A low-cost real time virtual system for postural stability assessment at home

Background and objective

The degeneration of the balance control system in the elderly and in many pathologies requires measuring the equilibrium conditions very often. In clinical practice, equilibrium control is commonly evaluated by using a force platform (stabilometric platform) in a clinical environment.In this paper, we demonstrate how a simple movement analysis system, based on a 3D video camera and a 3D real time model reconstruction of the human body, can be used to collect information usually recorded by a physical stabilometric platform.

Methods

The algorithm used to reconstruct the human body model as a set of spheres is described and discussed. Moreover, experimental measurements and comparisons with data collected by a physical stabilometric platform are also reported. The measurements were collected on a set of 6 healthy subjects to whom a change in equilibrium condition was stimulated by performing an equilibrium task.

Results

The experimental results showed that more than 95% of data collected by the proposed method were not significantly different from those collected by the classic platform, thus confirming the usefulness of the proposed system.

Conclusions

The proposed virtual balance assessment system can be implemented at low cost (about 500$) and, for this reason, can be considered a home use medical device. On the contrary, astabilometric platform has a cost of about 10,000$ and requires periodical calibration. The proposed system does not require periodical calibration, as is necessary for stabilometric force platforms, and it is easy to use. In future, the proposed system with little integration can be used, besides being an emulator of a stabilometric platform, also to recognize and track, in real time, head, legs, arms and trunk, that is to collect information actually obtained by sophisticated optoelectronic systems.     

Modeling and global trajectory tracking control for an over-actuated MAV

This paper deals with an original micro aerial vehicle (MAV) design, the Omnicopter MAV. It has two central coaxial rotors with fixed-pitch propellers and three perimeter mounted ducted fans with servo motors performing thrust vectoring. Compared with traditional rotary wing MAVs that have inherent underactuation, the Omnicopter possesses some advantages in mobility, for example, lateral translation with zero attitude and hover with nonzero attitude. The trajectory tracking control design, global stability analysis, and control allocation are demonstrated through numerical simulation. The advantage of zero attitude translation is illustrated through experimental results.     

Human tracking system based on adaptive multi-feature mean-shift for robot under the double-layer locating mechanism

Human tracking has been a challenging task for robot in the past decades. In this paper, to realize the human following in a cluttered environment, a human tracking system based on adaptive multi-feature mean-shift (AMF-MS) under the double-layer locating mechanism (DLLM) is proposed to solve the problem of distinguishing target, occlusion, and quick turning. The DLLM, considering the course location processing and fine location processing, is designed to estimate the person’s position using the fusion of heterogeneous data. As an ID tag attached on target can be detected by RF antennas, the course locating method can track the target easily and quickly. The Bayes rule is introduced to calculate the probability where the tag exists due to the instability of RF signals. In the fine locating step, the AMF-MS is proposed because it can reduce computational load and represent target by multi-feature histogram function. Meanwhile, we combine extended Kalman filter and AMF-MS to overcome MS’s inability of occlusion. To control the robot following the target person precisely, an intelligent gear shift strategy based on fuzzy control is implemented by analyzing the robot structure. Experiments demonstrate that the proposed approach is robust to handle complex tracking conditions, and show the system has an optimum performance.     

Online learning and fusion of orientation appearance models for robust rigid object tracking

We introduce a robust framework for learning and fusing of orientation appearance models based on both texture and depth information for rigid object tracking. Our framework fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depth cameras such as the Kinect. To combine these two completely different modalities, we propose to use features that do not depend on the data representation: angles. More specifically, our framework combines image gradient orientations as extracted from intensity images with the directions of surface normals computed from dense depth fields. We propose to capture the correlations between the obtained orientation appearance models using a fusion approach motivated by the original Active Appearance Models (AAMs). To incorporate these features in a learning framework, we use a robust kernel based on the Euler representation of angles which does not require off-line training, and can be efficiently implemented online. The robustness of learning from orientation appearance models is presented both theoretically and experimentally in this work. This kernel enables us to cope with gross measurement errors, missing data as well as other typical problems such as illumination changes and occlusions. By combining the proposed models with a particle filter, the proposed framework was used for performing 2D plus 3D rigid object tracking, achieving robust performance in very difficult tracking scenarios including extreme pose variations.     

