1
|
Hulshof CM, Schallig W, van den Noort JC, Streekstra GJ, Kleipool RP, Gg Dobbe J, Maas M, Harlaar J, van der Krogt MM. Skin marker-based versus bone morphology-based coordinate systems of the hindfoot and forefoot. J Biomech 2024; 166:112001. [PMID: 38527409 DOI: 10.1016/j.jbiomech.2024.112001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/31/2024] [Accepted: 02/14/2024] [Indexed: 03/27/2024]
Abstract
Segment coordinate systems (CSs) of marker-based multi-segment foot models are used to measure foot kinematics, however their relationship to the underlying bony anatomy is barely studied. The aim of this study was to compare marker-based CSs (MCSs) with bone morphology-based CSs (BCSs) for the hindfoot and forefoot. Markers were placed on the right foot of fifteen healthy adults according to the Oxford, Rizzoli and Amsterdam Foot Model (OFM, RFM and AFM, respectively). A CT scan was made while the foot was loaded in a simulated weight-bearing device. BCSs were based on axes of inertia. The orientation difference between BCSs and MCSs was quantified in helical and 3D Euler angles. To determine whether the marker models were able to capture inter-subject variability in bone poses, linear regressions were performed. Compared to the hindfoot BCS, all MCSs were more toward plantar flexion and internal rotation, and RFM was also oriented toward more inversion. Compared to the forefoot BCS, OFM and RFM were oriented more toward dorsal and plantar flexion, respectively, and internal rotation, while AFM was not statistically different in the sagittal and transverse plane. In the frontal plane, OFM was more toward eversion and RFM and AFM more toward inversion compared to BCS. Inter-subject bone pose variability was captured with RFM and AFM in most planes of the hindfoot and forefoot, while this variability was not captured by OFM. When interpreting multi-segment foot model data it is important to realize that MCSs and BCSs do not always align.
Collapse
Affiliation(s)
- Chantal M Hulshof
- Department of Rehabilitation Medicine, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands; Department of Rehabilitation Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1118 1081 HZ, Amsterdam, the Netherlands; Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands.
| | - Wouter Schallig
- Department of Rehabilitation Medicine, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands; Department of Rehabilitation Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1118 1081 HZ, Amsterdam, the Netherlands; Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands.
| | - Josien C van den Noort
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands; Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands
| | - Geert J Streekstra
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands; Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands
| | - Roeland P Kleipool
- Department of Medical Biology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands
| | - Johannes Gg Dobbe
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands
| | - Mario Maas
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands; Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands
| | - Jaap Harlaar
- Department of Rehabilitation Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1118 1081 HZ, Amsterdam, the Netherlands; Department of Biomechanical Engineering, Delft University of Technology, Mekelweg 2 2628 CD, Delft, the Netherlands; Department of Orthopedics & Sports Medicine, Erasmus MC, Doctor Molewaterplein 40 3015 GD, Rotterdam, the Netherlands
| | - Marjolein M van der Krogt
- Department of Rehabilitation Medicine, Amsterdam UMC, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, the Netherlands; Department of Rehabilitation Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1118 1081 HZ, Amsterdam, the Netherlands; Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands
| |
Collapse
|
2
|
Effect of the soft tissue artifact on marker measurements and on the calculation of the helical axis of the knee during a squat movement: A study on the CAMS-Knee dataset. Med Eng Phys 2022; 110:103915. [PMID: 36564140 PMCID: PMC9771824 DOI: 10.1016/j.medengphy.2022.103915] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 10/19/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Marker-based motion capture recordings of human body segments are often affected by soft tissue artifact (STA). The undesired and uncontrolled motion of the skin may introduce errors in the estimation of motion and position of body segments and, consequently, in the calculation of the relative functional quantities. METHODS This study exploited a recently published dataset consisting of six adult subjects that underwent a total knee arthroplasty. The subject performed squat tasks while the motion was concurrently recorded by passive markers attached to the skin of the lower limbs, an optoelectronic system, and a fluoroscope. The STA of shank and thigh was decomposed in local deformation and rigid motion. Additionally, we studied how the instantaneous helical axis (IHA) calculation is affected by STA. FINDINGS The cluster most affected by STA rigid motion was the thigh. The largest estimated effects were about 7 deg. and about 20 mm. The largest effect of local deformation was about 25 mm, and it was observed on the thigh cluster. INTERPRETATION The STA made the estimation of the IHA unreliable for both position and direction. The choice of the reference configuration influenced the results of the STA analysis.
