Viser treff 201-220 av 468

    • WANTED! – Virtual Coach for People with Thorny Diseases 

      Halonen, Raija; Savenstedt, Stefan; Hartvigsen, Gunnar; Abächerli, Roger; Jääskeläinen, Erika; Synnes, Kåre (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-01-03)
      The main objective of this study was to propose a concept for a virtual coach to be used by people who suffer from costly and challenging diseases such as dementia, depression, diabetes and cardiac related issues, and by their caretakers presenting healthcare service providers or family members of the people suffering from the named diseases. Those listed diseases form almost an unbearable ...
    • Video Analytics in Elite Soccer: A Distributed Computing Perspective 

      Jha, Debesh; Rauniyar, Ashish; Johansen, Håvard D.; Johansen, Dag; Riegler, Michael Alexander; Halvorsen, Pål; Bagci, Ulas (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-22)
      Ubiquitous sensors and Internet of Things (IoT)technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training, and match analysis post-game. New methods, including machine learning, image, and video processing, have been developed for performance evaluation, allowing the analyst to track the performance of a player in real-time. ...
    • Standards for reporting randomized controlled trials in medical informatics: a systematic review of CONSORT adherence in RCTs on clinical decision support 

      Augestad, Knut Magne; Berntsen, Gro; Lassen, Kristoffer; Bellika, Johan Gustav; Wootton, Richard; Lindsetmo, Rolv-Ole (Journal article; Tidsskriftartikkel; Peer reviewed, 2011-07-29)
      Introduction The Consolidated Standards for Reporting Trials (CONSORT) were published to standardize reporting and improve the quality of clinical trials. The objective of this study is to assess CONSORT adherence in randomized clinical trials (RCT) of disease specific clinical decision support (CDS).<p> <p>Methods A systematic search was conducted of the Medline, EMBASE, and Cochrane databases. ...
    • Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources 

      Eide, Siri Sofie; Riegler, Michael; Hammer, Hugo Lewi; Bremnes, John Bjørnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-06)
      Many data related problems involve handling multiple data streams of different types at the same time. These problems are both complex and challenging, and researchers often end up using only one modality or combining them via a late fusion based approach. To tackle this challenge, we develop and investigate the usefulness of a novel deep learning method called tower networks. This method is able ...
    • Efficient quantile tracking using an oracle 

      Hammer, Hugo Lewi; Yazidi, Anis; Riegler, Michael; Rue, Håvard (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-14)
      Concept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected quantile loss, a popular loss function in quantile regression, to monitor the quantile tracking error, which, in turn, is used to efficiently adapt to concept drift. The suggested ...
    • Towards a New Model for Chronic Disease Consultations 

      Randine, Pietro; Cooper, John Graham; Hartvigsen, Gunnar; Årsand, Eirik (Chapter; Bokkapittel, 2022-08-22)
      Medical consultations for chronic diseases form an arena to provide information from health personnel to patients. This information is necessary for patients to understand how to deal with the possible lifelong symptoms and needed self-management activities. The amount of patient-generated health data is increasing. Today’s patients gather an increasing amount of personalised health-related information. ...
    • Social media, physical activity and autism: better or bitter together? A scoping review 

      Gabarron, Elia; Henriksen, André; Nordahl-Hansen, Anders (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-22)
      This review provides an overview of the existing research on social media, autism, and physical activity. We searched for publications on PubMed, PsycInfo, Embase, Education source, ERIC, IEEE Xplore, and the proceedings from conferences on health informatics and autism. Eight studies were included in this review. Studies reported mixed results on the link between social media, physical activity, ...
    • Ubiquitous digital health-related data: clarification of concepts 

      Johannessen, Erlend; Henriksen, André; Hartvigsen, Gunnar; Horsch, Alexander; Årsand, Eirik; Johansson, Jonas (Chapter; Bokkapittel, 2022-08-22)
      The increased development and use of ubiquitous digital services reinforce the trend where health-related data is generated everywhere. Data usage in different areas introduces different terms for the same or similar concepts. This adds to the confusion of what these terms represent. We aim to provide an overview of concepts and terms used in connection with digital twins and in a healthcare context.
    • Predictive analytics beyond time series: Predicting series of events extracted from time series data 

      Mishra, Sambeet; Bordin, Chiara; Taharaguchi, Kota; Purkayastha, Adri (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-07)
      Realizing carbon neutral energy generation creates the challenge of accurately predicting time-series generation data for long-term capacity planning and for short-term operational decisions. The key challenges for adopting data-driven decision-making, specifically predictive analytics, can be attributed to data volume and velocity. Data volume poses challenges for data storage and retrieval. Data ...
    • Expectations of users and non-users of wearable sensors and mobile health applications 

      Henriksen, André; Pfuhl, Gerit; Woldaregay, Ashenafi Zebene; Issom, David-Zacharie; Årsand, Eirik; Sato, Keiichi; Hartvigsen, Gunnar (Chapter; Bokkapittel, 2022-08-22)
      Patient self-management is vital to improved health outcomes for patients with chronic diseases. The objective of this study was to understand the role of wearable sensors in patients’ self-management. A survey encompassing factors related to motivation in mHealth was conducted. Ease of use and sensory accuracy was found most important when choosing a wearable. Manual registration of most health-related ...
    • Designing an e-Health Program for Lifestyle Changes in Diabetes Care A Qualitative Pre-Study in Norway 

