A larger augmented-reality field of view improves interaction with nearby holographic objects

Eva M. Hoogendoorn; Daphne J. Geerse; Jip Helsloot; Bert Coolen; John F. Stins; Melvyn Roerdink

doi:10.1371/journal.pone.0311804

Abstract

Augmented-reality (AR) applications have shown potential for assisting and modulating gait in health-related fields, like AR cueing of foot-placement locations in people with Parkinson’s disease. However, the size of the AR field of view (AR-FOV), which is smaller than one’s own FOV, might affect interaction with nearby floor-based holographic objects. The study’s primary objective was to evaluate the effect of AR-FOV size on the required head orientations for viewing and interacting with real-world and holographic floor-based objects during standstill and walking conditions. Secondary, we evaluated the effect of AR-FOV size on gait speed when interacting with real-world and holographic objects. Sixteen healthy middle-aged adults participated in two experiments wearing HoloLens 1 and 2 AR headsets that differ in AR-FOV size. To confirm participants’ perceived differences in AR-FOV size, we examined the head orientations required for viewing nearby and far objects from a standstill position (Experiment 1). In Experiment 2, we examined the effect of AR-FOV size on head orientations and gait speeds for negotiating 2D and 3D objects during walking. Less downward head orientation was required for looking at nearby holographic objects with HoloLens 2 than with HoloLens 1, as expected given differences in perceived AR-FOV size (Experiment 1). In Experiment 2, a greater downward head orientation was observed for interacting with holographic objects compared to real-world objects, but again less so for HoloLens 2 than HoloLens 1 along the line of progression. Participants walked slightly but significantly slower when interacting with holographic objects compared to real-world objects, without any differences between the HoloLenses. To conclude, the increased size of the AR-FOV did not affect gait speed, but resulted in more real-world-like head orientations for seeing and picking up task-relevant information when interacting with floor-based holographic objects, improving the potential efficacy of AR cueing applications.

Citation: Hoogendoorn EM, Geerse DJ, Helsloot J, Coolen B, Stins JF, Roerdink M (2024) A larger augmented-reality field of view improves interaction with nearby holographic objects. PLoS ONE 19(10): e0311804. https://doi.org/10.1371/journal.pone.0311804

Editor: Omnia Hamdy, National Institute of Laser Enhanced Sciences (NILES), Cairo University, EGYPT

Received: October 5, 2023; Accepted: September 17, 2024; Published: October 21, 2024

Copyright: © 2024 Hoogendoorn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This publication was funded by 1) project ‘Holocue: Assisting gait in Parkinson’s disease with intelligent mixed-reality cueing’ (with project number 19357) which is financed by the Demonstrator programme of the Dutch Research Council (NWO)(https://www.nwo.nl/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript and 2) EMIL project financial support to third parties, which is funded by the European Union. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. MR and DJG received both grants.

Competing interests: MR is a scientific advisor with share options for Strolll Ltd., a digital therapeutics company building AR software for physical rehabilitation, for one day a week ancillary to his main position as associate professor Technology in Motion at Vrije Universiteit Amsterdam. The other authors declare no conflicts of interest. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products associated with this research to declare.

Introduction

Leading augmented-reality (AR) glasses, like Microsoft HoloLens and Magic Leap, are progressing towards consumer readiness, with profound improvements in wearer comfort, form factor, data quality, and AR field of view (AR-FOV). One of the strengths of AR compared to virtual reality is that the visible real world can be augmented with environment-aware digital content, facilitating direct bodily interaction with digital objects. AR has therefore gained interest in health-related fields like rehabilitation and physical therapy given its potential efficacy for gait assistance [1, 2], gait modulation [3–5] gait-and-balance assessment [6–10] and gait-and-balance training. In these fields, AR allows the user to experience the real world augmented with (interactive) holographic floor-based objects like 2D AR cues to step onto or 3D AR obstacles to step over, an action-relevant gait-guidance technique which could improve gait parameters like stride length, step length and walking velocity in gait-impaired individuals [11–15].

In people with Parkinson’s disease (PD), for example, AR has been explored for providing external visual cues [1, 2]. External cueing (i.e., the use of external temporal or spatial stimuli) is a well-established strategy for alleviating freezing of gait (FOG) and facilitating gait in people with PD [16]. Visual cues were originally applied with 2D stripes taped to the ground as targets for foot placement, but recent insights suggest that 3D cues, like an obstacle to cross, could be more effective than 2D cues for modifying gait and alleviating FOG [17, 18]. By using wearable AR glasses, such 2D or 3D holographic objects could be presented anywhere, anytime instead of being location-bound as with real-world 2D or 3D cues, thereby potentially broadening their applicability to everyday-life situations.

Geerse et al. examined the effect of 2D and 3D AR visual cueing using Microsoft HoloLens 1 (see Fig 1A) on FOG in the home environment of people with PD [1]. Objective and subjective immediate improvements in the number and duration of FOG episodes were found for participants with long and/or many FOG episodes [1]. Participants reported that the wearer comfort and the limited AR-FOV of HoloLens 1 (30°×17° [19]) needed improvement [1], as they experienced the holographic objects as if they were watching them through a relatively small, rectangular screen, affecting the visibility of nearby AR objects (Fig 1A). Consequently, relatively large downward head orientations were required to get nearby floor-based holographic objects into view [1], see also [20–22]. This might limit the efficacy of AR cueing for alleviating FOG and for assisting and modulating gait [1].

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Fig 1.

