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This study developed and validated a surgical instrument motion measurement system for skill evaluation during practical laparoscopic surgery training. Owing to the various advantages of laparoscopic surgery including minimal invasiveness, this technique has been widely used. However, expert surgeons have insufficient time for providing training to beginners due to the shortage of surgeons and limited working hours. Skill transfer efficiency has to be improved for which there is an urgent need to develop objective surgical skill evaluation methods. Therefore, a simple motion capture–based surgical instrument motion measurement system that could be easily installed in an operating room for skill assessment during practical surgical training was developed. The tip positions and orientations of the instruments were calculated based on the marker positions attached to the root of the instrument. Because the patterns of these markers are individual, this system can track multiple instruments simultaneously and detect exchanges. However due to the many obstacles in the operating room, the measurement data included noise and outliers. In this study, the effect of this decrease in measurement accuracy on feature calculation was determined. Accuracy verification experiments were conducted during wet-lab training to demonstrate the capability of this system to measure the motion of surgical instruments with practical accuracy. A surgical training experiment on a cadaver was conducted, and the motions of six surgical instruments were measured in 36 cases of laparoscopic radical nephrectomy. Outlier removal and smoothing methods were also developed and applied to remove the noise and outliers in the obtained data. The questionnaire survey conducted during the experiment confirmed that the measurement system did not interfere with the surgical operation. Thus, the proposed system was capable of making reliable measurements with minimal impact on surgery. The system will facilitate surgical education by enabling the evaluation of skill transfer of surgical skills. [ABSTRACT FROM AUTHOR]

The purpose of this study was to characterize the motion features of surgical devices associated with laparoscopic surgical competency and build an automatic skill-credential system in porcine cadaver organ simulation training. Participants performed tissue dissection around the aorta, dividing vascular pedicles after applying Hem-o-lok (tissue dissection task) and parenchymal closure of the kidney (suturing task). Movements of surgical devices were tracked by a motion capture (Mocap) system, and Mocap-metrics were compared according to the level of surgical experience (experts: ≥50 laparoscopic surgeries, intermediates: 10–49, novices: 0–9), using the Kruskal-Wallis test and principal component analysis (PCA). Three machine-learning algorithms: support vector machine (SVM), PCA-SVM, and gradient boosting decision tree (GBDT), were utilized for discrimination of the surgical experience level. The accuracy of each model was evaluated by nested and repeated k-fold cross-validation. A total of 32 experts, 18 intermediates, and 20 novices participated in the present study. PCA revealed that efficiency-related metrics (e.g., path length) significantly contributed to PC 1 in both tasks. Regarding PC 2, speed-related metrics (e.g., velocity, acceleration, jerk) of right-hand devices largely contributed to the tissue dissection task, while those of left-hand devices did in the suturing task. Regarding the three-group discrimination, in the tissue dissection task, the GBDT method was superior to the other methods (median accuracy: 68.6%). In the suturing task, SVM and PCA-SVM methods were superior to the GBDT method (57.4 and 58.4%, respectively). Regarding the two-group discrimination (experts vs. intermediates/novices), the GBDT method resulted in a median accuracy of 72.9% in the tissue dissection task, and, in the suturing task, the PCA-SVM method resulted in a median accuracy of 69.2%. Overall, the mocap-based credential system using machine-learning classifiers provides a correct judgment rate of around 70% (two-group discrimination). Together with motion analysis and wet-lab training, simulation training could be a practical method for objectively assessing the surgical competence of trainees.

In this paper, a multi-cell design method with built-in stiffeners is proposed to improve the crashworthiness of metal circular tubes. In the study, multi-cell circular tubes with three different stiffeners (Line, Waved, Polyline) were subjected to compression tests under quasi-static load. The finite element model of the metal circular tube was validated by ABAQUS/EXPLICIT, and the geometry of the stiffener was designed on this basis. The results showed that the energy absorption of the multi-cell tube was significantly better than that of the initial tube. Further, 'Waved' and 'Polyline' are more conducive to improving the crashworthiness of the multi-cell tube from the geometric design of the stiffeners. Through the analysis of load-displacement responses and crashworthiness indexs, it was found that the more the number of 'Waved' or 'Polyline' (from 2 to 8), the better the energy absorption of the multi-cell tubes and the smaller the load fluctuation. In addition the effect of the number of stiffeners on energy absorption was also revealed. [ABSTRACT FROM AUTHOR]

Due to distortion, limitations of vision, and occlusion, most of the existing vacant parking slot detection methods with a standalone around view monitor (AVM) are prone to miss some parking slots and incorrectly identify whether the parking slot is vacant. To overcome this problem, we propose a complete method for vacant parking slot detection and tracking during driving and parking. Considering the different conditions of driving and parking, two different deep convolutional neural networks (DCNNs) are used to detect parking slots, of which the vacant parking slot detection network (VPS-Net) is used to detect vacant parking slots during driving, and the directional marking point detection network (DMPR-PS) is used to detect the directional marking points of the target parking slot during parking. Furthermore, in the driving process, we design a new matching rule and tracking management rule based on the Kernelized Correlation Filter (KCF) to track the parking slots, and fuse classification results of multiple frames to determine the occupancy status. In the parking process, since the parking slot is easily blocked by the vehicle, we design another new tracker to track the directional marking points and infer the complete parking slot using tracking results and prior geometric information. To evaluate the proposed method, a labeled video sequence dataset is established. Experiments show that the proposed method has improved the accuracy and continuity of vacant parking slots detection and positioning whether in the driving process or parking process. [ABSTRACT FROM AUTHOR]

