensor system that can measure the stress level, during everyday situations e.g. at home and in work environment and can help the person to change the behaviour and decrease the stress level. The sensor explored is a finger temperature sensor. Clinical studies show that finger temperature, in general, decreases with stress; however this change pattern shows large individual variations. Diagnosing stress level from the finger temperature is difficult even for clinical experts. Therefore a computer-based stress diagnosis system is important. In this system, case-based reasoning and fuzzy logic have been applied to assists in stress diagnosis and biofeedback treatment utilizing the finger temperature sensor signal. An evaluation of the system with an expert in stress diagnosis shows promising result.

  • 21.
    Bergblomma, Marcus
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Martin
    Mälardalen University, School of Innovation, Design and Engineering.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Gerdtman, Christer
    Motion Control AB, Västerås, Sweden .
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    A wireless low latency control system for harsh environments2012In: IFAC Proceedings Volumes (IFAC-PapersOnline): Vol. 11, PART 1, 2012, p. 17-22Conference paper (Refereed)
    Abstract [en]

    The use of wireless communication technologies in the industry offer severaladvantages. One advantage is the ability to deploy sensors where they previously could noteasily be deployed, for instance on parts that rotate. To use wireless communication in industrialcontrol loops, demands on reliability and latency requirements has to be met. This in anenvironment that may be harsh for radio communication. This work presents a reliable, lowlatency wireless communication system. The system is used in a wireless thyristor control loopin a hydro power plant generator. The wireless communication is based on Bluetooth radiomodules. The work shows a latency analysis together with empirical hardware based latencyand packet error rate measurements. The background noise of a hydro power plant station isalso investigated. The average latency between the Bluetooth modules for the proposed systemis 5.09 ms. The packet error rate is 0.00288 for the wireless low latency control system deployedin a hydro power plant.

  • 22.
    Bergblomma, Marcus
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Martin
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Garcia Castaño, Javier
    Mälardalen University, School of Innovation, Design and Engineering.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Wireless ECG network2009In: WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, VOL 25, PT 5, 2009, p. 244-247Conference paper (Refereed)
    Abstract [en]

    This paper presents a time synchronized wireless ECG sensor network with reliable data communication. Wireless ECG systems are a popular research area where several research groups have presented point-to-point solutions. Alongside the wireless ECG research, the wireless sensor network research has created an increasing interest for secure, low power and predictable network applications. Combining these research areas is a natural step for the evolution of secure wireless monitoring of physiological parameters. In this study the Bluetooth radio standard has been chosen for its versatility. This paper focuses on both the hardware and the software development for a functional multihop ECG network using Bluetooth. The presented wireless ECG network is reliable up to link loss and is easily configured to send more or different types of signals. The system has been tested and verified for secure multihop communication.

  • 23.
    Berglin, Lena
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Monitoring health and activity by smartwear2005Conference paper (Other academic)
  • 24.
    Bergstrand, Sara
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Ek, Anna-Christina
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindberg, Lars-Göran
    Mälardalen University, School of Innovation, Design and Engineering.
    Länne, Torste
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindgren, Margareta
    Mälardalen University, School of Innovation, Design and Engineering.
    Tissue blood flow response to external pressure in the sacral region using PPG and laser Doppler technique2009In: 12th Annual European Pressure Ulcer Advisory Panel Open Meeting in Amsterdam, 3rd to 5th September 2009, Netherlands, 2009Conference paper (Refereed)
  • 25. Bergstrand, Sara
    et al.
    Lanne, Torste
    Ek, Anna-Christina
    Lindberg, Lars-Göran
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindgren, Margareta
    Existence of Tissue Blood Flow in Response to External Pressure in the Sacral Region of Elderly Individuals: Using an Optical Probe Prototype2010In: Microcirculation, ISSN 1073-9688, E-ISSN 1549-8719, Vol. 17, no 4, p. 311-319Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: The aim was to investigate the existence of sacral tissue blood flow at different depths in response to external pressure and compression in elderly individuals using a newly developed optical probe prototype. METHODS: The tissue blood flow and tissue thickness in the sacral area were measured during load in 17 individuals using laser Doppler flowmetry and photoplethysmography in a combined probe, and digital ultrasound. RESULTS: The mean age was 68.6 +/- 7.0 years. While loading, the mean compression was 60.3 +/- 11.9%. The number of participants with existing blood flow while loading increased with increased measurement depth. None had enclosed blood flow deep in the tissue and at the same time an existing more superficial blood flow. Correlation between tissue thickness and BMI in unloaded and loaded sacral tissue was shown: r = 0.68 (P = 0.003) and r = 0.68 (P = 0.003). CONCLUSIONS: Sacral tissue is highly compressed by external load. There seems to be a difference in responses to load in the different tissue layers, as occluded blood flow in deeper tissue layers do not occur unless the blood flow in the superficial tissue layers is occluded.

