Effects of driver's braking behavior by the real-time pedestrian scale warning system.

A driver warning system can improve pedestrian safety by providing drivers with alerts about potential hazards. Most driver warning systems have primarily focused on detecting the presence of pedestrians, without considering other factors, such as the pedestrian's gender and speed, and whether pedestrians are carrying luggage, that can affect driver braking behavior. Therefore, this study aims to investigate how driver braking behavior changes based on the information about the number of pedestrians in a crowd and examine if a developed warning system based on this information can induce safe braking behavior. For this purpose, an experiment scenario was conducted using a virtual reality-based driving simulator and an eye tracker. The collected driver data were analyzed using mixed ANOVA to derive meaningful conclusions. The research findings indicate that providing information about the number of pedestrians in a crowd has a positive impact on driver braking behavior, including deceleration, yielding intention, and attention. Particularly, It was found that in scenarios with a larger number of pedestrians, the Time to Collision (TTC) and distance to the crosswalk were increased by 12%, and the pupil diameter was increased by 9%. This research also verified the applicability of the proposed warning system in complex road environments, especially under conditions with poor visibility such as nighttime. The system was able to induce safe braking behavior even at night and exhibited consistent performance regardless of gender. In conclusion, considering various factors that influence driver behavior, this research provides a comprehensive understanding of the potential and effectiveness of a driver warning system based on information about the number of pedestrians in a crowd in complex road environments.

Metal 3D-Printed Bioinspired Lattice Elevator Braking Pads for Enhanced Dynamic Friction Performance.

The elevator industry is constantly expanding creating an increased demand for the integration of high technological tools to increase elevator efficiency and safety. Towards this direction, Additive Manufacturing (AM), and especially metal AM, is one of the technologies that could offer numerous competitive advantages in the production of industrial parts, such as integration of complex geometry, high manufacturability of high-strength metal alloys, etc. In this context, the present study has 3D designed, 3D printing manufactured, and evaluated novel bioinspired structures for elevator safety gear friction pads with the aim of enhancing their dynamic friction performance and eliminating the undesired behavior properties observed in conventional pads. Four different friction pads with embedded bioinspired surface lattice structures were formed on the template of the friction surface of the conventional pads and 3D printed by the Selective Laser Melting (SLM) process utilizing tool steel H13 powder as feedstock material. Each safety gear friction pad underwent tribological tests to evaluate its dynamic coefficient of friction (CoF). The results indicated that pads with a high contact surface area, such as those with car-tire-like and extended honeycomb structures, exhibit high CoF of 0.549 and 0.459, respectively. Based on the acquired CoFs, Finite Element Models (FEM) were developed to access the performance of braking pads under realistic operation conditions, highlighting the lower stress concentration for the aforementioned designs. The 3D-printed safety gear friction pads were assembled in an existing emergency progressive safety gear system of KLEEMANN Group, providing sufficient functionality.

Expiratory braking defines the breathing patterns of asphyxiated neonates during therapeutic hypothermia.

Introduction: Although neonatal breathing patterns vary after perinatal asphyxia, whether they change during therapeutic hypothermia (TH) remains unclear. We characterized breathing patterns in infants during TH for hypoxic-ischemic encephalopathy (HIE) and normothermia after rewarming. Methods: In seventeen spontaneously breathing infants receiving TH for HIE and in three who did not receive TH, we analyzed respiratory flow and esophageal pressure tracings for respiratory timing variables, pulmonary mechanics and respiratory effort. Breaths were classified as braked (inspiratory:expiratory ratio ≥1.5) and unbraked (<1.5). Results: According to the expiratory flow shape braked breaths were chategorized into early peak expiratory flow, late peak expiratory flow, slow flow, and post-inspiratory hold flow (PiHF). The most braked breaths had lower rates, larger tidal volume but lower minute ventilation, inspiratory airway resistance and respiratory effort, except for the PiHF, which had higher resistance and respiratory effort. The braked pattern predominated during TH, but not during normothermia or in the uncooled infants. Conclusions: We speculate that during TH for HIE low respiratory rates favor neonatal braked breathing to preserve lung volume. Given the generally low respiratory effort, it seems reasonable to leave spontaneous breathing unassisted. However, if the PiHF pattern predominates, ventilatory support may be required.

