Background: Quantitative functional assessment of patients remains an issue in physical rehabilitation practice. Extensive functional analysis (e.g., gait analysis) and balance assessment are limited to specialized centers. Although these analyses are considered as gold standard for research and clinical purposes, such systems present serious drawbacks (i.e., lack of transportability requesting patients to come to the analysis centers, needs of having specially-trained personnel, high prices). Because of these downsides, objective functional assessments are not frequently performed on the same patient while objective follow-up of many disorders could benefit from a more regular patient analysis also within private practice.

En 1886, la mise au jour de deux squelettes néandertaliens dans les sédiments de la terrasse de la grotte de Spy, en Belgique, fut une découverte majeure. Une étude pluridisciplinaire des fossiles a permis la découverte de nouveaux ossements néandertaliens qui appartiennent au squelette nommé « Spy II ». Bien que partiel, le squelette de Spy II est un de plus complets trouvés à ce jour ; il a donc servi dans cette étude comme de base à la reconstitution d’un squelette néandertalien virtuel. Les éléments osseux provenaient des fossiles Kebara 2 pour le bassin (en provenance d’Israël) et Neandertal 1 pour le fémur (Allemagne). Ces fossiles complémentaires présentaient des dimensions différentes de celles de Spy II. Afin de mettre ces ossements à l’échelle de Spy II, le logiciel lhpFusionBox, développé au LABO, a été amélioré afin de permettre des remises à l’échelle par utilisation d’os différents (en général, une telle remise à l’échelle se fait en utilisant des os homologues). L’utilisation de ces outils a permis l’obtention d’un modèle de membres inférieurs aussi proche que possible des dimensions et proportions du spécimen Spy II. Le modèle de membres inférieurs ainsi acquis a ensuite été augmenté d’une estimation des lignes d’actions de muscles ischio-jambiers. Enfin, ce dernier modèle a été fusionné avec un jeu de données cinématiques collectées sur un volontaire. Ceci a permis d’estimer le bras de levier des muscles reconstitués et de déterminer si les surfaces articulaires du modèle de Néandertalien est compatible avec la cinématique moderne. Les résultats semblent démontrer que les articulations des membres inférieurs des Néandertaliens était conciliable avec les mouvements de l’Homo Sapiens. Par contre, les estimations quantifiées des bras de levier musculaires du Néandertalien étaient plus élevés que ceux l’homme moderne. Ceci présente évidement un avantage mécanique conférant un plus grand moment musculaire. Plus récemment, le squelette a été entièrement reconstitué. Les modèles 3D virtuels des os ont ensuite été imprimés en 3D en taille réelle. Ces os ont servis de base à une reconstitution artistique hyperréaliste de l’Homme de Spy, visible à l’Espace de l’Homme de Spy à Onoz (province de Namur, Belgique).

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.

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 subject's 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.

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.

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.

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° and 5° 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 today's marker-based motion analysis systems (i.e., Helen–Hayes configuration, CAST method).

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±2.5mm for the humeral head, 2.5±1.1mm for the humeral trochlea, 2.3±0.9mm for the humeral capitulum, 8.2±3.9mm for the scapula glenoid cavity, 7.2±3.2mm for the scapular aspect of the acromio-clavicular joint, 3.5±1.8mm for the clavicular aspect of the sternoclavicular joint and 3.2±1.4mm 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.

INTRODUCTION Evaluation of the shoulder kinematics remains a challenge to document a functional disorder and its evolution. To ensure subject follow-up, the kinematic analysis must be repeatable and reproducible. Previously, a new technique of anatomical landmark (AL) palpation using a newly-developed finger gauntlet including a technical frame (TF) was developed to study the 3D shoulder joint kinematics. The precision and accuracy of this method of shoulder AL calibration have been evaluated [2]. The purpose of this paper was first to estimate the test-retest reproducibility of palpation performed by the same examiner who digitized eleven ALs on humerus and scapula three times on each subject the same session day and repeat the session one week later at the same day and hour. The second aim was to evaluate the propagation of palpation error on four analytical movements and three activities of daily living.

INTRODUCTION Calibration of anatomical landmarks (ALs) [1] is a key procedure for the determination of anatomical features related to the bones of a particular subject. Such ALs can then be used for the definition of local joint reference frames or registration with other data for advanced visualization or modeling [2]. In all cases the accuracy of the AL location will depend on the system used for such digitizing. The accuracy is directly proportional to the quality of the final registration and the repeatability of the measurements (a key element in a clinical setting, e.g., for patient follow-up) [2]. Standards procedures for AL location include setting of reflective markers on the subject’s skin at relevant spots, leading to relatively high errors because of skin artifacts. A more accurate method is the use of calibrated wands in order to better locate the ALs. Unfortunately, the latter method is time consuming and the protocol requires, 1 first to palpate the relevant AL with the finger pulp; -2 then to remove the finger from the AL; 3 to set the extremity of the wand on the AL; 4 to eventually digitize the AL location. The transition between steps 2 and 3 is prone to introduce errors since the palpating sensitive finger leaves the point of interest to be replaced by a non-sensitive instrument. The aim of this undergoing study is to develop a protocol able to calibrate a customized palpation system made of the palpating finger of the individual performing the palpation (i.e., the “palpator”) and a technical frame attached on this finger. Results will be presented during the conference.