  • 26. Bergstrand, Sara
    et al.
    Lindberg, Lars-Göran
    Ek, Anna-Christina
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindgren, Margareta
    Blood flow measurements at different depths using photoplethysmography and laser Doppler techniques2009In: Skin research and technology, ISSN 0909-752X, E-ISSN 1600-0846, Vol. 15, p. 139-147Article in journal (Refereed)
    Abstract [en]

    This study has evaluated a multi-parametric system combining laser Doppler flowmetry and photoplethysmography in a single probe for the simultaneous measurement of blood flow at different depths in the tissue. This system will be used to facilitate the understanding of pressure ulcer formation and in the evaluation of pressure ulcer mattresses.

    The blood flow in the tissue over the sacrum was measured before, during and after loading with 37.5 mmHg, respectively, 50.0 mmHg. The evaluation of the system consisted of one clinical part, and the other part focusing on the technicalities of the probe prototype.

    An increase in blood flow while loading was the most common response, but when the blood flow decreased during loading it was most affected at the skin surface and the blood flow responses may be different due to depths of measurement. Reactive hyperaemia may occur more frequently in the superficial layers of the tissue.

    The study showed that the new system is satisfactory for measuring tissue blood flow at different depths. The laser Doppler complements the photoplethysmography, and further development of the system into a thin flexible probe with the ability to measure a larger area is required.

  • 27.
    Björkman, Mats
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Trådlösa sensornät i vård och omsorg2009In: Medicinteknikdagarna 2009, 2009Conference paper (Refereed)
  • 28. Blobel, Bernd
    et al.
    Lindén, MariaMälardalen University, School of Innovation, Design and Engineering, Embedded Systems.Ahmed, Mobyen UddinMälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Proceedings of the 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health: pHealth20152015Conference proceedings (editor) (Other academic)
  • 29.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Motion Control i Västerås AB, Västerås.
    Gerdtman, C.
    Motion Control i Västerås AB, Västerås.
    Gharehbaghi, Arash
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A signal processing algorithm for improving the performance of a gyroscopic head-borne computer mouse2017In: Biomedical Signal Processing and Control, ISSN 1746-8094, E-ISSN 1746-8108, Vol. 35, p. 30-37Article in journal (Refereed)
    Abstract [en]

    This paper presents a signal processing algorithm to remove different types of noise from a gyroscopic head-borne computer mouse. The proposed algorithm is a combination of a Kalman filter (KF), a Weighted-frequency Fourier Linear Combiner (WFLC) and a threshold with delay method (TWD). The gyroscopic head-borne mouse was developed to assist persons with movement disorders. However, since MEMS-gyroscopes are usually sensitive to environmental disturbances such as shock, vibration and temperature change, a large portion of noise is added at the same time as the head movement is sensed by the MEMS-gyroscope. The combined method is applied to the specially adapted mouse, to filter out different types of noise together with the offset and drift, with marginal need of the calculation capacity. The method is examined with both static state tests and movement operation tests. Angular position is used to evaluate the errors. The results demonstrate that the combined method improved the head motion signal substantially, with 100.0% error reduction during the static state, 98.2% position error correction in the case of movements without drift and 99.9% with drift. The proposed combination in this paper improved the static stability and position accuracy of the gyroscopic head-borne mouse system by reducing noise, offset and drift, and also has the potential to be used in other gyroscopic sensor systems to improve the accuracy of signals. 