Diabetes mellitus and hard braking events in older adult drivers.

BACKGROUND: Diabetes mellitus (DM) can impair driving safety due to hypoglycemia, hyperglycemia, diabetic peripheral neuropathy, and diabetic eye diseases. However, few studies have examined the association between DM and driving safety in older adults based on naturalistic driving data. METHODS: Data for this study came from a multisite naturalistic driving study of drivers aged 65-79 years at baseline. Driving data for the study participants were recorded by in-vehicle recording devices for up to 44 months. We used multivariable negative binomial modeling to estimate adjusted incidence rate ratios (aIRRs) and 95% confidence intervals (CIs) of hard braking events (HBEs, defined as maneuvers with deceleration rates ≥ 0.4 g) associated with DM. RESULTS: Of the 2856 study participants eligible for this analysis, 482 (16.9%) reported having DM at baseline, including 354 (12.4%) insulin non-users and 128 (4.5%) insulin users. The incidence rates of HBEs per 1000 miles were 1.13 for drivers without DM, 1.15 for drivers with DM not using insulin, and 1.77 for drivers with DM using insulin. Compared to drivers without DM, the risk of HBEs was 48% higher for drivers with DM using insulin (aIRR 1.48; 95% CI: 1.43, 1.53). CONCLUSION: Older adult drivers with DM using insulin appear to be at increased proneness to vehicular crashes. Driving safety should be taken into consideration in DM care and management.

SDC-Net++: End-to-End Crash Detection and Action Control for Self-Driving Car Deep-IoT-Based System.

Few prior works study self-driving cars by deep learning with IoT collaboration. SDC-Net, which is an end-to-end multitask self-driving car camera cocoon IoT-based system, is one of the research areas that tackles this direction. However, by design, SDC-Net is not able to identify the accident locations; it only classifies whether a scene is a crash scene or not. In this work, we introduce an enhanced design for the SDC-Net system by (1) replacing the classification network with a detection one, (2) adapting our benchmark dataset labels built on the CARLA simulator to include the vehicles' bounding boxes while keeping the same training, validation, and testing samples, and (3) modifying the shared information via IoT to include the accident location. We keep the same path planning and automatic emergency braking network, the digital automation platform, and the input representations to formulate the comparative study. The SDC-Net++ system is proposed to (1) output the relevant control actions, especially in case of accidents: accelerate, decelerate, maneuver, and brake, and (2) share the most critical information to the connected vehicles via IoT, especially the accident locations. A comparative study is also conducted between SDC-Net and SDC-Net++ with the same input representations: front camera only, panorama and bird's eye views, and with single-task networks, crash avoidance only, and multitask networks. The multitask network with a BEV input representation outperforms the nearest representation in precision, recall, f1-score, and accuracy by more than 15.134%, 12.046%, 13.593%, and 5%, respectively. The SDC-Net++ multitask network with BEV outperforms SDC-Net multitask with BEV in precision, recall, f1-score, accuracy, and average MSE by more than 2.201%, 2.8%, 2.505%, 2%, and 18.677%, respectively.

Effect of eco-driving on commercial motor vehicle driver collision risk.

INTRODUCTION: This study investigates the effect among commercial motor vehicle (CMV) drivers of the adoption of fuel-efficient driving techniques (commonly known as eco-driving) on the odds of being involved in safety-related events. METHOD: For 2,637 long-haul class 8 drivers employed by four carriers in Canada, information on driving style, total distance driven, and safety-related events like collisions, hard-braking, hard-turning, and stability control events were collected for each trip. Three carriers provided driving style-related data from the ISAAC instrument, which provides a score on a 0 to 100 scale that measures the degree to which a driver is using an appropriate amount of engine power according to driving conditions. The fourth carrier provided data on driving style characteristics, including fuel consumption, use of cruise control, and use of top gear. Depending on the carrier, information on speeding, driver age, and years of experience driving a commercial vehicle was also collected. Logit statistical models were developed to estimate the change in odds of a driver experiencing a safety-related event dependent on the measures of driving style. RESULTS: A one-unit increase in the ISAAC score was associated with a 7%, 8%, 8%, and 4% reduction in the odds of having a hard-braking event, hard left-turn event, hard right-turn event, and collision, respectively. For the carrier not employing the ISAAC system, an increase of 10% in the time spent driving in top gear with steady speed near 100 km per hour (km/h) was associated with a substantial 34% decrease in stability control events. In addition, a year increase in the driver's age, as well as a 1% increase in the amount of time spent driving using cruise control, reduced the number of hard-braking events by 9% and 3%, respectively. Conclusion/Practical Applications: The adoption of fuel-efficient driving techniques enhances the safety of CMV drivers.

