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  • 1.
    Bentes, João
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Khandelwal, Siddhartha
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Carlsson, Hampus
    Halmstad University, School of Information Technology.
    Kärrman, Marcus
    Halmstad University, School of Information Technology.
    Svensson, Tim
    Halmstad University, School of Information Technology.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Novel System Architecture for Online Gait Analysis2017Conference paper (Refereed)
    Abstract [en]

    Although wearable devices can be used to perform continuous gait analysis in daily life, existing platforms only support short-term analysis in quasi-controlled environments. This paper proposes a novel system architecture that is designed for long-term, online gait analysis in free-living environments. Various aspects related to the feasibility and scalability of the proposed system are presented.

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  • 2.
    Byttner, Stefan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Holmberg, Ulf
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    An ion current algorithm for fast determination of high combustion variability2004Conference paper (Refereed)
    Abstract [en]

    It is desirable for an engine control system to maintain a stable combustion. A high combustion variability (typically measured by the relative variations in produced work, COV(IMEP)) can indicate the use of too much EGR or a too lean air-fuel mixture, which results in less engine efficiency(in terms of fuel and emissions) and reduced driveability. The coefficient of variation (COV) of the ion current integral has previously been shown in several papers to be correlated to the coefficient of variation of IMEP for various disturbances (e.g. AFR, EGR and fuel timing). This paper presents a cycle-to-cycle ion current based method of estimating the approximate category of IMEP (either normal burn, slow burn, partial burn or misfire) for the case of lean air-fuel ratio. The rate of appearance of the partial burn and misfire categories is then shown to be well correlated with the onset of high combustion variability(high COV(IMEP)). It is demonstrated that the detection of these categories can result in faster determination(prediction) of high variability compared to only using the COV(Ion integral). Copyright © 2004 SAE International.

  • 3.
    Byttner, Stefan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Holmberg, Ulf
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Using Multiple Cylinder Ion Measurements for Improved Estimation of Combustion Variability2005In: Proceedings of the SAE 2005 World Congress & Exhibition, Warrendale, PA: SAE Inc. , 2005Conference paper (Refereed)
    Abstract [en]

    Estimation of combustion variability can be performed by using ion currents measured at the spark plug. A scheme is here proposed that exploits the potential of using measurements from multiple cylinders to improve the estimation accuracy of combustion variability (measured by the coefficient of variation of IMEP). This is realised by dividing combustion variability into categories and having one classifier running for each cylinder with the ion current as input signal. The final estimate of combustion variability is then formed by a majority vote among the classifiers. This scheme is shown to improve estimation accuracy by up to 15% on measurements taken from highway driving in a production vehicle.

  • 4.
    Byttner, Stefan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Estimation of combustion variability using in-cylinder ionization measurements2001Conference paper (Refereed)
    Abstract [en]

    This paper investigates the use of the ionization current to estimate the Coefficient of Variation for the Indicated Mean Effective Pressure, COV(IMEP), which is a common variable for combustion stability in a spark-ignited engine. Stable combustion in this definition implies that the variance of the produced work, measured over a number of consecutive combustion cycles, is small compared to the mean of the produced work. The COV(IMEP) is varied experimentally either by increasing EGR flow or by changing the air-fuel ratio, in both a laboratory setting (engine in dynamometer) and in an on-road setting. The experiments show a positive correlation between COV(Ion integral), the Coefficient of Variation for the integrated Ion Current, and COV(IMEP), when measured under low load on an engine in a dynamometer, but not under high load conditions. On-road experiments show a positive correlation, but only in the EGR and the lean burn case. An approach based on individual cycle classification for real-time estimation of combustion stability is discussed. © Copyright 2001 Society of Automotive Engineers, Inc.

  • 5.
    Byttner, Stefan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Strategies for handling the fuel additive problem in neural network based ion current interpretation2001Conference paper (Refereed)
    Abstract [en]

    With the introduction of unleaded gasoline, special fuel agents have appeared on the market for lubricating and cleaning the valve seats. These fuel agents often contain alkali metals that have a significant impact on the ion current signal, thus affecting strategies that use the ion current for engine control and diagnosis, e.g., for estimating the location of the pressure peak. This paper introduces a method for making neural network algorithms robust to expected disturbances in the input signal and demonstrates how well this method applies to the case of disturbances to the ion current signal due to fuel additives containing sodium. The performance of the neural estimators is compared to a Gaussian fit algorithm, which they outperform. It is also shown that using a fuel additive significantly improves the estimation of the location of the pressure peak. © 2001 Society of Automotive Engineers, Inc.

  • 6.
    de Morais, Wagner Ourique
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Sant'Anna, Anita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    A Wearable Accelerometer Based Platform to Encourage Physical Activity for the Elderly2008In: Gerontechnology : international journal on the fundamental aspects of technology to serve the ageing society, ISSN 1569-1101, Vol. 07, no 02, p. 129-181Article in journal (Other academic)
    Abstract [en]

    The growth in the elderly population will pose great pressure on the healthcare system to treat common geriatric problem. Preventive approaches like encouraging elderly people to perform physical exercises can decrease the risk of developing chronic diseases. In cases when diseases already have developed, further developments could possibly be retarded. In this work a wearable platform to recognize user’ s    movements    presented.    The    platform    provides interactions with simple computer games designed to promote physical activity.