  • 30.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gerdtman, C.
    Motion Control i Västerås AB, Västerås, Sweden .
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Signal processing algorithms for position measurement with MEMS-based accelerometer2015In: IFMBE Proceedings, vol. 48, 2015, p. 36-39Conference paper (Refereed)
    Abstract [en]

    This paper presents signal processing algorithms for position measurements with MEMS-accelerometers in a motion analysis system. The motion analysis system is intended to analyze the human motion with MEMS-based-sensors which is a part of embedded sensor systems for health. MEMS-accelerometers can be used to measure acceleration and theoretically the velocity and position can be derived from the integration of acceleration. However, there normally is drift in the measured acceleration, which is enlarged under integration. In this paper, the signal processing algorithms are used to minimize the drift during integration by MEMS-based accel-erometer. The simulation results show that the proposed algorithms improved the results a lot. The algorithm reduced the drift in one minute by about 20 meters in the simulation. It can be seen as a reference of signal processing for the motion analysis system with MEMS-based accelerometer in the future work.

  • 31.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gerdtman, C.
    Motion Control i Vasteras AB, Vasteras, Sweden .
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Signal processing algorithms for temperauture drift in a MEMS-gyro-based head mouse2014In: Int. Conf. Syst. Signals Image Process., 2014, p. 123-126Conference paper (Refereed)
    Abstract [en]

    This paper presents a comparison between different signal processing algorithms applied to a gyro-based computer head mouse for persons with movement disorders. MEMS-gyros can be used to sense the head movement and rotation. However, the measured gyro signals are influenced by noise, offset, drift and especially temperature drift. Thus, there is a need to improve the signal by signal processing algorithms. Different gyros have different characteristics and the algorithms should be useful for any selected MEMS-gyro. In this paper, three different signal processing algorithms were designed and evaluated by simulation in MATLAB and implementation in a dsPIC, with the aim to compensate for the temperature drift problem. The algorithms are high-pass filtering, Kalman algorithm and Least Mean Square (LMS) algorithm. Comparisons and system test show that these filters can be used for temperature drift compensation and the Kalman filter showed the best in the application of a MEMS-gyro-based computer head mouse.

  • 32.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Motion Control i Västerås AB, Västerås, Sweden.
    Gerdtman, C.
    Motion Control i Västerås AB, Västerås, Sweden.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Signal quality improvement algorithms for MEMS gyroscope-based human motion analysis systems: A systematic review2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 4, article id 1123Article in journal (Refereed)
    Abstract [en]

    Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented.

  • 33.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gerdtman, Christer
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Development of a MEMS-sensor based motion analysis system for human movement rehabilitation2017In: International conference on movement: brain, body, cognition Movement2017, 2017Conference paper (Refereed)
  • 34.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gerdtman, Christer
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Motion Control i Västerås AB.
    Noise reduction for a MEMS-­gyroscope-­based head mouse2015In: Studies in Health Technology and Informatics, Volume 211: Proceedings of the 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 2–4 June 2015, Västerås, Sweden, Västerås, Sweden: IOS Press , 2015, p. 98-104Conference paper (Refereed)
    Abstract [en]