RBS and ABS Coordinated Control Strategy Based on Explicit Model Predictive Control.

During the braking process of electric vehicles, both the regenerative braking system (RBS) and anti-lock braking system (ABS) modulate the hydraulic braking force, leading to control conflict that impacts the effectiveness and real-time capability of coordinated control. Aiming to enhance the coordinated control effectiveness of RBS and ABS within the electro-hydraulic composite braking system, this paper proposes a coordinated control strategy based on explicit model predictive control (eMPC-CCS). Initially, a comprehensive braking control framework is established, combining offline adaptive control law generation, online optimized control law application, and state compensation to effectively coordinate braking force through the electro-hydraulic system. During offline processing, eMPC generates a real-time-oriented state feedback control law based on real-world micro trip segments, improving the adaptiveness of the braking strategy across different driving conditions. In the online implementation, the developed three-dimensional eMPC control laws, corresponding to current driving conditions, are invoked, thereby enhancing the potential for real-time braking strategy implementation. Moreover, the state error compensator is integrated into eMPC-CCS, yielding a state gain matrix that optimizes the vehicle braking status and ensures robustness across diverse braking conditions. Lastly, simulation evaluation and hardware-in-the-loop (HIL) testing manifest that the proposed eMPC-CCS effectively coordinates the regenerative and hydraulic braking systems, outperforming other CCSs in terms of braking energy recovery and real-time capability.

Greater prosociality toward other human drivers than autonomous vehicles: Human drivers' discriminatory behavior in mixed traffic.

The development of autonomous vehicles (AVs) has rapidly evolved in recent years, aiming to gradually replace humans in driving tasks. However, road traffic is a complex environment involving numerous social interactions. As new road users, AVs may encounter different interactive situations from those of human drivers. This study therefore investigates whether human drivers show distinct degrees of prosociality toward AVs or other human drivers and whether AV behavioral patterns exert a relevant influence. Sixty-two drivers participated in the driving simulation experiment and interacted with other human drivers and different kinds of AVs (conservative, human-like, aggressive). The results show that human drivers are more willing to yield to other human drivers than to all kinds of AVs. Their braking reaction time is longer when yielding to AVs and their distance to AVs is shorter when choosing not to yield. AVs of different behavioral patterns do not significantly differ in yielding rate, but the braking reaction time of human-like AVs is longer than conservative AVs and shorter than aggressive AVs. These findings suggest that human drivers show more prosocial behaviors toward other human drivers than toward AVs. And human drivers' yielding behavior changes as the behavioral patterns of AVs changes. Accordingly, this study improves the understanding of how human drivers interact with nonliving road users such as AVs and how the former accept AVs with different driving styles on the road.

Variable Universe Fuzzy-Proportional-Integral-Differential-Based Braking Force Control of Electro-Mechanical Brakes for Mine Underground Electric Trackless Rubber-Tired Vehicles.

Currently, the main solution for braking systems for underground electric trackless rubber-tired vehicles (UETRVs) is traditional hydraulic braking systems, which have the disadvantages of hydraulic pressure crawling, the risk of oil leakage and a high maintenance cost. An electro-mechanical-braking (EMB) system, as a type of novel brake-by-wire (BBW) system, can eliminate the above shortcomings and play a significant role in enhancing the intelligence level of the braking system in order to meet the motion control requirements of unmanned UETRVs. Among these requirements, the accurate control of clamping force is a key technology in controlling performance and the practical implementation of EMB systems. In order to achieve an adaptive clamping force control performance of an EMB system, an optimized fuzzy proportional-integral-differential (PID) controller is proposed, where the improved fuzzy algorithm is utilized to adaptively adjust the gain parameters of classic PID. In order to compensate for the deficiency of single-close-loop control and adjusting the brake gap automatically, a cascaded three-closed-loop control architecture with force/position switch technology is established, where a contact point detection method utilizing motor rotor angle displacement is proposed via experiments. The results of the simulation and experiments indicate that the clamping force response of the proposed multi-close-loop Variable Universe Fuzzy-PID (VUF-PID) controller is faster than the multi-closed-loop Fuzzy-PID and cascaded three-close-loop PID controllers. In addition, the chattering of braking force can be suppressed by 17%. This EMB system may rapidly and automatically finish the operation of the overall braking process, including gap elimination, clamping force tracking and gap recovery, which can obviously enhance the precision of the longitudinal motion control of UETRVs. It can thus serve as a BBW actuator of mine autonomous driving electric vehicles, especially in the stage of braking control.

