Abstract
Recent advances in visual motion detection and interpretation have made possible the rising of new robotic systems for autonomous and active surveillance. In this line of research, the current work discusses motion perception by proposing a novel technique that analyzes dense flow fields and distinguishes several regions with distinct motion models. The method is called Wise Optical Flow Clustering (WOFC) and extracts the moving objects by performing two consecutive operations: evaluating and resetting. Motion properties of the flow field are retrieved and described in the evaluation phase, which provides high level information about the spatial segmentation of the flow field. During the resetting operation, these properties are combined and used to feed a guided segmentation approach. The WOFC requires information about the number of motion models and, therefore, this paper introduces a model selection method based on a Bayesian approach that balances the model's fitness and complexity. It combines the correlation of a histogram-based analysis with the decay ratio of the normalized entropy criterion. This approach interprets the flow field and gives an estimative about the number of moving objects. The experiments conducted in a realistic environment have proved that the WOFC presents several advantages that meet the requirements of common robotic and surveillance applications: is computationally efficient and provides a pixel-wise segmentation, comparatively to other state-of-the-art methods.

Abstract
In this paper, we adopt a novel numerical algorithm, referred to as dual augmented Lagrangian method (DALM), for efficient test cost reduction based on spatial variation modeling. The key idea of DALM is to derive the dual formulation of the L1-regularized least-squares problem posed by Virtual Probe (VP), which can be efficiently solved with substantially lower computational cost than its primal formulation. In addition, a number of unique properties associated with discrete cosine transform (DCT) are exploited to further reduce the computational cost of DALM. Our experimental results of an industrial RF transceiver demonstrate that the proposed DALM solver achieves up to 38× runtime speed-up over the conventional interior-point solver without sacrificing any performance on escape rate and yield loss for test applications. © 2015 EDAA.

Abstract
Falls of patients are an important issue in hospitals nowadays; it causes severe injuries, increases hospitalization time and treatment costs. The detection of a fall, in time, provides faster rescue to the patient, preventing more serious injuries, as well as saving nursing time. The MovinSense (R) is an electronic device designed for monitoring patients to prevent pressure sores, and the main goal of this work was to develop a new tool for this device, with the purpose of detecting if the patient has fallen from the hospital bed, without changing any of the device's original features. Experiments for gathering data samples of inertial signals of falling from the bed were obtained using the device. For fall detection a sensitivity of 72% and specificity of 100% were reached. Another algorithm was developed to detect if the patient got out of his/her bed.

Abstract
The purpose of this study was to analyze the change in antagonist co-activation ratio of upper-limb muscle pairs, during the reaching movement, of both ipsilesional and contralesional limbs of post-stroke subjects. Nine healthy and nine post-stroke subjects were instructed to reach and grasp a target, placed in the sagittal and scapular planes of movement. Surface EMG was recorded from postural control and movement related muscles. Reaching movement was divided in two sub-phases, according to proximal postural control versus movement control demands, during which antagonist co-activation ratios were calculated for the muscle pairs LD/PM, PD/AD, TRIlat/BB and TRIlat/BR. Post-stroke's ipsilesional limb presented lower co-activation in muscles with an important role in postural control (LD/PM), comparing to the healthy subjects during the first sub-phase, when the movement was performed in the sagittal plane (p < 0.05). Conversely, the post-stroke's contralesional limb showed in general an increased co-activation ratio in muscles related to movement control, comparing to the healthy subjects. Our findings demonstrate that, in post-stroke subjects, the reaching movement performed with the ipsilesional upper limb seems to show co-activation impairments in muscle pairs associated to postural control, whereas the contralesional upper limb seems to have signs of impairment of muscle pairs related to movement.

Abstract
Sparse coding techniques have seen an increasing range of applications in recent years, especially in the area of image processing. In particular, sparse coding using l1-regularization has been efficiently solved with the Augmented Lagrangian (AL) applied to its dual formulation (DALM). This paper proposes the decomposition of the dictionary matrix in its Singular Value/Vector form in order to simplify and speed-up the implementation of the DALM algorithm. Furthermore, we propose an update rule for the penalty parameter used in AL methods that improves the convergence rate. The SVD of the dictionary matrix is done as a pre-processing step prior to the sparse coding, and thus the method is better suited for applications where the same dictionary is reused for several sparse recovery steps, such as block image processing. © 2014 IEEE.

Abstract
This study presents innovative analysis at the time, frequency and phase domain of the pelvis angular oscillation at transverse (T), sagittal (S) and coronal (C) planes, assessing its coordination during stiff knee gait (SKG) and slow running (SR) comparing it to normal gait (NG). Case study is considered of an adult male 70 kg mass and 1.86 m height. Computer vision is used with 8 Qualysis 100 Hz cameras tracking position of right and left anterior and posterior superior iliac spine (RAsis, LAsis, RPsis, LPsis) including one complete stride during NG, SKG and SR. 3D position coordinates are obtained from 2D image coordinate of multiple camera image using direct linear transformation (DLT). Inverse kinematics is performed using cartesian position data of RAsis, LAsis, RPsis, LPsis and scaled model to subject dimension. The angles, angular velocities and angular accelerations coordination of the pelvis oscillation at T, S, C planes were assessed using linear and cross correlation analysis (LCA, CCA), fast Fourier transform (FFT) and phase space analysis (PSA). Results point for important complementary analysis on entire series of time, frequency and phase analysis of human movement such as the pelvis coordination assessment on different gait modes.