    In this paper, four different signal processing algorithms which can be applied to reduce the noise from a MEMS-gyroscope-based computer head mouse are presented. MEMS-gyroscopes are small, light, cheap and widely used in many electrical products. MultiPos, a MEMS-gyroscope-based computer head mouse system was designed for persons with movement disorders. Noise such as physiological tremor and electrical noise is a common problem for the MultiPos system. In this study four different signal processing algorithms were applied and evaluated by simulation in MATLAB and implementation in a dsPIC, with aim to minimize the noise in MultiPos. The algorithms were low-pass filter, Least Mean Square (LMS) algorithm, Kalman filter and Weighted Fourier Linear Combiner (WFLC) algorithm. Comparisons and system tests show that these signal processing algorithms can be used to improve the MultiPos system. The WFLC algorithm was found the best method for noise reduction in the application of a MEMS-gyroscope-based head mouse.

  • 35.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gerdtman, Christer
    Mot Control & Vasteras AB, Angsgardsgatan 10, S-72130 Vasteras, Sweden..
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Malardalen Univ, Sch Innovat Design & Engn, Gurksaltargatan 9, S-72218 Vasteras, Sweden..
    Signal processing algorithms for temperauture drift in a MEMS-gyro-based head mouse2014In: 21ST INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP 2014) / [ed] Mustra, M Tralic, D Grgic, M ZovkoCihlar, B, IEEE , 2014, p. 123-126Conference paper (Refereed)
    Abstract [en]

    This paper presents a comparison between different signal processing algorithms applied to a gyro-based computer head mouse for persons with movement disorders. MEMS-gyros can be used to sense the head movement and rotation. However, the measured gyro signals are influenced by noise, offset, drift and especially temperature drift. Thus, there is a need to improve the signal by signal processing algorithms. Different gyros have different characteristics and the algorithms should be useful for any selected MEMS-gyro. In this paper, three different signal processing algorithms were designed and evaluated by simulation in MATLAB and implementation in a dsPIC, with the aim to compensate for the temperature drift problem. The algorithms are high-pass filtering, Kalman algorithm and Least Mean Square (LMS) algorithm. Comparisons and system test show that these filters can be used for temperature drift compensation and the Kalman filter showed the best in the application of a MEMS-gyro-based computer head mouse.

  • 36.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gerdtman, Christer
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Signal processing to improve the MEMS sensor signal in a small embedded sensor system for health2017In: Medicinteknikdagarna 2017 MTD 2017, 2017Conference paper (Refereed)
  • 37.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kade, Daniel
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Motion Control i Västerås AB, Västerås, Sweden.
    Gerdtman, Christer
    Motion Control i Västerås AB, Västerås, Sweden.
    Lindell, Rikard
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ozcan, Oguzhan
    Arçelik Research Center for Creative Industries, Koç University, Rumelifeneri, Sarıyer, İstanbul, Turkey.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Perception of Delay in Computer Input Devices Establishing a Baseline for Signal Processing of Motion Sensor Systems2016In: The 3rd EAI International Conference on IoT Technologies for HealthCare HealthyIoT'16, Västeraås, Sweden, 2016, Vol. 187, p. 107-112Conference paper (Refereed)
    Abstract [en]

    New computer input devices in healthcare applications using small embedded sensors need firmware filters to run smoothly and to provide a better user experience. Therefore, it has to be investigated how much delay can be tolerated for signal processing before the users perceive a delay when using a computer input device. This paper is aimed to find out a threshold of unperceived delay by performing user tests with 25 participants. A communication retarder was used to create delays from 0 to 100 ms between a receiving computer and three different USB-connected computer input devices. A wired mouse, a wifi mouse and a head-mounted mouse were used as input devices. The results of the user tests show that delays up to 50ms could be tolerated and are not perceived as delay, or depending on the used device still perceived as acceptable.

