Real-Time Strategy Games Bot Based on a Non- Simultaneous Human-Like Movement Characteristic

This paper discusses how to improve the behaviour ofartificial intelligence (AI) algorithms during real-time strategygames so as to behave more like human players. If we want toachieve this goal we must take into consideration several aspectsof human psychology – human characteristics. Here we focusedon the limited reaction times of the players in contrast to theenormous speed of modern computers. We propose an approachthat mimics the limitations of the human reaction times. In orderto work properly, the AI must know the average reaction times ofthe players. Some techniques and proposed algorithm outline arepresented on how to achieve this

Universal Algorithm for Creating A Small Scale Reusable Simulation Data in Real-time Strategy Games

Real-time strategy games are of such high complexity that consideration of trying to brute force all actions and states is not only impractical, but impossible. Approximations, information abstractions, and models are, therefore, the necessity when creating game bots that play this genre of games. To create such bots, the detailed data is needed to base them on. This article introduces a universal algorithm that creates reusable simulation data of one attacking unit on a building and tests the feasibility of doing such a task. This paper concludes that capturing all relevant data in a sub-segment of real-time strategygames is feasible. Gathered data holds valuable information and can be reused in new research without the need of repeating the simulations

Movement Onset Detection and Target Estimation for Robot-Aided Arm Training

This paper presents a motion intention estimation algorithm that is based on the recordings of joint torques, joint positions, electromyography, eye tracking and contextual information. It is intended to be used to support a virtual-reality-based robotic arm rehabilitation training. The algorithm first detects the onset of a reaching motion using joint torques and electromyography. It then predicts the motion target using a combination of eye tracking and context, and activates robotic assistance toward the target. The algorithm was first validated offline with 12 healthy subjects, then in a real-time robot control setting with 3 healthy subjects. In offline crossvalidation, onset was detected using torques and electromyography 116 ms prior to detectable changes in joint positions. Furthermore, it was possible to successfully predict a majority of motion targets, with the accuracy increasing over the course of the motion. Results were slightly worse in online validation, but nonetheless show great potential for real-time use with stroke patients

Evaluation of upper extremity robot-assistances in subacute and chronic stroke subjects

<p>Abstract</p> <p>Background</p> <p>Robotic systems are becoming increasingly common in upper extremity stroke rehabilitation. Recent studies have already shown that the use of rehabilitation robots can improve recovery. This paper evaluates the effect of different modes of robot-assistances in a complex virtual environment on the subjects' ability to complete the task as well as on various haptic parameters arising from the human-robot interaction.</p> <p>Methods</p> <p>The MIMICS multimodal system that includes the haptic robot HapticMaster and a dynamic virtual environment is used. The goal of the task is to catch a ball that rolls down a sloped table and place it in a basket above the table. Our study examines the influence of catching assistance, pick-and-place movement assistance and grasping assistance on the catching efficiency, placing efficiency and on movement-dependant parameters: mean reaching forces, deviation error, mechanical work and correlation between the grasping force and the load force.</p> <p>Results</p> <p>The results with groups of subjects (23 subacute hemiparetic subjects, 10 chronic hemiparetic subjects and 23 control subjects) showed that the assistance raises the catching efficiency and pick-and-place efficiency. The pick-and-place movement assistance greatly limits the movements of the subject and results in decreased work toward the basket. The correlation between the load force and the grasping force exists in a certain phase of the movement. The results also showed that the stroke subjects without assistance and the control subjects performed similarly.</p> <p>Conclusions</p> <p>The robot-assistances used in the study were found to be a possible way to raise the catching efficiency and efficiency of the pick-and-place movements in subacute and chronic subjects. The observed movement parameters showed that robot-assistances we used for our virtual task should be improved to maximize physical activity.</p

Psychophysiological responses to different levels of cognitive and physical workload in haptic i nteraction. Robotica

SUMMARY Psychophysiological measurements, which serve as objective indicators of psychological state, have recently been introduced into human-robot interaction. However, their usefulness in haptic interaction is uncertain, since they are influenced by physical workload. This study analyses psychophysiological responses to a haptic task with three different difficulty levels and two different levels of physical load. Four physiological responses were recorded: heart rate, skin conductance, respiratory rate and skin temperature. Results show that mean respiratory rate, respiratory rate variability and skin temperature show significant differences between difficulty levels regardless of physical load and can be used to estimate cognitive workload in haptic interaction