Microsoft HoloLens 1 (A) and 2 (B) with a representation of their AR-FOV relative to one’s own FOV.

https://doi.org/10.1371/journal.pone.0311804.g001

The second generation of Microsoft HoloLens, HoloLens 2, has a larger AR-FOV (43°×29° [19]; Fig 1B). The primary objective of this study was to systematically evaluate the effect of AR-FOV size on the head orientation required for viewing and interacting with floor-based real-world and holographic objects. The secondary objective was to evaluate the effect of AR-FOV size on gait speed when interacting with floor-based real-world and holographic objects. We invited a group of healthy, middle-aged adults (40–65 years) to participate in two experiments. In Experiment 1 we compared the head orientation when looking, from a standstill position, at floor-based real-world and holographic objects at various, nearby and far, distances (Fig 2A and 2B, left panels). We expected a greater downward head orientation for looking at nearby holographic compared to nearby real-world objects, but significantly less so for HoloLens 2 than HoloLens 1 given its larger AR-FOV size. In Experiment 2 we compared the head orientations when our participants were interacting with floor-based real-world and holographic 2D and 3D objects onto a 6-meter walkway (Fig 2, all panels). Again, we expected a greater downward head orientation in the vicinity of holographic compared to real-world 2D and 3D objects, but significantly less so for HoloLens 2 than HoloLens 1 given its larger AR-FOV size. Based on previous studies [3, 23], we expected that participants walked slightly slower when interacting with holographic than with real-world objects, while we had no a-priori expectations on the effect of AR-FOV size.

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Fig 2. Experimental setup.

(A) The 6-meter walkways with holographic objects as seen through HoloLens and (B) real-world projected 2D or physical 3D objects on the floor.

https://doi.org/10.1371/journal.pone.0311804.g002

Methods

Participants

A convenience sample of 16 healthy middle-aged adults (mean [range]: 57 [46–65] years), of which 6 females and 10 males, were included in the study. Participants had no conditions interfering with gait function and no restrictions interfering with their depth perception or vision (after potential corrective aids). Participants all provided written informed consent before participation. The study was approved by the local Scientific and Ethical Review Board (VCWE-2022-048).

Experimental design and setup

This n = 16 convenience sample allowed for a full block-randomized counterbalancing of the order of the experimental conditions. Specifically, all experiments comprised two experimental factors with two levels each (hence yielding four possible orders): 1) Type of Object (real-world or holographic) and 2) Type of HoloLens (HoloLens 1 or HoloLens 2) as our manipulation of AR-FOV size (AR-FOV size of HoloLens 2 is greater than that of HoloLens 1; Table 1). Holographic 2D and 3D objects were projected with the HoloLenses (Fig 2A). An overview of the technical specifications of both devices is shown in Table 1. Real-world 2D objects were presented with a projector (EPSON EB-585W, ultra-short-throw 3LCD projector; Fig 2B, left and centered panels) while 3D objects comprised adjustable physical obstacles (Fig 2B, right panel). HoloLens 1 and 2 were used to measure 3D head position and orientation in space, wherein holographic and real-world content was aligned using spatial anchors and headset position calibrated to real-world coordinates using a transformation matrix and predetermined calibration positions. For all experiments, a 6-meter walkway with a width of 75cm was projected, providing a floor-based canvas for presenting 1) 10 stepping stones (10×30cm with an imposed step length of 60cm, where left and right stones were colored yellow and red, respectively; Fig 2A and 2B, left panels), 2) a 2D stepping target (30×75cm, depth×width located midway; Fig 2A and 2B, centered panels) and 3) a 3D obstacle (20×2cm, height×depth, located midway; Fig 2A and 2B, right panels).

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Table 1. Relevant device specifications of HoloLens 1 and 2.

https://doi.org/10.1371/journal.pone.0311804.t001

Procedure

Both headset conditions started with calibration of the HoloLens to participant’s interpupillary distance using Microsoft’s inbuilt calibration software [24] followed by a few minutes of habituation to HoloLens 1 or 2 (depending on the condition) and various holographic objects (i.e., for holographic objects conditions). To methodologically validate if participants perceived differences in the AR-FOV size, we quantified the number of visible real-world and holographic objects reported by our participants while wearing HoloLens 1 and 2. As expected, participants reported more real-world than holographic objects because the AR-FOV size is smaller than one’s own unobstructed FOV size (210°×150° [25]). However, the difference between the reported real-world and holographic objects was significantly smaller for HoloLens 2 because its AR-FOV size is greater than that of HoloLens 1 (Fig 1A and 1B). Participants thus noticed AR-FOV size differences between HoloLenses. Subsequently, the two experiments were sequentially performed in each condition.

Experiment 1: Head orientations for looking at real-world and holographic objects.

We quantified the head orientation for looking, from a standstill position, at real-world and holographic objects (i.e., stepping stones) onto the floor at various, nearby and far, distances. Participants stood still and looked twice at every stepping stone in a predetermined random order for 8 seconds. The number of the stepping stone which the participant should look at was displayed on a screen next to the participant. Only the yellow stones were included, where the first stone was the one closest to the participant (at 75cm along the walkway), and the fifth stone was the most distant one (at 555cm along the walkway) (Fig 2A and 2B, left panels).

Experiment 2: Head orientation and gait speed for interacting with real-world and holographic 2D and 3D objects during walking.

