Benchmarking Foot Trajectory Estimation Methods for Mobile Gait Analysis.

Beitrag in einer Fachzeitschrift
(Originalarbeit)


Details zur Publikation

Autor(en): Hannink J, Ollenschläger M, Kluge F, Roth N, Klucken J, Eskofier B
Zeitschrift: Sensors
Jahr der Veröffentlichung: 2017
Band: 17
Heftnummer: 9
ISSN: 1424-8220


Abstract


Mobile gait analysis systems based on inertial sensing on the shoe are applied in a wide range of applications. Especially for medical applications, they can give new insights into motor impairment in, e.g., neurodegenerative disease and help objectify patient assessment. One key component in these systems is the reconstruction of the foot trajectories from inertial data. In literature, various methods for this task have been proposed. However, performance is evaluated on a variety of datasets due to the lack of large, generally accepted benchmark datasets. This hinders a fair comparison of methods. In this work, we implement three orientation estimation and three double integration schemes for use in a foot trajectory estimation pipeline. All methods are drawn from literature and evaluated against a marker-based motion capture reference. We provide a fair comparison on the same dataset consisting of 735 strides from 16 healthy subjects. As a result, the implemented methods are ranked and we identify the most suitable processing pipeline for foot trajectory estimation in the context of mobile gait analysis.



FAU-Autoren / FAU-Herausgeber

Eskofier, Björn Prof. Dr.
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Hannink, Julius
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Klucken, Jochen Prof. Dr.
Molekular-Neurologische Abteilung in der Neurologischen Klinik
Kluge, Felix
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Ollenschläger, Malte
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Roth, Nils
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)


Zitierweisen

APA:
Hannink, J., Ollenschläger, M., Kluge, F., Roth, N., Klucken, J., & Eskofier, B. (2017). Benchmarking Foot Trajectory Estimation Methods for Mobile Gait Analysis. Sensors, 17(9). https://dx.doi.org/10.3390/s17091940

MLA:
Hannink, Julius, et al. "Benchmarking Foot Trajectory Estimation Methods for Mobile Gait Analysis." Sensors 17.9 (2017).

BibTeX: 

Zuletzt aktualisiert 2018-19-04 um 04:28