Search Results - "Prossel, Dominik"

An Inertial Sensor-Based Gait Analysis Pipeline for the Assessment of Real-World Stair Ambulation Parameters by Roth, Nils, Küderle, Arne, Prossel, Dominik, Gassner, Heiko, Eskofier, Bjoern M., Kluge, Felix

“…Climbing stairs is a fundamental part of daily life, adding additional demands on the postural control system compared to level walking. Although real-world…”
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Gaitmap-An Open Ecosystem for IMU-Based Human Gait Analysis and Algorithm Benchmarking by Kuderle, Arne, Ullrich, Martin, Roth, Nils, Ollenschlager, Malte, Ibrahim, Alzhraa A., Moradi, Hamid, Richer, Robert, Seifer, Ann-Kristin, Zurl, Matthias, Simpetru, Raul C., Herzer, Liv, Prossel, Dominik, Kluge, Felix, Eskofier, Bjoern M.

“…Goal: Gait analysis using inertial measurement units (IMUs) has emerged as a promising method for monitoring movement disorders. However, the lack of public…”
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Three Approaches to Approximating the Fisher Information Number for Gaussian Mixture Densities by Prossel, Dominik, Hanebeck, Uwe D.

“…The Fisher information number (FIN) has previously been proposed as a regularizer to fit a probability density function to a set of constraints. Especially for…”
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Spline-Based Density Estimation Minimizing Fisher Information by Prossel, Dominik, Hanebeck, Uwe D.

“…The construction of a continuous probability density function (pdf) that fits a set of samples is a frequently occurring task in statistics. This is an…”
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Closed-Form Information-Theoretic Roughness Measures for Mixture Densities by Hanebeck, Uwe D., Frisch, Daniel, Prossel, Dominik

“…In estimation, control, and machine learning under uncertainties, latent variables are usually described by a probability density function (pdf). The optimal…”
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Dirac Mixture Reduction Using Wasserstein Distances on Projected Cumulative Distributions by Prossel, Dominik, Hanebeck, Uwe D.

“…The reapproximation of discrete probability densities is a common task in sample-based filters such as the particle filter. It can be viewed as the…”
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Progressive Particle Filtering Using Projected Cumulative Distributions by Prossel, Dominik, Hanebeck, Uwe D.

“…We propose a progressive particle filter that inherently avoids sample degeneracy by splitting the likelihood into a product of wider functions applied step by…”
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