  • 7.
    Franke, Axel
    et al.
    Lund Institute of Technology, Sweden.
    Einewall, Patrik
    Lund Institute of Technology, Sweden.
    Johansson, Bengt
    Lund Institute of Technology, Sweden.
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Reinmann, Raymond
    Fiat-GM Powertrain, Advanced Engineering, Sweden.
    Larsson, Anders
    Swedish Defence Research Agency, Sweden.
    The effect of in-cylinder gas flow on the interpretation of the ionization sensor signal2003Conference paper (Refereed)
    Abstract [en]

    The location of the peak pressure can serve as a control parameter to adjust ignition timing and optimize engine performance. The ionization sensor, an electrical probe for combustion diagnostics, can provide information about the peak pressure location. However, the reliability of such information is rather poor. In-cylinder gas flow at the electrodes may be one reason for this. We present results from an investigation of the relationship between ionization sensor current and pressure under various gas flow conditions. The gas flow velocity in the vicinity of the electrode gap was measured by LDA. From the results one may infer how the in-cylinder gas flow affects the reliability of the prediction of pressure peak location from the ionization sensor signal. One finding is that high bulk gas flow impairs the precision of the prediction in certain configurations.

  • 8.
    Grubinger, Thomas
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Björklund, Anders
    Volvo AB.
    Hellring, Magnus
    Volvo AB.
    Knowledge Extraction from Real-World Logged Truck Data2009In: SAE International Journal of Commercial Vehicles, ISSN 1946-391X, Vol. 2, no 1, p. 64-74Article in journal (Refereed)
    Abstract [en]

    In recent years more data is logged from the electronic control units on-board in commercial vehicles. Typically, the data is transferred from the vehicle at the workshop to a centralized storage for future analysis. This vast amount of data is used for debugging, as a knowledgebase for the design engineer and as a tool for service planning.

    Manual analysis of this data is often time consuming, due to the rich amount of information contained. However, there is an opportunity to automatically assist in the process based on knowledge discovery techniques, even directly when the trucks data is first offloaded at the workshop. One typical example of how this technique could be helpful is when two groups of trucks behave differently, e.g. one well-functioning group and one faulty group, when the two groups have the same specification. The desired information is the specific difference in the logged data, e.g. what particular sensors or signals are different.

    An evaluation cycle is proposed and applied to extract knowledge from three different large real-world data-sets measured on Volvo long haulage trucks. Information in the logged data that describes the vehicle’s operating environment, allows the detection of trucks that are operated differently from their intended use. Experiments to find such vehicles were conducted and recommendations for an automated application are given.

  • 9.
    Hellring, Magnus
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Munther, Thomas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Carlsson, Christian
    Mecel AB, Gothenburg, Sweden.
    Larsson, Magnus
    Mecel AB, Gothenburg, Sweden.
    Nytomt, Jan
    Mecel AB, Gothenburg, Sweden.
    Robust AFR estimation using the ion current and neural networks1999In: SAE transactions, ISSN 0096-736X, Vol. 108, no 03, p. 1585-1589Article in journal (Refereed)
    Abstract [en]

    A robust air/fuel ratio "soft sensor" is presented based on non-linear signal processing of the ion current signal using neural networks. Care is taken to make the system insensitive to amplitude variations, due to e.g. fuel additives, by suitable preprocessing of the signal. The algorithm estimates the air/fuel ratio to within 1.2% from the correct value, defined by a universal exhaust gas oxygen (UEGO) sensor, when tested on steady state test-bench data and using the raw ion current signal. Normalizing the ion current increases robustness but also increases the error by a factor of two. The neural network soft sensor is about 20 times better in the case where the ion current is not normalized, compared with a linear model. On normalized ion currents the neural network model is about 4 times better than the corresponding linear model. Copyright © 1999 Society of Automotive Engineers, Inc.

  • 10.
    Hellring, Magnus
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Munther, Thomas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Carlsson, Christian
    Mecel AB, Gothenburg, Sweden.
    Larsson, Magnus
    Mecel AB, Gothenburg, Sweden.
    Nytomt, Jan
    Mecel AB, Gothenburg, Sweden.
    Spark advance control using the ion current and neural soft sensors1999In: SAE transactions, ISSN 0096-736X, Vol. 108, no 03, p. 1590-1595Article in journal (Refereed)
    Abstract [en]

    Two spark advance control systems are outlined; both based on feedback from nonlinear neural network soft sensors and ion current detection. One uses an estimate on the location of the pressure peak and the other uses an estimate of the location of the center of combustion. Both quantities are estimated from the ion current signal using neural networks. The estimates are correct within roughly two crank angle degrees when evaluated on a cycle to cycle basis, and roughly within one crank angle degree when the quantities are averaged over consecutive cycles.

    The pressure peak detection based control system is demonstrated on a SAAB 9000 car, equipped with a 2.3 liter low-pressure turbo charged engine, during normal highway driving. © 1998 Society of Automotive Engineers, Inc.

  • 11.
    Hellring, Magnus
    et al.
    Volvo.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Larsson, Magnus
    Mecel AB.
    Ion current based pressure peak detection under different air humidity conditions2000In: Advanced Microsystems for Automotive Applications 2000 / [ed] Sven Krüger, Wolfgang Gessner, New York: Springer , 2000, p. 125-138Conference paper (Other academic)
    Abstract [en]

    A model based soft sensor that estimates the location of the in-cylinder pressure peak from the ion current is described. The soft sensor uses a neural network algorithm and has been implemented in a SAAB 9000 low-pressure turbo production car. It estimates the pressure peak location, in real time, during normal highway driving with an error of 2-3 crank angle degrees. The soft sensor has been tested during normal Scandinavian weather conditions, with a relative air humidity of about 50%, as well as when water is sprayed into the intake manifold, resulting in approximately 100% relative humidity. The neural network based soft sensor is significantly better than that of another method, based on nonlinear Gaussian curve fits, for the same task.