We quantified the head orientation and gait speed for interacting with real-world and holographic 2D and 3D objects while walking onto a 6-meter walkway. Participants were instructed to 1) walk as precisely as possible over the sequence of stepping stones at a self-selected comfortable speed (Fig 2A and 2B, left panels), 2) step onto a single 2D stepping target in the center of the walkway (Fig 2A and 2B, centered panels), and 3) cross a 3D obstacle in the center of the walkway (Fig 2A and 2B, right panels). For all three tasks, four trials were performed of which the first was considered a practice trial. At the start and end of each trial, participants fixated straight ahead to a red cross adjusted to their eye level to obtain their baseline head orientation.

Data and statistical analysis

Headset position and orientation data were recorded with either HoloLens 1 or 2 with a sampling frequency of 30 Hz to analyze participants’ head position along the line of progression on the walkway (i.e., increasing along the walkway from the starting position) and head orientation in terms of pitch (i.e., rotation of the headset along the lateral axis such that a downward rotation corresponds to an increase in the orientation angle).

For Experiment 1, the median head orientation from 4-7s for looking at each stepping stone separately was taken and averaged over the two repetitions for each stone (Fig 3A). In case of data irregularities (e.g., high peaks due to sneezing during the trial or external distractions as noted in the experimental logbook), the corresponding episode was excluded from analysis and the median of the remaining episode was included for further statistical analysis. The head orientation for the fifth stepping stone was regarded as the baseline, which was subtracted from the other headset orientations to enable a fair comparison between HoloLens 1 and 2 in case of variations over experimental conditions in the positioning of the AR display on the head relative to the eyes. The resultant headset orientations were subjected to a 2×2×4 (Type of Object × Type of HoloLens × Stone [1 to 4]) repeated-measures ANOVA. The assumption of sphericity was verified according to Girden [26]. If the Greenhouse-Geisser’s epsilon exceeded 0.750, the Huynh-Feldt correction was used. Otherwise, the Greenhouse-Geisser correction was applied.

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Fig 3. Representation of head-orientation data for Experiments 1 and 2.

Looking from a stand-still position at real and holographic objects at various, nearby and far, distances (A, Experiment 1; stone numbers increase with distance) and negotiating a continuous sequence of stepping targets (B, Experiment 2, continuous target-stepping task) as well as a single 2D stepping target (C, Experiment 2, 2D target-stepping task). Higher values represent a more downward head orientation. Head orientation was derived from the AR-headset orientation data, normalized to the baseline head orientation.

https://doi.org/10.1371/journal.pone.0311804.g003

For Experiment 2, baseline head orientation was again subtracted from the head-orientation data for a fair comparison over experimental conditions. Head-orientation data were then expressed as a function of distance along the walkway to enable comparing trials of different durations within and between participants. A trial was excluded in case of data irregularities (e.g., due to loss of spatial tracking for 2 out of 768 trials; there were always at least two trials available per condition). The following task-specific outcome parameters were derived, from which the median over repetitions was taken for further statistical analyses:

Continuous target-stepping task:

The height of the characteristic initial peak, indicative of the maximal initial downward orientation of the head to get the stepping stones in view at the start of the trial directly after fixating at the cross at eye level (Fig 3B).
The median head orientation between 2.0 and 4.0 meters, representing the constant downward orientation required for performing the continuous target-stepping task (Fig 3B).
The median gait speed (m/s) between 2.0 and 4.0 meters, calculated from the time required to cover this 2-meter distance.

Incidental 2D target-stepping and 3D obstacle-crossing tasks

The intercept and slope of the linear fit between the position and orientation of the headset between 1.0 and 3.0 meters along the walkway (Fig 3C), the region where we assumed participants oriented themselves towards the 2D stepping target and 3D obstacle, representing initial head orientation and the rate of change in head orientation, respectively.
The median gait speed (m/s) for approaching the 2D stepping target or 3D obstacle between 1.0 and 3.0 meters, calculated from the time required to cover this 2-meter distance

Outcome parameters were again subjected to a 2×2 (Type of Object × Type of HoloLens) repeated-measures ANOVA.

Effect sizes are reported as ƞ_p²-values. Significant interactions were further explored with paired-samples t-tests, focusing -considering the hypotheses- on differences between HoloLenses for both real-world and holographic objects. All data underlying the statistical analyses are available in S1 Table.

Results

Experiment 1: Smaller downward orientation for seeing nearby holographic objects with HoloLens 2 than with HoloLens 1

As can be appreciated from Fig 3A, the head orientation varied with object distance in all four conditions, with greater downward orientations for nearby stepping stones, supported by the main effect of Stone (F(1.55, 23.20) = 1328.67, p<0.001, ƞ_p² = 0.989), with significant orientation differences between all four stones (p<0.001). We expected a greater downward head orientation for looking at nearby holographic compared to real-world objects, but less so for HoloLens 2 than HoloLens 1 given its larger AR-FOV size. This was indeed the case, as supported by the three-way interaction (F(2.07, 30.97) = 14.59, p = 0.045, ƞ_p² = 0.191). Post-hoc paired-samples t-tests showed significant head-orientation differences between real-world and holographic objects for most stepping stones, for both HoloLenses alike (Fig 4), notably in magnitude for the two nearest objects. Head orientations for viewing any of the real-world stepping stones did not differ between HoloLenses, while for holographic stepping stones -as expected- a significantly greater downward orientation was required for HoloLens 1 than HoloLens 2, but only for the nearest object (stone 1: t(15) = 3.377, p = 0.004). AR-FOV size thus mainly affected the orientation for looking at nearby AR objects.

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Fig 4. Data visualization of Experiment 1.

