Development of Sliding Mode Controller Based on Internal Model Controller for Higher Precision Electro-Optical Tracking System

The electro-optical tracking system (ETS) on moving platforms is affected by the vibration of the moving carrier, the wind resistance torque in motion, the uncertainty of mechanisms and the nonlinear friction between frames and other disturbances, which may lead to the instability of the electro-optical tracking platform. Sliding mode control (SMC) has strong robustness to system disturbances and unknown dynamic external signals, which can enhance the disturbance suppression ability of ETSs. However, the strong robustness of SMC requires greater switching gain, which causes serious chattering. At the same time, the tracking accuracy of SMC has room for further improvement. Therefore, in order to solve the chattering problem of SMC and improve the tracking accuracy of SMC, an SMC controller based on internal model control (IMC) is proposed. Compared with traditional SMC, the proposed method can be used to suppress the strongest disturbance with the smallest switching gain, effectively solving the chattering problem of the SMC, while improving the tracking accuracy of the system. In addition, to reduce the adverse influence of sensor noise on the control effect, lifting wavelet threshold de-noising is introduced into the control structure to further improve the tracking accuracy of the system. The simulation and experimental results verify the superiority of the proposed control method.

A Novel, Automated, and Real-Time Method for the Analysis of Non-Human Primate Behavioral Patterns Using a Depth Image Sensor

By virtue of their upright locomotion, similar to that of humans, motion analysis of non-human primates has been widely used in order to better understand musculoskeletal biomechanics and neuroscience problems. Given the difficulty of conducting a marker-based infrared optical tracking system for the behavior analysis of primates, a 2-dimensional (D) video analysis has been applied. Distinct from a conventional marker-based optical tracking system, a depth image sensor system provides 3-D information on movement without any skin markers. The specific aim of this study was to develop a novel algorithm to analyze the behavioral patterns of non-human primates in a home cage using a depth image sensor. The behavioral patterns of nine monkeys in their home cage, including sitting, standing, and pacing, were captured using a depth image sensor. Thereafter, these were analyzed by observers’ manual assessment and the newly written automated program. We confirmed that the measurement results from the observers’ manual assessments and the automated program with depth image analysis were statistically identical.

Portable, open-source solutions for estimating wrist position during reaching in people with stroke

Arm movement kinematics may provide a more sensitive way to assess neurorehabilitation outcomes than existing metrics. However, measuring arm kinematics in people with stroke can be challenging for traditional optical tracking systems due to non-ideal environments, expense, and difficulty performing required calibration. Here, we present two open-source methods, one using inertial measurement units (IMUs) and another using virtual reality (Vive) sensors, for accurate measurements of wrist position with respect to the shoulder during reaching movements in people with stroke. We assessed the accuracy of each method during a 3D reaching task. We also demonstrated each method’s ability to track two metrics derived from kinematics-sweep area and smoothness-in people with chronic stroke. We computed correlation coefficients between the kinematics estimated by each method when appropriate. Compared to a traditional optical tracking system, both methods accurately tracked the wrist during reaching, with mean signed errors of 0.09 ± 1.81 cm and 0.48 ± 1.58 cm for the IMUs and Vive, respectively. Furthermore, both methods’ estimated kinematics were highly correlated with each other (p < 0.01). By using relatively inexpensive wearable sensors, these methods may be useful for developing kinematic metrics to evaluate stroke rehabilitation outcomes in both laboratory and clinical environments.

The Influence of Time Winning and Time Losing on Position-Specific Match Physical Demands in the Top One Spanish Soccer League

The aim of the present study was to analyze the influence of time winning and time losing on position-specific match physical demands with and without ball possession in the top Spanish professional soccer league. All matches played in the First Spanish soccer league over four consecutive seasons (from 2015/16 to 2018/19) were recorded using an optical tracking system (i.e., ChyronHego), and the data were analyzed via Mediacoach®. Total distance (TD), and TD > 21 km·h−1 covered with and without ball possession were analyzed using a Linear Mixed Model, taking into account the contextual variables time winning and losing. Results showed that TD and TD > 21 km·h−1 covered by central midfielders (0.01 and 0.005 m/min, respectively), wide midfielders (0.02 and 0.01 m/min, respectively), and forwards (0.03 and 0.02 m/min, respectively) significantly increased while winning (p < 0.05). By contrast, TD and TD > 21 km·h−1 covered by central defenders (0.01 and 0.008 m/min, respectively) and wide defenders (0.06 and 0.008 m/min, respectively) significantly increased while losing (p < 0.05). In addition, for each minute that teams were winning, total distance with ball possession (TDWP) decreased, while, for each minute that teams were losing, TDWP increased. Instead, TDWP > 21 km·h−1 obtained opposite results. Total distance without ball possession increased when teams were winning, and decreased when teams were losing. Therefore, the evolution of scoreline significantly influences tactical–technical and physical demands on soccer matches.

