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  • 1.
    Alawadi, Sadi
    et al.
    Uppsala University, Sweden.
    Kebande, Victor R.
    Umeå University, Sweden.
    Dong, Yuji
    School of Internet of ThingsXi’an Jiaotong-Liverpool UniversitySuzhouChina.
    Bugeja, Joseph
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Persson, Jan A.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    A Federated Interactive Learning IoT-Based Health Monitoring Platform2021Ingår i: New Trends in Database and Information Systems, Springer, 2021, s. 235-246Konferensbidrag (Refereegranskat)
    Abstract [en]

    Remote health monitoring is a trend for better health management which necessitates the need for secure monitoring and privacy-preservation of patient data. Moreover, accurate and continuous monitoring of personal health status may require expert validation in an active learning strategy. As a result, this paper proposes a Federated Interactive Learning IoT-based Health Monitoring Platform (FIL-IoT-HMP) which incorporates multi-expert feedback as ‘Human-in-the-loop’ in an active learning strategy in order to improve the clients’ Machine Learning (ML) models. The authors have proposed an architecture and conducted an experiment as a proof of concept. Federated learning approach has been preferred in this context given that it strengthens privacy by allowing the global model to be trained while sensitive data is retained at the local edge nodes. Also, each model’s accuracy is improved while privacy and security of data has been upheld.

  • 2.
    Alawadi, Sadi
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Mera, David
    Centro Singular de Investigación en Tecnoloxías da Información (CiTIUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain.
    Fernandez-Delgado, Manuel
    Centro Singular de Investigación en Tecnoloxías da Información (CiTIUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain.
    Alkhabbas, Fahed
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings2020Ingår i: Energy Systems, Springer Verlag, ISSN 1868-3967, E-ISSN 1868-3975, Vol. 13, s. 689-705Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The international community has largely recognized that the Earth's climate is changing. Mitigating its global effects requires international actions. The European Union (EU) is leading several initiatives focused on reducing the problems. Specifically, the Climate Action tries to both decrease EU greenhouse gas emissions and improve energy efficiency by reducing the amount of primary energy consumed, and it has pointed to the development of efficient building energy management systems as key. In traditional buildings, households are responsible for continuously monitoring and controlling the installed Heating, Ventilation, and Air Conditioning (HVAC) system. Unnecessary energy consumption might occur due to, for example, forgetting devices turned on, which overwhelms users due to the need to tune the devices manually. Nowadays, smart buildings are automating this process by automatically tuning HVAC systems according to user preferences in order to improve user satisfaction and optimize energy consumption. Towards achieving this goal, in this paper, we compare 36 Machine Learning algorithms that could be used to forecast indoor temperature in a smart building. More specifically, we run experiments using real data to compare their accuracy in terms of R-coefficient and Root Mean Squared Error and their performance in terms of Friedman rank. The results reveal that the ExtraTrees regressor has obtained the highest average accuracy (0.97%) and performance (0,058%) over all horizons.

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  • 3.
    Baldwin, Alexander
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö högskola, Internet of Things and People (IOTAP).
    Eriksson, Jeanette
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö högskola, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö högskola, Internet of Things and People (IOTAP).
    Bus Runner: Using Contextual Cues for Procedural Generation of Game Content on Public Transport2017Ingår i: HCI 2017: Human-Computer Interaction: Interaction Contexts, Springer, 2017, s. 21-34Konferensbidrag (Refereegranskat)
    Abstract [en]

    With the support of the regional public transport operator, this paper explores the potential for mobile games to make journeys on public transport more enjoyable. To this end we have developed a game called Bus Runner which is a context-aware endless runner, based on open and shared data. By blending features of the physical world, such as recognisable landmarks, with the game’s virtual world, we situate and enhance passengers’ experience of travelling on public transport. We identify a set of challenges and opportunities based on the development and evaluation of Bus Runner. These are of relevance not only for game development purposes, but also impact context-driven content generation of infotainment services as a whole.

