Xsens (Netherlands)

Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (ρ = 0.992, rRMSE = 5.3%), anterior (ρ = 0.965, rRMSE = 9.4%) and sagittal (ρ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (ρ = 0.862, rRMSE = 13.1%), frontal (ρ = 0.710, rRMSE = 29.6%), and transverse GRF&M (ρ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory.

BackgroundAn important objective of rehabilitation care is to regain adequate balance function to safely ambulate in community. However, in rehabilitation practice, it remains unclear if a stroke survivor functionally recovers by restitution or by learning to compensate for the lack of restoration of body function. Aim of this study is to propose and evaluate methods for the objective evaluation of balance during functional walking in stroke survivors.MethodsStroke survivors performed twice a Timed “Up & Go” (TUG) test. Ground reaction forces and position changes of both feet were measured using instrumented shoes and used to estimate the position of the center of mass (CoM). Balance control and efficiency metrics were defined to evaluate functional walking under variable conditions. Metrics were corrected based on the instantaneous velocity direction of CoM. Intra- and inter-participant variations for different phases of the TUG test were examined. Metrics were related to the Berg balance scale (BBS).ResultsParticipants with higher BBS scores show a more efficient walking pattern. Their walking velocity and walking direction is less variable and they are more frequently unstable when walking in a straight line or when turning. Furthermore, the less affected participants are able to move their CoM more towards their affected side.DiscussionWe developed and demonstrated a method to assess walking balance of stroke survivors. System design and evaluation methods allow balance evaluation during functional walking in daily life. Some presented metrics show correlations with BBS scores. Clear inter- and intra-patient variations in metric values are present that cannot be explained by BBS scores, which supports the additional value of the presented system. Presented methods may be used for objective evaluation of restitution and compensation of walking balance and have a potential application in individual evidence-based therapy.

Autonomous Simultaneous Localization and Mapping (SLAM) is an important topic in many engineering fields. Since stop-and-go systems are typically slow and full-kinematic systems may lack accuracy and integrity, this paper presents a novel hybrid “continuous stop-and-go” mobile mapping system called Scannect. A 3D terrestrial LiDAR system is integrated with a MEMS IMU and two Microsoft Kinect sensors to map indoor urban environments. The Kinects’ depth maps were processed using a new point-to-plane ICP that minimizes the reprojection error of the infrared camera and projector pair in an implicit iterative extended Kalman filter (IEKF). A new formulation of the 5-point visual odometry method is tightly coupled in the implicit IEKF without increasing the dimensions of the state space. The Scannect can map and navigate in areas with textureless walls and provides an effective means for mapping large areas with lots of occlusions. Mapping long corridors (total travel distance of 120 m) took approximately 30 minutes and achieved a Mean Radial Spherical Error of 17 cm before smoothing or global optimization.

In this paper, Non-Line-of-Sight (NLoS) identification/mitigation is proposed, based on systematic statistical hypothesis testing. In the proposed method, the combined statistics of timing-based measurements and Received-Signal-Strength (RSS) are used, and the fact that all collected measurements are related to the same unknown position is exploited. Four implementations are proposed, ranging from the rigorous optimal approach to a much simplified and approximate approach, offering a trade-off between performance and complexity. Validation results, using actual Ultra-Wideband radio signals, show that the correct detection rate can go up to 99% and the corresponding positioning accuracy with NLoS mitigation is substantially improved: the Root Mean Squared Error (RMSE) of the estimated position is reduced by up to a factor of seven. The use of the simplest approach comes with only a minor decrease in performance, compared to the full optimal implementation. Copyright © 2013 Institute of Navigation

This paper is concerned with the problem of estimating the relative translation and orientation of an inertial measurement unit and a camera, which are rigidly connected. The key is to realize that this problem is in fact an instance of a standard problem within the area of system identification, referred to as a gray-box problem. We propose a new algorithm for estimating the relative translation and orientation, which does not require any additional hardware, except a piece of paper with a checkerboard pattern on it. The method is based on a physical model which can also be used in solving, for example, sensor fusion problems. The experimental results show that the method works well in practice, both for perspective and spherical cameras.

One approach to improving the gait of patients with foot drop is the use of functional electrical stimulation (FES) as a neural prosthesis. However, there remain limitations with the current clinically used technology and the paper describes some recent developments addressing some of these problems. The paper describes initial work on an alternative surface-based solution and recent developments of an implantable two channel stimulator.