SpineDepth: A Multi-Modal Data Collection Approach for Automatic Labelling and Intraoperative Spinal Shape Reconstruction Based on RGB-D Data

Computer aided orthopedic surgery suffers from low clinical adoption, despite increased accuracy and patient safety. This can partly be attributed to cumbersome and often radiation intensive registration methods. Emerging RGB-D sensors combined with artificial intelligence data-driven methods have the potential to streamline these procedures. However, developing such methods requires vast amount of data. To this end, a multi-modal approach that enables acquisition of large clinical data, tailored to pedicle screw placement, using RGB-D sensors and a co-calibrated high-end optical tracking system was developed. The resulting dataset comprises RGB-D recordings of pedicle screw placement along with individually tracked ground truth poses and shapes of spine levels L1–L5 from ten cadaveric specimens. Besides a detailed description of our setup, quantitative and qualitative outcome measures are provided. We found a mean target registration error of 1.5 mm. The median deviation between measured and ground truth bone surface was 2.4 mm. In addition, a surgeon rated the overall alignment based on 10% random samples as 5.8 on a scale from 1 to 6. Generation of labeled RGB-D data for orthopedic interventions with satisfactory accuracy is feasible, and its publication shall promote future development of data-driven artificial intelligence methods for fast and reliable intraoperative registration.

Technical assessment of the NDI Polaris Vega optical tracking system

The Polaris product line from Northern Digital Inc. is well known for accurate optical tracking measurements in research and medical environments. The Spectra position sensor, to date often found in image guided radiotherapy suites, has however reached its end-of-life, being replaced by the new Vega model. The performance in static and dynamic measurements of this new device has been assessed in controlled laboratory conditions, against the strict requirements for system integration in radiation therapy. The system accuracy has improved with respect to the Spectra in both static (0.045 mm RMSE) and dynamic (0.09 mm IQR, < 20 cm/s) tracking and brings marginal improvement in the measurement latency (14.2 ± 1.8 ms). The system performance was further confirmed under clinical settings with the report of early results from periodic QA tests within specifications. Based on our tests, the Polaris Vega meets the quality standards of radiotherapy applications and can be safely used for monitoring respiratory breathing motion or verifying patient positioning.

In Vitro and In Vivo Assessment of a New Workflow for the Acquisition of Mandibular Kinematics Based on Portable Tracking System with Passive Optical Reflective Markers

Clinical use of portable optical tracking system in dentistry could improve the analysis of mandibular movements for diagnostic and therapeutic purposes. A new workflow for the acquisition of mandibular kinematics was developed. Reproducibility of measurements was tested in vitro and intra- and inter-rater repeatability were assessed in vivo in healthy volunteers. Prescribed repeated movements (n = 10) in three perpendicular directions of the tracking-device coordinate system were performed. Measurement error and coefficient of variation (CV) among repetitions were determined. Mandibular kinematics of maximum opening, left and right laterality, protrusion and retrusion of five healthy subjects were recorded in separate sessions by three different operators. Obtained records were blindly examined by three observers. Intraclass correlation coefficient (ICC) was calculated to estimate inter-rater and intra-rater reliability. Maximum in vitro measurement error was 0.54 mm and CV = 0.02. Overall, excellent intra-rater reliability (ICC > 0.90) for each variable, general excellent intra-rater reliability (ICC = 1.00) for all variables, and good reliability (ICC > 0.75) for inter-rater tests were obtained. A lower score was obtained for retrusion with “moderate reliability” (ICC = 0.557) in the inter-rater tests. Excellent repeatability and reliability in optical tracking of primary movements were observed using the tested portable tracking device and the developed workflow.