  • 4.
    Brondin, Anna
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Nordström, Marcus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Salvi, Dario
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Open source step counter algorithm for wearable devices2020Ingår i: Companion Proceedings of the 10th International Conference on the Internet of Things (IoT 2020), New York, United States: ACM Digital Library, 2020, artikel-id 6Konferensbidrag (Refereegranskat)
    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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  • 5.
    Davidsson, Paul
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Eklund, Ulrik
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Elis: An Open Platform for Mobile Energy Efficiency Services in Buildings2019Ingår i: Sustainability, E-ISSN 2071-1050, Vol. 11, nr 3, artikel-id 858Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The recent years have witnessed an enormous growth of mobile services for energy management in buildings. However, these solutions are often proprietary, non-interoperable, and handle only a limited function, such as lighting, ventilation, or heating. To address these issues, we have developed an open platform that is an integrated energy management solution for buildings. It includes an ecosystem of mobile services and open APIs as well as protocols for the development of new services and products. Moreover, it has an adapter layer that enables the platform to interoperate with any building management system (BMS) or individual device. Thus, the platform makes it possible for third-party developers to produce mobile energy efficiency applications that will work independently of which BMS and devices are used in the building. To validate the platform, a number of services have been implemented and evaluated in existing buildings. This has been done in cooperation with energy companies and property owners, together with the residents and other users of the buildings. The platform, which we call Elis, has been made available as open source software under an MIT license. View Full-Text

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  • 6.
    Eklund, Ulrik
    et al.
    Malmö högskola, Teknik och samhälle (TS).
    Olsson, Carl Magnus
    Malmö högskola, Teknik och samhälle (TS).
    Ljungblad, Marcus
    Characterising Software Platforms from an Architectural Perspective2013Ingår i: Software Architecure, Springer, 2013, s. 344-347Konferensbidrag (Refereegranskat)
    Abstract [en]

    With demands of speed in software development it is of interest to build on available software platforms that incorporate the necessary non-competitive functionalities and focus the development effort on adding features to a competitive product. This paper proposes that we move from an API-oriented focus and instead suggest four architectural concerns for describing software platforms as more relevant.

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  • 7.
    Engström, Jimmy
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP). Sony Europe BV, S-22362 Lund, Sweden..
    Jevinger, Åse
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Persson, Jan A.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Some Design Considerations in Passive Indoor Positioning Systems2023Ingår i: Sensors, E-ISSN 1424-8220, Vol. 23, nr 12, artikel-id 5684Artikel i tidskrift (Refereegranskat)
    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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  • 8.
    Holmberg, Lars
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Linde, Per
    Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3). Malmö universitet, Internet of Things and People (IOTAP).
    Contextual machine teaching2020Ingår i: 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, 2020Konferensbidrag (Refereegranskat)
    Abstract [en]

    Machine learning research today is dominated by atechnocentric perspective and in many cases disconnected fromthe users of the technology. The machine teaching paradigm insteadshifts the focus from machine learning experts towards thedomain experts and users of machine learning technology. Thisshift opens up for new perspectives on the current use of machinelearning as well as new usage areas to explore. In this study,we apply and map existing machine teaching principles ontoa contextual machine teaching implementation in a commutingsetting. The aim is to highlight areas in machine teaching theorythat requires more attention. The main contribution of this workis an increased focus on available features, the features space andthe potential to transfer some of the domain expert’s explanatorypowers to the machine learning system.

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  • 9.
    Jevinger, Åse
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Introducing an Intelligent Goods Service Framework2021Ingår i: Logistics, ISSN 2305-6290, Vol. 5, nr 3, artikel-id 54Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    With the increasing diffusion of Internet of Things (IoT) technologies, the transportation of goods sector is in a position to adopt novel intelligent services that cut across the otherwise highly fragmented and heterogeneous market, which today consists of a myriad of actors. Legacy systems that rely upon direct integration between all actors involved in the transportation ecosystem face considerable challenges for information sharing. Meanwhile, IoT based services, which are designed as devices that follow goods and communicate directly to cloud-based backend systems, may provide services that previously were not available. For the purposes of this paper, we present a theoretical framework for classification of such intelligent goods systems based on a literature study. The framework, labelled as the Intelligent Goods Service (IGS) framework, aims at increasing the understanding of the actors, agents, and services involved in an intelligent goods system, and to facilitate system comparisons and the development of new innovative solutions. As an illustration of how the IGS framework can be used and contribute to research in this area, we provide an example from a direct industry-academia collaboration.

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  • 10. Jonsson, Håkan
    et al.
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    User privacy attitudes regarding proximity sensing2018Ingår i: ARES 2018: Proceedings of the 13th International Conference on Availability, Reliability and Security, ACM Digital Library, 2018, artikel-id 25Konferensbidrag (Refereegranskat)
    Abstract [en]

    User attitudes on privacy with respect to location data has been extensively studied. However, user attitudes of privacy in relation to proximity sensing is still lacking. We present the results from a survey conducted on users of a proximity sensing application we developed and diffused by handing out phones with the proximity sensing application pre-installed, with 31 respondents. The results compare this type of application to location sensing in general, as well as positions our respondents in relation to previous studies in terms of general privacy policies. Four results stand out in particular: One, our respondents are more aware of and care about privacy policies than in previous studies. Two, trust is reported as being based more on the specific data access asked for, than EULA or similar text based policies. Third, the respondents are willing to allowing having proximity data about them sensed, as long as they are in control of who can sense it. Finally, our results indicate that there is no perceived difference in sensitivity between location and proximity sensing.