  • 12.
    Jonsson, Magnus
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Wiberg, Per-Arne
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Vision-based low-level navigation using a feed-forward neural network1997In: Proc. International Workshop on Mechatronical Computer Systems for Perception and Action (MCPA'97), Pisa, Italy, Feb. 10-12, 1997, p. 105-111Conference paper (Refereed)
    Abstract [en]

    In this paper we propose a simple method for low-level navigation for autonomous mobile robots, employing an artificial neural network. Both corridor following and obstacle avoidance in indoor environments are managed by the same network. Raw grayscale images of size 32 x 23 pixels are processed one at a time by a feed-forward neural network. The output signals from the network directly control the motor control system of the robot. The feed-forward network is trained using the RPROP algorithm. Experiments in both familiar and unfamiliar environments are reported.

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  • 13.
    Khandelwal, Siddhartha
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Detecting Gait Events from Outdoor Accelerometer Data for Long-term and Continuous Monitoring Applications2014In: 13th International Symposium on 3D Analysis of Human Movement: 14–17 July, 2014, Lausanne, Switzerland, 2014, , p. 4p. 151-154Conference paper (Refereed)
    Abstract [en]

    Detecting gait events is the key to many gait analysis applications which would immensely benefit if the analysis could be carried out using wearable sensors in uncontrolled outdoor environments, enabling continuous monitoring and long-term analysis. This would allow exploring new frontiers in gait analysis by facilitating the availability of more data and empower individuals, especially patients, to avail the benefits of gait analysis in their everyday lives. Previous gait event detection algorithms impose many restrictions as they have been developed from data collected incontrolled, indoor environments. This paper proposes a robust algorithm that utilizes a priori knowledge of gait in conjunction with continuous wavelet transform analysis, to accurately identify heel strike and toe off, from noisy accelerometer signals collected during indoor and outdoor walking. The accuracy of the algorithm is evaluated by using footswitches that are considered as ground truth and the results are compared with another recently published algorithm.

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  • 14.
    Khandelwal, Siddhartha
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Evaluation of the performance of accelerometer-based gait event detection algorithms in different real-world scenarios using the MAREA gait database2017In: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, Vol. 51, p. 84-90Article in journal (Refereed)
    Abstract [en]

    Numerous gait event detection (GED) algorithms have been developed using accelerometers as they allow the possibility of long-term gait analysis in everyday life. However, almost all such existing algorithms have been developed and assessed using data collected in controlled indoor experiments with pre-defined paths and walking speeds. On the contrary, human gait is quite dynamic in the real-world, often involving varying gait speeds, changing surfaces and varying surface inclinations. Though portable wearable systems can be used to conduct experiments directly in the real-world, there is a lack of publicly available gait datasets or studies evaluating the performance of existing GED algorithms in various real-world settings.

    This paper presents a new gait database called MAREA (n=20 healthy subjects) that consists of walking and running in indoor and outdoor environments with accelerometers positioned on waist, wrist and both ankles. The study also evaluates the performance of six state-of-the-art accelerometer-based GED algorithms in different real-world scenarios, using the MAREA gait database. The results reveal that the performance of these algorithms is inconsistent and varies with changing environments and gait speeds. All algorithms demonstrated good performance for the scenario of steady walking in a controlled indoor environment with a combined median F1score of 0.98 for Heel-Strikes and 0.94 for Toe-Offs. However, they exhibited significantly decreased performance when evaluated in other lesser controlled scenarios such as walking and running in an outdoor street, with a combined median F1score of 0.82 for Heel-Strikes and 0.53 for Toe-Offs. Moreover, all GED algorithms displayed better performance for detecting Heel-Strikes as compared to Toe-Offs, when evaluated in different scenarios. © 2016 Elsevier B.V.

  • 15.
    Khandelwal, Siddhartha
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Gait Event Detection in Real-World Environment for Long-Term Applications: Incorporating Domain Knowledge into Time-Frequency Analysis2016In: IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320, E-ISSN 1558-0210, Vol. 24, no 12, p. 1363-1372Article in journal (Refereed)
    Abstract [en]

    Detecting gait events is the key to many gait analysis applications that would benefit from continuous monitoring or long-term analysis. Most gait event detection algorithms using wearable sensors that offer a potential for use in daily living have been developed from data collected in controlled indoor experiments. However, for real-word applications, it is essential that the analysis is carried out in humans’ natural environment; that involves different gait speeds, changing walking terrains, varying surface inclinations and regular turns among other factors. Existing domain knowledge in the form of principles or underlying fundamental gait relationships can be utilized to drive and support the data analysis in order to develop robust algorithms that can tackle real-world challenges in gait analysis. This paper presents a novel approach that exhibits how domain knowledge about human gait can be incorporated into time-frequency analysis to detect gait events from longterm accelerometer signals. The accuracy and robustness of the proposed algorithm are validated by experiments done in indoor and outdoor environments with approximately 93,600 gait events in total. The proposed algorithm exhibits consistently high performance scores across all datasets in both, indoor and outdoor environments. © Copyright 2016 IEEE

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  • 16.
    Khandelwal, Siddhartha
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Identification of Gait Events using Expert Knowledge and Continuous Wavelet Transform Analysis2014In: BIOSIGNALS 2014: Proceedings of the International Conference on Bio-inspired Systems and Signal Processing / [ed] Harald Loose, Guy Plantier, Tanja Schultz, Ana Fred & Hugo Gamboa, [S.l.]: SciTePress, 2014, p. 197-204Conference paper (Refereed)
    Abstract [en]

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

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    Khandelwal_biosignals_2014
  • 17.
    Khandelwal, Siddhartha
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Novel methodology for estimating Initial Contact events from accelerometers positioned at different body locations2018In: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, Vol. 59, p. 278-285Article in journal (Refereed)
    Abstract [en]

    Identifying Initial Contact events (ICE) is essential in gait analysis as they segment the walking pattern into gait cycles and facilitate the computation of other gait parameters. As such, numerous algorithms have been developed to identify ICE by placing the accelerometer at a specific body location. Simultaneously, many researchers have studied the effects of device positioning for participant or patient compliance, which is an important factor to consider especially for long-term studies in real-life settings. With the adoption of accelerometery for long-term gait analysis in daily living, current and future applications will require robust algorithms that can either autonomously adapt to changes in sensor positioning or can detect ICE from multiple sensors locations.

