Browsing NTNU Open by Author "Bach, Kerstin"
Now showing items 21-40 of 93
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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 ... -
Container-Based IoT Architectures: Use Case for Visual Person Counting
Santos Veiga, Tiago; Asad, Hafiz Areeb; Kraemer, Frank Alexander; Bach, Kerstin (Chapter, 2023)This paper studies the deployment process for a use case of visual person counting from cameras located in outdoor areas and shows how a containerized solution fulfills the particular requirements for the use case, ... -
Creating Dynamic Checklists via Bayesian Case-Based Reasoning: Towards Decent Working Conditions for All
Flogard, Eirik Lund; Mengshoel, Ole Jakob; Bach, Kerstin (Peer reviewed; Journal article, 2022)Every year there are 1.9 million deaths world-wide attributed to occupational health and safety risk factors. To address poor working conditions and fulfill UN's SDG 8, "protect labour rights and promote safe working ... -
Creating Explainable Dynamic Checklists via Machine Learning to Ensure Decent Working Environment for All: A Field Study with Labour Inspections
Flogard, Eirik Lund; Mengshoel, Ole Jakob; Theisen, Ole Magnus; Bach, Kerstin (Chapter, 2023)To address poor working conditions and promote United Nations’ sustainable development goal 8.8, “protect labour rights and promote safe working environments for all workers [...]”, government agencies around the world ... -
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 ... -
Deep Learning for Blind Calibration of Wireless Sensor Networks
Ljunggren, Erling (Master thesis, 2020)Temporal drift of low-cost sensors is a crucial problem when considering the applicability of wireless sensor networks (WSN). Since they provide highly local measurements, which is key to combat the ever increasing problem ... -
Design of a clinician dashboard to facilitate co-decision making in the management of non-specific low back pain
Bach, Kerstin; Marling, Cindy; Mork, Paul Jarle; Aamodt, Agnar; Mair, Frances; Nicholl, Barbara I (Journal article; Peer reviewed, 2018)This paper presents the design of a Clinician Dashboard to promote co-decision making between patients and clinicians. Targeted patients are those with non-specific low back pain, a leading cause of discomfort, disability ... -
Detecting and Localizing Cell Nuclei in Medical Images.
Loudon, Johan Scott (Master thesis, 2018)In this master thesis we have adapted and implemented Mask R-CNN to the task of detecting and localizing nuclei in medical imaging. Mask R-CNN, which does instance segmentation, was chosen as the architecture to implement, ... -
A digital decision support system (selfBACK) for improved self-management of low back pain: a pilot study with 6-week follow-up
Sandal, Louise Fleng; Øverås, Cecilie K.; Nordstoga, Anne Lovise; Wood, Karen; Bach, Kerstin; Hartvigsen, Jan; Søgaard, Karen; Mork, Paul Jarle (Peer reviewed; Journal article, 2020)Background Very few of the publicly available apps directed towards self-management of low back pain (LBP) have been rigorously tested and their theoretical underpinnings seldom described. The selfBACK app was developed ... -
Effect of an Artificial Intelligence-Based Self-Management App on Musculoskeletal Health in Patients With Neck and/or Low Back Pain Referred to Specialist Care: A Randomized Clinical Trial
Marcuzzi, Anna; Nordstoga, Anne Lovise; Bach, Kerstin; Aasdahl, Lene; Nilsen, Tom Ivar Lund; Bardal, Ellen Marie; Boldermo, Nora; Bertheussen, Gro Falkener; Marchand, Gunn Hege; Gismervik, Sigmund Østgård; Mork, Paul Jarle (Peer reviewed; Journal article, 2023)Importance Self-management is a key element in the care of persistent neck and low back pain. Individually tailored self-management support delivered via a smartphone app in a specialist care setting has not been ... -
Effectiveness of App-Delivered, Tailored Self-management Support for Adults With Lower Back Pain–Related Disability A selfBACK Randomized Clinical Trial
Fleng Sandal, Louise; Bach, Kerstin; Øverås, Cecilie K.; Jagd Svendsen, Malene; Dalager, Tina; Stejnicher Drongstrup Jensen, Jesper; Kongsvold, Atle Austnes; Nordstoga, Anne Lovise; Bardal, Ellen Marie; Ashikhmin, Ilya; Wood, Karen; Rasmussen, Charlotte Diana Nørregaard; Stochkendahl, Mette J; Nicholl, Barbara I; Wiratunga, Nirmalie; Cooper, Kay; Hartvigsen, Jan; Kjaer, Per; Sjøgaard, Gisela; Nilsen, Tom Ivar Lund; Mair, Frances S; Søgaard, Karen; Mork, Paul Jarle (Journal article; Peer reviewed, 2021) -
Ensemble Classifier Managing Uncertainty in Accelerometer Data within Human Activity Recognition Systems
Wold, Thomas; Skaugvoll, Sigve André Evensen (Master thesis, 2019)Human activity recognition (HAR) er et forskningsområde med mål om å klassifisere aktiviteter utført av personer ved hjelp av data hentet inn av video eller sensorer festet på kroppen. HUNT er den største helseundersøkelsen ... -
Ensemble Classifier Managing Uncertainty in Accelerometer Data within Human Activity Recognition Systems
Wold, Thomas; Skaugvoll, Sigve André Evensen (Master thesis, 2019)Human activity recognition (HAR) er et forskningsområde med mål om å klassifisere aktiviteter utført av personer ved hjelp av data hentet inn av video eller sensorer festet på kroppen. HUNT er den største helseundersøkelsen ... -
Evaluation of Instance-based Explanations: An In-depth Analysis of Counterfactual Evaluation Metrics, Challenges, and the CEval Toolkit
Bayrak, Betül; Bach, Kerstin (Journal article; Peer reviewed, 2024)In eXplainable Artificial Intelligence (XAI), instance-based explanations have gained importance as a method for illuminating complex models by highlighting differences or similarities between the samples and their ... -
Explainable AI Approaches for Large Generative Transformer-Based Language Models
Eggen, Marte (Master thesis, 2024)Den seneste utviklingen innen store generative språkmodeller basert på transformer-arkitekturen har demonstrert svært gode resultater innenfor et spekter av forskjellige områder. Disse resultatene har både vakt oppmerksomhet ...