Victor Sholukha

Validity and reliability of the Kinect within functional assessment activities: comparison with standard stereophotogrammetry.

The recent availability of the Kinect™ sensor, a cost-effective markerless motion capture system (MLS), offers interesting possibilities in clinical functional analysis and rehabilitation. However, neither validity nor reproducibility of this device is known yet. These two parameters were evaluated in this study. Forty-eight volunteers performed shoulder abduction, elbow flexion, hip abduction and knee flexion motions; the same protocol was repeated one week later to evaluate reproducibility. Movements were simultaneously recorded by the Kinect (with Microsoft Kinect SDK v.1.5) MLS and a traditional marker-based stereophotogrammetry system (MBS). Considering the MBS as reference, discrepancies between MLS and MBS were evaluated by comparing the range of motion (ROM) between both systems. MLS reproducibility was found to be statistically similar to MBS results for the four exercises. Measured ROMs however were found different between the systems.

Registration of 6-DOFs electrogoniometry and CT medical imaging for 3D joint modeling

The paper describes a method in which two data-collecting systems, medical imaging and electrogoniometry, are combined to allow the accurate and simultaneous modeling of both the spatial kinematics and the morphological surface of a particular joint. The joint of interest (JOI) is attached to a Plexiglas jig that includes four metallic markers defining a local reference system (R(GONIO)) for the kinematics data. Volumetric data of the JOI and the R(GONIO) markers are collected from medical imaging. The spatial location and orientation of the markers in the global reference system (R(CT)) of the medical-imaging environment are obtained by applying object-recognition and classification methods on the image dataset. Segmentation and 3D isosurfacing of the JOI are performed to produce a 3D model including two anatomical objects-the proximal and distal JOI segments. After imaging, one end of a custom-made 3D electrogoniometer is attached to the distal segment of the JOI, and the other end is placed at the R(GONIO) origin; the JOI is displaced and the spatial kinematics data is recorded by the goniometer. After recording, data registration from R(GONIO) to R(CT) occurred prior to simulation. Data analysis was performed using both joint coordinate system (JCS) and instantaneous helical axis (IHA).Finally, the 3D joint model is simulated in real time using the experimental kinematics data. The system is integrated into a computer graphics interface, allowing free manipulation of the 3D scene. The overall accuracy of the method has been validated with two other kinematics data collection methods including a 3D digitizer and interpolation of the kinematics data from discrete positions obtained from medical imaging. Validation has been performed on both superior and inferior radio-ulna joints (i.e. prono-supination motion). Maximal RMS error was 1 degrees and 1.2mm on the helical axis rotation and translation, respectively. Prono-supination of the forearm showed a total rotation of 132 degrees for 0.8mm of translation. The method reproducibility using JCS parameters was in average 1 degrees (maximal deviation=2 degrees ) for rotation, and 1mm (maximal deviation=2mm) for translation. In vitro experiments have been performed on both knee joint and ankle joint. Averaged JCS parameters for the knee were 109 degrees, 17 degrees and 4 degrees for flexion, internal rotation and abduction, respectively. Averaged maximal translation values for the knee were 12, 3 and 4mm posteriorly, medially and proximally, respectively. Averaged JCS parameters for the ankle were 43 degrees, 9 degrees and 3 degrees for plantarflexion, adduction and internal rotation, respectively. Averaged maximal translation values for the ankle were 4, 2 and 1mm anteriorly, medially and proximally, respectively.

Determination of the precision and accuracy of morphological measurements using the Kinect™ sensor: comparison with standard stereophotogrammetry

The recent availability of the Kinect™ sensor, a low-cost Markerless Motion Capture (MMC) system, could give new and interesting insights into ergonomics (e.g. the creation of a morphological database). Extensive validation of this system is still missing. The aim of the study was to determine if the Kinect™ sensor can be used as an easy, cheap and fast tool to conduct morphology estimation. A total of 48 subjects were analysed using MMC. Results were compared with measurements obtained from a high-resolution stereophotogrammetric system, a marker-based system (MBS). Differences between MMC and MBS were found; however, these differences were systematically correlated and enabled regression equations to be obtained to correct MMC results. After correction, final results were in agreement with MBS data (p = 0.99). Results show that measurements were reproducible and precise after applying regression equations. Kinect™ sensors-based systems therefore seem to be suitable for use as fast and reliable tools to estimate morphology. Practitioner Summary: The Kinect™ sensor could eventually be used for fast morphology estimation as a body scanner. This paper presents an extensive validation of this device for anthropometric measurements in comparison to manual measurements and stereophotogrammetric devices. The accuracy is dependent on the segment studied but the reproducibility is excellent.

