Low-cost optical tracking for collaborative applications in immersive virtual environments

We present a novel way of interacting with an immersive virtual environment which involves inexpensive motion-capture using the Wii Remote®. A software framework is also presented to visualize and share this information across two remote CAVETM-like environments. The resulting application can be used to assist rehabilitation by sending motion information across remote sites. The application’s software and hardware components are scalable enough to be used on a desktop computer when home-based rehabilitation is preferred.

Efeitos da adição de carga no treino de marcha na esteira em indivíduos com Doença de Parkinson: ensaio clínico controlado randomizado

Introduction: The intrinsic gait disorders in individuals with Parkinson's disease (PD) are one of the most disabling motor symptoms. Among the therapeutic approaches used in attempts to improve the motor function, especially the gait pattern of individuals, stands out the treadmill gait training associated with the addition of load. However, there are few findings that elucidate the benefits arising from such practice. Objective: To assess the effects of adding load on the treadmill gait training in individuals with PD. Material and Methods: A controlled, randomized and blinded clinical trial, was performed with a sample of 27 individuals (18 men and 9 women) with PD, randomly assigned to three experimental conditions, namely: treadmill gait training (n=9), treadmill gait training associated with addition of 5% load (n=9) and treadmill gait training associated with addition of 10% load (n=9). All volunteers were assessed, during phase on of Parkinson's medication, regarding to demographic, clinical and anthropometric (identification form) data, level of disability (Hoehn and Yahr Modified Scale), cognitive function (Mini Mental State Examination), clinical functional - in those areas activity of daily living and motor examination (Unified Parkinson's Disease Rating Scale - UPDRS) and gait cinematic analysis was performed through Qualisys Motion Capture System®. The intervention protocol consisted of gait training in a period of 4 consecutive weeks, with three weekly sessions, lasting 30 minutes each. The post-intervention assessment occurred the next day after the last training session, which was performed cinematic analysis of gait and the UPDRS. Data analysis was performed using the software Statistical Package for Social Sciences® (SPSS) 17.0. Results: The age of volunteers ranged from 41 to 75 years old (62,26 ± 9,07) and the time of clinical diagnosis of PD between 2 to 9 years (4,56 ± 2,42). There was a reduction regarding the score from motor exam domain (p=0,005), only when training with the addition of a 5% load. As for the space-time variables there was no significant difference between groups (p>0,120); however, the training with addition of 5% load presented the following changes: increase in stride length (p=0,028), in step length (p=0,006), in time balance of the most affected member (p=0,006) and reduction in support time of the referred member (p=0,007). Regarding angular variables significant differences between groups submitted to treadmill gait training without addition load and with 5% of load were observed in angle of the ankle at initial contact (p=0,019), in plantar flexion at toe-off (p=0,003) and in the maximum dorsiflexion in swing (p=0,005). While within groups, there was a reduction in amplitude of motion of the ankle (p=0,048), the only workout on the treadmill. Conclusion: The treadmill gait training with addition of 5% load proved to be a better experimental condition than the others because it provided greater gains in a number of variables (space-time and angular gait) and in the motion function, becoming a therapy capable of effectively improving the progress of individuals with PD

Efeitos do treino em esteira na marcha com dupla tarefa de indivíduos com doença de Parkinson: ensaio clínico controlado randomizado

Background: The gait automaticity loss difficults realization of concurrent activities - Dual Task (DT). In these situations, individuals with Parkinson`s disease (PD) show a significant reduction in gait velocity and stride length, as strides variability and asymmetry increased, factors predisposing to falls. However, recent studies have shown that training involving DT may cause subsequent improvements in gait variables with DT in individuals with PD. The treadmill use was adopted by this study, by promoting greater regularity in step and enhance training. Objective:To investigate immediate effects of gait training associated with cognitive tasks on gait in individuals with PD. Methods: Twenty-two volunteers were randomly divided into two groups: control group (n = 11), who performed gait training on a treadmill for 20 minutes, and the experimental group (n = 11), who performed treadmill gait training for 20 minutes associated with cognitive tasks of verbal fluency, memory, and spatial planning. Participants were evaluated in phase on of antiparkinsonian medication as the demographic, clinical and anthropometric (identification form), cognitive status (Montreal Cognitive Assessment - MoCA), executive function (Frontal Assessment Battery), level of physical disability (Hoehn and Yahr Modified), motor and functional status (Unified Rating Scale for Parkinson`s Disease - UPDRS), and kinematics (Qualisys Motion Capture System). Results: There were not differences between groups, but both showed improvement after the intervention. The control group had an increase in velocity (p = 0.008), stride length (p = 0.04), step length (p = 0.02) and decreased double support time(p = 0.03). The experimental group showed an increase in speed (p = 0.002), stride length (p = 0.008), step length (p = 0.02) and cadence (p = 0.01), as well as a decrease in the width stride (p = 0.001) and total support time (p = 0.02). As the angular variables, the experimental group had a significant increase in the initial contact angle of ankle (p = 0.01). Conclusion: The gait training combined with cognitive activities didn`t provide significant improvements in gait variables with DT, but this study was the first to demonstrate that gait training on treadmill as simple task minimized the negative interference of DT in PD

