Real Walking Research Articles

Impact of Socio-Demographic Attributes and Mutual Gaze of Virtual Humans on Users' Visual Attention and Collision Avoidance in VR.

This study investigated the extent that the non-verbal behaviors of virtual humans (VHs) and their socio-demographic attributes altered users' collision avoidance behaviors in Virtual Reality (VR). Users interacted with VHs representing different levels of ethnicities and gender, exhibiting different conditions of physical movement, and gaze behaviors. The VHs were depicted in three major ethnic conditions namely Asian, Caucasian, and Black. The physical movement states of the VHs were either static in the path of the user or walking toward the user in the opposite direction. The non-verbal gaze behavior of the VHs was either direct gaze or averted gaze. We used an HTC Vive tracking system to track users' performing real walking while we collected objective measures (i,e., continuous gaze, fixation gaze, clearance distance, and travel length), and subjective variables (i.e., game experiences and social presence). The results showed that the ethnicity of the VHs significantly impacted the gaze behavior of the users, and the gender of the VHs affected the user avoidance movement and their reciprocal gaze behavior. Our results revealed that users' physical movement, gaze behaviors, and collision avoidance were moderated by the VHs' perceived ethnicity, gender, and gaze behaviors. Understanding the impact of the socio-demographics attributes of VHs and their gaze behavior on users' collision avoidance is critical for applications in which users are navigating through virtual traffic, crowd, and other inter-personal simulations.

A step length estimation method based on frequency domain feature analysis and gait recognition for pedestrian dead reckoning

Purpose Step length is a key factor for pedestrian dead reckoning (PDR), which affects positioning accuracy and reliability. Traditional methods are difficult to handle step length estimation of dynamic gait, which have larger error and are not adapted to real walking. This paper aims to propose a step length estimation method based on frequency domain feature analysis and gait recognition for PDR, which considers the effects of real-time gait. Design/methodology/approach The new step length estimation method transformed the acceleration of pedestrians from time domain to frequency domain, and gait characteristics of pedestrians were obtained and matched with different walking speeds. Findings Many experiments are conducted and compared with Weinberg and Kim models, and the results show that the average errors of the new method were improved by about 2 meters to 5 meters. It also shows that the proposed method has strong stability and device robustness and meets the accuracy requirements of positioning. Originality/value A sliding window strategy used in fast Fourier transform is proposed to implement frequency domain analysis of the acceleration, and a fast adaptive gait recognition mechanism is proposed to identify gait of pedestrians.

Correlations between SSQ Scores and ECG Data during Virtual Reality Walking by Display Type

To encourage the application of virtual reality (VR) in physical rehabilitation, this study analyzed the occurrence of motion sickness when walking on a treadmill in virtual straight paths presented on two types of displays (screen and head-mounted displays (HMDs)) at a constant speed of 3.6 km/h. The simulator sickness questionnaire (SSQ) scores, which indicate motion sickness, were collected from the participants. In addition, the heart rate (HR) and heart rate variability (HRV; RMSSD and LF/HF ratio) were measured from electrocardiogram data. The correlations between the SSQ scores and HR and HRV were examined to identify a reliable variable for evaluating motion sickness. The SSQ scores were used to classify the data into the motion-sickness and no-motion-sickness groups. The data were classified into the motion-sickness group if a minimum difference of 15 points existed between the walking and baseline phases when using the screen and HMD; otherwise, the data were classified into the no-motion-sickness group. The HR and LF/HF ratio were higher, whereas the RMSSD was lower in the motion-sickness group. Moreover, within the motion-sickness group, the reduction in RMSSD and increase in HR and LF/HF ratio were greater with the HMD than with the screen. Regression analysis was performed on the HR, HRV, and SSQ scores to differentiate between the motion-sickness and no-motion-sickness groups. The regression analysis results showed a high negative correlation between the SSQ score and RMSSD. The results of this study can assist in controlling the occurrence of motion sickness in VR-based applications.

JointTracker: Real-time inertial kinematic chain tracking with joint position estimation.