Automatic annotation of tennis games: An integration of audio,vision, and learning

Fully automatic annotation of tennis game using broadcast video is a task with a great potential but with enormous challenges. In this paper we describe our approach to this task, which integrates computer vision, machine listening, and machine learning. At the low level processing, we improve upon our previously proposed state-of-the-art tennis ball tracking algorithm and employ audio signal processing techniques to detect key events and construct features for classifying the events. At high level analysis, we model event classification as a sequence labelling problem, and investigate four machine learning techniques using simulated event sequences. Finally, we evaluate our proposed approach on three real world tennis games, and discuss the interplay between audio, vision and learning. To the best of our knowledge, our system is the only one that can annotate tennis game at such a detailed level.     

种子法制备聚合物乳液技术的进展

从建筑乳液的生产现状、自生种子法与外加种子法的区别、种子乳液的特点及外加种子法生产的乳液特性等方面介绍了种子法制备乳液技术的进展。     

Effect of particle size on the surface oxidation and flotation behavior of galena particles in lime system

ABSTRACT

In this research, the effect of particle size on the surface oxidation and flotation behavior of galena in the lime system was studied. Coarse (?0.074 + 0.038 mm), intermediate (?0.038 + 0.025 mm) and fine (?0.025 mm) galena particles were used in the experiment. The dissolution tests, flotation tests, and sorption tests were accomplished. Through further analysis by XPS, the effect of particle size and lime was observed. The decrease of mineral particle sizes increased the adsorption ratio of collector and the dissolution of galena, while the hydrophilic product OH^?/Ca(OH)⁺ produced by dissolution occupied the dominant position, which led to the minerals hydrophilic.     

不同重力环境的空间机械臂自抗扰轨迹跟踪控制

针对空间机械臂在地面装调与空间应用时,由于重力环境变化导致机械臂模型发生变化的问题,提出了一种自抗扰控制算法,用于完成空间机械臂轨迹跟踪控制的任务.该算法通过将系统模型及未知外扰作为系统的总和扰动,并利用扩张状态观测器对该扰动进行观测且给予补偿,从而提高了系统抗扰的性能.当机械臂模型随重力环境变化而发生变化时,使用同一个自抗扰控制器对其末端轨迹进行控制,均能取得较好的控制效果.通过对系统的稳定性进行分析,证明了所设计控制器的有效性.将仿真结果与PD控制及自适应鲁棒控制做比较,结果表明该控制算法不仅能适应机械臂模型的变化而且还能有效抵抗系统的扰动,从而使系统具有较强的鲁棒性.     

基于改进离散粒子群禁忌算法的并行测试任务调度

针对并行测试任务调度问题特点,提出了一种解决并行测试任务调度的离散粒子群禁忌算法,设计了符合并行测试任务调度特点的粒子初始化编码方式、粒子位置转移公式以及禁忌搜索邻域。通过与禁忌搜索相结合,避免了离散粒子群算法早熟问题。通过实验以及算法对比,表明提出的算法是快速有效的,能够很好地解决并行测试任务调度问题,求得测试总时间最短的任务调度序列。     

Preparation,characterization, and adsorption properties for metal ions of a novel chelating resin containing sulfoxide and diethylene glycol

A novel chelating resin containing sulfoxide and diethylene glycol, poly{4‐vinylbenzyl‐[2‐2‐(hydroxyethyl)ethoxyl]sulfoxide} (PVESO) was synthesized using chloromethylated polystyrene (PS‐Cl) as material. Its structure was characterized by elemental analysis, infrared spectra, and scanning electron microscopy (SEM). The adsorption capacities of the resin for Hg²⁺, Ag⁺, Cu²⁺, Zn²⁺, and Pb²⁺ at various pH values were determined. The maximum adsorption capacities for Hg²⁺ and Ag⁺ were 1.56 and 0.75 mmol g^?1 respectively. The resin had high selectivity for Hg²⁺ and Ag⁺ over the pH range 1.0–7.0. The adsorption capacities for Hg²⁺ and Ag⁺ under competitive condition were also determined by batch experiment method. In addition, the adsorption kinetics of the resin towards Hg²⁺ at different temperatures was also investigated. The results showed that the adsorption rate was governed by film diffusion at 20°C and 25°C, by particle diffusion at 30°C and 35°C. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 6054–6059, 2006