Papel da informação exproprioceptiva durante o andar em pessoas com doença de Parkinson e idosos sadios

A doença de Parkinson (DP) é uma neuropatologia que decorre em déficits na integração sensório-motora, destacando-se os problemas proprioceptivos e no sistema visual. Estudos mostram que pessoas com DP são mais dependentes da informação visual para executar a locomoção. Entretanto, pouco é conhecido quando a informação visual exproprioceptiva é anulada durante o andar livre e a ultrapassagem de obstáculo. Assim, o objetivo do estudo foi analisar o papel da informação visual exproprioceptiva durante o andar livre e a ultrapassagem de obstáculo em idosos com DP e idosos sadios. Participaram 12 idosos com DP, classificados em 1 e 2 na escala de Hoehn & Yahr, e 12 idosos sadios (pair matched). Os participantes foram convidados a andar, em velocidade preferida, sobre uma passarela de 8 metros sem e com obstáculo (SO e OB, respectivamente). As tentativas foram apresentadas combinando duas condições de informação visual: com e sem informação exproprioceptiva. Foram realizadas 3 tentativas por condição, totalizando 12 tentativas; realizadas em 2 blocos. A informação exproprioceptiva foi manipulada pelo uso de óculos que bloquearam a visão dos membros inferiores. Os dados cinemáticos foram coletados por um sistema optoeletrônico de análise do movimento (OPTOTRAK Certus – 3D Motion Measurement System, NDI). Para análise estatística foram empregadas ANOVAs. Os resultados revelaram efeito principal de grupo e condição para o andar livre e efeito de condição para a fase de ultrapassagem. No andar livre, a hipometria influenciou o comportamento locomotor de idosos com DP comparados a idosos sadios. Ainda, na ausência de informação exproprioceptiva os participantes modificaram seu comportamento locomotor aumentando a cadência, o comprimento e a velocidade da passada e diminuíram a duração da passada e da porcentagem de duplo suporte... (Resumo completo, clicar acesso eletrônico abaixo)

Comparação do efeito da fadiga muscular no andar livre e adaptativo entre adultos jovens e idosos

A fadiga muscular é definida como uma falha no sistema neuromuscular na capacidade de gerar uma força requerida ou esperada. Quanto maior a idade do indivíduo, maior é a probabilidade de chegar à fadiga, aumentando o risco de quedas. Dessa forma, a fadiga pode influenciar no andar dos indivíduos, causando prejuízos no controle postural e podendo causar lesões músculo-esqueléticas A partir dos estudos realizados, percebe-se que a fadiga muscular pode prejudicar o desempenho do andar, sendo ele adaptativo ou não. O objetivo do estudo foi analisar e comparar a influência da fadiga muscular sobre os parâmetros cinemáticos do andar livre e adaptativo entre adultos jovens e idosos. Participaram do estudo 20 indivíduos, distribuídos em dois grupos etários: Adulto Jovem - 20 a 40 anos; e Idoso - a partir de 60 anos. Os participantes realizaram o andar livre e adaptativo percorrendo uma distância retilínea de 8 metros sobre um carpete de borracha com 1,4m de largura. Foram realizadas 6 tentativas para cada condição experimental. Para a coleta dos dados cinemáticos dos ciclos do andar definidos foi utilizado um sistema tridimensional (3D) optoeletrônico de análise do movimento (OPTOTRAK Certus – 3D Motion Measurement System, NDI), com precisão de 0,1 mm, posicionado no plano frontal, face anterior, ao movimento do participante, com frequência de 100 Hz. A indução a fadiga será através da tarefa de sentar e levantar. Para a comparação entre os dois grupos foram analisados as seguintes variáveis espaciais e temporais do andar livre e adaptativo: comprimento de cada passo, largura de cada passo, velocidade média do andar, distância horizontal pé-obstáculo antes da ultrapassagem, distância horizontal depois do obstáculo e distância vertical péobstáculo. Estas variáveis foram analisadas durante o ciclo do andar antes e após fadiga muscular.

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.

Solución de bajo coste de captura de movimiento basada en Kinect

[ES] En este trabajo se estudia e implementa una solución de bajo coste basada en Kinect para la captura de movimiento y su integración con Blender, de manera que se cuente con una solución eficiente para la realización de captura de movimiento en animación. Dicho desarrollo está apoyado con la elaboración de un tutorial sobre el procedimiento necesario para realizar MOCAP con Kinect y Blender, facilitando así su uso con fines formativos.

