936 resultados para Markerless motion analysis
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Background: Central cord syndrome (CCS) is considered the most common incomplete spinal cord injury (SCI). Independent ambulation was achieved in 87-97% in young patients with CCS but no gait analysis studies have been reported before in such pathology. The aim of this study was to analyze the gait characteristics of subjects with CCS and to compare the findings with a healthy age, sex and anthropomorphically matched control group (CG), walking both at a self-selected speed and at the same speed. Methods: Twelve CCS patients and a CG of twenty subjects were analyzed. Kinematic data were obtained using a three-dimensional motion analysis system with two scanner units. The CG were asked to walk at two different speeds, at a self-selected speed and at a slower one, similar to the mean gait speed previously registered in the CCS patient group. Temporal, spatial variables and kinematic variables (maximum and minimum lower limb joint angles throughout the gait cycle in each plane, along with the gait cycle instants of occurrence and the joint range of motion ROM) were compared between the two groups walking at similar speeds. Results: The kinematic parameters were compared when both groups walked at a similar speed, given that there was a significant difference in the self-selected speeds (p < 0.05). Hip abduction and knee flexion at initial contact, as well as minimal knee flexion at stance, were larger in the CCS group (p < 0.05). However, the range of knee and ankle motion in the sagittal plane was greater in the CG group (p < 0.05). The maximal ankle plantar-flexion values in stance phase and at toe off were larger in the CG (p < 0.05). Conclusions: The gait pattern of CCS patients showed a decrease of knee and ankle sagittal ROM during level walking and an increase in hip abduction to increase base of support. The findings of this study help to improve the understanding how CCS affects gait changes in the lower limbs.
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Introduction: Ankle arthropathy is associated with a decreased motion of the ankle-hindfoot during ambulation. Ankle arthrodesis was shown to result in degeneration of the neighbour joints of the foot. Inversely, total ankle arthroplasty conceptually preserves the adjacent joints because of the residual mobility of the ankle but this has not been demonstrated yet in vivo. It has also been reported that degenerative ankle diseases, and even arthrodesis, do not result in alteration of the knee and hip joints. We present the preliminary results of a new approach of this problem based on ambulatory gait analysis. Patients and Methods: Motion analysis of the lower limbs was performed using a Physilog® (BioAGM, CH) system consisting of three-dimensional (3D) accelerometer and gyroscope, coupled to a magnetic system (Liberty©, Polhemus, USA). Both systems have been validated. Three groups of two patients were included into this pilot study and compared to healthy subjects (controls) during level walking: patients with ankle osteoarthritis (group 1), patients treated by ankle arthrodesis (group 2), patients treated by total ankle prosthesis (group 3). Results: Motion patterns of all analyzed joints over more than 20 gait cycles in each subject were highly repeatable. Motion amplitude of the ankle-hindfoot in control patients was similar to recently reported results. Ankle arthrodesis limited the motion of the ankle-hindfoot in the sagittal and horizontal planes. The prosthetic ankle allowed a more physiologic movement in the sagittal plane only. Ankle arthritis and its treatments did not influence the range of motion of the knee and hip joint during stance phase, excepted for a slight decrease of the hip flexion in groups 1 and 2. Conclusion: The reliability of the system was shown by the repeatability of the consecutive measurements. The results of this preliminary study were similar to those obtained through laboratory gait analysis. However, our system has the advantage to allow ambulatory analysis of 3D kinematics of the lower limbs outside of a gait laboratory and in real life conditions. To our knowledge this is a new concept in the analysis of ankle arthropathy and its treatments. Therefore, there is a potential to address specific questions like the difficult comparison of the benefits of ankle arthroplasty versus arthrodesis. The encouraging results of this pilot study offer the perspective to analyze the consequences of ankle arthropathy and its treatments on the biomechanics of the lower limbs ambulatory, in vivo and in daily life conditions.
