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  • 1. Berggren, Magnus
    et al.
    Stjernberg, Louise
    BTH.
    Lindström, Fredric
    Claesson, Ingvar
    Audio Processing Solution for Video Conference Based Aerobics2010Conference paper (Refereed)
    Abstract [en]

    In this paper an audio processing solution for video conference based aerobics is presented. The proposed solution leaves the workout music unaltered by separating it from the speech and processing each signal separately. The speech signal processing is also performed at a lower sample rate, which saves computational power. Real time evaluation of the system shows that high quality music as well as a good two-way communication is maintained during the aerobic session.

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  • 2.
    Brondin, Anna
    et al.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Nordström, Marcus
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Olsson, Carl Magnus
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Salvi, Dario
    Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Open source step counter algorithm for wearable devices2020In: Companion Proceedings of the 10th International Conference on the Internet of Things (IoT 2020), New York, United States: ACM Digital Library, 2020, article id 6Conference paper (Refereed)
    Abstract [en]

    Commercial wearable devices and fitness trackers are commonly sold as black boxes of which little is known about their accuracy. This poses serious issues especially in health-related contexts such as clinical research, where transparency about accuracy and reliability are paramount.

    We present a validated algorithm for computing step counting that is optimised for use in constrained computing environments. Released as open source, the algorithm is based on the windowed peak detection approach, which has previously shown high accuracy on smartphones. The algorithm is optimised to run on a programmable smartwatch (Pine Time) and tested on 10 subjects in 8 scenarios, with varying varying positions of the wearable and walking paces.

    Our approach achieves a 89% average accuracy, with the highest average accuracy when walking outdoor (98%) and the lowest in a slow-walk scenario (77%). This result can be compared with the built-in step counter of the smartwatch (Bosch BMA421), which yielded a 94% average accuracy for the same use cases. Our work thus shows that an open-source approach for extracting physical activity data from wearable devices is possible and achieves an accuracy comparable to the one produced by proprietary embedded algorithms.

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  • 3.
    Engström, Jimmy
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Sony Europe B.V., Lund, Sweden.
    Improving Indoor Positioning With Adaptive Noise Modeling2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 227213-227221Article in journal (Refereed)
    Abstract [en]

    Indoor positioning is important for applications within Internet of Things, such as equipment tracking and indoor maps. Inexpensive Bluetooth-beacons have become common for such applications, where the distance is estimated using the Received Signal Strength. Large installations require substantial efforts, either in determining the exact location of all beacons to facilitate lateration, or collecting signal strength data from a grid over all locations to facilitate fingerprinting. To reduce this initial setup cost, one may infer the positions using Simultaneous Location and Mapping. In this paper, we use a mobile phone equipped with an Inertial Measurement Unit, a Bluetooth receiver, and an Unscented Kalman Filter to infer beacon positions. Further, we apply adaptive noise modeling in the filter based on the estimated distance of the beacons, in contrast to using a fixed noise estimate which is the common approach. This gives us more granular control of how much impact each signal strength reading has on the position estimates. The adaptive model decreases the beacon positioning errors by 27% and the user positioning errors by 21%. The positioning accuracy is 0.3 m better compared to using known beacon positions with fixed noise, while the effort to setup and maintain the position of each beacon is also substantially reduced. Therefore, adaptive noise modeling of Received Signal Strength is a significant improvement over static noise modeling for indoor positioning.

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  • 4.
    Engström, Jimmy
    et al.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP). Sony Europe BV, S-22362 Lund, Sweden..
    Jevinger, Åse
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Persson, Jan A.
    Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Some Design Considerations in Passive Indoor Positioning Systems2023In: Sensors, E-ISSN 1424-8220, Vol. 23, no 12, article id 5684Article in journal (Refereed)
    Abstract [en]