* denotes a significant difference of p<0.05 between conditions. ** denotes a significant difference of p<0.001 between conditions.

https://doi.org/10.1371/journal.pone.0311804.g004

Experiment 2

Smaller initial and constant downward orientations for negotiating a sequence of stepping stones with HoloLens 2 than with HoloLens 1.

Head-orientation data showed statistically the same pattern of results over conditions for the continuous target-stepping task. For both parameters (i.e., initial maximal peak and constant orientation), a Type of Object × Type of HoloLens interaction was found (F(1,15) = 11.33, p = 0.004, ƞ_p² = 0.430 and F(1,15) = 4.89, p = 0.043, ƞ_p² = 0.246, respectively) on top of main effects for Type of Object (greater downward orientation for holographic than for real-world objects; F(1,15) = 66.86, p<0.001, ƞ_p² = 0.817 and F(1,15) = 84.83, p<0.001, ƞ_p² = 0.850, respectively) and Type of HoloLens (greater downward orientation for HoloLens 1 than HoloLens 2 for the initial peak only; F(1,15) = 24.09, p<0.001, ƞ_p² = 0.616 and F(1,15) = 0.28, p = 0.604, ƞ_p² = 0.018, respectively). In line with the results for nearby objects of Experiment 1, and as expected given the larger AR-FOV for HoloLens 2 than for HoloLens 1, paired-samples t-tests revealed that the initial maximal downward orientation (Fig 5A) as well as the constant downward orientation (Fig 5D) for holographic stepping targets was significantly smaller for HoloLens 2 than for HoloLens 1 (t(15) = 9.10, p<0.001 and t(15) = 3.01, p = 0.009, respectively), in the absence of a difference between HoloLenses for real-world stepping targets (t(15) = 0.63, p = 0.535 and t(15) = -1.00, p = 0.332, respectively).

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Fig 5. Data visualization of Experiment 2.

Continuous target-stepping task (A, D, and G), 2D stepping-target task (B, E, and H) and 3D obstacle-crossing task (C, F, and I). * denotes a significant main effect of p<0.05 between conditions. ** denotes a significant main effect of p<0.001 between conditions.

https://doi.org/10.1371/journal.pone.0311804.g005

Smaller initial orientation and rate of change in downward orientation for negotiating a single 2D stepping target or 3D obstacle with HoloLens 2 than with HoloLens 1.

In line with our expectations, we found -by and large- a smaller initial orientation (i.e., intercept) and rate of change in downward orientation towards the object (i.e., slope of the linear fit) for HoloLens 2 than for HoloLens 1 when negotiating a 2D stepping target and a 3D obstacle. That is, for the initial orientations (Fig 5B and 5C), we found a main effect of Type of Object for both the 2D target-stepping task (F(1,15) = 49.50, p<0.001, ƞ_p² = 0.767) and the 3D obstacle-crossing task (F(1,15) = 23.56, p<0.001, ƞ_p² = 0.611), indicating a smaller initial orientation for interacting with real-world than with holographic objects, aligning with the perception that the AR-FOV is smaller than one’s FOV. The main effect of Type of HoloLens was not significant for both tasks (2D stepping target: F(1,15) = 0.76, p = 0.398, ƞ_p² = 0.048; 3D obstacle crossing: F(1,15) = 2.64, p = 0.125, ƞ_p² = 0.149), while the Type of Object × Type of HoloLens interaction was borderline significant for 2D target-stepping (F(1,15) = 4.34, p = 0.055, ƞ_p² = 0.225; Fig 5B) and 3D obstacle-crossing (F(1,15) = 4.62, p = 0.048, ƞ_p² = 0.235; Fig 4C) tasks, indicating that, at least for holographic 3D obstacle crossing, the initial orientation was significantly smaller for HoloLens 2 than for HoloLens 1 (t(15) = 2.23, p = 0.041) in the absence of HoloLens differences for real-world 3D obstacles (t(15) = -0.57, p = 0.578), a finding consistent with our expectations regarding the difference in AR-FOV size between HoloLenses.

For the rate of change in downward orientation (Fig 5E and 5F), only a main effect of Type of HoloLens was observed for the 2D target-stepping task (F(1,15) = 7.39, p = 0.016, ƞ_p² = 0.330), in the absence of main and interaction effects with the factor Type of Object (F(1, 15) = 0.55, p = 0.469, ƞ_p² = 0.035 and F(1,15) = 2.10, p = 0.168, ƞ_p² = 0.123, respectively; Fig 5E) and any effect for the 3D obstacle-crossing task (Type of HoloLens: F(1,15) = 0.19, p = 0.669, ƞ_p² = 0.013; Type of Object: F(1,15) = 0.29, p = 0.596, ƞ_p² = 0.019; Interaction: F(1,15) = 1.17, p = 0.296, ƞ_p² = 0.072; Fig 5F). This implied, consistent with our expectations regarding the difference in AR-FOV size between HoloLenses, a significantly smaller rate of change in the downward orientation when approaching the holographic 2D stepping target for HoloLens 2 than for HoloLens 1.

Gait speeds are slightly slower for negotiating holographic than real-world objects.