Research on regenerative braking control of electric vehicles based on game theory optimization.

The energy-efficient, clean, and quiet attributes of electric vehicles offer solutions to conventional challenges related to resource scarcity and environmental pollution. Consequently, thorough research into harmonizing energy recuperation during braking, enhancing vehicle stability, and ensuring occupant comfort in electric vehicles is imperative for their effective advancement. The study introduces a regenerative braking control strategy for electric vehicles founded on game theory optimization to enhance braking performance and optimize braking energy utilization. Develop a regenerative braking control approach based on the dynamic model of an electric vehicle equipped with hub motors. Employing game theory, we establish participants, control variables, strategy sets, benefit functions, and constraints to optimize the coefficient K for regenerative braking. The efficacy and superiority of the control strategy model are validated through joint simulations using Matlab/Simulink and AVL Cruise. Research findings indicate: (1) Speed tracking error remains below 3% in both NEDC and CLTC-P simulations, underscoring the effectiveness of the dynamic model and control strategy devised in this study. (2) The energy recovery rate achieved by the game theory-based optimization strategy surpasses that of the Cruise self-contained strategy and fuzzy control strategy by 18.06% and 4.5% in the NEDC simulation, and by 13.48% and 3.85% in the CLTC-P simulation, respectively. The adhesion coefficient curves implemented on the front and rear axles, derived from the game theory optimization control strategy, closely approximate the ideal adhesion coefficient curve, leading to a substantial enhancement in the car's braking stability. The degree of jerk magnitude regulated by the game theory optimization strategy consistently falls within the ±3 m/s³ threshold, resulting in a considerable enhancement in the comfort of vehicle occupants. These outcomes underscore the efficacy of the game theory-based optimized control strategy in enhancing energy recovery, braking stability, and comfort throughout the braking process of the vehicle.

Association between polypharmacy and hard braking events in older adult drivers.

BACKGROUND: Polypharmacy (i.e., simultaneous use of two or more medications) poses a serious safety concern for older drivers. This study assesses the association between polypharmacy and hard braking events in older adult drivers. METHODS: Data for this study came from a naturalistic driving study of 2990 older adults. Information about medications was collected through the "brown-bag review" method. Primary vehicles of the study participants were instrumented with data recording devices for up to 44 months. Multivariable negative binomial model was used to estimate the adjusted incidence rate ratios (aIRRs) and 95 % confidence intervals (CIs) of hard-braking events (i.e., maneuvers with linear deceleration rates ≥0.4 g) associated with polypharmacy. RESULTS: Of the 2990 participants, 2872 (96.1 %) were eligible for this analysis. At the time of enrollment, 157 (5.5 %) drivers were taking fewer than two medications, 904 (31.5 %) were taking 2-5 medications, 895 (31.2 %) were taking 6-9 medications, 571 (19.9 %) were taking 10-13 medications, and 345 (12.0 %) were taking 14 or more medications. Compared to drivers using fewer than two medications, the risk of hard-braking events increased 8 % (aIRR 1.08, 95 % CI 1.04, 1.13) for users of 2-5 medications, 12 % (aIRR 1.12, 95 % CI 1.08, 1.16) for users of 6-9 medications, 19 % (aIRR 1.19, 95 % CI 1.15, 1.24) for users of 10-13 medications, and 34 % (aIRR 1.34, 95 % CI 1.29, 1.40) for users of 14 or more medications. CONCLUSIONS: Polypharmacy in older adult drivers is associated with significantly increased incidence of hard-braking events in a dose-response fashion. Effective interventions to reduce polypharmacy use may help improve driving safety in older adults.