    User location is becoming an increasingly common and important feature for a wide range of services. Smartphone owners increasingly use location-based services, as service providers add context-enhanced functionality such as car-driving routes, COVID-19 tracking, crowdedness indicators, and suggestions for nearby points of interest. However, positioning a user indoors is still problematic due to the fading of the radio signal caused by multipath and shadowing, where both have complex dependencies on the indoor environment. Location fingerprinting is a common positioning method where Radio Signal Strength (RSS) measurements are compared to a reference database of previously stored RSS values. Due to the size of the reference databases, these are often stored in the cloud. However, server-side positioning computations make preserving the user's privacy problematic. Given the assumption that a user does not want to communicate his/her location, we pose the question of whether a passive system with client-side computations can substitute fingerprinting-based systems, which commonly use active communication with a server. We compared two passive indoor location systems based on multilateration and sensor fusion using an Unscented Kalman Filter (UKF) with fingerprinting and show how these may provide accurate indoor positioning without compromising the user's privacy in a busy office environment.

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  • 5.
    Håkansson, Dennis
    et al.
    Malmö University, Faculty of Technology and Society (TS).
    Lövberg, Johan
    Malmö University, Faculty of Technology and Society (TS).
    Development of algorithm for a mobile-based estimation of heart rate2021Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    To perform a physical performance test is a good way to keep track of one’s health and can be beneficial to find evidence of deviations in the body. This thesis focuses on the development of a mobile-based heart rate algorithm that can be used with the Queens College Step Test, on the behalf of Mobistudy. Mobistudy wants to include such a test in their mobile application which aims to become a tool for researchers to use to gather data. The algorithm uses the mobile device’s camera to collect data from the user’s finger and uses that data to calculate the heart rate. The algorithm was first tested with data collected during the development and the results has an average error of less than 5% and a standard deviation of less than 3%. Two participants between the age of 20-25 performed three sets each of the Queens College Step Test and the results showed that the algorithm was accurate in its estimation of the heart rate after the test. 

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  • 6.
    Jayram, Shastri
    et al.
    Univ Johannesburg, Dept Elect & Elect Engn Sci, Auckland Pk, Johannesburg, South Africa..
    Ouahada, Khmaies
    Univ Johannesburg, Dept Elect & Elect Engn Sci, Auckland Pk, Johannesburg, South Africa..
    Rimer, Suvendi
    Univ Johannesburg, Dept Elect & Elect Engn Sci, Auckland Pk, Johannesburg, South Africa..
    Pitsillides, Andreas
    Univ Johannesburg, Dept Elect & Elect Engn Sci, Auckland Pk, Johannesburg, South Africa.;Univ Cyprus, Nicosia, Cyprus..
    Mekuria, Fisseha
    CSIR, Future Wireless Networks, Pretoria, South Africa..
    Stochastically Resonant Spectrum Sensing for White Space Communications Dynamic Spectrum Access and Intelligent Radios and Networks2018In: Proceedings of 2018 2nd International Conference on Recent Advances in Signal Processing, Telecommunications and Computing (SigTelCom) / [ed] Bao, VNQ Duy, TT, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 208-213Conference paper (Refereed)
    Abstract [en]

    This paper proposes and investigates Stochastically Resonant Spectrum Sensing (SRSS) in order to expedite Dynamic Spectrum Access and TV White Space (TVWS) communications. SRSS adds noise to a signal in order to enhance its Signal-to-Noise Ratio (SNR) and can be useful in sensing and detecting weak signals, e.g. weak Primary User or even Secondary User activity in TVWS. We demonstrate that SR is a useful Spectrum Sensing technique and can improve SNRs by similar to 8-10 dB using MATLAB simulations. Typically, SRSS uses only Additive SR Noise and we include and also investigate Multiplicative SR Noise effects, showing that in certain instances the latter can also improve SNRs by similar to 2 dB. We compare the Additive versus the combined Additive and Multiplicative cases using Uniform and Normal/ Gaussian distributions and present our results. Our ultimate goal is to include SRSS in an IEEE/DySPAN-SC 1900.* Standards based Interference Managing Ontological Cognitive Radio, Intelligent Radio or Policy Based Radio for Ad-Hoc and Heterogeneous i.e. Composite Wireless Networks.