EFFECTS OF ANTERIOR-POSTERIOR LOAD PLACEMENTS IMPOSED BY A TRANSFORMER BAR ON SQUAT BIOMECHANICS

Examining the effect of anterior-posterior load placements imposed by a transformer bar could provide additional options for squatting exercises. The purpose of this study was to quantify trunk and pelvis angles and low back and lower extremity joint moments among the regular back and front squats and four squats with a transformer bar. Twelve males and 12 females performed six different squatting variations with a load of 70% of their one-repetition maximum of the regular front squat: back and front squats with a regular bar, back and front squats with a transformer bar, and squats with more anterior or posterior loads with a transformer bar. Joint angles and moments were extracted at the thigh angle of 70° in the ascending phases, corresponding to a posture close to a parallel squat. Trunk flexion angles were the highest for the transformer bar back squat and transformer bar posterior load squat. The greatest pelvis flexion angles were observed for the regular back squat, transformer bar back squat, and transformer bar posterior load squat. Low back joint moments were the highest for the transformer bar anterior load squat. Hip joint moments were significantly lower for the regular bar front squat compared to the other squat conditions. More posterior load placements resulted in decreased low back moments, increased trunk and pelvis flexion angles, and similar hip and knee moments compared to more anterior load placements. Changing the load placement does not affect low back and lower extremity loading as expected because the trunk and pelvis angles could be adjusted according to load placements. An anterior load placement may result in greater low back moments while a posterior load placement has greater trunk and pelvis flexion, which should be taken into consideration for people with low back impairments

Effectiveness of different sensing modalities in predicting targets of reaching movements

Human motion recognition is essential for many biomedical applications, but few studies compare the abilities of multiple sensing modalities. This paper thus evaluates the effectiveness of different modalities when predicting targets of human reaching movements. Electroencephalography, electrooculography, camera-based eye tracking, electromyography, hand tracking and the user’s preferences are used to make predictions at different points in time. Prediction accuracies are calculated based on data from 10 subjects in within-subject crossvalidation. Results show that electroencephalography can make predictions before limb motion onset, but its accuracy decreases as the number of potential targets increases. Electromyography and hand tracking give high accuracy, but only after motion onset. Eye tracking is robust and gives high accuracy at limb motion onset. Combining multiple modalities can increase accuracy, though not always. While many studies have evaluated individual sensing modalities, this study provides quantitative data on many modalities at different points of time in a single setting. The information could help biomedical engineers choose the most appropriate equipment for a particular application

Closing the loop in exergaming - Health benefits of biocybernetic adaptation in senior adults

Exergames help senior players to get physically active by promoting fun and enjoyment while exercising. However, most exergames are not designed to produce recommended levels of exercise that elicit adequate physical responses for optimal training in the aged population. In this project, we developed physiological computing technologies to overcome this issue by making real-time adaptations in a custom exergame based on recommendations for targeted heart rate (HR) levels. This biocybernetic adaptation was evaluated against conventional cardiorespiratory training in a group of active senior adults through a floor-projected exergame and a smartwatch to record HR data. Results showed that the physiologically-augmented exergame leads players to exert around 40% more time in the recommended HR levels, compared to the conventional training, avoiding over exercising and maintaining good enjoyment levels. Finally, we made available our biocybernetic adaptation software tool to enable the creation of physiological adaptive videogames, permitting the replication of our study.info:eu-repo/semantics/publishedVersio

Crucial Role for BAFF-BAFF-R Signaling in the Survival and Maintenance of Mature B Cells

Defects in the expression of either BAFF (B cell activating factor) or BAFF-R impairs B cell development beyond the immature, transitional type-1 stage and thus, prevents the formation of follicular and marginal zone B cells, whereas B-1 B cells remain unaffected. The expression of BAFF-R on all mature B cells might suggest a role for BAFF-R signaling also for their in vivo maintenance. Here, we show that, 14 days following a single injection of an anti-BAFF-R mAb that prevents BAFF binding, both follicular and marginal zone B cell numbers are drastically reduced, whereas B-1 cells are not affected. Injection of control, isotype-matched but non-blocking anti-BAFF-R mAbs does not result in B cell depletion. We also show that this depletion is neither due to antibody-dependent cellular cytotoxicity nor to complement-mediated lysis. Moreover, prevention of BAFF binding leads to a decrease in the size of the B cell follicles, an impairment of a T cell dependent humoral immune response and a reduction in the formation of memory B cells. Collectively, these results establish a central role for BAFF-BAFF-R signaling in the in vivo survival and maintenance of both follicular and marginal zone B cell pools