  • 11. Katz, Dmitri
    et al.
    Arsand, Eirik
    Dalton, Nick
    Holland, Simon
    Martin, Clare
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV).
    Price, Blaine A.
    Designing, Developing, and Evaluating the Future Internet of Personal Health2016Ingår i: UBICOMP'16 Adjunct: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, ACM Digital Library, 2016, s. 1068-1073Konferensbidrag (Refereegranskat)
    Abstract [en]

    Ubiquitous computing technologies have the potential to revolutionize the support of chronic health conditions: improving quality of life, reducing costs and optimizing health outcomes. Wearable networks of connected devices and sensors offer the prospect of personalized support and contextually aware advice, for those with specific chronic health conditions. However, there are many obstacles and concerns that need to be addressed before the full potential can be realized. This workshop aims to bring together those interested in developing ubiquitous health management and related personal decision support systems to identify how gaps in knowledge can be addressed and design practices can be improved to better support key communities and contexts of use in this rapidly growing field.

  • 12.
    Kebande, Victor R.
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Alawadi, Sadi
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Bugeja, Joseph
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Persson, Jan A.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Leveraging Federated Learning & Blockchain to counter Adversarial Attacks in Incremental Learning2020Ingår i: IoT '20 Companion: 10th International Conference on the Internet of Things Companion, ACM Digital Library, 2020, s. 1-5, artikel-id 2Konferensbidrag (Refereegranskat)
    Abstract [en]

    Whereas data labelling in IoT applications is costly, it is also time consuming to train a supervised Machine Learning (ML) algorithm. Hence, a human oracle is required to gradually annotate the data patterns at run-time to improve the models’ learning behavior, through an active learning strategy in form of User Feedback Process (UFP). Consequently, it is worth to note that during UFP there may exist malicious content that may subject the learning model to be vulnerable to adversarial attacks, more so, manipulative attacks. We argue in this position paper, that there are instances during incremental learning, where the local data model may present wrong output, if retraining is done using data that has already been subjected to adversarial attack. We propose a Distributed Interactive Secure Federated Learning (DISFL) framework that utilizes UFP in the edge and fog node, that subsequently increases the amount of labelled personal local data for the ML model during incremental training. Furthermore, the DISFL framework addresses data privacy by leveraging federated learning, where only the model's knowledge is moved to a global unit, herein referred to as Collective Intelligence Node (CIN). During incremental learning, this would then allow the creation of an immutable chain of data that has to be trained, which in its entirety is tamper-free while increasing trust between parties. With a degree of certainty, this approach counters adversarial manipulation during incremental learning in active learning context at the same time strengthens data privacy, while reducing the computation costs.

  • 13.
    Leckner, Sara
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    The digital tourist bureau: Challenges and opportunities when transferring to a digital value creation2020Ingår i: The Routledge Companion to Media and Tourism / [ed] Maria Månsson, Annæ Buchmann, Cecilia Cassinger, Lena Eskilsson, New York: Routledge, 2020, s. 372-381Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    Using Malmö Turism-a tourist bureau in the south of Sweden-as a case, this chapter examines its digital transformation; from being based foremost on promoting storytelling of real-life interactions with a few expert assistants at a physical tourist bureau, towards becoming a primary digitally based cross-and transmedia operation, where support of the hosting relied on a larger number of connected media and actors. Based on interviews with the organization before and after the reorganization, the chapter analyses the drivers, determinants and challenges that faced the organization during the transformation. It contributes with insight and understanding from a novel case that other tourism organizations may contrast their findings with, a challenge many of them are likely to embrace in the future.

