Real-time hand tracking for rehabilitation and character animation

Hand and finger tracking has a major importance in healthcare, for rehabilitation of hand function required due to a neurological disorder, and in virtual environment applications, like characters animation for on-line games or movies. Current solutions consist mostly of motion tracking gloves with embedded resistive bend sensors that most often suffer from signal drift, sensor saturation, sensor displacement and complex calibration procedures. More advanced solutions provide better tracking stability, but at the expense of a higher cost. The proposed solution aims to provide the required precision, stability and feasibility through the combination of eleven inertial measurements units (IMUs). Each unit captures the spatial orientation of the attached body. To fully capture the hand movement, each finger encompasses two units (at the proximal and distal phalanges), plus one unit at the back of the hand. The proposed glove was validated in two distinct steps: a) evaluation of the sensors’ accuracy and stability over time; b) evaluation of the bending trajectories during usual finger flexion tasks based on the intra-class correlation coefficient (ICC). Results revealed that the glove was sensitive mainly to magnetic field distortions and sensors tuning. The inclusion of a hard and soft iron correction algorithm and accelerometer and gyro drift and temperature compensation methods provided increased stability and precision. Finger trajectories evaluation yielded high ICC values with an overall reliability within application’s satisfying limits. The developed low cost system provides a straightforward calibration and usability, qualifying the device for hand and finger tracking in healthcare and animation industries.

Produção de massa seca e teores de nutrientes do feijoeiro comum submetido à deriva de glyphosate em duas classes de solo

O glyphosate é o principal herbicida em utilização no mundo, sendo recomendado para o controle de plantas daninhas em diversas culturas. Em pulverizações com ventos de 2 m s-1, a deriva de glyphosate pode atingir até 160 m além do local considerado alvo colocando em risco as culturas vizinhas. Assim, o objetivo deste trabalho foi avaliar a matéria seca e os teores de nutrientes do feijoeiro comum (Phaseolus vulgarisL.) cv. Pérola submetido à deriva de glyphosate. O experimento foi conduzido em casa de vegetação na Universidade Estadual do Norte Fluminense Darcy Ribeiro - UENF, Campos dos Goytacazes - RJ, utilizando o feijoeiro comum. Utilizou-se o delineamento em blocos casualizados em esquema fatorial 4 x 2 com quatro repetições, sendo o primeiro fator constituído pelas subdoses de 0; 14,4; 43,2 e 86,4g ha-1 de equivalente ácido (e.a.) de glyphosate na forma de sal de amônio aplicado aos 25 dias após a semeadura (estádio V4) e o segundo fator constituído por dois tipos de solos: Neossolo Quartzarênico Órtico típico e Argissolo Vermelho Amarelo distrófico Tb. A deriva de glyphosate reduziu a massa seca de ramos e da parte aérea aos 20 dias após a aplicação (DAA), os teores de nitrogênio (N), fósforo (P), potássio (K), magnésio (Mg) e enxofre (S) aos 10 DAA e de N, P, Ca e Mg aos 20 DAA do feijoeiro cv. Pérola.

Productivity of irrigated beans due to sources of stabilized nitrogen fertilizer and controlled release

ABSTRACT New nitrogen fertilizers are available in the market actually, however, does not have results on the efficiency of the Cerrado conditions. With that objective of this study was to evaluate the effect of urea including stabilized and controlled release urea on yield of irrigated common beans (Phaseolus vulgaris L) in no-tillage system. The experiment was conducted in the winter crop, at Embrapa Arroz e Feijão, in Santo Antônio de Goiás, State of Goiás, Brazil. The experimental design was randomized blocks, with five replicates. Treatments consisted of five N sources (urea, urea + NBPT, urea + polymer, ammonium sulphate, and ammonium nitrate) and a control (without N) being applied 20 kg ha-1 of N at sowing and 80 kg ha-1 onf N in topdressing. We evaluated the chlorophyll content in leaves of common beans, the leaf N content and dry mass weight (MSPA) in the flowering of common beans, the number of pods per plant, number of grains per pod, mass of 100 grains, grain yield and final stand of the common beans. The sources of nitrogen fertilizer did not influence, leaf N content, the mass of MSPA and the relative chlorophyll index of common beans. The use of polymerized urea and urea with urease inhibitor, did not produce increases in the number of grains per pod, number of pods per plant, mass of 100 grains and common beans yield compared to traditional sources of N, urea, ammonium sulfate and ammonium nitrate.

Voxel-based registration of simulated and real patient CBCT data for accurate dental implant pose estimation

The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant’s pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant’s pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant’s main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant’s pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67±34μm and 108μm, and angular misfits of 0.15±0.08º and 1.4º, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants’ pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.

Computer-aided recognition of dental implants in X-ray images

Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.

Assessment of Laparoscopic Skills Performance: 2D Versus 3D Vision and Classic Instrument Versus New Hand-Held Robotic Device for Laparoscopy

Introduction and Objectives. Laparoscopic surgery has undeniable advantages, such as reduced postoperative pain, smaller incisions, and faster recovery. However, to improve surgeons’ performance, ergonomic adaptations of the laparoscopic instruments and introduction of robotic technology are needed. The aim of this study was to ascertain the influence of a new hand-held robotic device for laparoscopy (HHRDL) and 3D vision on laparoscopic skills performance of 2 different groups, naïve and expert. Materials and Methods. Each participant performed 3 laparoscopic tasks—Peg transfer, Wire chaser, Knot—in 4 different ways. With random sequencing we assigned the execution order of the tasks based on the first type of visualization and laparoscopic instrument. Time to complete each laparoscopic task was recorded and analyzed with one-way analysis of variance. Results. Eleven experts and 15 naïve participants were included. Three-dimensional video helps the naïve group to get better performance in Peg transfer, Wire chaser 2 hands, and Knot; the new device improved the execution of all laparoscopic tasks (P < .05). For expert group, the 3D video system benefited them in Peg transfer and Wire chaser 1 hand, and the robotic device in Peg transfer, Wire chaser 1 hand, and Wire chaser 2 hands (P < .05). Conclusion. The HHRDL helps the execution of difficult laparoscopic tasks, such as Knot, in the naïve group. Three-dimensional vision makes the laparoscopic performance of the participants without laparoscopic experience easier, unlike those with experience in laparoscopic procedures.