As expected, participants walked slower when negotiating holographic objects compared to real-world objects, as supported by a significant main effect of Type of Object for the continuous target-stepping and the 3D obstacle tasks (F(1,15) = 12.50, p = 0.003, ƞ_p² = 0.455 and F(1,15) = 11.34, p = 0.004, ƞ_p² = 0.431, respectively; Fig 5G and 5I) and a borderline significant difference for the 2D stepping-target task (F(1,15) = 4.48, p = 0.051, ƞ_p² = 0.230; Fig 5H). For all tasks, neither the main effect of Type of HoloLens (Continuous target stepping: F(1,15) = 1.18, p = 0.295, ƞ_p² = 0.073; 2D stepping target: F(1,15) = 1.91, p = 0.187, ƞ_p² = 0.113; 3D obstacle: F(1,15) = 0.26, p = 0.621, ƞ_p² = 0.017) nor the Type of Object × Type of HoloLens interaction (Continuous target stepping: F(1,15) = 0.18, p = 0.674, ƞ_p² = 0.012; 2D stepping target: F(1,15) = 1.75, p = 0.205, ƞ_p² = 0.105; 3D obstacle: F(1,15) = 2.57, p = 0.130, ƞ_p² = 0.146) were significant, indicating that AR-FOV size had no demonstrable effect on gait speed.

Discussion

The primary objective of this study was to evaluate the effect of AR-FOV size on head orientations for viewing and interacting with floor-based real-world and holographic objects. First, we observed, consistent with our expectations, a smaller downward head orientation when looking at the nearest holographic stone with HoloLens 2 compared to HoloLens 1 (Experiment 1) in the absence of HoloLens differences when looking at the other three, more distant holographic stones, probably because they become smaller and more centered in one’s AR-FOV. In Experiment 2, we found that a greater downward head orientation was required when interacting with holographic than real-world 2D or 3D objects during walking, but significantly less so for HoloLens 2 than HoloLens 1 because of its larger AR-FOV size. Results of 2D target-stepping and 3D obstacle-crossing tasks do not match completely: in the 3D holographic obstacle-crossing task the initial downward orientation was significantly smaller for HoloLens 2 than for HoloLens 1, whereas in the 2D target-stepping task the rate of change in downward orientation was significantly smaller for HoloLens 2 than for HoloLens 1. Although in both tasks the net result was a smaller downward head orientation with larger AR-FOV size, the discrepancy over tasks in the effects of the complementary outcome parameters (i.e., smaller initial orientation vs. smaller rate of change in downward orientation) probably hints at different gazing strategies when approaching 2D vs. 3D sized objects and/or different gaze-fixation patterns when negotiating targets vs. obstacles [27–29].

For the secondary objective, we evaluated the effect of different AR-FOV sizes on gait speeds when negotiating holographic and real-world objects. Overall, participants walked slightly slower when interacting with holographic objects compared to real-world objects (e.g., a difference of 8.8 cm/s for the continuous target-stepping task representing a 0.14 seconds difference over the calculated 2.0 meters) (Fig 5G–5I). This finding is in line with previous research [3, 23] where participants were suggested to walk more cautiously when approaching holographic objects. No differences were observed between HoloLens 1 and 2, suggesting that the gait speed was not influenced by the AR-FOV size.

This study was conducted in the broader context of AR applications for gait assistance utilizing action-relevant floor-based 2D and 3D objects, like AR cueing for people with neurological conditions like PD [1, 2]. In that regard, two observations are relevant that warrant further investigation, as discussed next.

First, AR cueing may be related to the ecological-psychology concept of affordances introduced by J.J. Gibson to refer to the action possibilities in the environment of an agent [30]. In the context of AR cueing, this environment is partly mediated by AR objects yielding functional possibilities for action: 2D AR stepping targets afford to step onto, while a 3D AR obstacle affords to step over. Such affordances exist by the detection of meaningful ecological information from mediated environments. On the one hand, the limited AR display may therefore have limited the availability of meaningful information from AR cues, yielding suboptimal action opportunities, and hence potentially reducing the efficacy of AR cueing as recently discussed [1, 2, 21]. Such reasoning matches with direct empirical proof that a smaller AR-FOV size resulted in an underestimation of gap-stepping affordances [20]. On the other hand, humans exploit a range of behaviors to extend the eye-brain connection by including movements of the eyes, head, and body for revealing and picking up ecological information in the optic array [31]. As E.J. Gibson [32] aptly put it: “We don’t simply see, we look. The visual system is a motor system as well as a sensory one. When we seek information in an optic array, the head turns, the eyes tum to fixate, the lens accommodates to focus, and spectacles may be applied and even adjusted by head position for far or near looking.” This ecological-psychology notion of perceptual systems may help in interpreting the effects of AR-FOV size on head orientations. That is, downward head orientations are required and appropriate for the pickup of ecological information from (mediated) environments to afford proper foot placement: participants oriented their head more downwards when interacting with nearby objects, for real-world and holographic objects alike, and appropriately changed their head orientation to pick up ecological information in mediated environments, scaled to AR-FOV size. It remains to be seen whether such changes in head orientations are sufficient for proper foot-placement (as afforded by AR stepping stones or the AR 2D stepping target) and obstacle-crossing (as afforded by the AR 3D obstacle) behaviors in mediated environments compared to gait modifications seen with real-world counterparts (but see [5]).

Second, this study included healthy middle-aged adults instead of people with neurological conditions like PD. This might be regarded as a limitation in the broader context of AR cueing because whereas healthy individuals are known to use a feedforward mechanism using exteroceptive information of the environment to plan proactive adjustments of gait [33], people with PD have a stronger dependence on visual information for making online corrections, often using conscious movement processing [34, 35]. Previous studies showed that visual cueing aids the pickup of task-relevant information (including the perception of affordances) in people with PD, improving safety of locomotion and foot-placement accuracy [36–38]. Together, this indicates that a sufficient AR-FOV size might be even more important for interacting with floor-based holographic objects for people with PD than for healthy individuals. Furthermore, a limited AR-FOV size could promote an even more stooped posture in people with PD, which is associated with poorer balance and an increased risk of falls, emphasizing the importance of a sufficient AR-FOV size even more [39, 40].

