A Novel Kalman Filter for Human Motion Tracking With an Inertial-Based Dynamic Inclinometer

IEEE Transactions on Bio-medical Engineering
Gabriele Ligorio, Angelo Maria Sabatini

Abstract

Design and development of a linear Kalman filter to create an inertial-based inclinometer targeted to dynamic conditions of motion. The estimation of the body attitude (i.e., the inclination with respect to the vertical) was treated as a source separation problem to discriminate the gravity and the body acceleration from the specific force measured by a triaxial accelerometer. The sensor fusion between triaxial gyroscope and triaxial accelerometer data was performed using a linear Kalman filter. Wrist-worn inertial measurement unit data from ten participants were acquired while performing two dynamic tasks: 60-s sequence of seven manual activities and 90 s of walking at natural speed. Stereophotogrammetric data were used as a reference. A statistical analysis was performed to assess the significance of the accuracy improvement over state-of-the-art approaches. The proposed method achieved, on an average, a root mean square attitude error of 3.6° and 1.8° in manual activities and locomotion tasks (respectively). The statistical analysis showed that, when compared to few competing methods, the proposed method improved the attitude estimation accuracy. A novel Kalman filter for inertial-based attitude estimation was presented in t...Continue Reading

References

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Citations

Feb 24, 2016·Sensors·Stefan LambrechtJosé L Pons
Jul 28, 2016·Sensors·Markus MiezalGabriele Bleser
Oct 21, 2016·PloS One·Shaghayegh Zihajehzadeh, Edward J Park
May 18, 2017·Biomedical Engineering Online·Samuel L NogueiraJose L Pons
Aug 29, 2018·Sensors·Liyao LiFeng Chen
Mar 9, 2016·Micromachines·Gabriele Ligorio, Angelo Maria Sabatini
Jul 9, 2021·Journal of Biomechanics·Damith SenanayakeDavid C Ackland

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