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Browsing NTNU Open by Author "Bach, Kerstin"

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Now showing items 1-20 of 52

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    • A Decision Support System to Enhance Self-Management of Low Back Pain: Protocol for the selfBACK Project 

      Mork, Paul Jarle; Bach, Kerstin (Journal article; Peer reviewed, 2018)
      Background: Low back pain (LBP) is a leading cause of disability worldwide. Most patients with LBP encountered in primary care settings have nonspecific LBP, that is, pain with an unknown pathoanatomical cause. Self-management ...
    • A User-Based Look at Visualization Tools for Air Quality Data harvested by micro-sensor units 

      Svendsen, Daniel (Master thesis, 2020)
      Målet med masteroppgaven som har tittel ”User-based look at Visualization tools for Air Quality Data harvested by IoT units” er å utvikle og brukerteste forskjellige visualiser- ingsverktøy rettet mot luftforurensning i ...
    • Activity Recognition for Stroke Patients 

      Vågeskar, Eirik (Master thesis, 2017)
      Stroke is a disruption in the blood flow to the brain which may lead to a death of brain cells. More than 12000 Norwegians experience a stroke each year. Survivors often suffer lasting movement disabilities, which affect ...
    • Analysis of The Norwegian Veterinary Institute's Model for Salmon Lice Abundance Prediction 

      Bogen, Johannes (Master thesis, 2018)
      Empirical studies have found that lice from salmon farms are a main source of infection of wild salmonids. Due to Norway s responsibility to conserve wild stocks of salmon, Veterinærinstituttet has created a statistical ...
    • App-Delivered Self-Management Intervention Trial selfBACK for People With Low Back Pain: Protocol for Implementation and Process Evaluation 

      Nørregaard Rasmussen, Charlotte Diana; Jagd Svendsen, Malene; Wood, Karen; Nicholl, Barbara I; Mair, Frances S; Fleng Sandal, Louise; Mork, Paul Jarle; Søgaard, Karen; Bach, Kerstin; Jensen Stochkendahl, Mette (Peer reviewed; Journal article, 2020)
      Background: Implementation and process evaluation is vital for understanding how interventions function in different settings, including if and why interventions have different effects or do not work at all. Objective: ...
    • An App-Delivered Self-Management Program for People With Low Back Pain: Protocol for the selfBACK Randomized Controlled Trial 

      Sandal, Louise Fleng; Stochkendahl, Mette J; Svendsen, Malene Jagd; Wood, Karen; Øverås, Cecilie Krage; Nordstoga, Anne Lovise; Villumsen, Morten; Rasmussen, Charlotte Diana Nørregaard; Nicholl, Barbara I; Cooper, Kay; Kjaer, Per; Mair, Frances; Sjøgaard, Gisela; Nilsen, Tom Ivar Lund; Hartvigsen, Jan; Bach, Kerstin; Mork, Paul Jarle; Søgaard, Karen (Peer reviewed; Journal article, 2019)
      Background: Low back pain (LBP) is prevalent across all social classes, in all age groups, and across industrialized and developing countries. From a global perspective, LBP is considered the leading cause of disability ...
    • Assessment of Machine Learning Models for Classification of Movement Patterns During a Weight-Shifting Exergame 

      Vonstad, Elise Klæbo; Su, Xiaomeng; Vereijken, Beatrix; Bach, Kerstin; Nilsen, Jan Harald (Peer reviewed; Journal article, 2021)
      In exercise gaming (exergaming), reward systems are typically based on rules/templates from joint movement patterns. These rules or templates need broad ranges in definitions of correct movement patterns to accommodate ...
    • Automatic Analysis and Presentation of Learning Resources 

      Bråthen, Bjørn (Master thesis, 2016)
      This master thesis investigates how to make examples of student assignments searchable online, and hence better accessible. Dokker.no provides a platform where students can document their work, given a provided assignment. ...
    • Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning 

      Murad, Abdulmajid Abdullah Yahya; Kraemer, Frank Alexander; Bach, Kerstin; Taylor, Gavin (Chapter, 2019)
      Reinforcement learning (RL) is capable of managing wireless, energy-harvesting IoT nodes by solving the problem of autonomous management in non-stationary, resource-constrained settings. We show that the state-of-the-art ...
    • Bayesian-Supported Retrieval in BNCreek: A Knowledge-Intensive Case-Based Reasoning System 