Another limitation in the broader context of AR cueing is that we only examined the effect of AR-FOV size on head orientations and performed gait speed, without examining possible effects on gait modulation in terms of step length, cadence and obstacle-crossing heights and lengths, which are relevant aspects for effective AR cueing. Future research with people with PD is warranted to investigate if an increased AR-FOV size improves the efficacy of AR cues for alleviating FOG and for assisting and modulating gait. Such studies may benefit from including or comparing HoloLens 2 with other AR devices with an even larger AR-FOV size, like Magic Leap 2 (45°×55° [41]) and the recently announced Meta Orion (with an AR-FOV expected to be even larger). Alternatively, one could consider including a video see-though device (e.g., Apple vision Pro) instead of only optical see-through devices as used in the current study, allowing for more fine grained and wider evaluations of the effect of AR-FOV size on head orientation and gait speed for interacting with nearby AR content. Video see-through devices, however, seem less suitable for assisting and modulating gait in health-related fields, mainly because of the risk of losing the vision of the real environment in case of system errors or an empty battery, which could lead to dangerous situations in daily life as wearers then find themselves in a pitch-black environment. Finally, studies may benefit from including eye-tracker data, present in state-of-the-art AR headsets, to confirm the above-mentioned different gaze strategies associated with negotiating targets vs. obstacles and/or 2D vs. 3D objects in real-world and AR environments.

To summarize, the downward head orientation was reduced for viewing and interacting with holographic objects along the line of sight with HoloLens 2 compared to HoloLens 1, particularly for objects nearby. Still, interacting with holographic objects required a somewhat greater downward head orientation compared to interacting with real-world objects, which may or may not affect affordance-based actions. Gait speed was not affected by AR-FOV size but was slightly but significantly slower for negotiating holographic objects than real-world objects. The ongoing technology development of AR devices will at least bring AR-FOV size closer to one’s FOV, from which AR applications for modulating and assisting gait in neurological conditions like PD will probably benefit.

Supporting information

S1 Table. Data file.

https://doi.org/10.1371/journal.pone.0311804.s001

(XLSX)

Acknowledgments

We would like to thank all participants for their voluntary participation.

References

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- View Article
- PubMed/NCBI
- Google Scholar
18. Snijders AH, Jeene P, Nijkrake MJ, Abdo WF, Bloem BR. Cueing for freezing of gait: A need for 3-Dimensional cues? The Neurologist. 2012;18(6):404–5. pmid:23114676
- View Article
- PubMed/NCBI
- Google Scholar
19. Heaney D. HoloLens 2’s field of view revealed [Internet]. UploadVR2021 [cited 2023 June 14]. Available from: https://www.uploadvr.com/hololens-2-field-of-view/.
- View Article
- Google Scholar
20. Gagnon HC, Zhao Y, Richardson M, Pointon GD, Stefanucci JK, Creem-Regehr SH, et al. Gap affordance judgments in mixed reality: Testing the role of display weight and field of view. Frontiers in Virtual Reality. 2021;2.
- View Article
- Google Scholar
21. Held JPO, Yu K, Pyles C, Veerbeek JM, Bork F, Heining S-M, et al. Augmented reality–based rehabilitation of gait impairments: Case report. JMIR Mhealth Uhealth. 2020;8(5):e17804. Epub 26.5.2020. pmid:32452815
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- View Article
- PubMed/NCBI
- Google Scholar
23. Binaee K, Diaz GJ. Assessment of an augmented reality apparatus for the study of visually guided walking and obstacle crossing. Behavior Research Methods. 2019;51(2):523–31. pmid:30132240
- View Article
- PubMed/NCBI
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25. Kalat JW. Biological psychology: Boston, MA, USA: Cengage; 2018.
26. Girden ER. ANOVA: Repeated measures. Thousand Oaks, CA, US: Sage Publications, Inc; 1992.
27. Patla AE, Vickers JN. Where and when do we look as we approach and step over an obstacle in the travel path? Neuroreport. 1997;8(17):3661–5. pmid:9427347
- View Article
- PubMed/NCBI
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28. Patla AE, Vickers JN. How far ahead do we look when required to step on specific locations in the travel path during locomotion? Experimental Brain Research. 2003;148(1):133–8. pmid:12478404
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- PubMed/NCBI
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29. Marigold DS, Patla AE. Gaze fixation patterns for negotiating complex ground terrain. Neuroscience. 2007;144(1):302–13. pmid:17055177
- View Article
- PubMed/NCBI
- Google Scholar
30. Gibson JJ. The ecological approach to visual perception. Boston, MA, US: Houghton, Mifflin and Company; 1979.
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- View Article
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- View Article
- Google Scholar
34. Alcock L, Galna B, Hausdorff JM, Lord S, Rochester L. Enhanced obstacle contrast to promote visual scanning in fallers with Parkinson’s disease: role of executive function. Neuroscience. 2020;436:82–92. Epub pmid:32222557.
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- PubMed/NCBI
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36. Vitório R, Lirani-Silva E, Pieruccini-Faria F, Moraes R, Gobbi LTB, Almeida QJ. Visual cues and gait improvement in Parkinson’s disease: Which piece of information is really important? Neuroscience. 2014;277:273–80. pmid:25065625
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- PubMed/NCBI
- Google Scholar
37. Hunt D, Stuart S, Nell J, Hausdorff JM, Galna B, Rochester L, et al. Do people with Parkinson’s disease look at task relevant stimuli when walking? An exploration of eye movements. Behavioural Brain Research. 2018;348:82–9. pmid:29559336
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- PubMed/NCBI
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- View Article
- PubMed/NCBI
- Google Scholar
40. Forsyth AL, Paul SS, Allen NE, Sherrington C, Fung VS, Canning CG. Flexed truncal posture in Parkinson disease: Measurement reliability and relationship with physical and cognitive impairments, mobility, and balance. J Neurol Phys Ther. 2017;41(2):107–13. pmid:28263252
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- PubMed/NCBI
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[ref1] 1. Geerse DJ, Coolen B, van Hilten JJ, Roerdink M. Holocue: A wearable holographic cueing application for alleviating freezing of gait in Parkinson’s disease. Frontiers in Neurology. 2022;12. pmid:35082741
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Janssen S, de Ruyter van Steveninck J, Salim HS, Bloem BR, Heida T, van Wezel RJA. The beneficial effects of conventional visual cues are retained when augmented reality glasses are worn. Parkinson’s Disease. 2020:4104712. pmid:32322385
View Article
PubMed/NCBI
Google Scholar

