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Effects of Soft Tissue Artifacts on the
Calculted Kinematic and Kinetic Variables of
the Knee During Cycling
Jia-Da Li
1, Tung-Wu Lu
1,2, Yu-Huan Wu
1, Mei-Ying Kuo
3, Tsung-Chi Lin
1, Cheng-Chung Lin
1,
Yen-Hung Liu
1, Horng-Chaung Hsu
41 Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan, R.O.C. 2 Department of Orthopaedic Surgery, School of Medicine, National Taiwan University, Taiwan, R.O.C.
3 Department of Physical Therapy, China Medical University, Taiwan, R.O.C. 4 Department of Orthopaedics, China Medical University Hospital, Taichung, Taiwan
Abstract- Effects of soft tissue artifacts (STA) on the calculated kinematic and kinetic variables at the knee during cycling has never been reported in the literature. The current study aimed to bridge the gap. Five healthy young adults cycled on an ergometer with instrumented pedals mimicking rehabilitation conditions. The subject wore 30 skin markers on the pelvis-leg apparatus while the marker trajectories were measured using a motion capture system, and the knee was imaged at 30 Hz by a bi-plane fluoroscopy system. Joint kinematic and kinetic variables were calculated using skin markers and bone data separately, the later being the gold standard. The results showed that using skin marker data the knee joint angles, shear forces and moments were underestimated and translations were overestimated. However, these effects were relatively small in the sagittal plane. The current results will be helpful for developing guidelines for using skin markers to study cycling motion.
Keywords-Soft tissue artifacts; Cycling; Knee; Joint angles; Joint moments
1. INTRODUCTION
Cycling has played an important role in transportation, recreation, and sport in our daily lives. Exercises with cycles have also grown in popularity over the past 10 years. About 15% of American adults and 24% of Canadian adults report cycling at least once a week for recreation or exercise purpose. However, with the increasing popularity of cycling, an increasing proportion of the billions of cyclists worldwide are also suffering from cycling-related overuse injuries. There has been a need in the development of injury-specific cycling exercise programs for the rehabilitation of the lower extremities, which requires a comprehensive knowledge of the biomechanics of cycling. Generally, biomechanics of the lower limb joints during cycling exercises has mostly been studied using skin marker-based motion analysis techniques and is subject to soft tissue artifacts (STA). However, no study has reported a complete assessment of the effects of STA on the calculated joint center motions, angles, shear forces, and moments at the knee during this activity. The current study aimed to evaluate in vivo the STA effects on these calculated variables by integrating 3D fluoroscopy and stereophotogrammetry. It was hypothesized that STA would significantly affect these calculated variables. 2. MATERIAL AND METHODS
Sujects
Five healthy young adults (age: 20.8Ʋ0.6 years, height: 171.6Ʋ2.5 cm, mass: 61.4Ʋ7.3 kg) participated in the current study with informed written consent, as approved by the Institutional Research Board. All subjects were free of neuromusculoskeletal dysfunction.
Experimental procedure
Each subject wore 30 skin markers on the pelvis and the right lower limb, and performed cycling on an ergometer at an average resistance of 20 Nm mimicking rehabilitation conditions. The pedals of the ergometer were instrumented with 6-component load-cells for measuring pedal reaction forces during cycling. The 3D marker trajectories were measured using a 12-camera motion capture system at a sampling rate of 120Hz (Vicon Motion Systems Ltd., UK). The knee was also imaged simultaneously at 60 Hz by a bi-plane dynamic fluoroscopy system (ALLURA XPER FD, Philips). The knees of the subjects were also CT scanned and used to construct CT-based bone models. A subject static calibration was also performed. A metronome was used to keep cycling speed at 30 RPM, which gave about 120 fluoroscopic images per cycle (approximate 3° crank angle per frame) and 240 data points for stereophotogrammetric system.
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Data analysis
The subject-specific, CT-based bone models were registered to the fluoroscopy images using a volumetric model-based fluoroscopy-to-CT registration method [1], giving poses of the femur and tibia, and the knee joint center positions. The means and standard deviations of the bone pose errors were less than -0.4 (0.4) mm and - 0.5ƱƱƱƱġġġġ(0.3ƱƱƱƱ) for all translational and all angular components, respectively [1]. During subject calibration without skin movement, bone coordinate systems were defined for the thigh and shank based on the registered poses of the femur and tibia following the ISB convention, which coincided with the segment-embedded coordinate systems. Meanwhile, the position of a skin marker relative to the associated bone coordinate system was taken as the reference for STA estimation. During movement, given the measured marker coordinate relative to the stereophotogrammetry system, the components of the STA in the bone coordinate system at time t, corresponding to the anterior/posterior (A/P), proximal/distal (P/D) and medial/lateral (M/L) components, were calculated as the current position of the marker relative to the bone and fluoroscopy coordinate systems, respectively. The gold standard positions of these markers, i.e., those of the so-called virtual bone markers (VBM), in the fluoroscopy coordinate system were obtained.
