Abstract
One of the most common knee joint disorders is known as osteoarthritis which results from the progressive degeneration of cartilage and subchondral bone over time, affecting essentially elderly adults. Current evaluation techniques are either complex, expensive, invasive or simply fails into detection of small and progressive changes that occur within the knee. Vibroarthrography appeared as a new solution where the mechanical vibratory signals arising from the knee are recorded recurring only to an accelerometer and posteriorly analyzed enabling the differentiation between a healthy and an arthritic joint. In this study, a vibration-based classification system was created using a dataset with 92 healthy and 120 arthritic segments of knee joint signals collected from 19 healthy and 20 arthritic volunteers, evaluated with k-nearest neighbors and support vector machine classifiers. The best classification was obtained using the k-nearest neighbors classifier with only 6 time-frequency features with an overall accuracy of 89.8% and with a precision, recall and f-measure of 88.3%, 92.4% and 90.1%, respectively. Preliminary results showed that vibroarthrography can be a promising, non-invasive and low cost tool that could be used for screening purposes. Despite this encouraging results, several upgrades in the data collection process and analysis can be further implemented.

Abstract
This study presents and applies a quantitative metric, based on entire time series of measured surface electromyography (sEMG) from selected lower limb muscles to validate multibody dynamics (MBD) estimated action of the same subject muscles during modified gait, stiff knee gait (SKG) and slow running (SR) in relation to normal gait (NG). MBD is being increasingly applied for estimation of internal actions according to difficulty of its direct measurements under natural conditions of movement and the importance of this estimation for prevention, diagnosis and treatment planning of specific subject skeletal and neuromuscular diseases. Inverse kinematics and inverse dynamics from position and force data have been used to estimate internal joint force moments, with muscle grouping and optimization techniques applied along with musculoskeletal model for estimation of muscle action. Nevertheless kinematic and kinetic input data of human movement must be accurate and employed model for simulation must be personalized to subject, task and moment of application. Also the results provided by the simulation with the musculoskeletal model must be compared with measured results for validation. Comparative analysis of kinematic and kinetic input data of human lower limbs is performed during modified gait modes and a personalized musculoskeletal model employed for MBD estimation of muscle actions and compare estimated muscle actions with measured sEMG of selected muscles on different gait modes, SKG and SR in relation to those registered at NG. The results from quantitative metrics followed qualitative agreement from visual inspection with better agreement between processed sEMG and MBD muscle estimated activity on phase metric than at magnitude, and combined metric presenting overall better agreement at NG and SKG than at SR, pointing to higher ability of the model to predict muscle force patterns in agreement with measured sEMG activity at NG and SKG than at SR and the need to improve model predictions for SR. Applied technique presents as a reproducible quantitative metric based on entire time series, both magnitude and phase, overcoming qualitative and subjective comparing by the observer, reducing time consuming and allowing increase at the number of automatic validation of MBD muscle action estimation.

Abstract
Mars and the Moon are envisaged as major destinations of future space exploration missions in the upcoming decades. Imaging LIDARs are seen as a key enabling technology in the support of autonomous guidance, navigation and control operations, as they can provide very accurate, wide range, high-resolution distance measurements as required for the exploration missions. Imaging LIDARs can be used at critical stages of these exploration missions, such as descent and selection of safe landing sites, rendezvous and docking manoeuvres, or robotic surface navigation and exploration. Despite these devices have been commercially available and used for long in diverse metrology and ranging applications, their size, mass and power consumption are still far from being suitable and attractive for space exploratory missions. Here, we describe a compact Single-Pixel Imaging LIDAR System that is based on a compressive sensing technique. The application of the compressive codes to a DMD array enables compression of the spatial information, while the collection of timing histograms correlated to the pulsed laser source ensures image reconstruction at the ranged distances. Single-pixel cameras have been compared with raster scanning and array based counterparts in terms of noise performance, and proved to be superior. Since a single photodetector is used, a better SNR and higher reliability is expected in contrast with systems using large format photodetector arrays. Furthermore, the event of failure of one or more micromirror elements in the DMD does not prevent full reconstruction of the images. This brings additional robustness to the proposed 3D imaging LIDAR. The prototype that was implemented has three modes of operation. Range Finder: Outputs the average distance between the system and the area of the target under illumination; Attitude Meter: Provides the slope of the target surface based on distance measurements in three areas of the target; 3D Imager: Produces 3D ranged images of the target surface. The implemented prototype demonstrated a frame rate of 30 mHz for 16x16 pixels images, a transversal (xy) resolution of 2 cm at 10 m for images with 64x64 pixels and the range (z) resolution proved to be better than 1 cm. The experimental results obtained for the "3D imaging" mode of operation demonstrated that it was possible to reconstruct spherical smooth surfaces. The proposed solution demonstrates a great potential for: Miniaturization; increase spatial resolution without using large format detector arrays; eliminate the need for scanning mechanisms; implementing simple and robust configurations. © 2014 SPIE.