In-field human motion capture (HMC) is drawing increasing attention due to the multitude of application areas. Plenty of research is currently invested in camera-based (markerless) HMC, with the advantage of no infrastructure being required on the body, and additional context information being available from the surroundings. However, the inherent drawbacks of camera-based approaches are the limited field of view and occlusions. In contrast, inertial HMC (IHMC) does not suffer from occlusions, thus being a promising approach for capturing human motion outside the laboratory. However, one major challenge of such methods is the necessity of spatial registration. Typically, during a predefined calibration sequence, the orientation and location of each inertial sensor are registered with respect to the underlying skeleton model. This work contributes to calibration-free IHMC, as it proposes a recursive estimator for the simultaneous online estimation of all sensor poses and joint positions of a kinematic chain model like the human skeleton. The full derivation from an optimization objective is provided. The approach can directly be applied to a synchronized data stream from a body-mounted inertial sensor network. Successful evaluations are demonstrated on noisy simulated data from a three-link chain, real lower-body walking data from 25 young, healthy persons, and walking data captured from a humanoid robot. The estimated and derived quantities, global and relative sensor orientations, joint positions, and segment lengths can be exploited for human motion analysis and anthropometric measurements, as well as in the context of hybrid markerless visual-inertial HMC.

Redirected walking for exploration of unknown environments

Real walking is the most natural locomotion method for exploring Virtual Environments (VE), enhancing the immersion of Virtual Reality (VR). Redirected Walking (RDW) is employed to enable real walking within limited tracking spaces in large VEs by subtly manipulating the mapping between the virtual and real environments. However, the effectiveness of RDW is greatly influenced by the convex shape and size of the manually defined physical tracking space, subsequently impacting the user’s immersive experience. To improve performance, one strategy is to integrate exploration methods from mobile robotics with RDW. This will expand the usable tracking space, facilitating dynamic environments and rapid exploration. For this, we adapted a Unity framework for an RDW algorithm to facilitate simulations for such an exploration. We conducted a simulation with artificially created non-convex explorable tracking spaces and pre-recorded path elements, simulating two adapted RDW artificial potential field (APF) concepts. Three conceptualized modes were applied: repulsive APF, exploration APF, and exploration APF with a distance threshold. Additionally, one APF was extended with a frontier-based exploration approach that utilized the path between the user’s position and a targeted frontier. The analysis revealed a significant trade-off between exploration and immersion. APF combined with frontier-based the exploration technique showed the fastest exploration speed, but - however - resulted in the lowest distance between resets.

To use or not to use viewpoint oscillations when walking in VR ? State of the art and perspectives.

Viewpoint oscillations are periodic changes in the position and/or orientation of the point of view in a virtual environment. They can be implemented in Virtual Reality (VR) walking simulations to make them feel closer to real walking. This is especially useful in simulations where users remain in place because of space or hardware constraints. As for today, it remains unclear what exact benefit they bring to user experience during walking simulations, and with what characteristics they should be implemented. To answer these questions, we conduct a systematic literature review focusing on five main dimensions of user experience (walking sensation, vection, cybersickness, presence and embodiment) and discuss 44 articles from the fields of VR, Vision, and Human-Computer Interaction. Overall, the literature suggests that viewpoint oscillations benefit vection, and with less evidence, walking sensation and presence. As for cybersickness, the literature contains contrasted results. Based on these results, we recommend using viewpoint oscillations in applications that require accurate distance or speed perception, or that aim to provide compelling walking simulations without a walking avatar, and a particular attention should be paid to cybersickness. Taken together, this work gives recommendations for enhancing walking simulations in VR, which may be applied to entertainment, virtual visits, and medical rehabilitation.

A Segmented Redirection Mapping Method for Roadmaps of Large Constrained Virtual Environments.

