Assessment of IMU-derived lower-limb kinematics in transtibial amputees: A practical and accessible clinical workflow

Clinical gait assessment in individuals with transtibial amputation is limited by the cost, technical demands, and space requirements of laboratory-based motion analysis. Although research-grade inertial measurement unit (IMU) systems provide a portable alternative, their hardware and software costs may restrict routine clinical use. Assessment in transtibial prosthesis users is further complicated by altered segment coordination, prosthetic component function, and limited anatomical landmarks. This study evaluated a transparent, independently implemented workflow using a consumer-grade IMU-based gait analysis system (cIMU) against a research-grade reference IMU system (rIMU). Thirty-two individuals with unilateral transtibial amputation completed five overground level-walking trials while wearing both systems, with sensors mounted in standardized adjacent positions. For the cIMU workflow, segment-orientation outputs were processed using custom Python scripts to derive bilateral hip, knee, and ankle kinematics, whereas rIMU kinematics were generated using the system’s proprietary processing software. Inter-workflow agreement and repeated-trial consistency were assessed using Statistical Parametric Mapping (SPM), Bland-Altman analysis, intraclass correlation coefficients (ICCs), intra-subject variability, and paired comparisons across three anatomical planes. Repeated-trial consistency was high for hip kinematics across all three anatomical planes and for sagittal-plane knee and ankle kinematics, with average-measure ICCs ranging from 0.945 to 0.996. Inter-workflow agreement was strongest for sagittal-plane measures, with Bland-Altman mean differences within 2.5° for sagittal-plane knee and ankle measures. Wider limits of agreement were observed for several frontal- and transverse-plane measures and distal-joint variables. SPM identified significant waveform differences across multiple gait-cycle phases, particularly for frontal- and transverse-plane measures, while paired comparisons showed that differences in discrete measures were concentrated in non-sagittal and distal-joint variables. The cIMU workflow may be most useful for repeated-trial assessment of broad sagittal-plane gait patterns, whereas frontal- and transverse-plane kinematics and distal-joint measures should be interpreted cautiously. This accessible workflow may provide a practical option where research-grade gait-analysis systems are unavailable.

Authors

Publication Details

Journal
PLoS ONE
Published
2026-08-24
DOI
https://doi.org/10.1371/journal.pone.0356786
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of IMU-derived lower-limb kinematics in transtibial amputees: A practical and accessible clinical workflow

Weerawat Limroongreungrat, Manunchaya Samala, Jutima Rattanakoch, Udomporn Manupibul et al.
PLoS ONE
Prosthetics and Rehabilitation Robotics
article

Assessment of IMU-derived lower-limb kinematics in transtibial amputees: A practical and accessible clinical workflow

Weerawat Limroongreungrat, Manunchaya Samala, Jutima Rattanakoch, Udomporn Manupibul, Wisavaporn Niamsang, Harit Apidech, Gary Guerra, Thanaphat Laucha, Mintra Suphab
article en

Abstract

Clinical gait assessment in individuals with transtibial amputation is limited by the cost, technical demands, and space requirements of laboratory-based motion analysis. Although research-grade inertial measurement unit (IMU) systems provide a portable alternative, their hardware and software costs may restrict routine clinical use. Assessment in transtibial prosthesis users is further complicated by altered segment coordination, prosthetic component function, and limited anatomical landmarks. This study evaluated a transparent, independently implemented workflow using a consumer-grade IMU-based gait analysis system (cIMU) against a research-grade reference IMU system (rIMU). Thirty-two individuals with unilateral transtibial amputation completed five overground level-walking trials while wearing both systems, with sensors mounted in standardized adjacent positions. For the cIMU workflow, segment-orientation outputs were processed using custom Python scripts to derive bilateral hip, knee, and ankle kinematics, whereas rIMU kinematics were generated using the system’s proprietary processing software. Inter-workflow agreement and repeated-trial consistency were assessed using Statistical Parametric Mapping (SPM), Bland-Altman analysis, intraclass correlation coefficients (ICCs), intra-subject variability, and paired comparisons across three anatomical planes. Repeated-trial consistency was high for hip kinematics across all three anatomical planes and for sagittal-plane knee and ankle kinematics, with average-measure ICCs ranging from 0.945 to 0.996. Inter-workflow agreement was strongest for sagittal-plane measures, with Bland-Altman mean differences within 2.5° for sagittal-plane knee and ankle measures. Wider limits of agreement were observed for several frontal- and transverse-plane measures and distal-joint variables. SPM identified significant waveform differences across multiple gait-cycle phases, particularly for frontal- and transverse-plane measures, while paired comparisons showed that differences in discrete measures were concentrated in non-sagittal and distal-joint variables. The cIMU workflow may be most useful for repeated-trial assessment of broad sagittal-plane gait patterns, whereas frontal- and transverse-plane kinematics and distal-joint measures should be interpreted cautiously. This accessible workflow may provide a practical option where research-grade gait-analysis systems are unavailable.

PLoS ONEVol. 21(8)
Openalex Percentile: Top 18%
Prosthetics and Rehabilitation Robotics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.