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This paper presents a technique to estimate and model patient-specific pulsatility of cerebral aneurysms over onecardiac cycle, using 3D rotational X-ray angiography (3DRA) acquisitions. Aneurysm pulsation is modeled as a time varying-spline tensor field representing the deformation applied to a reference volume image, thus producing the instantaneousmorphology at each time point in the cardiac cycle. The estimated deformation is obtained by matching multiple simulated projections of the deforming volume to their corresponding original projections. A weighting scheme is introduced to account for the relevance of each original projection for the selected time point. The wide coverage of the projections, together with the weighting scheme, ensures motion consistency in all directions. The technique has been tested on digital and physical phantoms that are realistic and clinically relevant in terms of geometry, pulsation and imaging conditions. Results from digital phantomexperiments demonstrate that the proposed technique is able to recover subvoxel pulsation with an error lower than 10% of the maximum pulsation in most cases. The experiments with the physical phantom allowed demonstrating the feasibility of pulsation estimation as well as identifying different pulsation regions under clinical conditions.
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Sophisticated magnetic resonance tagging techniques provide powerful tools for the non-invasive assessment of the local heartwall motion towards a deeper fundamental understanding of local heart function. For the extraction of motion data from the time series of magnetic resonance tagged images and for the visualization of the local heartwall motion a new image analysis procedure has been developed. New parameters have been derived which allows quantification of the motion patterns and are highly sensitive to any changes in these patterns. The new procedure has been applied for heart motion analysis in healthy volunteers and in patient collectives with different heart diseases. The achieved results are summarized and discussed.
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In this paper we present a new method to track bonemovements in stereoscopic X-ray image series of the kneejoint. The method is based on two different X-ray imagesets: a rotational series of acquisitions of the stillsubject knee that will allow the tomographicreconstruction of the three-dimensional volume (model),and a stereoscopic image series of orthogonal projectionsas the subject performs movements. Tracking the movementsof bones throughout the stereoscopic image series meansto determine, for each frame, the best pose of everymoving element (bone) previously identified in the 3Dreconstructed model. The quality of a pose is reflectedin the similarity between its simulated projections andthe actual radiographs. We use direct Fourierreconstruction to approximate the three-dimensionalvolume of the knee joint. Then, to avoid the expensivecomputation of digitally rendered radiographs (DRR) forpose recovery, we reformulate the tracking problem in theFourier domain. Under the hypothesis of parallel X-raybeams, we use the central-slice-projection theorem toreplace the heavy 2D-to-3D registration of projections inthe signal domain by efficient slice-to-volumeregistration in the Fourier domain. Focusing onrotational movements, the translation-relevant phaseinformation can be discarded and we only consider scalarFourier amplitudes. The core of our motion trackingalgorithm can be implemented as a classical frame-wiseslice-to-volume registration task. Preliminary results onboth synthetic and real images confirm the validity ofour approach.
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In this thesis, the suitability of different trackers for finger tracking in high-speed videos was studied. Tracked finger trajectories from the videos were post-processed and analysed using various filtering and smoothing methods. Position derivatives of the trajectories, speed and acceleration were extracted for the purposes of hand motion analysis. Overall, two methods, Kernelized Correlation Filters and Spatio-Temporal Context Learning tracking, performed better than the others in the tests. Both achieved high accuracy for the selected high-speed videos and also allowed real-time processing, being able to process over 500 frames per second. In addition, the results showed that different filtering methods can be applied to produce more appropriate velocity and acceleration curves calculated from the tracking data. Local Regression filtering and Unscented Kalman Smoother gave the best results in the tests. Furthermore, the results show that tracking and filtering methods are suitable for high-speed hand-tracking and trajectory-data post-processing.