Precision of shoulder anatomical landmark calibration by two approaches: A CAST-like protocol and a new Anatomical Palpator method

The objective of the study was to compare the precision of shoulder anatomical landmark palpation using a CAST-like method and a newly developed anatomical palpator device (called A-Palp) using the forefinger pulp directly. The repeated-measures experimental design included four examiners that twice repeated measurements on eleven scapula and humerus anatomical landmarks during two sessions. Inter-session and inter-examiner precision was determined on volunteers. A-Palp accuracy was obtained from in vitro measurements and using virtual palpation on 3D bone models. Error propagation on the motion representation was also analyzed for a continuous motion of abduction movement performed in the shoulder joint. Palpation results showed that CAST and A-Palp methods lead to similar precision with the Maximal A-Palp calibration error being 1.5mm. In vivo precision of the CAST and A-Palp methods varied between 4mm (inter-session) and 8mm (inter-examiner). Mean propagation of the palpation error on the motion graph representation was 2 degrees and 5 degrees for scapula and humerus, respectively. A-Palp accuracy was 3.6 and 8.1mm for scapula and humerus, respectively. The A-Palp seems promising and could probably become an additional method next to todays marker-based motion analysis systems (i.e., Helen-Hayes configuration, CAST method).

Femur shape prediction by multiple regression based on quadric surface fitting

Quadric surface fitting of joint surface areas is often performed to allow further processing of joint component size, location and orientation (pose), or even to determine soft tissue wrapping by collision detection and muscle moment arm evaluation. This study aimed to determine, for the femoral bone, if the position of its morphological joint centers and the shape morphology could be approximated using regression methods with satisfactory accuracy from a limited amount of palpable anatomical landmarks found on the femoral bone surface. The main aim of this paper is the description of the pipeline allowing on one hand the data collection and database storage of femoral bone characteristics, and on the other hand the determination of regression relationships from the available database. The femoral bone components analyzed in this study included the diaphysis, all joint surfaces (shape, location and orientation of the head, condyles and femoro-patellar surface) and their respective spatial relationships (e.g., cervico-diaphyseal angle, cervico-bicondylar angle, intercondylar angle, etc.). A total of 36 morphological characteristics are presented and can be estimated by regression method in in-vivo applications from the spatial location of 3 anatomical landmarks (lateral epicondyle, medial epicondyle and greater trochanter) located on the individual under investigation. The method does not require any a-priori knowledge on the functional aspect of the joint. In-vivo and in-vitro validations have been performed using data collected from medical imaging by virtual palpation and data collected directly on a volunteer using manual palpation through soft tissue. The prediction accuracy for most of the 36 femoral characteristics determined from virtual palpation was satisfactory, mean (SD) distance and orientation errors were 2.7(2.5)mm and 6.8(2.7)°, respectively. Manual palpation data allowed good accuracy for most femoral features, mean (SD) distance and orientation errors were 4.5(5.2)mm and 7.5(5.3)°, respectively. Only the in-vivo location estimation of the femoral head was worse (position error=23.2mm). In conclusion, results seem to show that the method allows in-vivo femoral joint shape prediction and could be used for further development (e.g., surface collision, muscle wrapping, muscle moment arm estimation, joint surface dimensions, etc.) in gait analysis-related applications.

Model-based approach for human kinematics reconstruction from markerless and marker-based motion analysis systems

Modeling tools related to the musculoskeletal system have been previously developed. However, the integration of the real underlying functional joint behavior is lacking and therefore available kinematic models do not reasonably replicate individual human motion. In order to improve our understanding of the relationships between muscle behavior, i.e. excursion and motion data, modeling tools must guarantee that the model of joint kinematics is correctly validated to ensure meaningful muscle behavior interpretation. This paper presents a model-based method that allows fusing accurate joint kinematic information with motion analysis data collected using either marker-based stereophotogrammetry (MBS) (i.e. bone displacement collected from reflective markers fixed on the subjects skin) or markerless single-camera (MLS) hardware. This paper describes a model-based approach (MBA) for human motion data reconstruction by a scalable registration method for combining joint physiological kinematics with limb segment poses. The presented results and kinematics analysis show that model-based MBS and MLS methods lead to physiologically-acceptable human kinematics. The proposed method is therefore available for further exploitation of the underlying model that can then be used for further modeling, the quality of which will depend on the underlying kinematic model.

