Daniel Groos
Background and activities
- Pursues PhD in Medical Technology (2018-)
- PhD project: "Explainable AI-based Movement Analysis to Promote Infant Care"
- Project in collaboration between NTNU (IKOM, INB and IDI), St. Olavs Hospital (Clinic of Clinical Services and Department of Neonatology) and Norwegian Open AI Lab
- Tracking of body parts from video recordings
- Video-based prediction of movement disorders
- Markerless gait analysis of children with cerebral palsy
- Kinematic analysis of elite ski jumpers in collaboration with Centre for Elite Sports Research and Olympiatoppen
- Co-inventor of smartphone app for early detection of cerebral palsy
- Co-supervisor of Master students in Computer Science
- Deep Learning
- Computer Vision
- Convolutional Neural Networks
- Human Pose Estimation
- Supervised learning
- Transfer learning
- Explainable Artificial Intelligence
- Master of Science in Computer Science from NTNU (2013-2018)
- Specialization in Artificial Intelligence
- Master's Thesis on tracking of infant movements in videos using Deep Learning
- Internships at Telenor Research and Skatteetatens IT- og servicepartner
Scientific, academic and artistic work
Displaying a selection of activities. See all publications in the database
2021
- (2021) In-Motion-App for remote General Movement Assessment: a multi-site observational study. BMJ Open. vol. 11 (3).
- (2021) Performance analysis in ski jumping with a differential global navigation satellite system and video-based pose estimation. Sensors. vol. 21 (16).
- (2021) New automatic, efficient, and highly precise tracking of infant spontaneous movements. Developmental Medicine & Child Neurology. vol. 63.
- (2021) New automatic, efficient, and highly precise tracking of infant spontaneous movements. European Academy of Childhood Disability 2021 . European Academy of Childhood Disability; Virtual. 2021-05-20 - 2021-06-10.
2020
- (2020) Approaching human precision on automatic markerless tracking of human movements. Gait & Posture. vol. 81.
- (2020) Approaching human precision on automatic markerless tracking of human movements. Virtual ESMAC 2020 . European Society of Movement Analysis for Adults & Children; 2020-09-17.
- (2020) EfficientPose: Scalable single-person pose estimation. Applied intelligence (Boston).
2019
- (2019) Deep Learning‐based infant motion tracking facilitating early detection of cerebral palsy. Developmental Medicine & Child Neurology. vol. 61.
- (2019) Deep Learning-based infant motion tracking facilitating early detection of cerebral palsy. European Academy of Childhood Disability 2019 . European Academy of Childhood Disability; Paris. 2019-05-23 - 2019-05-25.
2018
- (2018) Infant body part tracking in videos using Deep Learning. 2018.