Quantitative Gait Analysis Using Inertial Sensors: The Influence of Sensor Configuration on Extracted Gait Parameters.
- 1Instituto de Investigación Aplicada y Tecnología, Universidad Iberoamericana Ciudad de México, Mexico City 01219, Mexico.
Abstract
Inertial Measurement Units (IMUs) have emerged as a practical alternative for quantitative gait analysis. Although numerous studies have demonstrated their capability to estimate spatiotemporal and kinematic gait parameters, there is no clear consensus regarding the relationship between sensor configuration and the gait information that can be extracted. This review aimed to examine the relationship between IMU configuration, including sensor number and anatomical placement, and the quantitative gait parameters obtained, while also considering the processing methods used to derive these parameters. A structured literature review was conducted using PubMed, ScienceDirect, and Web of Science databases. Articles published between 2014 and 2025 were screened according to predefined inclusion and exclusion criteria. Information regarding sensor quantity, sensor placement, extracted gait parameters, processing methods, and validation systems was analyzed. A total of 59 studies were included. Sensor configurations ranged from one to seventeen IMUs. The extracted gait parameters were classified into gait phases, spatiotemporal parameters, and joint kinematics. The findings indicate that the relationship between the number of sensors and the gait parameters obtained is not linear. Sensor placement and signal-processing methods were found to be as important as sensor quantity in determining the gait parameters obtained. The number of IMUs alone is not a reliable predictor of the amount of gait information that can be extracted. Instead, the combination of sensor placement and processing methodology plays a critical role in determining the gait parameters obtained. These findings suggest that IMU configurations should be selected according to the gait parameters of interest rather than by maximizing the number of sensors employed.
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BibTeX
@article{lirazamacona2026quantitative,
title = {{Quantitative Gait Analysis Using Inertial Sensors: The Influence of Sensor Configuration on Extracted Gait Parameters.}},
author = {Marco Antonio Lira-Zamacona and Alma Delhi De León-Hernández and Carlos Omar López-López and Adriana Martínez-Hernández},
journal = {Journal of functional morphology and kinesiology},
year = {2026},
month = oct,
doi = {10.3390/jfmk11040433},
url = {https://europepmc.org/article/MED/42924712},
note = {CC BY},
}
RIS
TY - JOUR
TI - Quantitative Gait Analysis Using Inertial Sensors: The Influence of Sensor Configuration on Extracted Gait Parameters.
AU - Marco Antonio Lira-Zamacona
AU - Alma Delhi De León-Hernández
AU - Carlos Omar López-López
AU - Adriana Martínez-Hernández
PY - 2026
DA - 2026/10/19
JO - Journal of functional morphology and kinesiology
DO - 10.3390/jfmk11040433
UR - https://europepmc.org/article/MED/42924712
AB - Inertial Measurement Units (IMUs) have emerged as a practical alternative for quantitative gait analysis. Although numerous studies have demonstrated their capability to estimate spatiotemporal and kinematic gait parameters, there is no clear consensus regarding the relationship between sensor configuration and the gait information that can be extracted. This review aimed to examine the relationship between IMU configuration, including sensor number and anatomical placement, and the quantitative gait parameters obtained, while also considering the processing methods used to derive these parameters. A structured literature review was conducted using PubMed, ScienceDirect, and Web of Science databases. Articles published between 2014 and 2025 were screened according to predefined inclusion and exclusion criteria. Information regarding sensor quantity, sensor placement, extracted gait parameters, processing methods, and validation systems was analyzed. A total of 59 studies were included. Sensor configurations ranged from one to seventeen IMUs. The extracted gait parameters were classified into gait phases, spatiotemporal parameters, and joint kinematics. The findings indicate that the relationship between the number of sensors and the gait parameters obtained is not linear. Sensor placement and signal-processing methods were found to be as important as sensor quantity in determining the gait parameters obtained. The number of IMUs alone is not a reliable predictor of the amount of gait information that can be extracted. Instead, the combination of sensor placement and processing methodology plays a critical role in determining the gait parameters obtained. These findings suggest that IMU configurations should be selected according to the gait parameters of interest rather than by maximizing the number of sensors employed.
SN - 2411-5142
ER -