Affordance-based control of braking in cycling: Experience reveals differences in the style of control.

We investigated whether in an in-situ collision avoidance experiment cyclists regulate braking by adopting an affordance-based control strategy. Within an affordance-based control strategy for braking, deceleration is controlled relative to the maximum achievable deceleration rather than by nulling out deviations from ideal deceleration, and potentially allowing for different braking styles. Twenty active- and eighteen inactive-cyclists were asked to cycle on a straight path in an indoor gym and to stop as close as possible in front of a stationary obstacle. Maximum achievable deceleration was manipulated by loading the bike: no-load, load-5 kg, and load-10 kg. Two approach distances were used to vary cycling speed. Participants in both groups stopped farther from the obstacle when approaching with long- than short-initial distance conditions. No systematic effects of loading on braking performance and control were found across the two groups. However, both groups did increase the magnitude of brake adjustments as ideal deceleration increased and got closer to the action boundary, even when current deceleration approached the ideal deceleration. This indicates that participants adopted an affordance-based control strategy for braking. Two braking styles were identified: an aggressive style, characterized by a late braking onset and a high, steep peak in ideal deceleration, and a conservative style, characterized by an early braking onset and gradual, linear increase in ideal deceleration. The aggressive braking style was more prevalent among the active-cyclists. We suggest that the braking styles emerge from differences in calibration between information and action. The novelty of our work lies in confirming that cyclists adopt an affordance-based control strategy in an in-situ experiment and in demonstrating and explicating how affordance-based control can incorporate the emergence of different styles of braking.

The effectiveness of Q6 and PIPER 6-year-old models on quantification of the change of child sitting posture with AEB and its impact on child's injures in frontal crash.

OBJECTIVE: Automatic Emergency Braking (AEB) has a direct impact on the effectiveness of the restraint systems in providing protection toward child occupants. The objective is to evaluate the effectiveness of Q6 and PIPER 6-year-old models in predicting the kinematic responses of child models, and further to quantify and analyze the child injuries during a frontal crash with and without AEB. METHODS: The finite element model of a booster seat has been validated through a full vehicle test. Based on the validated finite element model, two sled test finite element models for the rear seat booster seat with Q6 and PIPER 6-year-old models were constructed. AEB condition was imposed on above the two models and the kinematic responses of sitting posture including head, neck and chest have been compared in detail. The peak head displacement and neck curvature of Q6 dummy and PIPER 6-year-old models have been compared with the test data from child volunteers. Based on the child model with better predictive capability for kinematic response under AEB, child injuries were evaluated and analyzed for the 50 km/h frontal crash test with and without AEB. Last, this study discussed the effects of internal neck and chest structure difference between Q6 and PIPER 6-year-old models on child kinematic response and the injury risks. RESULTS: Under AEB condition, PIPER 6-year-old model has higher head displacement and lower trunk displacement than Q6 dummy model, and the peak head displacement and neck curvature of PIPER 6-year-old model are similar to the test data of child volunteers. During the 50 km/h frontal crash simulation with pre-crash AEB, the HIC15, Head acceleration 3 ms, Nij decrease 43.7%, 19.6% and 28.8%, respectively and the chest deflection increases 15.5% compared to the simulation without AEB. CONCLUSIONS: This study shows that PIPER 6-year-old model is more suitable for the quantification of sitting posture change under AEB due to its higher biofidelity. The pre-crash AEB can substantially reduce the head, neck injuries. But it also increases the chest injury due to the chest pre-compression. Future efforts are recommended to lower the child chest injury by integrating AEB with active pre-tensioning seatbelts.

Engineering Phage Nanocarriers Integrated with Bio-Intelligent Plasmids for Personalized and Tunable Enzyme Delivery to Enhance Chemodynamic Therapy.