Redirected walking (RDW) enables users to explore large virtual spaces by real walking in small real spaces. How to effectively reduce physical collisions and decrease user perceptions of redirection are important for most RDW methods. This paper proposes a segmented redirection mapping method to calculate and map the roadmap of a large virtual space with inner obstacles to a mapped roadmap within a small real space. We adopt a Voronoi-based pruning method to extract the roadmap of the virtual space and design an RDW platform to interactively modify the virtual roadmap. We propose a roadmap mapping method based on divide-and-conquer and dynamic planning strategies to subdivide the virtual roadmap into several sub-virtual roads that are mapped individually. By recording connections of different sub-virtual roads, our method is applicable to virtual roadmaps with loop structures. During mapping, we apply the reset and redirection gains of the RDW technique as optimal aims and restrict conditions to obtain the mapped roadmap, which has small path curving and contains as few resets as possible. By real walking along the mapped roadmap, users perceive moving along the virtual roadmap to explore the entire virtual space. The experiment shows that our method works effectively for various virtual spaces with or without inner obstacles. Furthermore, our method is flexible in obtaining mapped roadmaps of different real spaces when the virtual space is fixed. Compared to prevalent RDW methods, our method can significantly reduce physical boundary collisions and maintain user experience of virtual roaming.

Strolling in Room-Scale VR: Hex-Core-MK1 Omnidirectional Treadmill.

The natural locomotion interface is critical to the development of many VR applications. For household VR applications, there are two basic requirements: natural immersive experience and minimized space occupation. The existing locomotion strategies generally do not simultaneously satisfy these two requirements well. This article presents a novel omnidirectional treadmill (ODT) system named Hex-Core-MK1 (HCMK1). By implementing two kinds of mirror-symmetrical spiral rollers to generate the omnidirectional velocity field, this proposed system is capable of providing real walking experiences with a full-degree of freedom in an area as small as 1.76 m 2, while delivering great advantages over several existing ODT systems in terms of weight, volume, latency and dynamic performance. Compared with the sizes of Infinadeck and HCP, the two best motor-driven ODTs so far, the 8 cm height of HCMK1 is only 20% of Infinadeck and 50% of HCP. In addition, HCMK1 is a lightweight device weighing only 110 kg, which provides possibilities for further expanding VR scenarios, such as terrain simulation. The system latency of HCMK1 is only 9ms. The experiments show that HCMK1 can deliver a starting acceleration of 16.00 m/s 2 and a braking acceleration of 30.00 m/s 2.

Estimating human sensitivity to curving of segmented paths within room-size environment

The curvature gain of the redirected walking (RDW) technique can map a straight virtual path to an arced real path, which enables users to real walk in large virtual space. However, the human perceptual abilities for curvature gain are mainly estimated on single walking paths in some large spaces, showing a lack of understanding the cognitive performance for more complex path conditions in room-size spaces. To explore this issue, this paper conducts three studies by using a novel psychophysical method of limits to evaluate human perception of curvature gain under different conditions of virtual paths. First, we evaluate the perception of path curving under a single path condition and reveal the impact of the path curving direction. Second, we study the ability to perceive curvature gain on a postorder path when the curving direction and degree of its preorder path vary. Our results show a moderation effect on the perceptual ability for the postorder path if both paths are in the same curving direction. Finally, we explore the effect of the preorder path length on the human sensitivity to the postorder curvature gain and demonstrate that longer preorder paths can increase the ability of users to adapt to postorder path curving. This paper reveals the adaptation characteristic of the curvature gain under complex path conditions, contributing to the development of path-based RDW methods.

A novel low cybersickness dynamic rotation gain enhancer based on spatial position and orientation in virtual environments

AbstractHardware and software resources nowadays make possible new Virtual Reality (VR) interaction methods. Numerous challenges have been involved over the years, and one of the most interesting is locomotion in virtual environments. In particular, Real Walking (RW) is one of the most effective Virtual Locomotion Techniques (VLT). It causes only reduced cybersickness, but it also requires proportional real walkable space to the virtual one, often requiring wide areas. In this context, optimization techniques have been proposed in the literature, e.g., reorientation or relocation. In this work, a novel method for improving reorientation in a virtual environment, exploiting a dynamic Rotation Gain Multiplication Factor (RGMF) based on the competence of the user in VR systems usage is proposed. The results highlight the effectiveness of the system and show the specific target of users that mainly appreciated it.

Redirected Walking for Exploring Immersive Virtual Spaces With HMD: A Comprehensive Review and Recent Advances.