    This study presents a novel methodology that is capable of estimating ICE from accelerometers placed at different body locations. The proposed methodology, called DK-TiFA, is based on utilizing domain knowledge about the fundamental spectral relationships present between the movement of different body parts during gait to drive the time-frequency analysis of the acceleration signal. In order to assess the performance, DK-TiFA is benchmarked on four large publicly available gait databases, consisting of a total of 613 subjects and 7 unique body locations, namely, ankle, thigh, center waist, side waist, chest, upper arm and wrist. The DK-TiFA methodology is demonstrated to achieve high accuracy and robustness for estimating ICE from data consisting of different accelerometer specifications, varying gait speeds and different environments. © 2017 Elsevier B.V.

  • 18.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Lundström, Jens
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A Database-Centric Architecture for Home-Based Health Monitoring2013In: Ambient Assisted Living and Active Aging: 5th International Work-Conference, IWAAL 2013, Carrillo, Costa Rica, December 2-6, 2013, Proceedings / [ed] Christopher Nugent, Antonio Coronato, José Bravo, Heidelberg, Germany: Springer, 2013, Vol. 8277, p. 26-34Chapter in book (Refereed)
    Abstract [en]

    Traditionally, database management systems (DBMSs) have been employed exclusively for data management in infrastructures supporting Ambient Assisted Living (AAL) systems. However, DBMSs provide other mechanisms, such as for security, dependability, and extensibility that can facilitate the development, use, and maintenance of AAL applications. This work utilizes such mechanisms, particularly extensibility, and proposes a database-centric architecture to support home-based healthcare applications. An active database is used to monitor and respond to events taking place in the home, such as bed-exits. In-database data mining methods are applied to model early night behaviors of people living alone. Encapsulating the processing into the DBMS avoids transferring and processing sensitive data outside of database, enables changes in the logic to be managed on-the-fly, and reduces code duplication. As a result, such an approach leads to better performance and increased security and privacy, and can facilitate the adaptability and scalability of AAL systems. An evaluation of the architecture with datasets collected in real homes demonstrated the feasibility and flexibility of the approach.

  • 19.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Lundström, Jens
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Active In-Database Processing to Support Ambient Assisted Living Systems2014In: Sensors, E-ISSN 1424-8220, Vol. 14, no 8, p. 14765-14785Article in journal (Refereed)
    Abstract [en]

    As an alternative to the existing software architectures that underpin the development of smart homes and ambient assisted living (AAL) systems, this work presents a database-centric architecture that takes advantage of active databases and in-database processing. Current platforms supporting AAL systems use database management systems (DBMSs) exclusively for data storage. Active databases employ database triggers to detect and react to events taking place inside or outside of the database. DBMSs can be extended with stored procedures and functions that enable in-database processing. This means that the data processing is integrated and performed within the DBMS. The feasibility and flexibility of the proposed approach were demonstrated with the implementation of three distinct AAL services. The active database was used to detect bed-exits and to discover common room transitions and deviations during the night. In-database machine learning methods were used to model early night behaviors. Consequently, active in-database processing avoids transferring sensitive data outside the database, and this improves performance, security and privacy. Furthermore, centralizing the computation into the DBMS facilitates code reuse, adaptation and maintenance. These are important system properties that take into account the evolving heterogeneity of users, their needs and the devices that are characteristic of smart homes and AAL systems. Therefore, DBMSs can provide capabilities to address requirements for scalability, security, privacy, dependability and personalization in applications of smart environments in healthcare.

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    de_morais_active_2014
  • 20.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Mayr, Matthias
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE). Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Philippsen, Roland
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Ambient Intelligence and Robotics: complementing one another to support Ambient Assisted Living2014In: IAS-13: The 13th International Conference on Intelligent Autonomous Systems: July 15-19, 2014: Padova and Venice, Italy: Proceedings of Workshops and Tutorials / [ed] Jangmyung Lee, Philippe Martinet, Marcus Strand, Stefano Ghidoni & Matteo Munaro, 2014Conference paper (Refereed)
    Abstract [en]

    This work combines a database-centric architecture, which supports Ambient Intelligence (AmI) for Ambient Assisted Living, with a ROS-based mobile sensing and interaction robot. The role of the active database is to monitor and respond to events in the environment and the robot subscribes to tasks issued by the AmI system. The robot can autonomously perform tasks such as to search for and interact with a person. Consequently, the two systems combine their capabilities and complement the lack of computational, sensing and actuation resources.

  • 21.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A lightweight method for detecting sleep-related activities based on load sensing2014In: SeGAH 2014: IEEE 3rd International Conference on Serious Games and Applications for Health, Red Hook, NY: Curran Associates, Inc., 2014, article id 7067080Conference paper (Refereed)
    Abstract [en]

    Current practices in healthcare rely on expensive and labor-intensive procedures that are not adequate for future healthcare demands. Therefore, alternatives are required to complement or enhance healthcare services, both at clinical and home settings. Hospital and ordinary beds can be equipped with load cells to enable load sensing applications, such as for weight and sleep assessment. Beds with such functionalities represent a tangible alternative to expensive and obtrusive routines for sleep assessment, such as polysomnography. A finite-state machine is proposed as a lightweight on-line method to detect sleep-related activities, such as bed entrances and exits, awakenings, wakefulness, and sleep atonia. The proposed approach is evaluated with a dataset collected in real homes of older people receiving night-time home care services.