  • 14.
    Maus, Benjamin
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Salvi, Dario
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Privacy Personas for IoT-Based Health Research: A Privacy Calculus Approach2021Ingår i: Frontiers in Digital Health, E-ISSN 2673-253X, Vol. 3, s. 1-12, artikel-id 675754Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The reliance on data donation from citizens as a driver for research, known as citizen science, has accelerated during the Sars-Cov-2 pandemic. An important enabler of this is Internet of Things (IoT) devices, such as mobile phones and wearable devices, that allow continuous data collection and convenient sharing. However, potentially sensitive health data raises privacy and security concerns for citizens, which research institutions and industries must consider. In e-commerce or social network studies of citizen science, a privacy calculus related to user perceptions is commonly developed, capturing the information disclosure intent of the participants. In this study, we develop a privacy calculus model adapted for IoT-based health research using citizen science for user engagement and data collection. Based on an online survey with 85 participants, we make use of the privacy calculus to analyse the respondents' perceptions. The emerging privacy personas are clustered and compared with previous research, resulting in three distinct personas which can be used by designers and technologists who are responsible for developing suitable forms of data collection. These are the 1) Citizen Science Optimist, the 2) Selective Data Donor, and the 3) Health Data Controller. Together with our privacy calculus for citizen science based digital health research, the three privacy personas are the main contributions of this study.

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  • 15.
    Maus, Benjamin
    et al.
    Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3).
    Salvi, Dario
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Enhancing citizens trust in technologies for data donation in clinical research: validation of a design prototype2020Ingår i: Companion Proceedings of the 10th International Conference on the Internet of Things (IoT 2020), ACM Digital Library, 2020Konferensbidrag (Refereegranskat)
    Abstract [en]

    Mobile phones, wearable trackers and Internet of Things devices continuously produce data about our health and lifestyle that can be used for medical research. However, how data is accessed, by whom and for what purpose is not always understood. This lack of transparency undermines citizens trust in the use of such technologies for research purposes. This paper proposes a set of 6 use cases and related mock-up interfaces for citizen science, mobile-based health research: “Curated information about the institution”, “Sequential consent of shared data”, “Updates from the institution”, “Privacy notifications”, “Overview of donated data” and “Personal impact in medical research”. Interviews and Kano analysis of the interfaces with 6 prospective users show that all except “Privacy notifications” are perceived as important and beneficial for increasing users’ trust. The defined use cases can guide the development of future data collection platforms.

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  • 16.
    Ohlin, Fredrik
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Beyond a Utility View of Personal Informatics: A Postphenomenological Framework2015Ingår i: UbiComp/ISWC'15 Adjunct: Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers, ACM Digital Library, 2015, s. 1087-1092Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Quantified self apps and other personal informatics designs have rapidly grown in popularity through the advent of convenient Internet of Things related wearables and improved sensor technology. The rapid growth has, however, left its mark on how we study this area as the utility that could be provided has become the centerpiece of attention. This appears somewhat contradictory, as personal informatics technology becomes integrated in life in nuanced ways, contributing value beyond the instrumental data analysis role. In this paper, we propose relying on postphenomenology as a useful foundation for extending the study of personal informatics, and provide three concluding implications intended to guide the discussion of such an extension.

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  • 17.
    Ohlin, Fredrik
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Intelligent Computing in Personal Informatics: Key Design Considerations2015Ingår i: Proceedings of the 20th ACM International Conference on Intelligent User Interfaces, ACM Associaltion of Computing Machinery , 2015, s. 263-274Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    An expanding range of apps supported by wearable and mobile devices are being used by people engaged in personal informatics in order to track and explore data about themselves and their everyday activities. While the aspect of data collection is easier than ever before through these technologies, more advanced forms of support from personal informatics systems are not presently available. This lack of next generation personal informatics systems presents research with an important role to fill, and this paper presents a two-step contribution to this effect. The first step is to present a new model of human cooperation with intelligent computing, which collates key issues from the literature. The second step is to apply this model to personal informatics, identifying twelve key considerations for integrating intelligent computing in the design of future personal informatics systems. These design considerations are also applied to an example system, which illustrates their use in eliciting new design directions.

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  • 18.
    Ohlin, Fredrik
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Analyzing the Design Space of Personal Informatics: A State-of-practice Based Classification of Existing Tools2015Ingår i: Universal Access in Human-Computer Interaction: Access to Today's Technologies: 9th International Conference, UAHCI 2015, Held as Part of HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015, Proceedings, Part I, Springer, 2015, s. 85-97Konferensbidrag (Refereegranskat)
    Abstract [en]

    We are presently seeing a rapid increase of tools for tracking and analyzing activities, from lifelogging in general to specific activities such as exercise tracking. Guided by the perspectives of collection, procedural, and analysis support, this paper presents the results from a review of 71 existing tools, striving to capture the design choices within personal informatics that such tools are using. The classification system this creates is a contribution in three ways: as a standalone state-of-practice representation, for assessing individual tools and potential future design directions for them, and as a guide for new development of personal informatics tools

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  • 19.
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Engagement Issues in Self-Tracking Lessons Learned from User Feedback of Three Major Self-Tracking Services2017Ingår i: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, 2017, s. 152-157Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper recognizes the relevance of self-tracking as a growing trend within the general public. As this develops further, pervasive computing has an opportunity to embrace user-feedback from this broader user group than the previously emphasized 'quantified self: ers'. To this end, the paper takes an empirically driven approach to understand engagement issues by reviewing three popular self-tracking services. Using a postphenomenological lens for categorization of the feedback, this study contributes by illustrating how this lens may be used to identifying challenges that even best-case self-tracking services still struggle with.