  • 7.
    Li, Yicheng
    et al.
    Jiangsu Univ, Automot Engn Res Inst, Zhenjiang 212013, Jiangsu, Peoples R China.;Wuhan Univ Technol, Hubei Key Lab Transportat Internet Things, Wuhan 430063, Peoples R China..
    Cai, Yingfeng
    Jiangsu Univ, Automot Engn Res Inst, Zhenjiang 212013, Jiangsu, Peoples R China..
    Malekian, Reza
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Wang, Hai
    Jiangsu Univ, Automot Engn Res Inst, Zhenjiang 212013, Jiangsu, Peoples R China..
    Angel Sotelo, Miguel
    Univ Alcala De Henares, Dept Comp Engn, Alcala De Henares 28801, Madrid, Spain..
    Li, Zhixiong
    Ocean Univ China, Sch Engn, Qingdao 266100, Peoples R China.;Yonsei Univ, Yonsei Frontier Lab, 50 Yonsei Ro, Seoul 03722, South Korea..
    Creating navigation map in semi-open scenarios for intelligent vehicle localization using multi-sensor fusion2021In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 184, article id 115543Article in journal (Refereed)
    Abstract [en]

    In order to pursue high-accuracy localization for intelligent vehicles (IVs) in semi-open scenarios, this study proposes a new map creation method based on multi-sensor fusion technique. In this new method, the road scenario fingerprint (RSF) was employed to fuse the visual features, three-dimensional (3D) data and trajectories in the multi-view and multi-sensor information fusion process. The visual features were collected in the front and downward views of the IVs; the 3D data were collected by the laser scanner and the downward camera and a homography method was proposed to reconstruct the monocular 3D data; the trajectories were computed from the 3D data in the downward view. Moreover, a new plane-corresponding calibration strategy was developed to ensure the fusion quality of sensory measurements of the camera and laser. In order to evaluate the proposed method, experimental tests were carried out in a 5 km semi-open ring route. A series of nodes were found to construct the RSF map. The experimental results demonstrate that the mean error of the nodes between the created and actual maps was 2.7 cm, the standard deviation of the nodes was 2.1 cm and the max error was 11.8 cm. The localization error of the IV was 10.8 cm. Hence, the proposed RSF map can be applied to semi-open scenarios in practice to provide a reliable basic for IV localization.

  • 8.
    Liu, Wi
    et al.
    Xuzhou, China.
    Li, Zhixiong
    Iowa State University, USA.
    Sun, Shuaishua
    Tohoku University, 13101 Sendai, Miyagi, Japan.
    Gupta, Munish Kumar
    Shandong University, China.
    Du, H.
    University of Wollongong, Australia.
    Malekian, Reza
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Sotelo, Miguel Angel
    University of Alcal, Spain.
    Li, Weihua
    University of Wollongong, Australia.
    Design a Novel Target to Improve Positioning Accuracy of Autonomous Vehicular Navigation System in GPS Denied Environments2021In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 17, no 11, p. 7575-7588Article in journal (Refereed)
    Abstract [en]

    Accurate positioning is an essential requirement of autonomous vehicular navigation system (AVNS) for safe driving. Although the vehicle position can be obtained in Global Position System (GPS) friendly environments, in GPS denied environments (such as suburb, tunnel, forest or underground scenarios) the positioning accuracy of AVNS is easily reduced by the trajectory error of the vehicle. In order to solve this problem, the plane, sphere, cylinder and cone are often selected as the ground control targets to eliminate the trajectory error for AVNS. However, these targets usually suffer from the limitations of incidence angle, measuring range, scanning resolution, and point cloud density, etc. To bridge this research gap, an adaptive continuum shape constraint analysis (ACSCA) method is presented in this paper to design a new target with optimized identifiable specific shape to eliminate the trajectory error for AVNS. First of all, according to the proposed ACSCA method, we conduct extensive numerical simulations to explore the optimal ranges of the vertexes and the faces for target shape design, and based on these trials, the optimal target shape is found as icosahedron, which composes of 10 vertexes, 20 faces and combines the properties of plane and volume target. Moreover, the algorithm of automatic detection and coordinate calculation is developed to recognize the icosahedron target and calculate its coordinates information for AVNS. Lastly, a series of experimental investigation were performed to evaluate the effectiveness of our designed icosahedron target in GPS denied environments. The experimental results demonstrate that compared with the plane, sphere, cylinder and cone targets, the developed icosahedron target can produce better performances than the above targets in terms of the clustered minimum registration error, ambiguity and range of field-of-view; also can significantly improve the positioning accuracy of AVNS in GPS denied environments.