  • 22.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    A Serious Computer Game to Assist Tai Chi Training for the Elderly2011In: 2011 IEEE 1st International Conference on Serious Games and Applications for Health, SeGAH 2011, Piscataway: IEEE Press, 2011Conference paper (Refereed)
    Abstract [en]

    This paper describes the development of a computer-based serious game to enable older individuals to practice Tai Chi at home on their own. The player plays the game by imitating Tai Chi movements presented by a virtual instructor on the screen. The proposed system is decomposed into two modules. The first module is the game design, i.e., the process of recording an instructor training Tai Chi. Acquired data are used to create gesture templates and a virtual instructor. The second module is the game play in which the player attempts to mimic the virtual instructor. Gestures are measured in real-time and then compared with the prerecorded Tai Chi gesture template corresponding to the displayed movement. Visual feedback indicates how well the player imitated the instructor. The proposed system is not designed to classify gestures but to evaluate the similarity of a given gesture with a gesture template. The Longest Common Sub-Sequence (LCSS) method is applied to compute such similarity. The proposed approach (1) facilitates the design of assessment tools in which the user has to follow a sequence of predefined movements and (2) applicable to other domains, such as telerehabilitation.

  • 23.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A "Smart Bedroom" as an Active Database System2013In: Proceedings – 9th International Conference on Intelligent Environments, IE 2013, Los Alamitos, CA: IEEE Computer Society, 2013, p. 250-253, article id 6597820Conference paper (Refereed)
    Abstract [en]

    Home-based healthcare technologies aim to enable older people to age in place as well as to support those delivering care. Although a number of smart homes exist, there is no established method to architect these systems. This work proposes the development of a smart environment as an active database system. Active rules in the database, in conjunction with sensors and actuators, monitor and respond to events taking place in the home environment. Resource adapters integrate heterogeneous hardware and software technologies into the system. A 'Smart Bedroom' has been developed as a demonstrator. The proposed approach represents a flexible and robust architecture for smart homes and ambient assisted living systems. © 2013 IEEE.

  • 24.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Evaluation of Extensibility, Portability and Scalability in a Database-centric System Architecture for Smart Home Environments2015Report (Refereed)
    Abstract [en]

    Advances in database technology allow modern database systems to serve as a platform for the development, deployment and management of smart home environments and ambient assisted living systems. This work investigates non-functional issues of a database-centric system architecture for smart home environments when: (i) extending the system with new functionalities other than data storage, such as on-line reactive behaviors and advanced processing of longitudinal information, (ii) porting the whole system to different operating systems on distinct hardware platforms, and (iii) scaling the system by incrementally adding new instances of a given functionality. The outcome of the evaluation is demonstrated, and analyzed, for three test functionalities on three heterogeneous computing platforms. As a contribution, this work can help developers in identifying which architectural components in the database-centric system architecture that may become performance bottlenecks when extending, porting and scaling the system.

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    fulltext
  • 25.
    Ourique de Morais, Wagner
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Sleep and night activities of care beneficiaries at the "Trygg om Natten" (Safe at Night) Project2013Report (Other academic)
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    fulltext
  • 26.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Ourique de Morais, Wagner
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Gait Unsteadiness Analysis from Motion Primitives2008In: Gerontechnology : international journal on the fundamental aspects of technology to serve the ageing society, ISSN 1569-1101, Vol. 7, no 2, p. 204-Article in journal (Other academic)
    Abstract [en]

    The development of intelligent ambulatory monitoring systems and smart living environments is important when considering the aging of society and its implications. This work concerns the use of human motion analysis as a tool for supporting elderly life. Movement recognition has so far been achieved through some form of template matching after manual segmentation or modeling of important features. However, previous works have failed to generalize movement and have only been able to recognize few predetermined activities. To cope with those limitations, this work suggests a new “motion language” approach. To demonstrate the viability and usefulness of this methodology, the concept of “motion primitives” was used to quantitatively analyze gait unsteadiness, which relates to physical condition and cognitive performance. The variability of stride time and temporal walk symmetry between the two feet were measured. Accelerometers were chosen as motion sensors since they offer desirable features in monitoring human movements such as response to both movement frequency and intensity, miniaturization and low power consumption. This study shows that a motion language methodology is capable of quantitatively measuring temporal gait characteristics and providing tools for continuous, unobtrusive, home-based gait analysis.

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    SantAnna2008
  • 27.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Salarian, Arash
    Oregon Health and Science Univeristy.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    A new measure of movement symmetry in early Parkinson's disease patients using symbolic processing of inertial sensor data2011In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 58, no 7, p. 2127-2135Article in journal (Refereed)
    Abstract [en]

    Movement asymmetry is one of the motor symptoms associated with Parkinson's Disease (PD). Therefore, being able to detect and measure movement symmetry is important for monitoring the patient's condition.

    The present paper introduces a novel symbol based symmetry index calculated from inertial sensor data. The method is explained, evaluated and compared to six other symmetry measures. These measures were used to determine the symmetry of both upper and lower limbs during walking of 11 early-to-mid-stage PD patients and 15 control subjects. The patients included in the study showed minimal motor abnormalities according to the Unified Parkinson's Disease Rating Scale (UPDRS).

    The symmetry indices were used to classify subjects into two different groups corresponding to PD or control. The proposed method presented high sensitivity and specificity with an area under the Receiver Operating Characteristic (ROC) curve of 0.872, 9\% greater than the second best method. The proposed method also showed an excellent Intraclass Correlation Coefficient (ICC) of 0.949, 55\% greater than the second best method. Results suggest that the proposed symmetry index is appropriate for this particular group of patients.