Real walking techniques can provide the user with a more natural, highly immersive walking experience compared to the experience of other locomotion techniques. In contrast to the direct mapping between the virtual space and an equal-sized physical space that can be simply realized, the nonequivalent mapping that enables the user to explore a large virtual space by real walking within a confined physical space is complex. To address this issue, the redirected walking (RDW) technique is proposed by many works to adjust the user's virtual and physical movements based on some redirection manipulations. In this manner, subtle or overt motion deviations can be injected between the user's virtual and physical movements, allowing the user to undertake real walking in large virtual spaces by using different redirection controller methods. In this paper, we present a brief review to describe major concepts and methodologies in the field of redirected walking. First, we provide the fundamentals and basic criteria of RDW, and then we describe the redirection manipulations that can be applied to adjust the user's movements during virtual exploration. Furthermore, we clarify the redirection controller methods that properly adopt strategies for combining different redirection manipulations and present a classification of these methods by several categories. Finally, we summarize several experimental metrics to evaluate the performance of redirection controller methods and discuss current challenges and future work. Our study systematically classifies the relevant theories, concepts, and methods of RDW, and provides assistance to the newcomers in understanding and implementing the RDW technique.

Cortical Mechanisms Underlying Immersive Interactive Virtual Walking Treatment for Amelioration of Neuropathic Pain after Spinal Cord Injury: Findings from a Preliminary Investigation of Thalamic Inhibitory Function.

Neuropathic pain following spinal cord injury (SCI) affects approximately 60% of individuals with SCI. Effective pharmacological and non-pharmacological treatments remain elusive. We recently demonstrated that our immersive virtual reality walking intervention (VRWalk) may be effective for SCI NP. Additionally, we found that SCI NP may result from a decrease in thalamic γ-aminobutyric-acid (GABA), which disturbs central sensorimotor processing. While we identified GABAergic changes associated with SCI NP, a critical outstanding question is whether a decrease in SCI NP generated by our VRWalk intervention causes GABA content to rise. A subset of participants (n = 7) of our VRWalk trial underwent magnetic resonance spectroscopy pre- and post-VRWalk intervention to determine if the decrease in SCI NP is associated with an increase in thalamic GABA. The findings revealed a significant increase in thalamic GABA content from pre- to post-VRWalk treatment. While the current findings are preliminary and should be interpreted with caution, pre- to post-VRWalk reductions in SCI NP may be mediated by pre- to post-treatment increases in thalamic GABA by targeting and normalizing maladaptive sensorimotor cortex reorganization. Understanding the underlying mechanisms of pain recovery can serve to validate the efficacy of home-based VR walking treatment as a means of managing pain following SCI. Neuromodulatory interventions aimed at increasing thalamic inhibitory function may provide more effective pain relief than currently available treatments.

Seize: A Mobile Augmented Reality Walking Game through Critical Making

Seize: A Mobile Augmented Reality Walking Game through Critical Making

Dynamic collision envelope in virtual reality walking with colliding pedestrians

Dynamic collision envelope in virtual reality walking with colliding pedestrians

Comparing the Lower-Limb Muscle Activation Patterns of Simulated Walking Using an End-Effector-Type Robot with Real Level and Stair Walking in Children with Spastic Bilateral Cerebral Palsy.

Cerebral palsy is a neurologic disorder caused by lesions on an immature brain, often resulting in spasticity and gait abnormality. This study aimed to compare the muscle activation patterns of real level and stair walking with those of simulated walking using an end-effector-type robot in children with spastic cerebral palsy. The electromyographic activities of the vastus lateralis, biceps femoris, tibialis anterior and medial gastrocnemius of nine children with spastic bilateral cerebral palsy were measured during gait using a wireless surface EMG device. Morning walk was used for the simulated gait. Differences in the muscle activation patterns between the real and simulated gait conditions were analyzed. In the loading response, all four muscles showed reduced activity during two simulated conditions. In mid-stance, mGCM showed reduced activity during simulated conditions, whereas BFem showed greater activity during simulated level walking. In the swing phase, BFem and TAnt activity was reduced during the simulated conditions. The onset-offset of the VLat, BFem and TAnt activity was significantly delayed during simulated versus real level walking. No differences in activity onset-offset were observed between the simulated level and stair conditions. In conclusion, the robot-simulated gait showed differences in its muscle activation patterns compared with the real gait conditions, which must be considered for gait training using an end-effector-type robot.

