• Characteristics of general movements in preterm infants assessed by computer-based video analysis 

      Adde, Lars; yang, hong; Sæther, Rannei; Jensenius, Alexander Refsum; Ihlen, Espen Alexander F.; Cao, Jia-yan; Støen, Ragnhild (Journal article; Peer reviewed, 2017)
      Background: Previous evidence suggests that the variability of the spatial center of infant movements, calculated by computer-based video analysis software, can identify fidgety general movements (GMs) and predict cerebral ...
    • Development and Validation of a Deep Learning Method to Predict Cerebral Palsy From Spontaneous Movements in Infants at High Risk 

      Groos, Daniel; Adde, Lars; Aubert, Sindre Aarnes; Boswell, Lynn; De Regnier, Raye-Ann; Fjørtoft, Toril Larsson; Gaebler-Spira, Deborah; Haukeland, Andreas; Loennecken, Marianne; Msall, Michael; Moinichen, Unn Inger; Pascal, Aurelie; Peyton, Colleen; Ramampiaro, Heri; Schreiber, Michael D.; Silberg, Inger Elisabeth; Songstad, Nils Thomas; Thomas, Niranjan; van den Broeck, Christine; Øberg, Gunn Kristin; Ihlen, Espen Alexander F.; Støen, Ragnhild (Peer reviewed; Journal article, 2022)
      Importance Early identification of cerebral palsy (CP) is important for early intervention, yet expert-based assessments do not permit widespread use, and conventional machine learning alternatives lack validity. Objective ...
    • In-Motion-App for remote General Movement Assessment: a multi-site observational study 

      Adde, Lars; Brown, Annemette; van den Broeck, Christine; DeCoen, Kris; Eriksen, Beate Horsberg; Fjørtoft, Toril Larsson; Groos, Daniel; Ihlen, Espen Alexander F.; Osland, Siril; Pascal, Aurelie; Paulsen, Henriette; Skog, Ole-Morten; Sivertsen, Wiebke; Støen, Ragnhild (Peer reviewed; Journal article, 2021)
      Objectives: To determine whether videos taken by parents of their infants' spontaneous movements were in accordance with required standards in the In-Motion-App, and whether the videos could be remotely scored by a trained ...
    • Machine Learning of Infant Spontaneous Movements for the Early Prediction of Cerebral Palsy: A Multi-Site Cohort Study 

      Ihlen, Espen Alexander F.; Støen, Ragnhild; Boswell, Lynn; de-Regnier, Raye-Ann; Fjørtoft, Toril Larsson; Gaebler-spira, Deborah; Labori, Cathrine; Loennecken, Marianne; Msall, Me; Møinicken, Unn inger; Peyton, Colleen; Schreiber, Me; Silberg, Inger Elisabeth; Songstad, Nils Thomas; Vaagen, Randi; Øberg, Gunn Kristin; Adde, Lars (Journal article; Peer reviewed, 2019)
      Background: Early identification of cerebral palsy (CP) during infancy will provide opportunities for early therapies and treatments. The aim of the present study was to present a novel machine-learning model, the ...
    • The Predictive Accuracy of the General Movement Assessment for Cerebral Palsy: A Prospective, Observational Study of High-Risk Infants in a Clinical Follow-Up Setting 

      Støen, Ragnhild; Boswell, Lynn; De Regnier, Raye-Ann; Fjørtoft, Toril Larsson; Gaebler-Spira, Deborah; Ihlen, Espen Alexander F.; Labori, Cathrine; Loennecken, Marianne; Msall, Michael E.; Moinichen, Unn Inger; Peyton, Colleen; Russow, Annamarie; Schreiber, Michael D.; Silberg, Inger Elisabeth; Songstad, Nils Thomas; Vågen, Randi Tynes; Øberg, Gunn Kristin; Adde, Lars (Journal article; Peer reviewed, 2019)
      Background: Early prediction of cerebral palsy (CP) using the General Movement Assessment (GMA) during the fidgety movements (FM) period has been recommended as standard of care in high-risk infants. The aim of this study ...
    • Towards human-level performance on automatic pose estimation of infant spontaneous movements 

      Groos, Daniel; Adde, Lars; Støen, Ragnhild; Ramampiaro, Heri; Ihlen, Espen Alexander F. (Peer reviewed; Journal article, 2021)
      Assessment of spontaneous movements can predict the long-term developmental disorders in high-risk infants. In order to develop algorithms for automated prediction of later disorders, highly precise localization of segments ...