  • 38.
    Du, Jiaying
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kade, Daniel
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gerdtman, Christer
    Motion Control, Västerås, Sweden.
    Özcan, Oguzhan
    Koç University, Turkey.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    The effects of perceived USB-delay for sensor and embedded system development2016In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBSVolume 2016, 2016, p. 2492-2495, article id 7591236Conference paper (Refereed)
    Abstract [en]

    Perceiving delay in computer input devices is a problem which gets even more eminent when being used in healthcare applications and/or in small, embedded systems. Therefore, the amount of delay found as acceptable when using computer input devices was investigated in this paper. A device was developed to perform a benchmark test for the perception of delay. The delay can be set from 0 to 999 milliseconds (ms) between a receiving computer and an available USB-device. The USB-device can be a mouse, a keyboard or some other type of USB-connected input device. Feedback from performed user tests with 36 people form the basis for the determination of time limitations for the USB data processing in microprocessors and embedded systems without users' noticing the delay. For this paper, tests were performed with a personal computer and a common computer mouse, testing the perception of delays between 0 and 500 ms. The results of our user tests show that perceived delays up to 150 ms were acceptable and delays larger than 300 ms were not acceptable at all.

  • 39.
    Ekström, Martin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Bergblomma, Marcus
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Mikael
    Edith Cowan University, Bunbury, Australia.
    A Bluetooth Radio Energy Consumption Model for Low Duty-Cycle Applications2012In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 61, no 3, p. 609-617Article in journal (Refereed)
    Abstract [en]

    This paper presents a realistic model of the radio energy consumption for Bluetooth-equipped sensor nodes used in a low-duty-cycle network. The model is based on empirical energy consumption measurements of Bluetooth modules. This model will give users the possibility to optimize their radio communication with respect to energy consumption while sustaining the data rate. This paper shows that transmission power cannot always be directly related to energy consumption. Measurements indicate that, when the transmission power ranges from $-$5 to $+$10 dBm, the difference in consumed energy can be detected for each transmission peak in the sniff peak. However, the change is negligible for the overall energy consumption. The nonlinear behavior of the idle state for both master and slave when increasing the interval and number of attempts is presented. The energy consumption for a master node is in direct relation to the number of slaves and will increase by approximately 50% of the consumption of one slave per additional slave, regardless of the radio setting.

  • 40.
    Ekström, Martin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Bergblomma, Marcus
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Comparison study of ZigBee and Bluetooth with regards to power consumption, packet-error-rate and distanceManuscript (preprint) (Other academic)
    Abstract [en]

    This paper present a empirical measurement comparison study of ZigBee and Bluetooth. The parameters investigated are power consumption, packet-error-rate or retransmissions and distance in different environments. This study shows the differences and similarities for the two different short range radio technologies. A measurement set-up and procedure that makes it possible to investigate power consumption of the radio module, retransmissions and packet-error-rate as well as ambient noise is presented. For both the Bluetooth and the ZigBee modules used in this study the distance itself have no influence of the power consumption. However the retransmission rate and packet-error-rate have a large influence on the power consumption. This study have show that the environment has a great impact on the range of the radio modules and the behaviour concerning the retransmission rate and packet-error-rate.

  • 41.
    Ekström, Martin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Bergblomma, Marcus
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Development of Programmable Micro Power Meter Testbed for Radio ModulesManuscript (preprint) (Other academic)
    Abstract [en]

    This paper presents the POMPOM testbed for high precision power consumption \textit{in situ} measurements for interchangeable radio modules.The main requirements for the development have been;

    Interchangeable radio modules to enable the same hardware testbed to be used independently of the radio standard used make comparison studies possible.

    The testbed should be programmable so that the need for hardware development should be minimized. The testbed must be able to act as a controller for the communication and simultaneously make accurate \textit{in situ} measurements of the energy consumption of the radio.

    The required sample rate must be at least 50 kSamples per second. The range of the current measurement should cover at least 0.2~$\mu$Ampere to 60~mAmpere with at least 14-bit resolution.

    Mobility, low cost and small size are vital for the testbed. It must be possible to deploy several measurement testbeds to act as sensor nodes in a wireless sensor network to capture the behavior of the entire network.