  • 20.
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV). Malmö högskola, Internet of Things and People (IOTAP).
    Fundamentals for writing research: A game-oriented perspective2015Ingår i: Game Research Methods / [ed] Petri Lankoski, Staffan Björk, ETC Press, 2015, s. 9-20Kapitel i bok, del av antologi (Övrigt vetenskapligt)
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  • 21.
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap (DV). Malmö högskola, Internet of Things and People (IOTAP).
    Systematic interviews and analysis: Using the repertory grid technique2015Ingår i: Game Research Methods / [ed] Petri Lankoski, Staffan Björk, ETC Press, 2015, s. 291-307Kapitel i bok, del av antologi (Övrigt vetenskapligt)
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  • 22.
    Olsson, Carl Magnus
    et al.
    Malmö högskola, Teknik och samhälle (TS).
    Björk, Staffan
    Dahlskog, Steve
    Malmö högskola, Teknik och samhälle (TS).
    The conceptual relationship model: understanding patterns and mechanics in game design2014Ingår i: DIGRA '14 - PROCEEDINGS OF THE 2014 DIGRA INTERNATIONAL CONFERENCE, DIGRA , 2014, s. 1-16Konferensbidrag (Refereegranskat)
    Abstract [en]

    Rooted in the complexity of purposeful design, this paper embraces a phenomenological perspective of design as both a process and artifact. We use this perspective to interpret why the conceptualization and realization of design intentions can be difficult to achieve and why design is often perceived as a so called ‘wicked problem’. This paper revisits the concepts of game design patterns and game mechanics, arguing that refactoring these concepts is needed to clarify their relationships and motivations. We outline the separation of concerns between them and suggest that an additional contextualizing layer should be added to the discourse. Using this, we define and reflect upon what we refer to as the conceptual relationship model.

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  • 23.
    Olsson, Carl Magnus
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Eriksson, Jeanette
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Methodological capabilities for emergent design2014Ingår i: Human-Computer Interaction. Theories, Methods, and Tools: 16th International Conference, HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014, Proceedings;1, Springer, 2014, s. 110-121Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    In this paper we revisit emergent design and review five design oriented methodologies; action research, design research, controlled experiments, participatory design and ethnographic based approaches. Based on this review, we outline implications for the use of these methodologies in conjunction with an emergent design stance. Adopting such a stance is in line with both the exploratory way in which users embrace technology and the strong acceptance that agile software development approaches have had. It is therefore, we argue, appropriate that our research methodologies are adapted to embrace this change.

  • 24.
    Russo, Nancy L
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Hermodsson, Klas
    Olsson, Carl Magnus
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Personalising Applications to Influence Health-Related Behaviour: An Exploration of Differences in Motivation2017Ingår i: 22nd UK Academy for Information Systems International Conference: Ubiquitous Information Systems: Surviving & thriving in a connected society, 2017, artikel-id 31Konferensbidrag (Refereegranskat)
    Abstract [en]

    To support health-related behaviour changes, consumers may use technologies such as smartphones, smartbands, sensors and other devices connected to the Internet of Things. Research has shown that personalising the interaction, including the interface, data, and feedback, can result in more effective outcomes in terms of the desired changes in behaviour. This paper reports on a pilot study that tested a smartphone step challenge application that was personalised based on the user’s motivational style using the Behavioural Inhibition System/Behavioural Approach System (BIS/BAS) scales of Reinforcement Sensitivity Theory. The results indicated that participation in the step challenge did change the behaviour of the participants. For half the days of the challenge, the application delivered pep talks tailored to the two motivational styles and to the participant’s behaviour (taking more or fewer steps than on the previous day). While the study found that participants with different motivational styles responded differently to the motivational cues (pep talks), their responses did not appear to be influenced by the personalisation of the pep talks.