      Nikpour, Hoda; Aamodt, Agnar; Bach, Kerstin (LNCS;volume 11156, Journal article; Peer reviewed, 2018)
      This study presents a case-based reasoning (CBR) system that makes use of general domain knowledge - referred to as a knowledge-intensive CBR system. The system applies a Bayesian analysis aimed at increasing the accuracy ...
    • Blind Calibration of Air Quality Wireless Sensor Networks Using Deep Neural Networks 

      Veiga, Tiago Santos; Ljunggren, Erling; Bach, Kerstin; Akselsen, Sigmund (Chapter, 2021)
      Temporal drift of low-cost sensors is crucial for the applicability of wireless sensor networks (WSN) to measure highly local phenomenon such as air quality. The emergence of wireless sensor networks in locations without ...
    • Case Representation and Similarity Modeling for Non-Specific Musculoskeletal Disorders - A Case-Based Reasoning Approach 

      Jaiswal, Amar Deep; Bach, Kerstin; Meisingset, Ingebrigt; Vasseljen, Ottar (Book, 2019)
      This paper presents a method for developing case-based reasoning (CBR) application for discovering similar patients with non-specific musculoskeletal disorders (MSDs) and recommending treatment plans using previous ...
    • Case-Based Reasoning and Computational Creativity in a Recipe Recommender System 

      Skjold, Kari; Øynes, Marthe Sofie (Master thesis, 2017)
      A domain where humans have unfolded their creativity for thousands of years is cooking. However, can a human's creativity within cooking be transferred to a computer program? The case-based reasoning (CBR) methodology ...
    • Classification of movement quality in a weight-shifting exercise 

      Vonstad, Elise Klæbo; Su, Xiaomeng; Vereijken, Beatrix; Nilsen, Jan Harald; Bach, Kerstin (Journal article; Peer reviewed, 2018)
      In exercise games, it is often possible to gain rewards, i.e. points, by only partly completing an intended movement, which can undermine the effect of using such games for exercise. To ensure usability and reliability of ...
    • Clustering of Physical Behaviour Profiles using Knowledge-intensive Similarity Measures 

      Verma, Deepika; Bach, Kerstin; Mork, Paul Jarle (Chapter, 2020)
      In this paper, we reuse the Case-Based Reasoning model presented in our last work (Verma et al., 2018) to create a new knowledge intensive similarity-based clustering method that clusters a case base such that the intra-cluster ...
    • Comparison of a Deep Learning-Based Pose Estimation System to Marker-Based and Kinect Systems in Exergaming for Balance Training 

      Vonstad, Elise Klæbo; Su, Xiaomeng; Vereijken, Beatrix; Bach, Kerstin; Nilsen, Jan Harald (Peer reviewed; Journal article, 2020)
      Using standard digital cameras in combination with deep learning (DL) for pose estimation is promising for the in-home and independent use of exercise games (exergames). We need to investigate to what extent such DL-based ...
    • Data Analysis for the Mobile Application of the selfBACK Decision Support System 

      He, Yu (Master thesis, 2018)
      The aim of the thesis is to find user behavior patterns by applying unsupervised learning methods on the selfBACK app usage data. The recognized patterns will be used as references to select interviewees in the process ...
    • Data Analytics for HUNT: Recognition of Physical Activity on Sensor Data Streams 

      Reinsve, Øyvind (Master thesis, 2018)
      Human Activity Recognition (HAR) is the field of recognizing activities by analyzing measurements of a subject s movement and environment. A major application of HAR systems is medical research. Th e Nord-Trøndelag Health ...
    • A Data-Driven Approach for Determining Weights in Global Similarity Functions 

      Jaiswal, Amar Deep; Bach, Kerstin (Peer reviewed; Journal article, 2019)
      This paper presents a method to discover initial global similarity weights while developing a case-based reasoning (CBR) system. The approach is based on multiple feature relevance scoring methods and the relevance of ...
    • Decision support in patient-centered health care 

      Prestmo, Tale (Master thesis, 2017)
      This thesis aims to create exercise plans for patients with low back pain and is a part of the research project selfBACK. Case-based reasoning is used to create the exercise plans, which is the process of solving new ...

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