A Dual-Module-Driven Method for Foot Posture Indirect Measurement With Potential Application in Rehabilitation Robots

Currently, wearable systems have become mainstream in human motion analysis due to their low cost, minimal environmental constraints, and capability for prolonged monitoring. However, wearable inertial sensors can only directly measure motion data at their mounting locations, which necessitates increasing the number of sensors in the network to capture multi-limb data. This, in turn, diminishes the advantages of lightweight design and minimal motion interference. To address this issue, this paper proposes a dual-module driven indirect estimation method for foot orientation. The approach is based on two significant factors in foot orientation changes during gait: the direct driving from the shank and the foot’s intrinsic fine adjustment. Accordingly, two driving modules are constructed, and real-time adjustable weight factors are applied. Validation on 7 healthy subjects and 11 pathological subjects yielded a root mean square error (RMSE) of 3.81 ± 1.21 and an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> value of 0.95. Compared with similar studies, the proposed method not only is applicable to healthy subjects but also demonstrates high robustness in pathological gait. Moreover, the hardware system, consisting solely of two inertial measurement units (IMUs) mounted on the shank, offers significant clinical value.

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Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3572996
Citations
2
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
2.05

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article

A Dual-Module-Driven Method for Foot Posture Indirect Measurement With Potential Application in Rehabilitation Robots

Haozhou Zeng, Tao Liu, Jiaxing Li, Xiangliang Zhang et al.
2 citations
IEEE Transactions on Instrumentation and Measurement
Stroke Rehabilitation and Recovery
2.05
article

A Dual-Module-Driven Method for Foot Posture Indirect Measurement With Potential Application in Rehabilitation Robots

Haozhou Zeng, Tao Liu, Jiaxing Li, Xiangliang Zhang, Xiangzhi Liu
article en
2 citations

Abstract

Currently, wearable systems have become mainstream in human motion analysis due to their low cost, minimal environmental constraints, and capability for prolonged monitoring. However, wearable inertial sensors can only directly measure motion data at their mounting locations, which necessitates increasing the number of sensors in the network to capture multi-limb data. This, in turn, diminishes the advantages of lightweight design and minimal motion interference. To address this issue, this paper proposes a dual-module driven indirect estimation method for foot orientation. The approach is based on two significant factors in foot orientation changes during gait: the direct driving from the shank and the foot’s intrinsic fine adjustment. Accordingly, two driving modules are constructed, and real-time adjustable weight factors are applied. Validation on 7 healthy subjects and 11 pathological subjects yielded a root mean square error (RMSE) of 3.81 ± 1.21 and an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> value of 0.95. Compared with similar studies, the proposed method not only is applicable to healthy subjects but also demonstrates high robustness in pathological gait. Moreover, the hardware system, consisting solely of two inertial measurement units (IMUs) mounted on the shank, offers significant clinical value.

IEEE Transactions on Instrumentation and MeasurementVol. 74
Zhejiang University (CN)
National Natural Science Foundation of China
Gender equality
Openalex Percentile: Top 13%
Stroke Rehabilitation and Recovery
2.05
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