Estimation and visualization of sagittal kinematics of lower limbs orientation using body-fixed sensors
Open accessAbstract
A new method of estimating lower limbs orientations using a combination of accelerometers and gyroscopes is presented. The model is based on estimating the accelerations of ankle and knee joints by placing virtual sensors at the centers of rotation. The proposed technique considers human locomotion and biomechanical constraints, and provides a solution to fusing the data of gyroscopes and accelerometers that yields stable and drift-free estimates of segment orientation. The method was validated by measuring lower limb motions of eight subjects, walking at three different speeds, and comparing the results with a reference motion measurement system. The results are very close to those of the reference system presenting very small errors (Shank: rms = 1.0, Thigh: rms = 1.6 degrees) and excellent correlation coefficients (Shank: r = 0.999, Thigh: r = 0.998). Technically, the proposed ambulatory system is portable, easily mountable, and can be used for long-term monitoring without hindrance to natural activities. Finally, a gait analysis tool was designed to visualize the motion data as synthetic skeletons performing the same actions as the subjects.
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Kinematic data from accelerometers lack precision because they are affected by increased segment acceleration or drifts.
“However, kinematic data have been shown to lack precision since they are affected by increased segment acceleration or the presence of drifts (algorithms have been developed to decrease the effect of drifting in accelerometers) [4,5,6].”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [5]
Hip RMSE and correlation coefficients varied from 0.2 to 9.3° and 0.53 to 1.00, showing fair to excellent validity.
“RMSE and correlation coefficients varied respectively from 0.2 to 9.3° and 0.53 to 1.00, showing fair to excellent validity [5,30,37,41,42,46,53,54,55,56,57,58,59].”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [5]
Knee RMSE and correlation varied from 1 to 11.5° and 0.4 to 1.00.
“RMSE and coefficient correlation varied respectively from 1 to 11.5° and 0.4 to 1.00 [5,30,37,41,43,48,50,53,54,55,57,58,59,60,61].”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [5]
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References 38 · Cited by 189
- Authors
- Dejnabadi, H., Jolles, B. M., Casanova, E., Fua, P., & Aminian, K.
- Affiliations
- École Polytechnique Fédérale de Lausanne (CH)
- Centre Hospitalier Universitaire Vaudois (CH)
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2006-07
- Volume
- 53
- Issue
- 7
- Pages
- 1385-1393
- ISSN
- 0018-9294 (ISSN-L)
- OpenAlex
- W2146592202
- Cited by
- 189
- References
- 38
- Citations by year
- 2025: 3 · 2024: 4 · 2023: 3 · 2022: 7 · 2021: 11 · 2020: 12 · 2019: 15 · 2018: 9 · 2017: 8 · 2016: 7 · 2015: 8 · 2014: 16 · 2013: 14 · 2012: 15
- FWCI
- 21.06
- Type
- journal article
- Language
- en
- Open access
- green
- infoscience.epfl.ch
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- IRIS (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Funders
- Fonds De La Recherche Scientifique - FNRS
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Biomedical Engineering › Gait Recognition and Analysis
- Keywords
- soft sensors, gait analysis, wearable motion sensing
- MeSH terms
- Acceleration, Adult, Aged, Algorithms, Biomechanical Phenomena, Computer Graphics, Diagnosis, Computer-Assisted, Equipment Design, Female, Gait, Humans, Joints, Male, Middle Aged, Orientation, Software, Transducers, User-Computer Interface, Range of Motion, Articular, Monitoring, Ambulatory, Equipment Failure Analysis, Lower Extremity
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