Model-Based Estimation of Ankle Joint Stiffness
We address the estimation of biomechanical parameters with wearable measurement technologies. In particular, we focus on the estimation of sagittal plane ankle joint stiffness in dorsiflexion/plantar flexion. For this estimation, a novel nonlinear biomechanical model of the lower leg was formulated...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-03-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/17/4/713 |
| _version_ | 1818000513429405696 |
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| author | Berno J. E. Misgeld Tony Zhang Markus J. Lüken Steffen Leonhardt |
| author_facet | Berno J. E. Misgeld Tony Zhang Markus J. Lüken Steffen Leonhardt |
| author_sort | Berno J. E. Misgeld |
| collection | DOAJ |
| description | We address the estimation of biomechanical parameters with wearable measurement technologies. In particular, we focus on the estimation of sagittal plane ankle joint stiffness in dorsiflexion/plantar flexion. For this estimation, a novel nonlinear biomechanical model of the lower leg was formulated that is driven by electromyographic signals. The model incorporates a two-dimensional kinematic description in the sagittal plane for the calculation of muscle lever arms and torques. To reduce estimation errors due to model uncertainties, a filtering algorithm is necessary that employs segmental orientation sensor measurements. Because of the model’s inherent nonlinearities and nonsmooth dynamics, a square-root cubature Kalman filter was developed. The performance of the novel estimation approach was evaluated in silico and in an experimental procedure. The experimental study was conducted with body-worn sensors and a test-bench that was specifically designed to obtain reference angle and torque measurements for a single joint. Results show that the filter is able to reconstruct joint angle positions, velocities and torque, as well as, joint stiffness during experimental test bench movements. |
| first_indexed | 2024-04-14T03:23:38Z |
| format | Article |
| id | doaj.art-5b4c57b4be304f9193ceaeb9515073a3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T03:23:38Z |
| publishDate | 2017-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5b4c57b4be304f9193ceaeb9515073a32022-12-22T02:15:15ZengMDPI AGSensors1424-82202017-03-0117471310.3390/s17040713s17040713Model-Based Estimation of Ankle Joint StiffnessBerno J. E. Misgeld0Tony Zhang1Markus J. Lüken2Steffen Leonhardt3Philips Chair for Medical Information Technology, RWTH Aachen University, Pauwelsstrasse 20, 52074 Aachen, GermanyPhilips Chair for Medical Information Technology, RWTH Aachen University, Pauwelsstrasse 20, 52074 Aachen, GermanyPhilips Chair for Medical Information Technology, RWTH Aachen University, Pauwelsstrasse 20, 52074 Aachen, GermanyPhilips Chair for Medical Information Technology, RWTH Aachen University, Pauwelsstrasse 20, 52074 Aachen, GermanyWe address the estimation of biomechanical parameters with wearable measurement technologies. In particular, we focus on the estimation of sagittal plane ankle joint stiffness in dorsiflexion/plantar flexion. For this estimation, a novel nonlinear biomechanical model of the lower leg was formulated that is driven by electromyographic signals. The model incorporates a two-dimensional kinematic description in the sagittal plane for the calculation of muscle lever arms and torques. To reduce estimation errors due to model uncertainties, a filtering algorithm is necessary that employs segmental orientation sensor measurements. Because of the model’s inherent nonlinearities and nonsmooth dynamics, a square-root cubature Kalman filter was developed. The performance of the novel estimation approach was evaluated in silico and in an experimental procedure. The experimental study was conducted with body-worn sensors and a test-bench that was specifically designed to obtain reference angle and torque measurements for a single joint. Results show that the filter is able to reconstruct joint angle positions, velocities and torque, as well as, joint stiffness during experimental test bench movements.http://www.mdpi.com/1424-8220/17/4/713joint stiffness estimationbody-worn sensorsmagnetic, angular rate and gravity sensorsBSN |
| spellingShingle | Berno J. E. Misgeld Tony Zhang Markus J. Lüken Steffen Leonhardt Model-Based Estimation of Ankle Joint Stiffness Sensors joint stiffness estimation body-worn sensors magnetic, angular rate and gravity sensors BSN |
| title | Model-Based Estimation of Ankle Joint Stiffness |
| title_full | Model-Based Estimation of Ankle Joint Stiffness |
| title_fullStr | Model-Based Estimation of Ankle Joint Stiffness |
| title_full_unstemmed | Model-Based Estimation of Ankle Joint Stiffness |
| title_short | Model-Based Estimation of Ankle Joint Stiffness |
| title_sort | model based estimation of ankle joint stiffness |
| topic | joint stiffness estimation body-worn sensors magnetic, angular rate and gravity sensors BSN |
| url | http://www.mdpi.com/1424-8220/17/4/713 |
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