Stress, anxiety, and depression negatively affect productivity and the global economy with an estimated annual cost of ${\$}$1 trillion U.S. dollars, according to the World Health Organization. Moreover, prolonged daily stress—even if minor—can lead to severe health consequences, including cancer and various mental disorders. Virtual reality (VR) has been shown to be a promising tool for relieving daily stressors given its accessibility and its projected availability as compared to visiting with mental health professionals. Prior work in this area has mostly focused on the restorative effects of nature simulations, demonstrating that passively experiencing immersive nature scenes improves positive affect. However, aside from providing opportunities for exercise, little is known about how active VR engagement can improve one’s mental health. To address this research gap, this paper presents a new, active form of VR therapy and assesses its effectiveness as compared to passive VR experiences. We developed VR Drawing—inspired by art therapy, which promotes positive emotions through artistic creation—and VR Throwing—inspired by “rage rooms”, which allow people to release negative emotions via intentional destruction. In a between- participants study (n = 64), we found that both VR Drawing and VR Throwing significantly reduced participants’ stress levels and increased positive affect when compared to passively watching nature scenes in VR. Linear regression models suggest that the total number of user interactions positively affects improvement in positive emotions for VR Drawing, but has a negative impact on positive emotions for VR Throwing. This study provides empirical evidence of how active VR experiences may reduce stress and offers guidelines for creating future VR applications to promote psychological well-being.

Teleoperation platforms often require the user to be situated at a fixed location to both visualize and control the movement of the robot and thus do not provide the operator with much mobility. One example is in existing robotic surgery solutions that require the surgeons to be away from the patient, attached to consoles where their heads must be fixed and their arms can only move in a limited space. This creates a barrier between physicians and patients that does not exist in normal surgery. To address this issue, we propose a mobile telesurgery solution where the surgeons are no longer mechanically limited to control consoles and are able to teleoperate the robots from the patient bedside, using their arms equipped with wireless sensors and viewing the endoscope video via optical see-through head-mounted displays (HMDs). We evaluate the feasibility and efficiency of our user interaction method compared to a standard surgical robotic manipulator via two tasks with different levels of required dexterity. The results indicate that with sufficient training our proposed platform can attain similar efficiency while providing added mobility for the operator.

One major cause of preventable death is a lack of proper skills for providing critical care. Conventional training for advanced emergency medical procedures is often limited to a verbal block of instructions and/or an instructional video. In this study, we evaluate the benefits of using an optical see-through head-mounted display (OST-HMD) for training of caregivers in an emergency medical environment. A rich user interface was implemented that provides 3D visual aids including images, text and tracked 3D overlays for each task. A user study with 20 participants was conducted for two medical tasks, where each subject received conventional training for one task and HMD training for the other task. Our results indicate that using a mixed reality HMD is more engaging, improves the time-on-task, and increases the confidence level of users.

Uncertainty in measurement of point correspondences negatively affects the accuracy and precision in the calibration of head-mounted displays (HMD). In general, the distribution of alignment errors for optical see-through calibration are not isotropic, and one can estimate its distribution based on interaction requirements of a given calibration process and the user's measurable head motion and hand-eye coordination characteristics. Current calibration methods, however, mostly utilize the Direct Linear Transformation (DLT) method which minimizes Euclidean distances for HMD projection matrix estimation, disregarding the anisotropicity in the alignment errors. We utilize the error covariance in order to take the anisotropic nature of error distribution into account. The main hypothesis of this study is that using Mahalonobis distance within the nonlinear optimization can improve the accuracy of the HMD calibration. The simulation results indicate that our new method outperforms the standard DLT method both in accuracy and precision, and is more robust against user alignment errors. To the best of our knowledge, this is the first time that anisotropic noise has been accommodated in the optical see-through HMD calibration.

An effective and simple method is proposed for multi-camera collaborative tracking, based on the prioritization of all tracking units, and then modeling the discrepancy between different tracking units as a locally static transformation error. Static error compensation is applied to the lower-priority tracking systems when high-priority trackers are not available. The method does not require high-end or carefully calibrated tracking units, and is able to effectively provide a comfortable augmented reality experience for users. A pilot study demonstrates the validity of the proposed method.

Precise tumor identification is crucial in image-guided neurosurgical procedures. With existing navigation systems, the surgeon must turn away from the patient to view the imaging data on a separate monitor. In this study, an innovative system is introduced that illustrates the tumor boundaries precisely augmented on the spot where the tumor is located with regard to the patient. Additionally, it allows the surgeon to track the distal end of the tools contextually, where direct visualization is not possible. In this approach, the tracking system is compact and worn by the surgeon, eliminating the need for additional devices that are bulky and typically limited by line of sight constraints.