In vivo registration of both electrogoniometry and medical imaging: development and application on the ankle joint complex

An in vivo method for joint kinematics visualization and analysis is described. Low-dose computed tomography allowed three-dimensional joint modeling, and electrogoniometry collected joint kinematic data. Data registration occurred using palpated anatomical landmarks to obtain interactive computer joint simulation. The method was applied on one volunteers ankle, and reproducibility was tested (maximal discrepancy: 3.6 deg and 5.5 mm for rotation and translation respectively).

Musculoskeletal modeling of the suboccipital spine: kinematics analysis, muscle lengths, and muscle moment arms during axial rotation and flexion extension.

Study Design. In vitro and modeling study of upper cervical spine (UCS) three-dimensional (3D) kinematics and muscle moment arm (MA) during axial rotation (AR) and flexion extension (FE). Objective. To create musculoskeletal models with movement simulation including helical axis (HA) and muscle features. Summary of Background Data. Integration of various kinematics and muscle data into specific-specimen 3D anatomical models with graphical representation of HA and muscle orientation and MA is not reported for the UCS musculoskeletal system. Methods. Kinematics, anatomical, and computed tomographic imaging data were sampled in 10 anatomical specimens. Using technical markers and anatomical landmarks digitizing, spatial position of segments was computed for five discrete positions of AR and FE using a 3D digitizer. To obtain musculoskeletal model simulation, a registration method was used to combine collected data. Processing was performed using orientation vector and HA computation and suboccipital muscle features (i.e., length and MA) relative to motion angle. Results. Range of motion and coupling were in agreement with previous in vitro studies. HA (i.e., location and orientation) showed low variation at the occipitoaxial and atlantoaxial levels for FE and AR, respectively. The main orientation of the HA was vertical at C1–C2 during AR and horizontal at C0–C1 during FE. For muscles MA, absolute peak value (ranging from 20 to 40 mm) occurred at different poses depending on the analyzed muscle and motion. Poor magnitude was found for obliquus capitis inferior and rectus capitis posterior minor in FE and AR, respectively. Conclusion. On the basis of previous methods, we developed a protocol to create UCS musculoskeletal modeling with motion simulation including HA and suboccipital muscles representation. In this study, simultaneous segmental movement displaying with HA and muscles features was shown to be feasible.

Data representation for joint kinematics simulation of the lower limb within an educational context.

Three-dimensional (3D) visualization is becoming increasingly frequent in both qualitative and quantitative biomechanical studies of anatomical structures involving multiple data sources (e.g. morphological data and kinematics data). For many years, this kind of experiment was limited to the use of bi-dimensional images due to a lack of accurate 3D data. However, recent progress in medical imaging and computer graphics has forged new perspectives. Indeed, new techniques allow the development of an interactive interface for the simulation of human motions combining data from both medical imaging (i.e., morphology) and biomechanical studies (i.e., kinematics). Fields of application include medical education, biomechanical research and clinical research. This paper presents an experimental protocol for the development of anatomically realistic joint simulation within a pedagogical context. Results are shown for the lower limb. Extension to other joints is straightforward. This work is part of the Virtual Animation of the Kinematics of the Human project (VAKHUM) (http://www.ulb.ac.be/project/vakhum).

In vivo thorax 3D modelling from costovertebral joint complex kinematics

BACKGROUND The costovertebral joint complex is mechanically involved in both respiratory function and thoracic spine stability. The thorax has been studied for a long time to understand its involvement in the physiological mechanism leading to specific gas exchange. Few studies have focused on costovertebral joint complex kinematics, and most of them focused on experimental in vitro analysis related to loading tests or global thorax and/or lung volume change analysis. There is however a clinical need for new methods allowing to process in vivo clinical data. This paper presents results from in vivo analysis of the costovertebral joint complex kinematics from clinically-available retrospective data. METHODS In this study, in vivo spiral computed tomography imaging data were obtained from 8 asymptomatic subjects at three different lung volumes (from total lung capacity to functional residual capacity) calibrated using a classical spirometer. Fusion methods including 3D modelling and kinematic analysis were used to provide 3D costovertebral joint complex visualization for the true ribs (i.e., first seven pairs of ribs). FINDINGS The 3D models of the first seven pairs of costovertebral joint complexes were obtained. A continuous kinematics simulation was interpolated from the three discrete computerized tomography positions. Helical axis representation was also achieved. INTERPRETATION Preliminary results show that the method leads to meaningful and relevant results for clinical and pedagogical applications. Research in progress compares data from a sample of healthy volunteers with data collected from patients with cystic fibrosis to obtain new insights about the costovertebral joint complex range of motion and helical axis assessment in different pathological conditions.