Blar i Fakultet for medisin og helsevitenskap (MH) på forfatter "Bach, Kerstin"
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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 ... -
Acceptance and use of a clinical decision support system in musculoskeletal pain disorders – the SupportPrim project
Granviken, Fredrik; Meisingset, Ingebrigt; Vasseljen, Ottar; Bach, Kerstin; Bones, Anita Formo; Klevanger, Nina Elisabeth (Journal article; Peer reviewed, 2023)Background We have developed a clinical decision support system (CDSS) based on methods from artificial intelligence to support physiotherapists and patients in the decision-making process of managing musculoskeletal (MSK) ... -
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 ... -
Application of Machine Learning Methods on Patient Reported Outcome Measurements for Predicting Outcomes: A Literature Review
Verma, Deepika; Bach, Kerstin; Mork, Paul Jarle (Journal article; Peer reviewed, 2021)The field of patient-centred healthcare has, during recent years, adopted machine learning and data science techniques to support clinical decision making and improve patient outcomes. We conduct a literature review with ... -
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 ... -
Can the bias of self-reported sitting time be corrected? A statistical model validation study based on data from 23 993 adults in the Norwegian HUNT study
Kongsvold, Atle Austnes; Flaaten, Mats; Logacjov, Aleksej; Skarpsno, Eivind Schjelderup; Bach, Kerstin; Nilsen, Tom Ivar Lund; Mork, Paul Jarle (Peer reviewed; Journal article, 2023)Background Despite apparent shortcomings such as measurement error and low precision, self-reported sedentary time is still widely used in surveillance and research. The aim of this study was threefold; (i) to examine ... -
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 ... -
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 ... -
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 ... -
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) -
Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes
Verma, Deepika; Jansen, Duncan; Bach, Kerstin; Poel, Mannes; Mork, Paul Jarle; Oude Nijeweme d’Hollosy, Wendy (Peer reviewed; Journal article, 2022)Background Patient-reported outcome measurements (PROMs) are commonly used in clinical practice to support clinical decision making. However, few studies have investigated machine learning methods for predicting PROMs ... -
Harth: A human activity recognition dataset for machine learning
Logacjov, Aleksej; Bach, Kerstin; Kongsvold, Atle; Bårdstu, Hilde Bremseth; Mork, Paul Jarle (Peer reviewed; Journal article, 2021)Existing accelerometer-based human activity recognition (HAR) benchmark datasets that were recorded during free living suffer from non-fixed sensor placement, the usage of only one sensor, and unreliable annotations. We ... -
Individually tailored self-management app-based intervention (selfBACK) versus a self-management web-based intervention (e-Help) or usual care in people with low back and neck pain referred to secondary care: protocol for a multiarm randomised clinical trial
Marcuzzi, Anna; Bach, Kerstin; Nordstoga, Anne Lovise; Bertheussen, Gro Falkener; Ashikhmin, Ilya; Boldermo, Nora; Kvarner, Else-Norun; Nilsen, Tom Ivar Lund; Marchand, Gunn Hege; Ose, Solveig Osborg; Aasdahl, Lene; Kaspersen, Silje Lill; Bardal, Ellen Marie; Børke, Janne-Birgitte; Mork, Paul Jarle; Gismervik, Sigmund Østgård (Peer reviewed; Journal article, 2021)Introduction: Low back pain (LBP) and neck pain (NP) are common and costly conditions. Self-management is a key element in the care of persistent LBP and NP. Artificial intelligence can be used to support and tailor ... -
Large-Scale Pre-Training for Dual-Accelerometer Human Activity Recognition
Logacjov, Aleksej; Herland, Sverre; Ustad, Astrid; Bach, Kerstin (Peer reviewed; Journal article, 2023) -
A Machine Learning Classifier for Detection of Physical Activity Types and Postures During Free-Living
Bach, Kerstin; Kongsvold, Atle Austnes; Bårdstu, Hilde Bremseth; Bardal, Ellen Marie; Kjærnli, Håkon Slåtten; Herland, Sverre; Logacjov, Aleksej; Mork, Paul Jarle (Journal article; Peer reviewed, 2021)Accelerometer-based measurements of physical activity types are commonly used to replace self-reports. To advance the field, it is desirable that such measurements allow accurate detection of key daily physical activity ...