Benchmarking Foot Trajectory Estimation Methods for Mobile Gait Analysis

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2017 Aug 24

PMID 28832511

Citations 12

Authors

Julius Hannink

Malte Ollenschlager

Felix Kluge

Nils Roth

Jochen Klucken

Bjoern M Eskofier

Affiliations

Soon will be listed here.

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.

Citing Articles

Development and Assessment of Artificial Intelligence-Empowered Gait Monitoring System Using Single Inertial Sensor.

Zhou J, Mao Q, Yang F, Zhang J, Shi M, Hu Z Sensors (Basel). 2024; 24(18).

PMID: 39338743 PMC: 11436140. DOI: 10.3390/s24185998.

Foot orientation and trajectory variability in locomotion: Effects of real-world terrain.

Gibson E, Douglas G, Jeffries K, Delaurier J, Chestnut T, Charlton J PLoS One. 2024; 19(5):e0293691.

PMID: 38753603 PMC: 11098422. DOI: 10.1371/journal.pone.0293691.

Gaitmap-An Open Ecosystem for IMU-Based Human Gait Analysis and Algorithm Benchmarking.

Kuderle A, Ullrich M, Roth N, Ollenschlager M, Ibrahim A, Moradi H IEEE Open J Eng Med Biol. 2024; 5:163-172.

PMID: 38487091 PMC: 10939318. DOI: 10.1109/OJEMB.2024.3356791.

Subthalamic 85 Hz deep brain stimulation improves walking pace and stride length in Parkinson's disease patients.

Mugge F, Kleinholdermann U, Heun A, Ollenschlager M, Hannink J, Pedrosa D Neurol Res Pract. 2023; 5(1):33.

PMID: 37559161 PMC: 10413698. DOI: 10.1186/s42466-023-00263-7.

The placement of foot-mounted IMU sensors does affect the accuracy of spatial parameters during regular walking.

Kuderle A, Roth N, Zlatanovic J, Zrenner M, Eskofier B, Kluge F PLoS One. 2022; 17(6):e0269567.

PMID: 35679231 PMC: 9182246. DOI: 10.1371/journal.pone.0269567.

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