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    SantAnna2011
  • 28.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    A linguistic approach to the analysis of accelerometerdata for gait analysis2010In: Proceedings of the seventh IASTED International Conference on Biomedical Engineering: February 17-19, 2010, Innsbruck, Austria / [ed] A. Hierlemann, Anaheim, CA: ACTA Press, 2010, p. 8-Conference paper (Refereed)
    Abstract [en]

    There is evidence that many cognitive conditions affect the human motor system. Gait analysis has lately been used as a means of studying this physical-cognitive correlation. The development of gait analysis systems, able to record and analyze gait during normal daily activities and in uncontrolled environment, is an important addition to this area of research. Lately, linguistic approaches have been studied as means to achieve activity classification from vision sensors. The present work aims to extend the linguistic approach to achieve quantitative analysis of gait from accelerometer data. The proposed method can be used to extend the Human Activity Language framework to include the analysis of inertial sensors such as accelerometers. Results show that the proposed method is more accurate and robust than previous methods and can be used to extract a number of clinically relevant gait measurements. A novel symmetry index is presented to exemplify how the proposed method is able to extract more information from accelerometer signals than previous methods.

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    FULLTEXT01
  • 29.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    A Symbol-Based Approach to Gait Analysis From Acceleration Signals: Identification and Detection of Gait Events and a New Measure of Gait Symmetry2010In: IEEE transactions on information technology in biomedicine, ISSN 1089-7771, E-ISSN 1558-0032, Vol. 14, no 5, p. 1180-1187Article in journal (Refereed)
    Abstract [en]

    Gait analysis can convey important information about one’s physical and cognitive condition. Wearable inertial sensor systems can be used to continuously and unobtrusively assess gait during everyday activities in uncontrolled environments. An important step in the development of such systems is the processing and  analysis of the sensor data. This paper presents a symbol-based method used to detect the phases of gait and convey important dynamic information from accelerometer signals. The addition of expert knowledge substitutes the need for supervised learning techniques, rendering the system easy to interpret and easy to improve incrementally. The proposed method is compared to an approach based on peak-detection. A new symbol-based symmetry index is created and compared to a traditional temporal symmetry index and a symmetry measure based on cross-correlation. The symbol-based symmetry index exemplifies how the proposed method can extract more information from the acceleration signal than previous approaches

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    FULLTEXT01
  • 30.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Developing a Motion Language: Gait Analysis from Accelerometer Sensor Systems2009In: Pervasive Health 2009: 3rd International Conference on Pervasive Computing Technologies for Healthcare, Piscataway, N.J.: IEEE Press, 2009, p. 1-8Conference paper (Refereed)
    Abstract [en]

    The advances in sensing technology provide us with the opportunity to develop mobile and unobtrusive systems to continuously gather gait data. Accelerometers have been shown to be an adequate choice for recording human motion data. For that reason, many previous works have investigated the use of accelerometers for gait analysis. Previous works were able to extract either static temporal information or dynamic general information about the gait patterns. This work aims at extracting both static and dynamic information from acceleration signals. The ability to extract information about the dynamics of gait is exemplified with a novel symmetry measure. The method presented here is based on the motion language approach. A method based on peak detection was chosen as a reference, which we compare to our method. A Gait Rite pressure sensitive mat was used to detect heel-strike and toe-off ground truths. Results show that the proposed approach is as accurate as, more robust than, and conveys more information than the reference method.

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    SantAnna2009
  • 31.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Symbolic Approach to Motion Analysis: Framework and Gait Analysis Case Studies2013In: Telehealthcare Computing and Engineering: Principles and Design / [ed] Fei Hu, Boca Raton: CRC Press, 2013, 1, p. 561-606Chapter in book (Other academic)
  • 32.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Symbolization of time series: an evaluation of SAX, persist, and ACA2011In: CISP 2011: Proceedings, the 4th International Congress on Image and Signal Processing, 15-17 October 2011, Shanghai, China / [ed] Peihua Qiu, Piscataway, N.J.: IEEE Press, 2011, p. 2223-2228Conference paper (Refereed)
    Abstract [en]

    Symbolization of time-series has successfully been used to extract temporal patterns from experimental data. Segmentation is an unavoidable step of the symbolization process, and it may be characterized on two domains: the amplitude and the temporal domain. These two groups of methods present advantages and disadvantages each. Can their performance be estimated a priori based on signal characteristics? This paper evaluates the performance of SAX, Persist and ACA on 47 different time-series, based on signal periodicity. Results show that SAX tends to perform best on random signals whereas ACA may outperform the other methods on highly periodic signals. However, results do not support that a most adequate method may be determined a priory.

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    fulltext
  • 33.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Eklund, Helene
    Center for Person-Centered Care, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Tranberg, Roy
    Department of Orthopedics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    A wearable gait analysis system using inertial sensors Part II: Evaluation in a clinical setting2012In: BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing, [S. l.]: SciTePress, 2012, p. 5-14Conference paper (Refereed)
    Abstract [en]

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

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    fulltext
  • 34.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Eklund, Helene
    Sahlgrenska Academy, Göteborg, Sweden.
    Zügner, Roland
    Sahlgrenska Academy, Göteborg, Sweden.
    Tranberg, Roy
    Sahlgrenska Academy, Göteborg, Sweden.
    Assessment of Gait Symmetry and Gait Normality Using Inertial Sensors: In-Lab and In-Situ Evaluation2013In: Biomedical Engineering Systems and Technologies: 5th International Joint Conference, BIOSTEC 2012, Vilamoura, Portugal, February 1-4, 2012, Revised Selected Papers / [ed] Joaquim Gabriel et al., Heidelberg: Springer Berlin/Heidelberg, 2013, p. 239-254Chapter in book (Refereed)
    Abstract [en]

    Quantitative gait analysis is a powerful tool for the assessment of a number of physical and cognitive conditions. Unfortunately, the costs involved in providing in-lab 3D kinematic analysis to all patients is prohibitive. Inertial sensors such as accelerometers and gyroscopes may complement in-lab analysis by providing cheaper gait analysis systems that can be deployed anywhere. The present study investigates the use of inertial sensors to quantify gait symmetry and gait normality. The system was evaluated in-lab, against 3D kinematic measurements; and also in-situ, against clinical assessments of hip-replacement patients. Results show that the system not only correlates well with kinematic measurements but it also corroborates various quantitative and qualitative measures of recovery and health status of hip-replacement patients