Abstract
This study presents and applies generalized angular phase space analysis to lower limb joint angles of specific subject during normal and modified gait for discrimination of gait and joint angular movements. Case study of an adult healthy male in-vivo and noninvasive kinematic assessment of skin surface adhesive markers at lower limb was performed at human movement lab during normal gait, stiff knee gait and slow running. Musculoskeletal modeling was performed using AnyGait v.0.92 morphing Twente Lower Extremity Model (TLEM) to match the size and joint morphology of the stick-figure model. Inverse kinematics was performed obtaining hip, knee and ankle joint flexion-extension angular displacements, velocities and accelerations. Generalized phase space analysis was applied to lower limb joint angular displacements, velocities and accelerations. Directional statistics was applied to generalized phase planes with mean direction, resultant length and circular standard deviation assessment. Rayleigh test was employed for directional concentration and coordination assessment, and Watson's U2 goodness of fit test applied to the von Mises distribution. Results point for the importance of subject specific study, generalized joint angular phase space analysis, comparing results with other normalization methods and validation of applied methods with qualitative clinical analysis. © 2018 IEEE.

Abstract
This study presents and applies combined phase and magnitude metrics for validation of multibody dynamics (MBD) estimated muscle actions with simultaneous registered sEMG of lower limb muscles. Subject-specific tests were performed for acquisition of ground reaction forces and kinematic data from joint reflective markers during NG, SKG and SR. Inverse kinematics and dynamics was performed using AnyBody musculoskeletal personalized modeling and simulation. MBD estimated muscle activity (MA) of soleus medialis (SM) and tibialis anterior (TA) were compared on phase, magnitude and combined metric with simultaneous acquisition of sEMG for the same muscles. Results from quantitative metrics presented better agreement between MDB MA and sEMG on phase (P) than on magnitude (M) with combined (C) metric following the same pattern as the magnitude. Soleus medialis presented for specific subject lower P and M error on NG and SKG than at SR with similar P errors for tibialis anterior and higher error on M for TA at NG and SKG than SR. Separately and combined quantitative metrics of phase and magnitude presents as a suitable tool for comparing measured sEMG and MBD estimated muscle activities, contributing to overcome qualitative and subjective comparisons, need for intensive observer supervision, low reproducibility and time consuming.

Abstract
This study presents and applies 3D spherical angular analysis in relation with 2D polar coordinates to assess anatomic pelvic movement on modified gait, namely stiff knee (SKG) gait and slow running (SR) comparing with normal gait (NG). Subject specific analysis was performed of an adult healthy male based on inverse kinematics from in vivo and noninvasive capture at human movement lab of reflective markers position from pelvis anatomical selected points with Qualisys camera system during a complete stride of NG, SKG and SR. Radial distance (R), pitch (psi) and azimuth (lambda) angular phases were computed from pelvic angle-angle diagrams (theta(T), theta(C), theta(S)) at transverse (T), coronal (C) and sagittal (S) planes, and angular phase (phi) and planar radial distance (r) polar coordinates computed from pelvic angle-angle diagrams projections at cartesian planes (theta(T), theta(C)), (theta(T), theta(S)), (theta(C), theta(S)). Average radial distances and phase standard deviation were assessed on spherical and polar coordinates.