      Rishaug, Tina; Henriksen, André; Aas, Anne-Marie; Hartvigsen, Gunnar; Birkeland, Kåre Inge; Årsand, Eirik (Chapter; Bokkapittel, 2022-08-22)
      Type 2 diabetes mellitus (T2D) and prediabetes prevalence rates are high. Consequences are serious, but current treatment is often not efficient for achieving remission. Remission may be achieved through lifestyle intervention. Frequent follow-up is necessary, and health care personnel (HCP) lack resources, time, and often adequate knowledge. Self-management of T2D can benefit from better use of ...
    • Data collection and smart nudging to promote physical activity and a healthy lifestyle using wearable devices 

      Dhanasekaran, Seshathiri; Andersen, Anders; Karlsen, Randi; Håkansson, Anne; Henriksen, André (Chapter; Bokkapittel, 2022-08-22)
      Nudge principles and techniques can motivate and improve personal health through emerging digital devices, such as activity trackers. Tracking people's health and well-being using such devices have earned widespread interest. These devices can continuously capture and analyze health-related data from individuals and communities in their everyday environment. Providing context-aware nudges can help ...
    • Proceedings of the 18th Scandinavian Conference on Health Informatics 

      Henriksen, André; Gabarron, Elia; Vimarlund, Vivian (Book; Bok, 2022-08-22)
      This proceeding presents the papers presented at the 18th Scandinavian Conference on Health Informatics - SHI 2022 in Tromsø, Norway on August 22-24, 2022.
    • Smart contract formation enabling energy-as-a-service in a virtual power plant 

      Mishra, Sambeet; John Crasta, Cletus; Bordin, Chiara; Mateo‐Fornés, Jordi (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-22)
      Energy as a service (EaaS) is an emerging business model that enables the otherwise passive energy consumers to play an active role and participate in the energy utility services. This platform is formed through smart contracts registering peer-to-peer (P2P) transactions of energy through price and quantity. Many industries, including finance, have already leveraged smart contracts to introduce ...
    • Resilient expansion planning of virtual power plant with an integrated energy system considering reliability criteria of lines and towers 

      Bordin, Chiara; Mishra, Sambeet; Wu, Qiuwei; Manninen, Henri (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-05-25)
      The portfolio of virtual power plants (VPP) is a flexible system for facilitating a wide range of resources with wide geographical coverage. A VPP can be placed at the intersection of electric power and energy systems by adding heat pumps to the portfolio, thereby accelerating the formation of integrated energy systems. VPPs, while virtual, still rely on a physical network for operations. The power ...
    • Áika: A Distributed Edge System for AI Inference 

      Alslie, Joakim Aalstad; Ovesen, Aril Bernhard; Nordmo, Tor-Arne Schmidt; Johansen, Håvard D.; Halvorsen, Pål; Riegler, Michael; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-17)
      Video monitoring and surveillance of commercial fisheries in world oceans has been proposed by the governing bodies of several nations as a response to crimes such as overfishing. Traditional video monitoring systems may not be suitable due to limitations in the offshore fishing environment, including low bandwidth, unstable satellite network connections and issues of preserving the privacy of crew ...
    • Physics-Guided Loss Functions Improve Deep Learning Performance in Inverse Scattering 

      Liu, Zicheng; Roy, Mayank; Prasad, Dilip K.; Agarwal, Krishna (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-03-15)
      Solving electromagnetic inverse scattering problems (ISPs) is challenging due to the intrinsic nonlinearity, ill-posedness, and expensive computational cost. Recently, deep neural network (DNN) techniques have been successfully applied on ISPs and shown potential of superior imaging over conventional methods. In this paper, we discuss techniques for effective incorporation of important physical ...
    • Dataset of fitness trackers and smartwatches to measuring physical activity in research 

      Henriksen, André; Woldaregay, Ashenafi Zebene; Muzny, Miroslav; Hartvigsen, Gunnar; Hopstock, Laila Arnesdatter; Grimsgaard, Sameline (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-16)
      Objectives: Accelerometer-based wrist-worn ftness trackers and smartwatches (wearables) appeared on the consumer market in 2011. Many wearable devices have been released since. The objective of this data paper is to describe a dataset of 423 wearables released before July 2017.<p> <p>Data description: We identifed wearables and extracted information from six online and ofine databases. We ...
    • Statistical supervised learning with engineering data: a case study of low frequency noise measured on semiconductor devices 

      Gámiz, María Luz; Kalén, Anton; Nozal Cañadas, Rafael; Raya-Miranda, Rocío (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-04)
      Our practical motivation is the analysis of potential correlations between spectral noise current and threshold voltage from common on-wafer MOSFETs. The usual strategy leads to the use of standard techniques based on Normal linear regression easily accessible in all statistical software (both free or commercial). However, these statistical methods are not appropriate because the assumptions they ...
    • Virtual Power Plants and Integrated Energy System: Current Status and Future Prospects 

      Mishra, Sambeet; Bordin, Chiara; Leinakse, Madis; Wen, Fushuan; J. Howlett, Robert; Palu, Ivo (Chapter; Bokkapittel, 2022)
      The power system is undergoing a digitalization, decarbonization, and decentralization. Economic incentives along with resiliency and reliability concerns are partly driving the transition. In the process of decentralization, local energy markets are forming at various places. A virtual power plant (VPP) is a by-product of this digitalization capitalizing on the opportunity to further promote renewable ...