Comparing a friction-based uni-directional treadmill and a slip-style omni-directional treadmill on first-time HMD-VR user task performance, cybersickness, postural sway, posture angle, ease of use, enjoyment, and effort

Treadmills allow users to translate their real world walking into movement in virtual worlds. Conventional treadmills used for fitness can be repurposed for users to move around in virtual reality, but permit walking in only one direction (uni-directional). Treadmills that allow walking in any direction (omni-directional) are available, in which users walk-in-place and their feet slip on a low-friction surface. Given that users can experience cybersickness and postural instability in virtual reality, this study explored user performance and side effects of using two different walking platforms: a conventional uni-directional treadmill and a slip-style omni-directional treadmill (Virtuix OMNI).All participants (n = 46) played a game in which they collected items distributed around a virtual world. Participants moved around the virtual world by walking on the conventional uni-directional treadmill (for 10 minutes) and on the omni-directional treadmill (for 10 minutes), whilst in HMD-VR, with a 5-minute break between platforms. Measurements of cybersickness, task achievement, distance covered, posture, postural sway and user experience (ease, enjoyment, and effort) were collected.Participants experienced significantly higher total cybersickness after walking on the slip-style omni-directional treadmill compared to after walking on the uni-directional treadmill (p=.003), and significantly higher Nausea and Oculomotor cybersickness after walking on the slip-style omni-directional treadmill compared to after walking on the uni-directional treadmill (p<.001 and p=.005 respectively). Participants had lowest postural sway after using the uni-directional treadmill compared to after using the omni-directional treadmill (p=.052). Participants completed significantly more of the task (p<.001) and walked further (p<.001) on the uni-directional treadmill compared to the omni-directional treadmill, and their posture angle (back tilt angle) was significantly more forward on the omni-directional treadmill compared to the uni-directional treadmill (p<.001). Significant differences were found with participants reporting walking on the omni-directional treadmill to be more difficult (p<.001), require more effort (p<.001) and be less enjoyable (p=.005), and changing direction to require more effort (p=.010), than compared to the uni-directional treadmill.This study recommends that alternatives to slip-style locomotion treadmills be developed due the non-natural walking action required to use slip-style platforms and the consequent negative psychophysiological impacts of their use with HMD-VR.

Spatial updating in virtual reality for reproducing object locations in vista space-Boundaries, landmarks, and idiothetic cues.

Keeping track of locations across self-motion is possible by continuously updating spatial representations or by encoding and later instantaneously retrieving spatial representations. In virtual reality (VR), sensory cues to self-motion used in continuous updating are typically reduced. In passive translation compared to real walking in VR, optic flow is available but body-based (idiothetic) cues are missing. With both kinds of translation, boundaries and landmarks as static visual cues can be used for instantaneous updating. In two experiments, we let participants encode two target locations, one of which had to be reproduced by pointing after forward translation in immersive VR (HMD). We increased sensory cues to self-motion in comparison to passive translation either by strengthening optic flow or by real walking. Furthermore, we varied static visual cues in the form of boundaries and landmarks inside boundaries. Increased optic flow and real walking did not reliably increase performance suggesting that optic flow even in a sparse environment was sufficient for continuous updating or that merely instantaneous updating took place. Boundaries and landmarks, however, did support performance as quantified by decreased bias and increased precision, particularly if they were close to or even enclosed target locations. Thus, enriched spatial context is a viable method to support spatial updating in VR and synthetic environments (teleoperation). Spatial context does not only provide a static visual reference in offline updating and continuous allocentric self-location updating but also, according to recent neuroscientific evidence on egocentric bearing cells, contributes to continuous egocentric location updating as well.