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In this paper, we propose a new velocity constraint type for Redundant Drive Wire Mechanisms. The purpose of this paper is to demonstrate that the proposed velocity constraint module can fix the orientation of the movable part and to use the kinematical analysis method to obtain the moving direction of the movable part. First, we discuss the necessity of using this velocity constraint type and the possible applications of the proposed mechanism. Second, we derive the basic equations of a wire mechanism with this constraint type. Next, we present a method of motion analysis on active and passive constraint spaces, which is used to find the moving direction of a movable part. Finally, we apply the above analysis method on a wire mechanism with a velocity constraint module and on a wire mechanism with four double actuator modules. By evaluating the results, we prove the validity of the proposed constraint type.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This study investigated kinematic patterns in clinically normal German Shepherd dogs (GSDs) compared to those with hip dysplasia and with no clinical signs of lameness. Two groups of GSDs, including 10 clinically healthy dogs (G1) and 10 with hip dysplasia (G2), were trotted on a treadmill at a constant speed. Kinematic data were collected by a 3-camera system and analysed by a motion-analysis program. Flexion and extension joint angles and angular velocities were determined for the shoulder, elbow, carpal, hip, stifle, and tarsal joints.Within each group, the differences between the right and left limbs in all kinematic variables were not significant. Minimum angle, angular displacement and minimum angular velocity did not differ between groups. Significant differences were observed in the maximum angular velocity and maximum angle of the hip joint (dysplastic. >. healthy), and in the maximum angular velocity of the carpal joint (healthy. >. dysplastic). It was concluded that, when trotting on a treadmill, dysplastic dogs with no signs of lameness may present joint kinematic alterations in the hind as well as the forelimbs. © 2012 Elsevier Ltd.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Recenti studi hanno evidenziato come il cammino in ambiente acquatico possa portare a notevoli benefici nell’ambito di un processo riabilitativo: il cammino in acqua è infatti oggi considerato una delle principali terapie per pazienti con disturbi nella deambulazione, oltre ad essere impiegato per migliorare il recupero a seguito di interventi ed infortuni. Una caratterizzazione biomeccanica del cammino umano in acqua permetterebbe tuttavia di giungere a una conoscenza più approfondita degli effetti di quest’attività sul processo riabilitativo, e dunque a una sua prescrizione più mirata come parte delle terapie. Nonostante il crescente interesse, uno dei motivi per cui ancora pochi studi sono stati condotti in questo senso risiede nell’inadeguatezza di molti dei tradizionali sistemi di Motion Capture rispetto all’impiego subacqueo. La nuova branca della Markerless Motion Capture potrebbe invece in questo senso rappresentare una soluzione. In particolare, ci si occuperà in questo lavoro di tesi della tecnica markerless basata sulla ricostruzione del visual hull per retroproiezione delle silhouette. Il processo iniziale che permette di ottenere le silhouette dai video delle acquisizioni è detto segmentazione, la quale è anche una fase particolarmente importante per ottenere una buona accuratezza finale nella ricostruzione della cinematica articolare. Si sono pertanto sviluppati e caratterizzati in questo lavoro di tesi sette algoritmi di segmentazione, nati specificamente nell’ottica dell’analisi del cammino in acqua con tecnica markerless. Si mostrerà inoltre come determinate caratteristiche degli algoritmi influenzino la qualità finale della segmentazione, e sarà infine presentato un ulteriore algoritmo di post-processing per il miglioramento della qualità delle immagini segmentate.
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The present work covers the first validation efforts of the EVA Tracking System for the assessment of minimally invasive surgery (MIS) psychomotor skills. Instrument movements were recorded for 42 surgeons (4 expert, 22 residents, 16 novice medical students) and analyzed for a box trainer peg transfer task. Construct validation was established for 7/9 motion analysis parameters (MAPs). Concurrent validation was determined for 8/9 MAPs against the TrEndo Tracking System. Finally, automatic determination of surgical proficiency based on the MAPs was sought by 3 different approaches to supervised classification (LDA, SVM, ANFIS), with accuracy results of 61.9%, 83.3% and 80.9% respectively. Results not only reflect on the validation of EVA for skills? assessment, but also on the relevance of motion analysis of instruments in the determination of surgical competence.
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This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.
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The aim of this work is to contribute to the analysis and characterization of training with whole body vibration (WBV) and the resultant neuromuscular response. WBV aims to mechanically activate muscle by eliciting stretch reflexes. Generally, surface electromyography is utilized to assess muscular response elicited by vibrations. However, EMG analysis could potentially bring to erroneous conclusions if not accurately filtered. Tiny and lightweight MEMS accelerometers were found helpful in monitoring muscle motion. Displacements were estimated integrating twice the acceleration data after gravity and small postural subject adjustments contribution removal. Results showed the relevant presence of motion artifacts on EMG recordings, the high correlation between muscle motion and EMG activity and how resonance frequencies and dumping factors depended on subject and his positioning onto the vibrating platform. Stimulations at the resonant frequency maximize muscles lengthening and in turn, muscle spindle solicitation , which may produce more muscle activation. Local mechanical stimulus characterization (Le, muscle motion analysis) could be meaningful in discovering proper muscle stimulation and may contribute to suggest appropriate and effective WBV exercise protocols. ©2009 IEEE.