Collapse
|
3
|
Schallig W, van den Noort JC, Piening M, Streekstra GJ, Maas M, van der Krogt MM, Harlaar J. The Amsterdam Foot Model: a clinically informed multi-segment foot model developed to minimize measurement errors in foot kinematics. J Foot Ankle Res 2022; 15:46. [PMID: 35668453 PMCID: PMC9172122 DOI: 10.1186/s13047-022-00543-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 05/03/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Foot and ankle joint kinematics are measured during clinical gait analyses with marker-based multi-segment foot models. To improve on existing models, measurement errors due to soft tissue artifacts (STAs) and marker misplacements should be reduced. Therefore, the aim of this study is to define a clinically informed, universally applicable multi-segment foot model, which is developed to minimize these measurement errors. METHODS The Amsterdam foot model (AFM) is a follow-up of existing multi-segment foot models. It was developed by consulting a clinical expert panel and optimizing marker locations and segment definitions to minimize measurement errors. Evaluation of the model was performed in three steps. First, kinematic errors due to STAs were evaluated and compared to two frequently used foot models, i.e. the Oxford and Rizzoli foot models (OFM, RFM). Previously collected computed tomography data was used of 15 asymptomatic feet with markers attached, to determine the joint angles with and without STAs taken into account. Second, the sensitivity to marker misplacements was determined for AFM and compared to OFM and RFM using static standing trials of 19 asymptomatic subjects in which each marker was virtually replaced in multiple directions. Third, a preliminary inter- and intra-tester repeatability analysis was performed by acquiring 3D gait analysis data of 15 healthy subjects, who were equipped by two testers for two sessions. Repeatability of all kinematic parameters was assessed through analysis of the standard deviation (σ) and standard error of measurement (SEM). RESULTS The AFM was defined and all calculation methods were provided. Errors in joint angles due to STAs were in general similar or smaller in AFM (≤2.9°) compared to OFM (≤4.0°) and RFM (≤6.7°). AFM was also more robust to marker misplacement than OFM and RFM, as a large sensitivity of kinematic parameters to marker misplacement (i.e. > 1.0°/mm) was found only two times for AFM as opposed to six times for OFM and five times for RFM. The average intra-tester repeatability of AFM angles was σ:2.2[0.9°], SEM:3.3 ± 0.9° and the inter-tester repeatability was σ:3.1[2.1°], SEM:5.2 ± 2.3°. CONCLUSIONS Measurement errors of AFM are smaller compared to two widely-used multi-segment foot models. This qualifies AFM as a follow-up to existing foot models, which should be evaluated further in a range of clinical application areas.
Collapse
Affiliation(s)
- Wouter Schallig
- Amsterdam UMC location Vrije Universiteit Amsterdam, Rehabilitation Medicine, De Boelelaan 1117, Amsterdam, The Netherlands.
- Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands.
- Amsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands.
| | - Josien C van den Noort
- Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands
- Amsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Musculoskeletal Health, Amsterdam, the Netherlands
| | - Marjolein Piening
- Amsterdam UMC location Vrije Universiteit Amsterdam, Rehabilitation Medicine, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Geert J Streekstra
- Amsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Musculoskeletal Health, Amsterdam, the Netherlands
- Amsterdam UMC location University of Amsterdam, Biomedical Engineering and Physics, Meibergdreef 9, Amsterdam, the Netherlands
| | - Mario Maas
- Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands
- Amsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Musculoskeletal Health, Amsterdam, the Netherlands
| | - Marjolein M van der Krogt
- Amsterdam UMC location Vrije Universiteit Amsterdam, Rehabilitation Medicine, De Boelelaan 1117, Amsterdam, The Netherlands
- Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands
| | - Jaap Harlaar
- Amsterdam UMC location Vrije Universiteit Amsterdam, Rehabilitation Medicine, De Boelelaan 1117, Amsterdam, The Netherlands
- Department of Biomechanical Engineering, Delft University of Technology, Delft, the Netherlands
- Department of Orthopedics & Sports Medicine , ErasmusMC, Rotterdam, the Netherlands
| |
Collapse
|