Customizable and number-tunable enzyme delivery nanocarriers will be useful in tumor therapy. Herein, a phage vehicle, T4-Lox-DNA-Fe (TLDF), which adeptly modulates enzyme numbers using phage display technology to remodel the tumor microenvironment (TME) is presented. Regarding the demand for lactic acid in tumors, each phage is engineered to display 720 lactate oxidase (Lox), contributing to the depletion of lactic acid to restructure the tumor's energy metabolism. The phage vehicle incorporated dextran iron (Fe) with Fenton reaction capabilities. H2O2 is generated through the Lox catalytic reaction, amplifying the H2O2 supply for dextran iron-based chemodynamic therapy (CDT). Drawing inspiration from the erythropoietin (EPO) biosynthetic process, an EPO enhancer is constructed to impart the EPO-Keap1 plasmid (DNA) with tumor hypoxia-activated functionality, disrupting the redox homeostasis of the TME. Lox consumes local oxygen, and positive feedback between the Lox and the plasmid promotes the expression of kelch ECH Associated Protein 1 (Keap1). Consequently, the downregulation of the antioxidant transcription factor Nrf2, in synergy with CDT, amplifies the oxidative killing effect, leading to tumor suppression of up to 78%. This study seamlessly integrates adaptable T4 phage vehicles with bio-intelligent plasmids, presenting a promising approach for tumor therapy.

Are front crash prevention systems less effective at preventing rear-end crashes where trucks and motorcycles are struck?

OBJECTIVE: Automatic emergency braking (AEB) and forward collision warning (FCW) are effective at preventing rear-end crashes, but they may perform better in some rear-end crash scenarios than others. The goal of this study was to estimate the effects of front crash prevention systems equipped to passenger vehicles in crashes where another passenger vehicle, a medium/heavy truck, or a motorcycle is struck and compare effectiveness by struck vehicle type. METHODS: More than 160,000 two-vehicle rear-end crashes were identified where a passenger vehicle with or without FCW and AEB was the striking vehicle and another passenger vehicle, medium/heavy truck, or motorcycle was the struck vehicle. Poisson regression was used to estimate the effect of front crash prevention by struck vehicle type on rear-end crash rates per registered vehicle year, accounting for the state and year of the crash and the make, model year, class, and engine type of the striking vehicle. RESULTS: Front crash prevention was associated with a 53% reduction in rear-end crash rates when striking another passenger vehicle, which was significantly larger than the reductions of 38% when striking a medium/heavy truck and 41% when striking a motorcycle. Reductions in rear-end injury crash rates when striking a passenger vehicle also were larger than when striking a medium/heavy truck and when striking a motorcycle. DISCUSSION: If all passenger vehicles were equipped with FCW and AEB that were as effective in crashes striking a truck or motorcycle as they are in crashes with another passenger vehicle, over 5,500 additional crashes with medium/heavy trucks and 500 with motorcycles could potentially be prevented annually in the United States above what would be expected from current front crash prevention systems. Extending front crash prevention testing in consumer information programs to include motorcycle and truck targets could encourage auto manufacturers to improve performance in these crash scenarios.

Kinematic analysis of an unrestrained passenger in an autonomous vehicle during emergency braking.

Analyzing human body movement is a critical aspect of biomechanical studies in road safety. While most studies have traditionally focused on assessing the head-neck system due to the restraint provided by seat belts, it is essential to examine the entire pelvis-thorax-head kinematic chain when these body regions are free to move. The absence of restraint systems is prevalent in public transport and is also being considered for future integration into autonomous vehicles operating at low speeds. This article presents an experimental study examining the movement of the pelvis, thorax and head of 18 passengers seated without seat belts during emergency braking in an autonomous bus. The movement was recorded using a video analysis system capturing 100 frames per second. Reflective markers were placed on the knee, pelvis, lumbar region, thorax, neck and head, enabling precise measurement of the movement of each body segment and the joints of the lumbar and cervical spine. Various kinematic variables, including angles, displacements, angular velocities and accelerations, were measured. The results delineate distinct phases of body movement during braking and elucidate the coordination and sequentiality of pelvis, thorax and head rotation. Additionally, the study reveals correlations between pelvic rotation, lumbar flexion, and vertical trunk movement, shedding light on their potential impact on neck compression. Notably, it is observed that the elevation of the C7 vertebra is more closely linked to pelvic tilt than lumbar flexion. Furthermore, the study identifies that the maximum angular acceleration of the head and the maximum tangential force occur during the trunk's rebound against the seatback once the vehicle comes to a complete stop. However, these forces are found to be insufficient to cause neck injury. While this study serves as a preliminary investigation, its findings underscore the need to incorporate complete trunk kinematics, particularly of the pelvis, into braking and impact studies, rather than solely focusing on the head-neck system, as is common in most research endeavors.