[6] View Article

[7] PubMed/NCBI

[8] Google Scholar

[ref3] 3. Coolen B, Beek PJ, Geerse DJ, Roerdink M. Avoiding 3D obstacles in mixed reality: does it differ from negotiating real obstacles? Sensors. 2020;20(4):1095. pmid:32079351
View Article
PubMed/NCBI
Google Scholar

[10] View Article

[11] PubMed/NCBI

[12] Google Scholar

[ref4] 4. Miyake T, Al-Sada M, Zhong T, Wang W, Sugano S, editors. Feasibility evaluation of mixed reality obstacles on treadmill using HoloLens to elicit real obstacle negotiation. 2021 IEEE/SICE International Symposium on System Integration (SII); 2021.

[ref5] 5. Hoogendoorn EM, Geerse DJ, van Dam AT, Stins JF, Roerdink M. Gait-modifying effects of augmented-reality cueing in people with Parkinson’s disease. Frontiers in Neurology. 2024;15. pmid:38654737
View Article
PubMed/NCBI
Google Scholar

[15] View Article

[16] PubMed/NCBI

[17] Google Scholar

[ref6] 6. Geerse DJ, Coolen B, Roerdink M. Quantifying spatiotemporal gait parameters with HoloLens in healthy adults and people with Parkinson’s disease: Test-retest reliability, concurrent validity, and face validity. Sensors. 2020;20(11):3216. pmid:32517076
View Article
PubMed/NCBI
Google Scholar

[19] View Article

[20] PubMed/NCBI

[21] Google Scholar

[ref7] 7. Hsieh K, Sun R, Sosnoff J. Usability of self-guided mixed reality fall risk assessment for older adults. Gerontechnology. 2020;19:1–7.
View Article
Google Scholar

[23] View Article

[24] Google Scholar

[ref8] 8. Miller Koop M, Rosenfeldt AB, Owen K, Penko AL, Streicher MC, Albright A, et al. The Microsoft HoloLens 2 provides accurate measures of gait, turning, and functional mobility in healthy adults. Sensors. 2022;22(5):2009. pmid:35271156
View Article
PubMed/NCBI
Google Scholar

[26] View Article

[27] PubMed/NCBI

[28] Google Scholar

[ref9] 9. Sun R, Aldunate RG, Sosnoff JJ. The validity of a mixed reality-based automated functional mobility assessment. Sensors. 2019;19(9):2183. pmid:31083514
View Article
PubMed/NCBI
Google Scholar

[30] View Article

[31] PubMed/NCBI

[32] Google Scholar

[ref10] 10. van Bergem JS, van Doorn PF, Hoogendoorn EM, Geerse DJ, Roerdink M. Gait and Balance Assessments with Augmented Reality Glasses in People with Parkinson’s Disease: Concurrent Validity and Test–Retest Reliability. Sensors. 2024;24(17):5485. pmid:39275397
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref11] 11. Alberts JL, Kaya RD, Scelina K, Scelina L, Zimmerman EM, Walter BL, et al. Digitizing a therapeutic: development of an augmented reality dual-task training platform for Parkinson’s disease. Sensors. 2022;22(22):8756. pmid:36433353
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref12] 12. Espay AJ, Baram Y, Dwivedi AK, Shukla R, Gartner M, Gaines L, et al. At-home training with closed-loop augmented-reality cueing device for improving gait in patients with Parkinson disease. Journal of rehabilitation research and development. 2010;47(6):573–81. pmid:20848370
View Article
PubMed/NCBI
Google Scholar

[42] View Article

[43] PubMed/NCBI

[44] Google Scholar

[ref13] 13. Ko LW, Stevenson C, Chang WC, Yu KH, Chi KC, Chen YJ, et al. Integrated gait triggered mixed reality and neurophysiological monitoring as a framework for next-generation ambulatory stroke rehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2021;29:2435–44. pmid:34748494
View Article
PubMed/NCBI
Google Scholar

[46] View Article

[47] PubMed/NCBI

[48] Google Scholar

[ref14] 14. Lee C-H, Kim Y, Lee B-H. Augmented reality-based postural control training improves gait function in patients with stroke: Randomized controlled trial. Hong Kong Physiotherapy Journal. 2014;32(2):51–7.
View Article
Google Scholar