    The results for test measurement setup for POMPOM is presented to illustrate a typical usage of the testbed. The results presented show how the testbed can be used to investigate the correlation between distance, packet-error-rate and current consumption for a Zigbee radio.

  • 42.
    Ekström, Martin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Blom, Marcus
    Mälardalen University, School of Innovation, Design and Engineering.
    Garcia Castaño, Javier
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Ekström, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Bluetooth energy characteristics in wireless sensor networks2008In: 2008 3RD INTERNATIONAL SYMPOSIUM ON WIRELESS PERVASIVE COMPUTING, VOLS 1-2, 2008, p. 198-202Conference paper (Refereed)
    Abstract [en]

    In this paper a measurement system to create an experimental model and a tool box for simulations concerning both the energy consumption and the time aspect when creating wireless sensor networks using Bluetooth 2.0 + enhanced data rate has been developed. Further energy and time characteristics for critical events when using Bluetooth 2.0 in wireless sensor networks are investigated experimentally, with the main events; create connection, send data, receive data, and idle state. Results show that when allowing higher latencies for the connection in the Wireless Sensor Networks the power consumption drops drastically when using low power mode as sniff.

  • 43.
    Folke, Mia
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Bexander, Catharina
    Mälardalen University, School of Innovation, Design and Engineering.
    Gerdtman, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Brodd, Anita
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Sensor system for rehabilitation of patients suffering from WAD 2009In: Medicinteknikdagarna, Vasteras, 2009Conference paper (Refereed)
  • 44.
    Folke, Mia
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Hermans, Frederic
    Mälardalen University, School of Innovation, Design and Engineering.
    Rodhe, Ioana
    Mälardalen University, School of Innovation, Design and Engineering.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Gunningberg, Per
    Mälardalen University, School of Innovation, Design and Engineering.
    A non-invasive, mobile system for lactate threshold estimation2011In: Medicinteknikdagarna 2011, Linkoping, Sweden, 2011Conference paper (Refereed)
  • 45.
    Folke, Mia
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Hermans, Frederic
    Rodhe, Ioana
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Gunningberg, Per
    Mobile system for establishing the lactate threshold by analysing the respiratory air2011Conference paper (Refereed)
  • 46.
    Gardasevic, Gordana
    et al.
    University of Banja Luka, Bosnia-Herzegovina.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomasic, Ivan
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Vahabi, Maryam
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Heterogeneous IoT-based Architecture for Remote Monitoring of Physiological and Environmental Parameters2018In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, p. 48-53Conference paper (Refereed)
    Abstract [en]

    A heterogeneous Internet of Things (IoT) architecture for remote health monitoring (RHM) is proposed, that employs Bluetooth and IEEE 802.15.4 wireless connectivity. The RHM system encompasses Shimmer physiological sensors with Bluetooth radio, and OpenMote environmental sensors with IEEE 802.15.4 radio. This system architecture collects measurements in a relational database in a local server to implement a Fog node for fast data analysis as well as in a remote server in the Cloud. 

  • 47.
    Gerdtman, Christer
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Ahlfont, Jesper
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Oscillating Test Rig for MEMS gyroscopes2012Conference paper (Refereed)
    Abstract [en]

    Motion sensors like MEMS accelerometers and gyroscopes (gyros) are rather small, cheap and reliable sensors that have found their place in a variety of applications. Some of the applications are in the field of human motion measurements. This is a growing market field and an increasing number of MEMS sensors find their way into products for human measurements, such as fall detection, running sensor, movement capacity analysis and stress measurement. In many of these applications the sensors are supposed to be worn by a human for a longer time to track their movements in one way or another. For MEMS gyros in particular, it is interesting to study the sensors reactions to typical human movements over time. Comparing humans and machines, human movements are often smoother and more oscillating than the more linear movement pattern of a machine. Datasheets for gyros usually only specify hard performance like resistance to impact and shock. It is also quite common that the datasheets are incorrect, especially for brand new sensors being released in new versions.