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  • 25.
    Salvi, Dario
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Ymeri, Gent
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Carrasco-Lopez, Carmen
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Tsang, Kevin C.H.
    University of Edinburgh, United Kingdom.
    Shah, Seyed Ahmar
    University of Edinburgh, United Kingdom.
    Mobistudy: Mobile-based, platform-independent, multi-dimensional data collection for clinical studies2022Ingår i: IoT 2021: Conference Proceedings, ACM Digital Library, 2022, s. 219-222Konferensbidrag (Refereegranskat)
    Abstract [en]

    Internet of Things (IoT) can work as a useful tool for clinical research. We developed a software platform that allows researchers to publish clinical studies and volunteers to participate into them using an app and connected IoT devices. The platform includes a REST API, a web interface for researchers and an app that collects data during tasks volunteers are invited to contribute. Nine tasks have been developed: Forms, Positioning, Finger tapping, Pulse-oximetry, Peak Flow measurement, Activity tracking, Data query, Queen’s College step test and Six-minute walk test. These leverage sensors embedded in the phone, connected Bluetooth devices and additional APIs like HealthKit and Google Fit. Currently, the platform is used in two clinical studies by 25 patients: an asthma management study in the United Kingdom, and a neuropathic pain management study in Spain.

  • 26.
    Salvi, Dario
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Ymeri, Gent
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Jimeno, Daniel
    Escuela Tecnica Superior de Ingenieria y sistemas de Telecomunicacion, Universidad Politecnica de Madrid.
    Soto-Léon, Vanesa
    National Hospital for Paraplegics, Toledo.
    Pérez Borrego, Yolanda
    National Hospital for Paraplegics, Toledo.
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Carrasco-Lopez, Carmen
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    An IoT-based system for the study of neuropathic pain in spinal cord injury2023Ingår i: Pervasive Computing Technologies for Healthcare: 16th EAI International Conference, PervasiveHealth 2022, Thessaloniki, Greece, December 12-14, 2022, Proceeding / [ed] Athanasios Tsanas; Andreas Triantafyllidis, Springer, 2023, s. 93-103Konferensbidrag (Refereegranskat)
    Abstract [en]

    Neuropathic pain is a difficult condition to treat and would require reliable biomarkers to personalise and optimise treatments. To date, pain levels are mostly measured with subjective scales, but research has shown that electroencephalography (EEG) and heart rate variability (HRV) can be linked to those levels. Internet of Things technology could allow embedding EEG and HRV in easy-to-use systems that patients can use at home in their daily life. We have developed a system for home monitoring that includes a portable EEG device, a tablet application to guide patients through imaginary motor tasks while recording EEG, a wearable HRV sensor and a mobile phone app to report pain levels. We are using this system in a clinical study involving 15 spinal cord injury patients for one month. Preliminary results show that relevant data are being collected, with inter and intra-patients variability for both HRV and pain levels, and that the mobile phone app is perceived as usable, of good quality and useful. However, because of its complexity, the system requires some effort from patients, is sometimes unreliable and the collected EEG signals are not always of the desired quality.

    Publikationen är tillgänglig i fulltext från 2024-06-11 11:20
  • 27.
    Stefansson, Petter
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Karlsson, Fredrik
    Sony Network Communications, 223 62 Lund, Sweden.
    Persson, Magnus
    Sony Network Communications, 223 62 Lund, Sweden.
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Synthetic generation of passive infrared motion sensor data using a game engine2021Ingår i: Sensors, E-ISSN 1424-8220, Vol. 21, nr 23, artikel-id 8078Artikel i tidskrift (Refereegranskat)
    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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  • 28.
    Tsang, Kevin CH
    et al.
    Usher Institute, University of Edinburgh.
    Pinnock, Hilary
    Usher Institute, University of Edinburgh.
    Wilson, Andrew M
    Norwich Medical School, University of East Anglia.
    Salvi, Dario
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Syed Ahmar, Shah
    Usher Institute, University of Edinburgh.
    Compliance and Usability of an Asthma Home Monitoring System2023Ingår i: Pervasive Computing Technologies for Healthcare: 16th EAI International Conference, PervasiveHealth 2022, Thessaloniki, Greece, December 12-14, 2022, Proceedings / [ed] Athanasios Tsanas; Andreas Triantafyllidis, Springer, 2023, s. 116-126Konferensbidrag (Refereegranskat)
    Abstract [en]

    Asthma monitoring is an important aspect of patient self-management. However, due to its repetitive nature, patients can find long-term monitoring tedious. Mobile health can provide an avenue to monitor asthma without needing high levels of active engagement, and instead rely on passive monitoring. In our recent AAMOS-00 study, we collected mobile health data over six months from 22 asthma patients using passive and active monitoring technology, including smartwatch, peak flow measurements, and daily asthma diaries.