The knee joint angles were obtained following a z–x–y Cardanic rotation sequence, using both skin marker and VBM data. With the measured pedal reaction force (PRF), the moments about the knee joint center were calculated by considering the free bodies of the foot and shank using the measured motion data and PRF. The results from the VBM were taken as the gold standard. The knee joint center (KJC) was defined as the mid- point of the trans-epicondylar axis in the anatomical position, and its movement in the shank coordinate system as the knee joint center translation. Inertial properties for each body segment were obtained using an optimization method [2]. The calculated moments were normalized to body weight and leg length. Translations, forces, and moments were reported with respect to the shank embedded anatomical coordinate system.
Statistical Analysis
Descriptive statistics data was reported for maximum differences throughout analyzed cycle between the results obtained from skin marker and VBM, as well as root mean square of errors (RMSE). To compare the results from skin markers and VBM, a paired t-test was used for each time instances of the whole cycle at an increment of 3° crank angle (i.e. 120 data points) for each of the variables. A significant level of 0.05 was set for all tests.
3. RESULTS
Accurate 3D skeletal kinematics of the knee during cycling was measured using the 3D fluoroscopy method, giving accurate joint rotations, KJC translations, forces and moments that were taken as the gold standard.
Rotations and translations
Skin markers underestimated significantly the knee flexion angles at crank angles of 0
ƱƱƱƱ
-112ƱƱƱƱġġġġ
and 186ƱƱƱƱ
-360ƱƱƱƱġġġġ
(corresponding to knee flexion angles of 103.3ƱƱƱƱ
-29.25ƱƱƱƱġġġġ
and 23.67ƱƱƱƱ
-103.3ƱƱƱƱ
), the maximum difference being 10.77ƱƱƱƱ
(1.89ƱƱƱƱ
) with a RMSE of 6.14ƱƱƱƱ
(0.98ƱƱƱƱ
) (Fig. 1a, Table 1). The abduction angles were also underestimated but no significance was found, the maximum difference being 6.71ƱƱƱƱ
(2.5ƱƱƱƱ
) with a RMSE of 4.06ƱƱƱƱ
(1.9ƱƱƱƱ
). Internal rotation angles were also significantly underestimated at crank angles of 53ƱƱƱƱ
-80ƱƱƱƱġġġġ
(corresponding to knee flexion angles of 76.3ƱƱƱƱ
-55.45ƱƱƱƱ
), the maximum difference being 6.11ƱƱƱƱ
(1.39ƱƱƱƱ
) with a RMSE of 3.22ƱƱƱƱ
(0.77ƱƱƱƱ
).Compared to the gold standard, the posterior translations of the KJC calculated from skin markers were significantly overestimated at crank angles of 50
ƱƱƱƱ
-113ƱƱƱƱġġġġ
and 182ƱƱƱƱ
-248ƱƱƱƱġġġġ
(corresponding to knee flexion angles of 78.6ƱƱƱƱ
-28.5ƱƱƱƱġġġġ
and 20.8ƱƱƱƱ
-68.6ƱƱƱƱ
) (Fig 1b, Table 1), with a maximum difference of 9.12 (2.8) mm and a RMSE of 5.6 (2.57) mm. Distal translations of the KJC was also significantly overestimated at crank angles of 0ƱƱƱƱ
-94ƱƱƱƱġ
and 165ƱƱƱƱ
-360ƱƱƱƱġġġġ
(corresponding to knee flexion angles of 103.3ƱƱƱƱ
-44ƱƱƱƱġġġġ
and 11.9ƱƱƱƱ
-103.3ƱƱƱƱ
), the maximum error being 17.49 (3.85) mm with a RMSE of 10.7 (3.1) mm. Lateral translations of the KJC was significantly underestimated at crank angles of 289ƱƱƱƱ
-350ƱƱƱƱġġġġ
(corresponding to knee flexion angles of 92.7ƱƱƱƱ
-104.9ƱƱƱƱ
), the maximum error being 5.57 (1.23) mm with a RMSE of 2.86 (0.57) mm.džƚĞŶĚĞĚďƐƚƌĂĐƚƐ
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(a)*
*
*
(b)*
*
*
*
*
Figure 1. Mean curves of the angles (a) and joint center translations (b) of the knee obtained using skin markers (red dashed lines) and VBM (blue solid lines, gold standard) during a complete cycling cycle. Blue and red areas represent one standard deviation. Ranges marked with asterisks represent significant differences between the means.
Forces and moments
Knee joint forces calculated from skin markers were slightly different from the gold standard for the anterior/posterior, proximal/distal components (maximum error less than 2.8% of the maximum value of the gold standard). No significant differences were found for the medial/lateral force component. Maximum difference was 5.15 (2.69) N and a RMSE of 1.9 (0.95) N (Table 1).