Path planning for image based visual servoing

This thesis deals with Visual Servoing and its strictly connected disciplines like projective geometry, image processing, robotics and non-linear control. More specifically the work addresses the problem to control a robotic manipulator through one of the largely used Visual Servoing techniques: the Image Based Visual Servoing (IBVS). In Image Based Visual Servoing the robot is driven by on-line performing a feedback control loop that is closed directly in the 2D space of the camera sensor. The work considers the case of a monocular system with the only camera mounted on the robot end effector (eye in hand configuration). Through IBVS the system can be positioned with respect to a 3D fixed target by minimizing the differences between its initial view and its goal view, corresponding respectively to the initial and the goal system configurations: the robot Cartesian Motion is thus generated only by means of visual informations. However, the execution of a positioning control task by IBVS is not straightforward because singularity problems may occur and local minima may be reached where the reached image is very close to the target one but the 3D positioning task is far from being fulfilled: this happens in particular for large camera displacements, when the the initial and the goal target views are noticeably different. To overcame singularity and local minima drawbacks, maintaining the good properties of IBVS robustness with respect to modeling and camera calibration errors, an opportune image path planning can be exploited. This work deals with the problem of generating opportune image plane trajectories for tracked points of the servoing control scheme (a trajectory is made of a path plus a time law). The generated image plane paths must be feasible i.e. they must be compliant with rigid body motion of the camera with respect to the object so as to avoid image jacobian singularities and local minima problems. In addition, the image planned trajectories must generate camera velocity screws which are smooth and within the allowed bounds of the robot. We will show that a scaled 3D motion planning algorithm can be devised in order to generate feasible image plane trajectories. Since the paths in the image are off-line generated it is also possible to tune the planning parameters so as to maintain the target inside the camera field of view even if, in some unfortunate cases, the feature target points would leave the camera images due to 3D robot motions. To test the validity of the proposed approach some both experiments and simulations results have been reported taking also into account the influence of noise in the path planning strategy. The experiments have been realized with a 6DOF anthropomorphic manipulator with a fire-wire camera installed on its end effector: the results demonstrate the good performances and the feasibility of the proposed approach.

Sviluppo e caratterizzazione di algoritmi di segmentazione per l'analisi del cammino in acqua con tecnica markerless

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.

Riabilitazione e valutazione di pazienti con deficit neurologici mediante l'utilizzo di realtà virtuale, feedback aumentati, sensori inerziali e tecnologie video a basso costo.

La neuroriabilitazione è un processo attraverso cui individui affetti da patologie neurologiche mirano al conseguimento di un recupero completo o alla realizzazione del loro potenziale ottimale benessere fisico, mentale e sociale. Elementi essenziali per una riabilitazione efficace sono: una valutazione clinica da parte di un team multidisciplinare, un programma riabilitativo mirato e la valutazione dei risultati conseguiti mediante misure scientifiche e clinicamente appropriate. Obiettivo principale di questa tesi è stato sviluppare metodi e strumenti quantitativi per il trattamento e la valutazione motoria di pazienti neurologici. I trattamenti riabilitativi convenzionali richiedono a pazienti neurologici l’esecuzione di esercizi ripetitivi, diminuendo la loro motivazione. La realtà virtuale e i feedback sono in grado di coinvolgerli nel trattamento, permettendo ripetibilità e standardizzazione dei protocolli. È stato sviluppato e valutato uno strumento basato su feedback aumentati per il controllo del tronco. Inoltre, la realtà virtuale permette l’individualizzare il trattamento in base alle esigenze del paziente. Un’applicazione virtuale per la riabilitazione del cammino è stata sviluppata e testata durante un training su pazienti di sclerosi multipla, valutandone fattibilità e accettazione e dimostrando l'efficacia del trattamento. La valutazione quantitativa delle capacità motorie dei pazienti viene effettuata utilizzando sistemi di motion capture. Essendo il loro uso nella pratica clinica limitato, una metodologia per valutare l’oscillazione delle braccia in soggetti parkinsoniani basata su sensori inerziali è stata proposta. Questi sono piccoli, accurati e flessibili ma accumulano errori durante lunghe misurazioni. È stato affrontato questo problema e i risultati suggeriscono che, se il sensore è sul piede e le accelerazioni sono integrate iniziando dalla fase di mid stance, l’errore e le sue conseguenze nella determinazione dei parametri spaziali sono contenuti. Infine, è stata presentata una validazione del Kinect per il tracking del cammino in ambiente virtuale. Risultati preliminari consentono di definire il campo di utilizzo del sensore in riabilitazione.