It is essential to obtain accurate location of vehicles for new applications of Intelligent Transportation Systems. To remedy the defects of present Global Positioning System and vehicle-to-infrastructure (V-I) positioning technology, a new positioning approach based on vision and V-I communication is proposed. This approach aims at lane-level positioning with lower cost than conventional ones. In this approach, the position of the vehicle is represented by its lateral position (the lane number) and longitudinal position (the distance from entrance of the road) in a course coordinate system along the road; the specific lane the vehicle is occupying (the lane number) can be judged using the information of lane lines detected by vision systems; then the distance to the vehicle is obtained by a Road Side Unit (RSU) during the V-I communication; and the longitudinal position is calculated. The error of the approach on typical operating conditions is analyzed, indicating that the new approach can achieve the accuracy of less than 0.31 m for straight road and 0.58 m for typical arc road with ultra-wideband communication and ranging technologies and rational arrangement of RSUs. The feasibility of this approach is presented. [ABSTRACT FROM AUTHOR]

Objective: Crash test dummies are full-scale anthropomorphic test devices (ATDs) that simulate the dimensions, weight proportions, and articulation of the human body and are used to measure human injury potential in vehicle crashes. The Hybrid III dummy family, which is widely used currently, takes selected percentiles of anthropometry dimensions of U.S. adults as design references. The objective of this study was to assess the difference in anthropometry between Chinese adults and the currently used dummy.Methods: Based on the Chinese National Physical Fitness Surveillance of the year 2000, 2005, 2010 and National Standard of China GB/T 10000-1988, a series of anthropometric parameters for Chinese adults were obtained, and data analysis was conducted between Chinese adults and ATDs that are currently used.Results: The comparison revealed distinct anthropometric difference between ATDs and Chinese adults. Based on the latest data, median Chinese females were about 2.6% lower in stature and about 8.03% lower in body weight than the ATD design targets. Similarly, median Chinese males were about 3.48% shorter and weighed 11.89% less than the ATD design targets.Conclusions: Although the anthropometric differences between Chinese adults and the Hybrid III ATD specifications were modest and growing smaller, it is advisable to take the differences in anthropometry between ATDs and Chinese adults into consideration when developing new vehicles in China to provide effective protection specifically for Chinese occupants. [ABSTRACT FROM AUTHOR]

A simulation model for Jordan rollover system (JRS) is developed and validated by comparing the simulation results with the injury results in a real world accident and the results of unconstrained real rollover simulation. It is shown that the model can reflect the injury trend and risk and the crash characteristics of real rollover accident. Then a simulation is conducted with different initial crash parameters to study the effects of crash parameters on rollover safety characteristics. The results indicate that in a rollover event the vehicle dynamic responses are highly related to drop height, rollover speed, roll angle and the speed of impact sled, but in which only drop height has apparent correlation with occupant injury responses. [ABSTRACT FROM AUTHOR]

A four-point child safety belt with looped waist-belt is presented, which is mounted in the middle of rear seats, suitable for children aged 3 to 10 years. The safety belt is comfortable and convenient to wear, and can also avoid child occupant submarining in collision. A simulation model is developed with MADYMO software and validated by sled test. The parameters of safety belt are optimized with uniform design of experiment, stepwise regression analysis and genetic algorithm, and the injuries of 3, 6 and 10-year-old child dummies with the child safety belts before and after optimization are compared. The results show that four-point child safety belt with looped waist-belt can provide effective protection to child passengers and its optimization leads to a 10. 8% reduction in child injury criterion of child dummies. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the current study was to investigate whether an isolated human body lower limb FE model could predict leg kinematics and biomechanical response of a full body Chinese pedestrian model in vehicle collisions., Methods: A human body lower limb FE model representing midsize Chinese adult male anthropometry was employed with different upper body weight attachments being evaluated by comparing the predictions to those of a full body pedestrian model in vehicle-to-pedestrian collisions considering different front-end shapes., Results: The results indicate that upper body mass has a significant influence on pedestrian lower limb injury risk, the effect varies from vehicle front-end shape and is more remarkable to the femur and knee ligaments than to the tibia. In particular, the upper body mass can generally increase femur and knee ligaments injury risk, but has no obvious effect on the injury risk of tibia. The results also show that a higher attached buttock mass is needed for isolated pedestrian lower limb model for impacts with vehicles of higher bonnet leading edge., Conclusions: The findings of this study may suggest that it is necessary to consider vehicle shape variation in assessment of vehicle pedestrian protection performance and leg-form impactors with adaptive upper body mass should be used for vehicles with different front-end shapes, and the use of regional leg-form impactor modeling the local anthropometry to evaluate the actual lower limb injury of pedestrians in different countries and regions.