Kati Nispel
6 Papers
Kati Nispel is an academic researcher. The author has contributed to research in topics: Biomechanics & Computer science. The author has an hindex of 1, co-authored 4 publications.
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Papers
Multibody Models of the Thoracolumbar Spine: A Review on Applications, Limitations, and Challenges
TL;DR: In this article , a review of the current state-of-the-art literature on multibody models of the thoracolumbar spine is presented, identifying limitations and challenges related to current modeling approaches.
Recent Advances in Coupled MBS and FEM Models of the Spine—A Review
TL;DR: In this paper , the authors classified the studies into unidirectional and bidirectional co-simulation, according to their data exchange methods, and proposed a new approach for improved spine modeling, as a main challenge in spinal biomechanics is the nonlinear deformation of the intervertebral discs.
The Potential of Co-simulation in Sports Engineering - A Review on Spine Simulations
Kati Nispel
- 01 Jan 2022
TL;DR: This paper will present a review on the recent developments in Co-simulations of the spine and afterwards finish with the potential benefits a nonlinear approach can bring for sports engineering.
Validation of a Patient-Specific Musculoskeletal Model for Lumbar Load Estimation Generated by an Automated Pipeline From Whole Body CT
Tanja Lerchl,Malek El Husseini,Amirhossein Bayat,Anjany Sekuboyina,Luis Hermann,Kati Nispel,Thomas Baum,Maximilian T. Löffler,Veit Senner,Jan S. Kirschke +9 more
TL;DR: An automatically generated patient-specific musculoskeletal model of the spine simulating static loading tasks was validated and was able to calculate loads of the lumbar spine for static activities with respect to individual biomechanical properties, such as spinal alignment, bodyweight distribution, and ligament and muscle insertion points.
Rule-based Key-Point Extraction for MR-Guided Biomechanical Digital Twins of the Spine
Robert Graf,Tanja Lerchl,Kati Nispel,H. Möller,Matan Atad,Julian McGinnis,Julius Maria Watrinet,Johannes C. Paetzold,Daniel Rueckert,J. Kirschke +9 more
TL;DR: This study presents a rule-based approach for extracting subpixel-accurate key-points from MRI for MR-guided biomechanical digital twins of the spine, enabling radiation-free, subject-specific simulation and clinical decision support for spinal mechanics and personalized healthcare.