    Download full text (pdf)
    fulltext
  • 35.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Zügner, Roland
    Department of Orthopedics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Tranberg, Roy
    Department of Orthopedics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    A wearable gait analysis system using inertial sensors Part I: Evaluation of measures of gait symmetry and normality against 3D kinematic data2012In: BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing, [S. l.]: SciTePress, 2012, p. 180-188Conference paper (Refereed)
    Abstract [en]

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

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    fulltext
  • 36.
    Weman Josefsson, Karin
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Ebbesson, Esbjörn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Sport Health and Physical activity.
    Lund, Jesper
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Application of self-determination theory in the e-health industry – promoting sustainable exercise motivation2015In: Proceeding: 14th European Congress of Sport Psychology: Sport Psychology: Theories and Applications for Performance, Health and Humanity: 14-19 July 2015, Bern, Switzerland / [ed] Olivier Schmid & Roland Seiler, Bern: University of Bern , 2015, p. 372-372Conference paper (Refereed)
    Abstract [en]

    Developing tailored digital interventions for exercise motivation by applying behavioral theory into existing web services in cooperation with the e-health industry could create a mutual base for experience exchange and practical implications. It could also add higher standards to e-health business by providing a scientifically sound and trustworthy foundation for digital solutions. This project aims to design an interactive tool grounded in sport and exercise psychology and combined with the latest expertise from information technology and innovation science, considering e-health industrial requirements and user needs. A main objective is to test the efficacy of using Self-Determination Theory (SDT) in designing, constructing and evaluating an exercise intervention. The digital intervention is based on a literature review mapping exercise motivation related to self-determination theory, complemented by qualitative cross-disciplinary interaction design methodologies, such as qualitative analysis of interviews and contextual observation capturing participant goals, behaviour, preferences, attitudes and frustrations. Intervention contents are essentially autonomy supportive structures, goal-setting support and relapse prevention, self-regulation structures, health information and web links. In February 2015 the intervention prototype will be pilot tested in a randomized controlled trial (RCT), involving existing members and clients (N > 10 000) of two health service companies. Outcomes relate to self-determined exercise motivation (The Basic Psychological Needs in Exercise Scale and The Behavioral Regulation in Exercise Questionnaire-2) and exercise behaviour, measured both by self-report measures (Godin Leisure-Time Exercise Questionnaire) and step counters. The RCT contains three measure points in order to allow advanced analyses of change and mechanisms based on the SDT-process model and motivational profiles. Latent growth curve and structural equation models will primarily be used to analyse data. This pilot study will create a baseline for elaboration into a second phase, were the digital tool will be further developed and longitudinally tested and evaluated over a nine months period. © 2015 University of Bern, Institut of Sport Science 

  • 37.
    Weman Josefsson, Karin
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI). University of Gothenburg, Gothenburg, Sweden.
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Lindwall, Magnus
    University of Gothenburg, Gothenburg, Sweden.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Digital innovations and self-determined exercise motivation: a person-centred perspective2014In: Vitalis – Nordens ledande eHälsomöte 2014: Vetenskapliga papers presenterade vid Vitalis konferens, Svenska Mässan, Göteborg, 8-10 april 2014, Göteborg: Vitalis & Sahlgrenska akademin, Göteborgs universitet , 2014, p. 22-25Conference paper (Refereed)
    Abstract [en]

    Health care costs are increasing twice as fast as wealth, making health promotion and development of cost-effective care increasingly important in order to generate sustainable health care solutions. E-health, applications and interactive tools for exercise promotion flourish; but despite this and an overflow of information regarding health benefits of regular physical activity, exercise adherence has proven to be a significant challenge. This article concerns a project aimed to design an interactive tool based on comprehensive knowledge from the field of psychology combined with expertise from information technology and innovation, based on e-health industrial requirements and user needs. The research group will, together with the expertise and infrastructure of the collaborating companies Health Profile Institute AB and Tappa Service AB, support and progress an existing PhD-project on digital interventions in exercise motivation. This will be done by designing; applying and evaluating a person-centred digital intervention prototype for exercise motivation and adherence enhancement based on Self-Determination Theory.

  • 38.
    Weman Josefsson, Karin
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Sport Health and Physical activity.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Digital interventions in self-determined exercise motivation – interdisciplinary innovations2015In: ISBNPA 2015: Advancing Behavior Change Science : 3rd – 6th June 2015: Abstract Book, 2015, p. 592-592Conference paper (Refereed)
    Abstract [en]

    Purpose:There is a need for scientifically sound and theory based tools and services in e-health. In this project knowledge from the field of psychology will be complemented by expertise in information technology and innovation science in designing a digital intervention based on Self-determination theory (SDT) aiming to facilitate exercise motivation.

    Methods:The intervention will be tested by a three wave RCT design in a population of e-health clients (n = 200) in a web based exercise service. Sensors (step counters) and self-reports (Godin Leisure-Time Exercise Questionnaire) will be used to measure objective and subjective exercise behavior while instruments based on SDT (Basic Psychological Needs in Exercise Scale and Behavioral Regulation in Exercise Questionnaire-2 ) will measure factors related to motivation.  Advanced mediation variable analyses (MVA) and latent growth curve models (LGCM) will be used to explore motivational processes, changes and profiles in relation to exercise behavior.

    Expected Results:Based on the SDT process model, it is hypothesized that a (digital) environment supporting basic psychological need satisfaction will facilitate internalization and enhanced self-determined motivation, which in turn will have a positive effect on exercise behavior.