    Compliance to smartwatch monitoring was found to lie between the compliance to complete daily asthma diaries and measuring daily peak flow. However, some study participants faced technical issues with the devices which could have affected the relative compliance of the monitoring tasks.

    Moreover, as evidenced by standard usability questionnaires, we found that the AAMOS-00 study’s data collection system was similar in quality to other studies and published apps.

    Publikationen är tillgänglig i fulltext från 2024-06-11 08:26
  • 29.
    Ymeri, Gent
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Salvi, Dario
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Linking data collected from mobile phones withsymptoms level in Parkinson’s Disease: Dataexploration of the mPower study2022Ingår i: Pervasive Computing Technologies for Healthcare: 16th EAI International Conference, PervasiveHealth 2022, Thessaloniki, Greece, December 12-14, 2022, Proceedings / [ed] Tsanas, Athanasios; Triantafyllidis, Andreas, Cham: Springer, 2022Konferensbidrag (Refereegranskat)
    Abstract [en]

    Advancements in technology, such as smartphones and wearabledevices, can be used for collecting movement data through embeddedsensors. This paper focuses on linking Parkinson’s Disease severitywith data collected from mobile phones in the mPower study. As referencefor symptoms’ severity, we use the answers provided to part 2 ofthe standard MDS-UPDRS scale. As input variables, we use the featurescomputed within mPower from the raw data collected during 4 phonebasedactivities: walking, rest, voice and finger tapping. The features arefiltered in order to remove unreliable datapoints and associated to referencevalues. After pre-processing, 5 Machine Learning algorithms areapplied for predictive analysis. We show that, notwithstanding the noisedue to the data being collected in an uncontrolled manner, the regressedsymptom levels are moderately to strongly correlated with the actualvalues (highest Pearson’s correlation = 0.6). However, the high differencebetween the values also implies that the regressed values can not beconsidered as a substitute for a conventional clinical assessment (lowestmean absolute error = 5.4).

    Publikationen är tillgänglig i fulltext från 2024-07-11 08:28
  • 30.
    Ymeri, Gent
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Salvi, Dario
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Thanasis, Tsanas
    Usher Institute, The University of Edinburgh, UK.
    Svenningsson, Per
    Department of Clinical Neuroscience, Karolinska Institute.
    Mobile-based multi-dimensional data collection for Parkinson’s symptoms in home environments2022Konferensbidrag (Refereegranskat)
    Abstract [en]

    We extended the Mobistudy app for clinical research in order to gather data about Parkinson’s motor and non-motor symptoms. We developed 5 tests that make use of the phone’s embedded sensors and 3 questionnaires. We show through data collected by healthy individuals simulating PD symptoms that the tests are able to identify the presence of symptoms.

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  • 31.
    Ymeri, Gent
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Salvi, Dario
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Wassenburg, Myrthe Vivianne
    Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Center for Neurology, Academic Specialist Center Torsplan, Region Stockholm, Sweden.
    Tsanas, Athanasios
    Usher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh, UK; Alan Turing Institute, London, UK.
    Svenningsson, Per
    Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Center for Neurology, Academic Specialist Center Torsplan, Region Stockholm, Sweden.
    Quantifying Parkinson's disease severity using mobile wearable devices and machine learning: the ParkApp pilot study protocol2023Ingår i: BMJ Open, E-ISSN 2044-6055, Vol. 13, nr 12, artikel-id e077766Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    INTRODUCTION: The clinical assessment of Parkinson's disease (PD) symptoms can present reliability issues and, with visits typically spaced apart 6 months, can hardly capture their frequent variability. Smartphones and smartwatches along with signal processing and machine learning can facilitate frequent, remote, reliable and objective assessments of PD from patients' homes.

    AIM: To investigate the feasibility, compliance and user experience of passively and actively measuring symptoms from home environments using data from sensors embedded in smartphones and a wrist-wearable device.

    METHODS AND ANALYSIS: In an ongoing clinical feasibility study, participants with a confirmed PD diagnosis are being recruited. Participants perform activity tests, including Timed Up and Go (TUG), tremor, finger tapping, drawing and vocalisation, once a week for 2 months using the Mobistudy smartphone app in their homes. Concurrently, participants wear the GENEActiv wrist device for 28 days to measure actigraphy continuously. In addition to using sensors, participants complete the Beck's Depression Inventory, Non-Motor Symptoms Questionnaire (NMSQuest) and Parkinson's Disease Questionnaire (PDQ-8) questionnaires at baseline, at 1 month and at the end of the study. Sleep disorders are assessed through the Parkinson's Disease Sleep Scale-2 questionnaire (weekly) and a custom sleep quality daily questionnaire. User experience questionnaires, Technology Acceptance Model and User Version of the Mobile Application Rating Scale, are delivered at 1 month. Clinical assessment (Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS)) is performed at enrollment and the 2-month follow-up visit. During visits, a TUG test is performed using the smartphone and the G-Walk motion sensor as reference device. Signal processing and machine learning techniques will be employed to analyse the data collected from Mobistudy app and the GENEActiv and correlate them with the MDS-UPDRS. Compliance and user aspects will be informing the long-term feasibility.

