Objective: We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI).

Background: To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice.

Method: Meta-analytic methods were applied to the available literature on trust and HRI. A total of 29 empirical studies were collected, of which 10 met the selection criteria for correlational analysis and 11 for experimental analysis. These studies provided 69 correlational and 47 experimental effect sizes.

Results: The overall correlational effect size for trust was r̄ = +0.26, with an experimental effect size of d̄ = +0.71. The effects of human, robot, and environmental characteristics were examined with an especial evaluation of the robot dimensions of performance and attribute-based factors. The robot performance and attributes were the largest contributors to the development of trust in HRI. Environmental factors played only a moderate role.

Conclusion: Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated. There was little evidence for effects of human-related factors.

Application: The findings provide quantitative estimates of human, robot, and environmental factors influencing HRI trust. Specifically, the current summary provides effect size estimates that are useful in establishing design and training guidelines with reference to robot-related factors of HRI trust. Furthermore, results indicate that improper trust calibration may be mitigated by the manipulation of robot design. However, many future research needs are identified.

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The objective of this study was to determine the utility of a passive gravity-balanced arm orthosis, the Wilmington roboticexoskeleton (WREX), for patients with neuromuscular diseases. The WREX, a four-degrees-of-freedom functional orthosis, is energized by rubber bands to eliminate gravity and is attached to the wheelchair. The development and clinical testing of WREX is described in this report. Seventeen patients (14 boys and 3 girls) with muscular disabilities participated in the study. Ages ranged from 4 to 20 years. Criteria for inclusion included a weakened arm, use of a wheelchair, the ability to grasp and release objects, and the ability to provide feedback on device use. Testing consisted of administering the Jebsen test of hand function without WREX and then testing again after approximately two weeks of wearing the WREX orthosis. The timed results of each task within the test then were compared. Specific tasks related to vertical movement required less time to perform with the WREX. A large number of subjects were able to perform the Jebsen tasks with the WREX, where they were unable to perform the task without the WREX. Patients can benefit from WREX because it increases their performance in daily living activities and makes many tasks possible. The range-of-motion in the patients’ arms increased considerably, while the time required to complete some of the Jebsen test tasks decreased. Most patients were very receptive to WREX, although a few were ambivalent.

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In this paper, we propose a multipurpose sensing system and fast phase analysis algorithms to predict and estimate behaviors of human being in advance. The sensing system is designed lightly and simply to minimize data acquisition errors and composed of six absolute encoders, eight FSR sensors, and FPGA board for data processing. The eight FSR sensors are attached at four points of sole of each foot where human weight is largely concentrated. The leg detaching structure that connects up with six light steel links is tuned according to the fittest condition of a subject. Thus, each link can be adjusted according to subject’s body length. The phase analysis algorithms have two major categories for analyzing walk behaviors and stand behaviors, and four subordinate phases for standing, lift, swing, and landing. This algorithm considers standing motion and two leg behaviors. Experimental implementations are performed successfully to estimate various human gaits. This acquisition data are efficient for locomotion trajectory generation of biped robots and exoskeleton systems

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The Lower-limb Power Assisted Robot is a typical exoskeleton power assistance device, which is worn on the user’s lower extremities. It can help the elderly and the infirm walk independently. According to the characteristics of human lower extremity joints, a robot with four-bar knee joint whose pelvis and knee joint are driven by the motor-driven screw-nut body is designed. Employing the Denanit-Hartenberg (D-H) method, the robot kinematics is analyzed, the equation of which was established. Based upon the law of human gait, the robot’s trajectory planning is accomplished. According to the dSPACE system, the hardware-in-the-loop experiment system of the single leg is established; the step experiment, sine response and walking test with load are accomplished. Experimental results show that the robot can achieve the gait law and has strong load capacity.

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It is thought that the dynamic motions with lower limbs such as walking can be made more effectively by moving each joint along to its natural frequency. If the natural frequency were able to be modified purposefully, the effective motion could be performed at any angular frequency around joint. We realized that with the exoskeleton-type powered suit, HAL (Hybrid Assistive Leg)-3 we developed for walking aid. In this research, we considered the operator’s leg as pendulum model, identified the physical parameters around human’s knee joints, tried to adjust the impedance, and applied that to pendular movement of leg. The effectiveness of adjusting the natural frequency in power assist control can be confirmed through the experiments evaluated with myoelectricity.

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