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Abstract Recent immersive mixed reality (MR) and virtual reality (VR) displays enable users to use their hands to interact with both veridical and virtual environments simultaneously. Therefore, it becomes important to understand the performance of human hand-reaching movement in MR. Studies have shown that different virtual environment visualization modalities can affect point-to-point reaching performance using a stylus, but it is not yet known if these effects translate to direct human-hand interactions in mixed reality. This paper focuses on evaluating human point-to-point motor performance in MR and VR for both finger-pointing and cup-placement tasks. Six performance measures relevant to haptic interface design were measured for both tasks under several different visualization conditions (“MR with indicator,” “MR without indicator,” and “VR”) to determine what factors contribute to hand-reaching performance. A key finding was evidence of a trade-off between reaching “motion confidence” measures (indicated by throughput, number of corrective movements, and peak velocity) and “accuracy” measures (indicated by end-point error and initial movement error). Specifically, we observed that participants tended to be more confident in the “MR without Indicator” condition for finger-pointing tasks. These results contribute critical knowledge to inform the design of VR/MR interfaces based on the application's user performance requirements. 

Abstract Objective.This study’s objective is to understand distally-referred surface electrical nerve stimulation (DR-SENS) and evaluates the effects of electrode placement, polarity, and stimulation intensity on the location of elicited sensations in non-disabled individuals.Approach.A two-phased human experiment was used to characterize DR-SENS. In Experiment One, we explored 182 electrode combinations to identify a subset of electrode position combinations that would be most likely to elicit distally-referred sensations isolated to the index finger without discomfort. In Experiment Two, we further examined this subset of electrode combinations to determine the effect of stimulation intensity and electrode position on perceived sensation location. Stimulation thresholds were evaluated using parameter estimation by sequential testing and sensation locations were characterized using psychometric intensity tests.Main Results.We found that electrode positions distal to the wrist can consistently evoke distally referred sensations with no significant polarity dependency. The finger-palm combination had the most occurrences of distal sensations, and the different variations of this combination did not have a significant effect on sensation location. Increasing stimulation intensity significantly expanded the area of the sensation, moved the most distal sensation distally, and moved the vertical centroid proximally. Also, a large anodic-leading electrode at the elbow mitigated all sensation at the anodic-leading electrode site while using symmetric stimulation waveforms. Furthermore, this study showed that the most intense sensation for a given percept can be distally referred. Lastly, for each participant, at least one of the finger-palm combinations evaluated in this study worked at both perception threshold and maximum comfortable stimulation intensities.Significance.These findings show that a non-invasive surface electrical stimulation charge modulated haptic interface can be used to elicit distally-referred sensations on non-disabled users. Furthermore, these results inform the design of novel haptic interfaces and other applications of surface electrical stimulation based haptic feedback on electrodes positioned distally from the wrist. 

Specifying leg placement is a key element for legged robot control, however current methods for specifying individual leg motions with human-robot interfaces require mental concentration and the use of both arm muscles. In this paper, a new control interface is discussed to specify leg placement for hexapod robot by using finger motions. Two mapping methods are proposed and tested with lab staff, Joint Angle Mapping (JAM) and Tip Position Mapping (TPM). The TPM method was shown to be more efficient. Then a manual controlled gait based on TPM is compared with fixed gait and camera-based autonomous gait in a Webots simulation to test the obstacle avoidance performance on 2D terrain. Number of Contacts (NOC) for each gait are recorded during the tests. The results show that both the camera-based autonomous gait and the TPM are effective methods in adjusting step size to avoid obstacles. In high obstacle density environments, TPM reduces the number of contacts to 25% of the fixed gaits, which is even better than some of the autonomous gaits with longer step size. This shows that TPM has potential in environments and situations where autonomous footfall planning fails or is unavailable. In future work, this approach can be improved by combining with haptic feedback, additional degrees of freedom and artificial intelligence.