Details
Original language | English |
---|---|
Article number | 6621 |
Journal | Sensors |
Volume | 21 |
Issue number | 19 |
Publication status | Published - 5 Oct 2021 |
Abstract
Gait symmetry analysis plays an important role in the diagnosis and rehabilitation of pathological gait. Recently, wearable devices have also been developed for simple gait analysis so-lutions. However, measurement in clinical settings can differ from gait in daily life, and simple wearable devices are restricted to a few parameters, providing one-sided trajectories of one arm or leg. Therefore, head-worn devices with sensors (e.g., earbuds) should be considered to analyze gait symmetry because the head sways towards the left and right side depending on steps. This paper proposed new visualization methods using head-worn sensors, able to facilitate gait symmetry analysis outside as well as inside. Data were collected with an inertial measurement unit (IMU) based motion capture system when twelve participants walked on the 400-m running track. From head trajectories on the transverse and frontal plane, three types of diagrams were displayed, and five concepts of parameters were measured for gait symmetry analysis. The mean absolute percentage error (MAPE) of step counting was lower than 0.65%, representing the reliability of measured pa-rameters. The methods enable also left-right step recognition (MAPE ≤ 2.13%). This study can support maintenance and relearning of a balanced healthy gait in various areas with simple and easy-to-use devices.
Keywords
- Eye diagram, Gait symmetry, Gait symmetry analysis, Head-worn sensor, Inertial measurement unit, Wearable sensor
ASJC Scopus subject areas
- Chemistry(all)
- Analytical Chemistry
- Computer Science(all)
- Information Systems
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
- Biochemistry, Genetics and Molecular Biology(all)
- Biochemistry
- Physics and Astronomy(all)
- Instrumentation
- Engineering(all)
- Electrical and Electronic Engineering
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In: Sensors, Vol. 21, No. 19, 6621, 05.10.2021.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Head Trajectory Diagrams for Gait Symmetry Analysis Using a Single Head-Worn IMU
AU - Hwang, Tonghun
AU - Effenberg, Alfred O.
N1 - Funding Information: The publication of this article was funded by the Open Access Fund of Leibniz Universität Hannover. Acknowledgments: The authors acknowledge support by European Commission HORIZON2020-FETPROACT-2014 No. 641321.
PY - 2021/10/5
Y1 - 2021/10/5
N2 - Gait symmetry analysis plays an important role in the diagnosis and rehabilitation of pathological gait. Recently, wearable devices have also been developed for simple gait analysis so-lutions. However, measurement in clinical settings can differ from gait in daily life, and simple wearable devices are restricted to a few parameters, providing one-sided trajectories of one arm or leg. Therefore, head-worn devices with sensors (e.g., earbuds) should be considered to analyze gait symmetry because the head sways towards the left and right side depending on steps. This paper proposed new visualization methods using head-worn sensors, able to facilitate gait symmetry analysis outside as well as inside. Data were collected with an inertial measurement unit (IMU) based motion capture system when twelve participants walked on the 400-m running track. From head trajectories on the transverse and frontal plane, three types of diagrams were displayed, and five concepts of parameters were measured for gait symmetry analysis. The mean absolute percentage error (MAPE) of step counting was lower than 0.65%, representing the reliability of measured pa-rameters. The methods enable also left-right step recognition (MAPE ≤ 2.13%). This study can support maintenance and relearning of a balanced healthy gait in various areas with simple and easy-to-use devices.
AB - Gait symmetry analysis plays an important role in the diagnosis and rehabilitation of pathological gait. Recently, wearable devices have also been developed for simple gait analysis so-lutions. However, measurement in clinical settings can differ from gait in daily life, and simple wearable devices are restricted to a few parameters, providing one-sided trajectories of one arm or leg. Therefore, head-worn devices with sensors (e.g., earbuds) should be considered to analyze gait symmetry because the head sways towards the left and right side depending on steps. This paper proposed new visualization methods using head-worn sensors, able to facilitate gait symmetry analysis outside as well as inside. Data were collected with an inertial measurement unit (IMU) based motion capture system when twelve participants walked on the 400-m running track. From head trajectories on the transverse and frontal plane, three types of diagrams were displayed, and five concepts of parameters were measured for gait symmetry analysis. The mean absolute percentage error (MAPE) of step counting was lower than 0.65%, representing the reliability of measured pa-rameters. The methods enable also left-right step recognition (MAPE ≤ 2.13%). This study can support maintenance and relearning of a balanced healthy gait in various areas with simple and easy-to-use devices.
KW - Eye diagram
KW - Gait symmetry
KW - Gait symmetry analysis
KW - Head-worn sensor
KW - Inertial measurement unit
KW - Wearable sensor
UR - http://www.scopus.com/inward/record.url?scp=85116239528&partnerID=8YFLogxK
U2 - 10.3390/s21196621
DO - 10.3390/s21196621
M3 - Article
C2 - 34640945
AN - SCOPUS:85116239528
VL - 21
JO - Sensors
JF - Sensors
SN - 1424-8220
IS - 19
M1 - 6621
ER -