Studio di validità concorrente tra sistema indossabile basato su IMU e stereofotogrammetria usata come gold standard

L’analisi della postura e del movimento umano costituiscono un settore biomedico in forte espansione e di grande interesse dal punto di vista clinico. La valutazione delle caratteristiche della postura e del movimento, nonché delle loro variazioni rispetto ad una situazione di normalità, possono essere di enorme utilità in campo clinico per la diagnosi di particolari patologie, così come per la pianificazione ed il controllo di specifici trattamenti riabilitativi. In particolare è utile una valutazione quantitativa della postura e del movimento che può essere effettuata solo utilizzando metodologie e tecnologie ‘ad hoc’. Negli ultimi anni la diffusione di sensori MEMS e lo sviluppo di algoritmi di sensor fusion hanno portato questi dispositivi ad entrare nel mondo della Motion Capture. Queste piattaforme multi-sensore, comunemente chiamate IMU (Inertial Measurement Unit), possono rappresentare l’elemento base di una rete sensoriale per il monitoraggio del movimento umano.

Characterizing full-body reach duration across task and viewpoint modalities

The full-body control of virtual characters is a promising technique for application fields such as Virtual Prototyping. However it is important to assess to what extent the user full-body behavior is modified when immersed in a virtual environment. In the present study we have measured reach durations for two types of task (controlling a simple rigid shape vs. a virtual character) and two types of viewpoint (1st person vs. 3rd person). The paper first describes the architecture of the motion capture approach retained for the on-line full-body reach experiment. We then present reach measurement results performed in a non-virtual environment. They show that the target height parameter leads to reach duration variation of ∓25% around the average duration for the highest and lowest targets. This characteristic is highly accentuated in the virtual world as analyzed in the discussion section. In particular, the discrepancy observed for the first person viewpoint modality suggests to adopt a third person viewpoint when controling the posture of a virtual character in a virtual environment.

Learning Two-Person Interaction Models for Responsive Synthetic Humanoids

Imitation learning is a promising approach for generating life-like behaviors of virtual humans and humanoid robots. So far, however, imitation learning has been mostly restricted to single agent settings where observed motions are adapted to new environment conditions but not to the dynamic behavior of interaction partners. In this paper, we introduce a new imitation learning approach that is based on the simultaneous motion capture of two human interaction partners. From the observed interactions, low-dimensional motion models are extracted and a mapping between these motion models is learned. This interaction model allows the real-time generation of agent behaviors that are responsive to the body movements of an interaction partner. The interaction model can be applied both to the animation of virtual characters as well as to the behavior generation for humanoid robots.

Comfort of two shoulder actuation mechanisms for arm therapy exoskeletons: a comparative study in healthy subjects

Robotic exoskeletons can be used to study and treat patients with neurological impairments. They can guide and support the human limb over a large range of motion, which requires that the movement trajectory of the exoskeleton coincide with the one of the human arm. This is straightforward to achieve for rather simple joints like the elbow, but very challenging for complex joints like the human shoulder, which is comprised by several bones and can exhibit a movement with multiple rotational and translational degrees of freedom. Thus, several research groups have developed different shoulder actuation mechanism. However, there are no experimental studies that directly compare the comfort of two different shoulder actuation mechanisms. In this study, the comfort and the naturalness of the new shoulder actuation mechanism of the ARMin III exoskeleton are compared to a ball-and-socket-type shoulder actuation. The study was conducted in 20 healthy subjects using questionnaires and 3D-motion records to assess comfort and naturalness. The results indicate that the new shoulder actuation is slightly better than a ball-and-socket-type actuation. However, the differences are small, and under the tested conditions, the comfort and the naturalness of the two tested shoulder actuations do not differ a lot.

Using virtual reality to teach special populations how to cope in crisis: the case of a virtual earthquake

The unique characteristics of special populations such as pre-school children and Down syndrome kids in crisis and their distorted self-image were never studied before, because of the difficulty of crisis reproduction. This study proposes a VR setting that tries to model some special population's behaviour in the time of crises and offers them a training scenario. The sample population consisted of 30 pre-school children and 20 children with Down syndrome. The VR setting involved a high-speed PC, a VPL EyePhone 1, a MR toolkit, a vibrations plate, a motion capture system and other sensors. The system measured and modelled the typical behaviour of these special populations in a Virtual Earthquake scenario with sight and sound and calculated a VR anthropomorphic model that reproduced their behaviour and emotional state. Afterwards one group received an emotionally enhanced VR self-image as feedback for their training, one group received a plain VR self-image and another group received verbal instructions. The findings strongly suggest that the training was a lot more biased by the emotionally enhanced VR self-image than the other approaches. These findings could highlight the special role of the self-image to therapy and training and the interesting role of imagination to emotions, motives and learning. Further studies could be done with various scenarios in order to measure the best-biased behaviour and establish the most natural and affective VR model. This presentation is going to highlight the main findings and some theories behind them.