    Conclusions:Clarifying mechanisms and indirect effects provide knowledge of how intervention effects could be interpreted and understood. Combining high level research design like RCT and advanced analyses as MVA provides valuable contributions to the understanding of theoretical mechanisms of motivation that could inform the tailoring of effective interventions promoting healthy exercise behaviours.  In addition, the project might form a prosperous interdisciplinary fusion generating innovative and theory based digital solutions for e-health.

  • 39.
    Weman-Josefsson, Karin Anna
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Sport Health and Physical activity. University of Gothenburg, Gothenburg, Sweden.
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Sport Health and Physical activity.
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Digital Innovations and Self-determined exercise motivation: an interdisciplinary approach2015In: Proceedings of The 6th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC March 2015. Orlando, Florida., 2015Conference paper (Refereed)
    Abstract [en]

    In face of escalating health care costs, new technology holds great promise for innovative solutions and new, more sustainable health care models. Technology centers around the individual, allowing for greater autonomy and control in health issues and access to tailored information and customized health behavior interventions. While this offers good opportunities for both public health impact and improved well-being at individual levels, it also emphasizes the need for properly designed e-health models firmly based on scientific principles and adequate theoretical frameworks. Consequently, this project aims to design an interactive tool utilizing an interdisciplinary approach combining motivational theory with the fields of information technology and business model innovation. In collaboration with two companies from the e-health industry, the purpose is to design, apply and evaluate a person-centered interactive prototype for maintainable and self-determined exercise motivation.

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    fulltext
  • 40.
    Weman-Josefsson, Karin
    et al.
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Wärnestål, Pontus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Man and Information technology laboratory (MI-lab).
    Johnson, Urban
    Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI).
    Halila, Fawzi
    Halmstad University, School of Business, Engineering and Science, Centre for Innovation, Entrepreneurship and Learning Research (CIEL).
    Wickström, Nicholas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    An interdisciplinary project plan on Digital Innovations and Self-determined Exercise Motivation2013Conference paper (Other academic)
  • 41.
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Virtual sensing of combustion quality in SI engines using the ion current2004Doctoral thesis, comprehensive summary (Other academic)
  • 42.
    Wickström, Nicholas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Byttner, Stefan
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Hellring, Magnus
    Volvo Technology Corporation, Gothenburg, Sweden.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Neural networks for extracting the pressure peak position from the ion current2004In: Virtual sensing of combustion quality in SI engines using the ion current, Göteborg: Chalmers tekniska högskola , 2004, p. 95-110Chapter in book (Other academic)
  • 43.
    Wickström, Nicholas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Byttner, Stefan
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Holmberg, Ulf
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Robust tuning of Individual Cylinders AFR in SI Engines with the Ion Current2005In: SAE Transactions, ISSN 0096-736X, Vol. 114, no 03, p. 48-52Article in journal (Refereed)
    Abstract [en]

    A method for robust tuning of individual cylinders air-fuel ratio is proposed. The fuel injection is adjusted so that each cylinder has the same air-fuel ratio in inner control loops, and the resulting air-fuel ratio in the exhaust pipe is controlled with an exhaust gas oxygen sensor (EGO) in an outer control loop to achieve stoichiometric air-fuel ratio. Correction factors to provide cylinder individual fuel injection timing are calculated based on measurements of the ion currents for the individual cylinders. An implementation in a production vehicle is shown with results from driving on the highway. © 2005 SAE International.

  • 44.
    Wickström, Nicholas
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Larsson, Magnus
    Mecel AB, Åmål, Sweden.
    Taveniku, Mikael
    Chalmers University of Technology, Göteborg, Sweden.
    Linde, Arne
    Chalmers University of Technology, Göteborg, Sweden.
    Svensson, Bertil
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). Chalmers University of Technology, Göteborg, Sweden.
    Neural Virtual Sensors — Estimation of Combustion Quality in SI Engines using the Spark Plug1998In: ICANN 98: Proceedings of the 8th International Conference on Artificial Neural Networks, Skövde, Sweden, 2-4 September 1998 / [ed] Lars Niklasson, Mikael Bodén, Tom Ziemke, London: Springer , 1998, p. 215-220Conference paper (Refereed)
    Abstract [en]

    We propose two virtual sensors which estimate the location of the pressure peak and the air-fuel ratio from measurements of the ionization current across the spark plug gap.

    The location of pressure peak virtual sensor produces estimates on a cycle-by-cycle basis for each of the cylinders. These estimates are twice as good as estimates obtained from a linear model.

    The air-fuel ratio virtual sensor uses the universal exhaust gas oxygen sensor as reference; it produces estimates that are ten times better than estimates obtained from a linear model.

  • 45.
    Wickström, Nicholas
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Taveniku, Mikael
    Chalmers.
    Linde, Arne
    Chalmers.
    Larsson, Magnus
    Mecel AB.
    Svensson, Bertil
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Estimating pressure peak position and air-fuel ratio using the ionization current and artificial neural networks1997In: IEEE Conference on Intelligent Transportation Systems: proceedings, Boston Park Plaza Hotel, Boston, Massachusetts, November 9-12, 1997, Piscataway, N.J.: IEEE , 1997, p. 927-977Conference paper (Other academic)
    Abstract [en]

    We propose two artificial neural network models which use the ionization current for estimation of the position of the pressure peak and the air-fuel ratio. The pressure peak position model produces estimates on a cycle-by-cycle basis for each of the cylinders. These estimates are twice as good as estimates obtained from a linear model. The air-fuel ratio model uses the universal exhaust gas oxygen sensor as reference; it produces estimates that are ten times better than estimates obtained fi om a linear model.

    Download full text (pdf)
    FULLTEXT01
  • 46.
    Wåxnäs, Pär
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Speech Enhancement using Artificial Neural Networks1995Independent thesis Advanced level (degree of Master (One Year))Student thesis
1 - 46 of 46
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