    ETHICS AND DISSEMINATION: The study received ethical approval by the Swedish Ethical Review Authority (Etikprövningsmyndigheten), with application number 2022-02885-01. Results will be reported in peer-reviewed journals and conferences. Results will be shared with the study participants.

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  • 32. Yordanova, Kristina
    et al.
    Paiement, Adeline
    Schröder, Max
    Tonkin, Emma
    Woznowski, Przemyslaw
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Rafferty, Joseph
    Sztyler, Timo
    Challenges in annotation of useR data for UbiquitOUs systems: results from the 1st ARDUOUS workshop2018Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Labelling user data is a central part of the design and evaluation of pervasive systems that aim to support the user through situation-aware reasoning. It is essential both in designing and training the system to recognise and reason about the situation, either through the definition of a suitable situation model in knowledge-driven applications, or through the preparation of training data for learning tasks in data-driven models. Hence, the quality of annotations can have a significant impact on the performance of the derived systems. Labelling is also vital for validating and quantifying the performance of applications. In particular, comparative evaluations require the production of benchmark datasets based on high-quality and consistent annotations. With pervasive systems relying increasingly on large datasets for designing and testing models of users' activities, the process of data labelling is becoming a major concern for the community. In this work we present a qualitative and quantitative analysis of the challenges associated with annotation of user data and possible strategies towards addressing these challenges. The analysis was based on the data gathered during the 1st International Workshop on Annotation of useR Data for UbiquitOUs Systems (ARDUOUS) and consisted of brainstorming as well as annotation and questionnaire data gathered during the talks, poster session, live annotation session, and discussion session.

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  • 33.
    Dorthé, Lotti (Utställningsansvarig, utställningskommissarie)
    Malmö universitet, Malmö universitetsbibliotek.
    Olsson, Annsofie (Utställningsansvarig, utställningskommissarie)
    Malmö universitet, Malmö universitetsbibliotek.
    Spikol, Daniel (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Spalazzese, Romina (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Linde, Per (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3). Malmö universitet, Internet of Things and People (IOTAP).
    Leckner, Sara (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Russo, Nancy (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Eriksson, Jeanette (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Persson, Jan (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Holmberg, Johan (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus (Upphovsman, Forskare)
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Brandström, Maria (Formgivare)
    Malmö universitet, Malmö universitetsbibliotek.
    Tosting, Åsa (Formgivare)
    Malmö universitet, Malmö universitetsbibliotek.
    Egevad, Per (Ljusdesigner, ljussättare)
    Malmö universitet, Malmö universitetsbibliotek.
    Svensson, Anneli (Medarbetare/bidragsgivare)
    Malmö universitet, Malmö universitetsbibliotek.
    Topgaard, Richard (Medarbetare/bidragsgivare)
    Malmö universitet, Gemensamt verksamhetsstöd. Malmö universitet, Internet of Things and People (IOTAP).
    Forskarnas galleri #5: People have the power: IOTAP on exhibit2018Konstnärlig output (Ogranskad)
    Abstract [sv]

    Överallt samlar sensorer data som analyseras för att räkna ut hur man sparar energi, hur mycket insulin som ska injiceras, var den närmaste hyrbilen finns, hur många människor som fortfarande är kvar inne i en brinnande byggnad... Denna snabba spridning av teknik kallas för Sakernas Internet, eller IoT. Människor har makten, eller har vi verkligen det? Hur mycket värderar vi vår integritet? Vilka internetanslutna gadgets hjälper oss att leva ett hälsosamt och hållbart liv - och vilka prylar kommer bara att öka vår stressnivå? När blir användningen missbruk? Utställningen undersöker hur IoT påverkar människor, samhälle och industri. Forskningsprojekt i utställningen: Emergent Configuration for IoT Systems (ECOS+), Smart energy management and security (SEMS), Fair Data, Walk the ward, Dynamic Intelligent Sensor-Intensive Systems (DISS), PELARS-projektet och Busrunner presenteras i "IOTAP-labbet"

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