Knee Angle Generation with Walking Speed Adaptation Ability for a Powered Transfemoral Prosthetic Leg Prototype

This paper presents a microcontroller-based solution for generating real-time normal walking knee angle of a powered transfemoral prosthetic leg prototype. The proposed control algorithm was used to determine the prosthetic knee angle by utilizing seven hip angle movement features generated from only the inertia measurement unit (IMU) deployed on the prosthetic socket on the thigh of the same side. Then, a proportional–integral–derivative (PID) controller is developed to control the motor to reach the desired knee angle in real time. Furthermore, a novel parallel four-bar linkage-based master–slave validation framework combining a motion capture system was introduced to evaluate the performance of the knee angle generation on a speed-adjustable treadmill with able-bodied subjects. In the framework evaluation, 3 different walking speeds were applied to the treadmill to validate different speed adaptation capabilities of the prosthetic leg control system, precisely 50 cm/s, 60 cm/s, and 70 cm/s. Through the proposed 4-bar linkage framework, the prosthesis’s movement can simulate able-bodied subjects well with maximum RMSE never exceeding 0.27° in the swing flexion phase, 4.4° to 5.8° in the stance phase, and 1.953° to 13.466° in the swing extension phase. The treadmill results showed that the prosthetic leg is able to perform a normal walking gait following different walking speeds of the subject. Finally, a corridor walking experiment with a bypass adapter was successfully performed to examine the feasibility of real prosthetic walking situations.

Development of Virtual Reality Walking Collision Detection Test on Head-mounted display.

Detecting and avoiding collisions during walking is critical for safe mobility. To determine the effectiveness of clinical interventions, a realistic objective outcome measure is needed. A real-world obstacle course with moving hazards has numerous limitations (e.g., safety concerns of physical collision, inability to control events, maintaining event consistency, and event randomization). Virtual reality (VR) platforms may overcome such limitations. We developed a VR walking collision detection test using a standalone head-mounted display (HMD, Meta Quest 2) with the Unity 3D engine to enable subjects' physical walking within a VR environment (i.e., a busy shopping mall). The performance measures focus on the detection and avoidance of potential collisions, where a pedestrian may (or may not) walks toward a collision with the subject, while various non-colliding pedestrians are presented simultaneously. The physical space required for the system was minimized. During the development, we addressed expected and unexpected hurdles, such as mismatch of visual perception of VR space, limited field of view (FOV) afforded by the HMD, design of pedestrian paths, design of the subject task, handling of subject's response (detection or avoidance behavior), use of mixed reality (MR) for walking path calibration. We report the initial implementation of the HMD VR walking collision detection and avoidance scenarios that showed promising potential as clinical outcome measures.

A Coaxial Wrist-Worn Energy Harvester for Self-Powered Internet of Things Sensors

Energy harvesting from human motion has great potential of sustainably powering Internet of Things (IoT) sensors and satisfying their continuous sensing requirement. In this article, we propose a high-performance wrist-worn energy harvester to efficiently capture the biomechanical energy of arm swinging to self-power wearable sensors. Based on coaxial topology, a planetary gear system serves as frequency-up converter to increase energy conversion capacity, and all the functional units are coaxially installed to achieve a highly compact structure. Thanks to improved energy conversion capacity and structure compactness, the energy harvester can efficiently capture the kinetic energy of arm swinging and achieve high average power. We derive an analytical model to predict the system dynamics and power generation performance using the Lagrangian approach and mirror image method. We fabricate a miniature prototype with different proof mass configurations, which is characterized under bench-top excitations and tested under real walking excitations. The results show that in bench-top testing, the prototype generates maximum average power of 2.73 mW and maximum power density of 535.29 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {\mathrm {\mu }}\text{W}$ </tex-math></inline-formula> /cm3 at the excitation frequency of 1.2 Hz among different configurations. In terms of average power and power density, this energy harvester significantly overperforms its counterparts. In real walking testing, the prototype generates maximum average power of 3.13 mW at a walking frequency of 1.2 Hz among different configurations and achieves higher power output than bench-top testing. Finally, the prototype is used to simultaneously power four sensors and demonstrates great potential in self-powered IoT applications.