  • 9.
    Ouhaichi, Hamza
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Towards designing a flexible multimodal learning analytics system2022Licentiate thesis, comprehensive summary (Other academic)
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  • 10.
    Ouhaichi, Hamza
    et al.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Olsson, Helena Holmström
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Bosch, Jan
    Chalmers University of TechnologyGothenburgSweden.
    Dynamic Data Management for Machine Learning in Embedded Systems: A Case Study2019In: Software Business: 10th International Conference, ICSOB 2019, Jyväskylä, Finland, November 18–20, 2019, Proceedings / [ed] Sami Hyrynsalmi; Mari Suoranta; Anh Nguyen-Duc; Pasi Tyrväinen; Pekka Abrahamsson, Springer, 2019Conference paper (Refereed)
    Abstract [en]

    Dynamic data and continuously evolving sets of records are essential for a wide variety of today’s data management applications. Such applications range from large, social, content-driven Internet applications, to highly focused data processing verticals like data intensive science, telecommunications and intelligence applications. However, the dynamic and multimodal nature of data makes it challenging to transform it into machine-readable and machine-interpretable forms. In this paper, we report on an action research study that we conducted in collaboration with a multinational company in the embedded systems domain. In our study, and in the context of a real-world industrial application of dynamic data management, we provide insights to data science community and research to guide discussions and future research into dynamic data management in embedded systems. Our study identifies the key challenges in the phases of data collection, data storage and data cleaning that can significantly impact the overall performance of the system.

  • 11.
    Samandari, Rohan
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Integration of Bluetooth Sensors in a Windows-Based Research Platform2021Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This thesis describes how to build a solution for transmitting data from an           Electroencephalography (EEG) device to a server in real-time while guiding the user through a number of predefined exercises. This solution will be used by Spinal Cord Injury (SCI) patients suffering from neuropathic pain, in order to understand if it is possible to predict such pain from EEG. The collected data will help clinicians analyze the brain activity data from patients who can submit the data from their home. To accomplish this development task, an application was built that connects to a portable EEG device, gather brain activity data from patients, guides patients through a set of imaginary tasks and sends the data to a server. This project made use of a Software Development Kit (SDK) for the Python programming language and a web sockets server written in JavaScript. The application was tested both in terms of usability and end-to-end latency, showing high usability and low latency. The proposed solution will support a clinical trial in Spain with 40 SCI patients.

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  • 12.
    Stefansson, Petter
    et al.
    Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Karlsson, Fredrik
    Sony Network Communications, 223 62 Lund, Sweden.
    Persson, Magnus
    Sony Network Communications, 223 62 Lund, Sweden.
    Olsson, Carl Magnus
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Synthetic generation of passive infrared motion sensor data using a game engine2021In: Sensors, E-ISSN 1424-8220, Vol. 21, no 23, article id 8078Article in journal (Refereed)
    Abstract [en]

    Quantifying the number of occupants in an indoor space is useful for a wide variety of applications. Attempts have been made at solving the task using passive infrared (PIR) motion sensor data together with supervised learning methods. Collecting a large labeled dataset containing both PIR motion sensor data and ground truth people count is however time-consuming, often requiring one hour of observation for each hour of data gathered. In this paper, a method is proposed for generating such data synthetically. A simulator is developed in the Unity game engine capable of producing synthetic PIR motion sensor data by detecting simulated occupants. The accuracy of the simulator is tested by replicating a real-world meeting room inside the simulator and conducting an experiment where a set of choreographed movements are performed in the simulated environment as well as the real room. In 34 out of 50 tested situations, the output from the simulated PIR sensors is comparable to the output from the real-world PIR sensors. The developed simulator is also used to study how a PIR sensor’s output changes depending on where in a room a motion is carried out. Through this, the relationship between sensor output and spatial position of a motion is discovered to be highly non-linear, which highlights some of the difficulties associated with mapping PIR data to occupancy count. 

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