Fedor Moiseev

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.

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.

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.

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.

Prediction of joint center location by customizable multiple regressions: Application to clavicle, scapula and humerus

Accurate spatial location of joint center (JC) is a key issue in motion analysis since JC locations are used to define standardized anatomical frames, in which results are represented. Accurate and reproducible JC location is important for data comparison and data exchange. This paper presents a method for JC locations based on the multiple regression algorithms without preliminary assumption on the behavior of the joint-of-interest. Regression equations were obtained from manually palpable ALs on each bone-of-interest. Results are presented for all joint surfaces found on the clavicle, scapula and humeral bone. Mean accuracy errors on the JC locations obtained on dry bones were 5.2+/-2.5 mm for the humeral head, 2.5+/-1.1 mm for the humeral trochlea, 2.3+/-0.9 mm for the humeral capitulum, 8.2+/-3.9 mm for the scapula glenoid cavity, 7.2+/-3.2 mm for the scapular aspect of the acromio-clavicular joint, 3.5+/-1.8mm for the clavicular aspect of the sternoclavicular joint and 3.2+/-1.4 mm for the clavicular aspect of the acromio-clavicular joint. In-vitro and in-vivo validation accuracy was 5.3 and 8.5mm, respectively, for the humeral head center location. Regression coefficients for joint radius dimension and joint surface orientation were also processed and reported in this paper.

Une plate-forme technologique liée à la paralysie cérébrale - Le projet ICT4Rehab

The musculoskeletal system (MSS) is essential to allow us performing every-day tasks, being able to have a professional life or developing social interactions with our entourage. MSS pathologies have a significant impact on our daily life. It is therefore not surprising to find MSS-related health problems at the top of global statistics on professional absenteeism or societal health costs. The MSS is also involved in central nervous conditions, such as cerebral palsy (CP). Such conditions show complex etiology that complicates the interpretation of the observable clinical signs and the establishment of a wide consensus on the best practices to adopt for clinical monitoring and patient follow-up. These elements justify the organization of fundamental and applied research projects aiming to develop new methods to help clinicians to cope with the complexity of some MSS disorders. The ICT4Rehab project (www.ict4rehab.org) developed an integrated platform providing tools that enable easier management and visualization of clinical information related to the MSS of CP patients. This platform is opened to every interested clinical centre.

Sex determination using the Probabilistic Sex Diagnosis (DSP: Diagnose Sexuelle Probabiliste) tool in a virtual environment.

The hip bone is one of the most reliable indicators of sex in the human body due to the fact it is the most dimorphic bone. Probabilistic Sex Diagnosis (DSP: Diagnose Sexuelle Probabiliste) developed by Murail et al., in 2005, is a sex determination method based on a worldwide hip bone metrical database. Sex is determined by comparing specific measurements taken from each specimen using sliding callipers and computing the probability of specimens being female or male. In forensic science it is sometimes not possible to sex a body due to corpse decay or injury. Skeletalization and dissection of a body is a laborious process and desecrates the body. There were two aims to this study. The first aim was to examine the accuracy of the DSP method in comparison with a current visual sexing method on sex determination. A further aim was to see if it was possible to virtually utilise the DSP method on both the hip bone and the pelvic girdle in order to utilise this method for forensic sciences. For the first part of the study, forty-nine dry hip bones of unknown sex were obtained from the Body Donation Programme of the Université Libre de Bruxelles (ULB). A comparison was made between DSP analysis and visual sexing on dry bone by two researchers. CT scans of bones were then analysed to obtain three-dimensional (3D) virtual models and the method of DSP was analysed virtually by importing the models into a customised software programme called lhpFusionBox which was developed at ULB. The software enables DSP distances to be measured via virtually-palpated bony landmarks. There was found to be 100% agreement of sex between the manual and virtual DSP method. The second part of the study aimed to further validate the method by analysing thirty-nine supplementary pelvic girdles of known sex blind. There was found to be a 100% accuracy rate further demonstrating that the virtual DSP method is robust. Statistically significant differences were found in the identification of sex between researchers in the visual sexing method although both researchers identified the same sex in all cases in the manual and virtual DSP methods for both the hip bones and pelvic girdles.

From KinectTM to anatomically-correct motion modelling: Preliminary results for human application.

The KinectTM sensors can be used as cost effective and easy to use Markerless Motion Capture devices. Therefore a wide range of new potential applications are possible. Unfortunately, right now, the stick model skeleton provided by the KinectTM is only composed of 20 points located approximately at the joint level of the subject which movements are being captured by the camera. This relatively limited amount of key points is limiting the use of such devices to relatively crude motion assessment. The field of motion analysis however is requesting more key points in order to represent motion according to clinical conventions based on so-called anatomical planes. To extend the possibility of the KinectTM supplementary data must be added to the available standard skeleton. This paper presents a new Model-Based Approach (MBA) that has been specially developed for KinectTM input based on previous validated anatomical and biomechanical studies performed by the authors. This approach allows real 3D motion analysis of complex movements respecting conventions expected in biomechanics and clinical motion analysis.