Assessing the reliability of biomechanical variables during a horizontal deceleration task in healthy adults.

Horizontal deceleration technique is an underpinning factor to musculoskeletal injury risk and performance in multidirectional sport. This study primarily assessed within- and between-session reliability of biomechanical and performance-based aspects of a horizontal deceleration technique and secondarily investigated the effects of limb dominance on reliability. Fifteen participants completed four horizontal decelerations on each leg during test and retest sessions. A three-dimensional motion analysis system was used to collect kinetic and kinematic data. Completion time, ground contact time, rate of horizontal deceleration, minimum centre of mass height, peak eccentric force, impulse ratio, touchdown distance, sagittal plane foot and knee angles at initial contact, maximum sagittal plane thorax angle, and maximum knee flexion moment were assessed. Coefficients of variation (COV) and intraclass correlation coefficients (ICC) were used to assess within- and between-session reliability, respectively. Seven variables showed "great" within-session reliability bilaterally (COV ≤9.13%). ICC scores were 'excellent' (≥0.91; n = 4), or 'good' (0.76-0.89; n = 7), bilaterally. Limb dominance affected five variables; three were more reliable for the dominant leg. This horizontal deceleration task was reliable for most variables, with little effect of limb dominance on reliability. This deceleration task may be reliably used to assess and track changes in deceleration technique in healthy adults.

Vertical Center-of-Mass Braking and Motor Performance during Gait Initiation in Young Healthy Adults, Elderly Healthy Adults, and Patients with Parkinson's Disease: A Comparison of Force-Plate and Markerless Motion Capture Systems.

BACKGROUND: This study tested the agreement between a markerless motion capture system and force-plate system ("gold standard") to quantify stability control and motor performance during gait initiation. METHODS: Healthy adults (young and elderly) and patients with Parkinson's disease performed gait initiation series at spontaneous and maximal velocity on a system of two force-plates placed in series while being filmed by a markerless motion capture system. Signals from both systems were used to compute the peak of forward center-of-mass velocity (indicator of motor performance) and the braking index (indicator of stability control). RESULTS: Descriptive statistics indicated that both systems detected between-group differences and velocity effects similarly, while a Bland-Altman plot analysis showed that mean biases of both biomechanical indicators were virtually zero in all groups and conditions. Bayes factor 01 indicated strong (braking index) and moderate (motor performance) evidence that both systems provided equivalent values. However, a trial-by-trial analysis of Bland-Altman plots revealed the possibility of differences >10% between the two systems. CONCLUSION: Although non-negligible differences do occur, a markerless motion capture system appears to be as efficient as a force-plate system in detecting Parkinson's disease and velocity condition effects on the braking index and motor performance.

Exploratory` study on driving ability of people with schizophrenia: Relationships among cognitive function, symptoms, and brain activity.

BACKGROUND: This study aimed to examine the relationships among cognitive function, symptoms, prefrontal activation, basic driving skills, and collision risk factors using a hazard prediction task in simulated driving. METHODS: Participants included 42 people with schizophrenia aged 20-50 years who had actual experience of driving. The Trail making test (TMT) A and TMTB, Wechsler Memory Test-Revised (WMS-R), and Zoo Map test (ZMT) were used to evaluate cognitive function. Positive and negative syndrome scale was used to assess symptoms, and brain activity was assessed by evaluating cerebral blood flow during a visual working memory task using functional near-infrared spectroscopy. Driving tasks that tested basic skills, such as brake reaction, steering wheel skills, and standard deviation of lateral position, were analyzed using multiple regression analysis. Three hazard prediction tasks were performed using discriminant analysis. RESULTS: Brake reaction associated with cerebral blood flow and TMT-A. Steering wheel skills associated with WMS-R, driving experience and depression. Significant differences were found between the collision and noncollision groups in the hazard prediction task, as shown by the ZMT, driving experience, and brake reaction. CONCLUSIONS: Brain activity in the frontal lobe during a desk task may be useful data for driving assessment. Assessment of processing speed and learning ability may be particularly important in the evaluation of basic skills for safe driving. In addition, for people with schizophrenia, foresight, as represented by proactive planning, experience, and quick braking may be an essential characteristic to anticipate danger and react quickly enough to avoid collisions.