ArticleSensors (Basel, Switzerland)2022
Evaluation of Error-State Kalman Filter Method for Estimating Human Lower-Limb Kinematics during Various Walking Gaits.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
- IMU- and Vision-Based Measurement Techniques for Joint Kinematics: A Narrative Review.Sensors (Basel, Switzerland) · 2026Review
- Validity of Poststroke Gait Spatiotemporal and Joint Excursion Metrics Between Inertial Measurement Units and a Marker-Based System.Journal of applied biomechanics · 2025Article
- An Open-Source Wearable System for Real-Time Human Biomechanical Analysis.Sensors (Basel, Switzerland) · 2025Article
- Quantifying shoulder motion in the free-living environment using wearable inertial measurement units: Challenges and recommendations.Journal of biomechanics · 2025Review
- The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions.Bioengineering (Basel, Switzerland) · 2024Review
- Identification and interpretation of gait analysis features and foot conditions by explainable AI.Scientific reports · 2024Article
- Wearable sensing for understanding and influencing human movement in ecological contexts.Current opinion in biomedical engineering · 2023Article
- Drift-Free Joint Angle Calculation Using Inertial Measurement Units without Magnetometers: An Exploration of Sensor Fusion Methods for the Elbow and Wrist.Sensors (Basel, Switzerland) · 2023Article
- Gait Analysis in Neurorehabilitation: From Research to Clinical Practice.Bioengineering (Basel, Switzerland) · 2023Review
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Authors and funding
6 authors at 5 institutions in 1 country.
Funding
Abstract
Inertial measurement units (IMUs) offer an attractive way to study human lower-limb kinematics without traditional laboratory constraints. We present an error-state Kalman filter method to estimate 3D joint angles, joint angle ranges of motion, stride length, and step width using data from an array of seven body-worn IMUs. Importantly, this paper contributes a novel joint axis measurement correction that reduces joint angle drift errors without assumptions of strict hinge-like joint behaviors of the hip and knee. We evaluate the method compared to two optical motion capture methods on twenty human subjects performing six different types of walking gait consisting of forward walking (at three speeds), backward walking, and lateral walking (left and right). For all gaits, RMS differences in joint angle estimates generally remain below 5 degrees for all three ankle joint angles and for flexion/extension and abduction/adduction of the hips and knees when compared to estimates from reflective markers on the IMUs. Additionally, mean RMS differences in estimated stride length and step width remain below 0.13 m for all gait types, except stride length during slow walking. This study confirms the method's potential for non-laboratory based gait analysis, motivating further evaluation with IMU-only measurements and pathological gaits.
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Registered trials
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