Integration of force and IMU sensors for developing low-cost portable gait measurement system in lower extremities

Manupibul, Udomporn; Tanthuwapathom, Ratikanlaya; Jarumethitanont, Wimonrat; Kaimuk, Panya; Limroongreungrat, Weerawat; Charoensuk, Warakorn

doi:10.1038/s41598-023-37761-2

Cited by 9 publications

(1 citation statement)

References 42 publications

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“…Inertial sensors are the most common type of wearable sensor used for gait analysis [ 14 – 16 ]. The advantages of IMU systems include their smaller size and lower cost compared to Optical motion capture (OMC) systems, which has led to increased utilization in clinical diagnosis [ 17 – 20 ]. Previous studies have verified the feasibility of IMU.…”

Section: Introductionmentioning

confidence: 99%

Accuracy validation of a wearable IMU-based gait analysis in healthy female

He,

Chen,

Tang

et al. 2024

BMC Sports Sci Med Rehabil

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Objective The aim of this study was to assess the accuracy and test-retest reliability of a wearable inertial measurement unit (IMU) system for gait analysis in healthy female compared to a gold-standard optoelectronic motion capture (OMC) system. Methods In our study, we collected data from 5 healthy young females. Participants were attached with markers from both the OMC system and the IMU system simultaneously. Data was collected when participants walked on a 7 m walking path. Each participant performed 50 repetitions of walking on the path. To ensure the collection of complete gait cycle data, a gait cycle was considered valid only if the participant passed through the center of the walking path at the same time that the OMC system detected a valid marker signal. As a result, 5 gait cycles that met the standards of the OMC system were included in the final analysis. The stride length, cadence, velocity, stance phase and swing phase of the spatio-temporal parameters were included in the analysis. A generalized linear mixture model was used to assess the repeatability of the two systems. The Wilcoxon rank-sum test for continuous variables was used to compare the mean differences between the two systems. For evaluating the reliability of the IMU system, we calculated the Intra-class Correlation Coefficient (ICC). Additionally, Bland-Altman plots were used to compare the levels of agreement between the two systems. Results The measurements of Spatio-temporal parameters, including the stance phase (P = 0.78, 0.13, L-R), swing phase (P = 0.78, 0.13, L-R), velocity (P = 0.14, 0.13, L-R), cadence (P = 0.53, 0.22, L-R), stride length (P = 0.05, 0.19, L-R), by the IMU system and OMC system were similar. Which suggested that IMU and OMC systems could be used interchangeably for gait measurements. The intra-rater reliability showed an excellent correlation for the stance phase, swing phase, velocity and cadence (Intraclass Correlation Coefficient, ICC > 0.9) for both systems. However, the correlation of stride length was poor (ICC = 0.36, P = 0.34, L) to medium (ICC = 0.56, P = 0.22, R). Additionally, the measurements of IMU systems were repeatable. Conclusions The results of IMU system and OMC system shown good repeatability. Wearable IMU system could analyze gait data accurately. In particular, the measurement of stance phase, swing phase, velocity and cadence showed excellent reliability. IMU system provided an alternative measurement to OMC for gait analysis. However, the measurement of stride length by IMU needs further consideration.

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