The extensor moments calculated using skin markers were significantly underestimated at crank angles of 0ƱƱƱƱ- 125ƱƱƱƱġġġġand 331ƱƱƱƱ-360ƱƱƱƱġġġġ(corresponding to knee flexion angles of 103.3ƱƱƱƱ-19.52ƱƱƱƱġġġġand 105.9ƱƱƱƱ-103.3ƱƱƱƱ), the maximum difference being 3.31(1.12) Nm with a RMSE of 1.38(0.49) Nm. The abductor moments were significantly underestimated at crank angles of 7-22ƱƱƱƱġġġġ(corresponding to knee flexion angles of 101.7ƱƱƱƱ-95.7ƱƱƱƱ), the maximum difference being 2.02(1.09) Nm with a RMSE of 0.77(0.39) Nm. In contrast to the other two components, the internal rotator moments were small (maximum value: 4.1 Nm) and no significant difference was found.
4. DISCUSSION
The current study aimed to assess the STA effects on the calculated kinematics and kinetics of the normal knee during cycling. The results showed that STA caused a significant underestimation in the knee angles, forces and moments, but a significant overestimation of joint center translations at high knee flexion angles. No significant differences were found on the abduction angles between gold standard and skin marker results. It is noted that large standard deviations were found between subjects in most of the angular displacement components, suggesting that subject-specific STA compensation is necessary.
Joint moments are often used to assess the function of muscles during exercises. Muscle moments were generated to counteract the external moments as a product of RPF and its leverarm lengths at the KJC, the calculated moments were affected by the KJC position. Therefore, inaccuracies in the KJC positions will lead to inaccurate joint moments. The maximum differences and RMSE in joint moments found in the current study indicate that care should be exercised when interpreting results obtained from skin markers during cycling.
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The current study was limited to a small number of subjects. Further study to include more subjects may be necessary to generalize the current results to the same young subject population. Nonetheless, the large variation between the subjects may also suggest that average patterns of the STA and the associated effects may not apply to individual subjects. Subject-specific compensation for the effects of STA is necessary, especially for the interpretation of subtle but significant differences between subject groups in clinical studies.
In conclusion, the current study reported the first data on the STA effects on the calculated knee kinematics and kinetics in healthy young subjects during cycling. The results will be helpful for developing guidelines for using skin markers to study cycling motion, and for developing STA compensation methods for future applications.
Table 1. Means (SD) of the maximum differences and RMSE values of the calculated knee angles, translations, shear forces, and moments across all subjects, also as percentages of the maximum value obtained from VBM.
Maximum Differences RMSE
Angles Flexion/Extension (Degree) 10.77 (1.89) (%) 10.10 (1.68) (Degree) 6.14 (0.98) (%) 5.77 (0.95)
Abduction/Adduction 6.71 (2.50) 56.19 (20.28) 4.06 (1.90) 32.94 (13.31) Internal/External 6.11 (1.39) 77.94 (37.20) 3.22 (0.77) 40.87 (19.73) Translations Anterior/Posterior (mm) 9.12 (2.80) (%) 34.73 (15.75) (mm) 5.60 (2.57) (%) 21.93 (12.71) Proximal/Distal 17.49 (3.85) 148.80 (147.06) 10.70 (3.10) 95.04 (101.45) Medial/Lateral 5.57 (1.23) 72.88 (21.52) 2.86 (0.57) 37.73 (12.39) Forces Anterior/Posterior (N) 3.56 (0.31) (%) 2.70 (0.41) (N) 1.39 (0.30) (%) 1.04 (0.24) Proximal/Distal 2.61 (1.01) 1.72 (0.77) 0.96 (0.29) 0.63 (0.23) Medial/Lateral 5.15 (2.69) 16.77 (6.11) 1.90 (0.95) 6.31 (2.41) Moments Abduction/Adduction (Nm) 2.02 (1.09) (%) 13.96 (7.68) (Nm) 0.77 (0.39) (%) 5.32 (2.72) Internal/External 1.00 (0.56) 22.79 (11.22) 0.37 (0.20) 8.50 (4.32) Flexion/Extension 3.31 (1.12) 7.30 (1.82) 1.38 (0.49) 3.04 (0.85) 5. ACKNOWLEDGMENTThe authors gratefully acknowledge the financial support from Nation Science Council, Taiwan (NSC 102- 2627-B-002-001-).
6. REFERENCES
[1] Lin, C.-C., Lu, T.-W., Wang, T.-M., Hsu, C.-Y. and Shih, T.-F., 2013. Comparisons of Surface vs. Volumetric Model-Based Registration Methods Using Single-Plane vs. Bi-Plane Fluoroscopy in Measuring Spinal Kinematics. Medical Engineering & Physics, 1350-4533.
[2] Chen, S.-C., Hsieh, H.-J., Lu, T.-W., Tseng, C.-H., 2011. A method for estimating subject-specific body segment inertial parameters in human movement analysis. Gait & Posture 33(4), 695-700.