  • 48.
    Gerdtman, Christer
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Bäcklund, Ylva
    Office for Science and Technology, Uppsala University, Uppsala, Sweden.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    A gyro sensor based computer mouse with a USB interface: A technical aid for motor-disabled people2012In: Technology and disability, ISSN 1055-4181, Vol. 24, no 2, p. 117-127Article in journal (Refereed)
    Abstract [en]

    The aim of this study was to develop an alternative computer mouse for disabled persons. The mouse developed is a flexible input device with a multi-click function, which can be attached to a selectable body part (eg head, arm, foot). The mouse has a MEMS-gyroscope as the motion sensor, which is both small and sensitive. A USB-interface with a HID-profile is used to make the installation easy, "plug & play", and to make it compatible for use on any modern computer, independent of the operating system (Windows, Linux, Mac etc.). The structure is modular to achieve a flexible functionality. The mouse has individually adapted click-functions with selectable click devices, in addition to which, it is possible to define individual settings of the mouse parameters. The functionality can be extended by adding further personal settings, thereby programming the mouse for individual optimal performance. The result is a reliable and useful computer mouse for people with disabilities. In the development process, 23 users have been interviewed, three of whom participated in a 6 month long-term test. The study shows that a computer mouse incorporating a MEMS-gyroscope is a good, flexible solution, providing a high performance technical aid with extremely good sensitivity at a modest cost.

  • 49.
    Gerdtman, Christer
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Bäcklund, Ylva
    Uppsala University.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Development of a Test Rig for MEMS-based Gyroscopic Motion Sensors in Human Applications2011In: IFMBE Proceedings,  Volume 34 IFMBE, 2011, 2011, p. 203-206Conference paper (Refereed)
    Abstract [en]

    This paper describes the development of a test rig for MEMS gyroscopes. The purpose of the test rig is testing and verification of various gyroscopes that are intended for human motion analysis. The test rig will be a tool to test functionality and help in the selection process of appropriate MEMS-gyroscopes. Human movement pattern differs from mechanical motion and thus puts specific demands on the test equipment and verification procedures. The main function of the test rig is to rotate the gyroscope and measure the precision in the sensor signal response in different situations. This includes detection of different movement patterns and performances in different environment conditions (e.g. temperature, vibrations, etc). Several components can be tested at the same time in the test rig. Among the things that can be evaluated is the performance of the components, comparisons between different individual components or batches, aging processes of components and verification of the component performance for comparison of the specifications from the manufacturer. There are several different pre-programmed test-programs available but the test rig can also be manually operated. The data from the tests are stored and can be analyzed and processed afterwards.

  • 50.
    Gerdtman, Christer
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering.
    Bexander, Catharina
    Hälsans hus.
    Brodd, Anita
    Mälardoktorerna HB.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Portable sensor system for rehabilitation of WAD patients2009In: IEEE Xplore proceedings of the 6 th international workshop on Wearable Micro and Nanosystems for Personalised Health (pHealth 2009), 24-26 June 2009, Oslo, Norway, IEEE , 2009, p. 65-68Conference paper (Refereed)
    Abstract [en]

    Whiplash Associated Disorders (WAD) are several remaining symptoms after an acceleration-/deceleration injury of the neck, often due to a road accident. Common symptoms are neck pain, headache, stiffness, loss of sensation, memory impairment and concentration difficulties. The whiplash-related injuries were estimated to cost Sweden more than SEK 4 billion 2005, the main part of these costs takes the form of compensation for loss of income, as a result of incapacity for work. The aim of this project has been to develop a training and rehabilitation system for patients suffering from WAD. The portable system is based on a 2-axis gyroscopic sensor with a computer interface. The sensor system is placed on the head of the patient and movements of the head are mirrored on the computer screen. The patient is supposed to follow a visible track on the screen. This enables interactive training facilities for patients, who can use the system unsupervised in their home environment.

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