[50] View Article

[51] Google Scholar

[ref15] 15. Alberts JL, Kaya RD, Penko AL, Streicher M, Zimmerman EM, Davidson S, et al. A randomized clinical trial to evaluate a digital therapeutic to enhance gait function in individuals with Parkinson’s disease. Neurorehabil Neural Repair. 2023;37(9):603–16. pmid:37465959
View Article
PubMed/NCBI
Google Scholar

[53] View Article

[54] PubMed/NCBI

[55] Google Scholar

[ref16] 16. Nieuwboer A, Kwakkel G, Rochester L, Jones D, van Wegen E, Willems AM, et al. Cueing training in the home improves gait-related mobility in Parkinson’s disease: the RESCUE trial. J Neurol Neurosurg Psychiatry. 2007;78(2):134–40. pmid:17229744
View Article
PubMed/NCBI
Google Scholar

[57] View Article

[58] PubMed/NCBI

[59] Google Scholar

[ref17] 17. Janssen S, Bolte B, Nonnekes J, Bittner M, Bloem BR, Heida T, et al. Usability of three-dimensional augmented visual cues delivered by smart glasses on (freezing of) gait in Parkinson’s disease. Frontiers in Neurology. 2017;8. pmid:28659862
View Article
PubMed/NCBI
Google Scholar

[61] View Article

[62] PubMed/NCBI

[63] Google Scholar

[ref18] 18. Snijders AH, Jeene P, Nijkrake MJ, Abdo WF, Bloem BR. Cueing for freezing of gait: A need for 3-Dimensional cues? The Neurologist. 2012;18(6):404–5. pmid:23114676
View Article
PubMed/NCBI
Google Scholar

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[66] PubMed/NCBI

[67] Google Scholar

[ref19] 19. Heaney D. HoloLens 2’s field of view revealed [Internet]. UploadVR2021 [cited 2023 June 14]. Available from: https://www.uploadvr.com/hololens-2-field-of-view/.
View Article
Google Scholar

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[70] Google Scholar

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View Article
Google Scholar

[72] View Article

[73] Google Scholar

[ref21] 21. Held JPO, Yu K, Pyles C, Veerbeek JM, Bork F, Heining S-M, et al. Augmented reality–based rehabilitation of gait impairments: Case report. JMIR Mhealth Uhealth. 2020;8(5):e17804. Epub 26.5.2020. pmid:32452815
View Article
PubMed/NCBI
Google Scholar

[75] View Article

[76] PubMed/NCBI

[77] Google Scholar

[ref22] 22. Baugher B, Szewczyk N, Liao J. Augmented reality cueing for freezing of gait: Reviewing an emerging therapy. Parkinsonism and Related Disorders. 2023:105834. pmid:37699779
View Article
PubMed/NCBI
Google Scholar

[79] View Article

[80] PubMed/NCBI

[81] Google Scholar

[ref23] 23. Binaee K, Diaz GJ. Assessment of an augmented reality apparatus for the study of visually guided walking and obstacle crossing. Behavior Research Methods. 2019;51(2):523–31. pmid:30132240
View Article
PubMed/NCBI
Google Scholar

[83] View Article

[84] PubMed/NCBI

[85] Google Scholar

[ref24] 24. Microsoft. Improve visual quality and comfort [Internet]. 2022 [cited 2023 June 4]. Available from: https://learn.microsoft.com/en-us/hololens/hololens-calibration#calibrating-your-hololens-1st-gen.

[ref25] 25. Kalat JW. Biological psychology: Boston, MA, USA: Cengage; 2018.

[ref26] 26. Girden ER. ANOVA: Repeated measures. Thousand Oaks, CA, US: Sage Publications, Inc; 1992.

[ref27] 27. Patla AE, Vickers JN. Where and when do we look as we approach and step over an obstacle in the travel path? Neuroreport. 1997;8(17):3661–5. pmid:9427347
View Article
PubMed/NCBI
Google Scholar

[90] View Article

[91] PubMed/NCBI

[92] Google Scholar

[ref28] 28. Patla AE, Vickers JN. How far ahead do we look when required to step on specific locations in the travel path during locomotion? Experimental Brain Research. 2003;148(1):133–8. pmid:12478404
View Article
PubMed/NCBI
Google Scholar

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[95] PubMed/NCBI

[96] Google Scholar

[ref29] 29. Marigold DS, Patla AE. Gaze fixation patterns for negotiating complex ground terrain. Neuroscience. 2007;144(1):302–13. pmid:17055177
View Article
PubMed/NCBI
Google Scholar

[98] View Article

[99] PubMed/NCBI

[100] Google Scholar

[ref30] 30. Gibson JJ. The ecological approach to visual perception. Boston, MA, US: Houghton, Mifflin and Company; 1979.

[ref31] 31. Lobo L, Heras-Escribano M, Travieso D. The history and philosophy of ecological psychology. Frontiers in Psychology. 2018;9. pmid:30555368
View Article
PubMed/NCBI
Google Scholar

[103] View Article

[104] PubMed/NCBI

[105] Google Scholar

[ref32] 32. Gibson EJ. Exploratory behavior in the development of perceiving, acting, and the acquiring of knowledge. Annual Review of Psychology. 1988;39(1):1–42.
View Article
Google Scholar

[107] View Article

[108] Google Scholar

[ref33] 33. Patla AE. Understanding the roles of vision in the control of human locomotion. Gait & Posture. 1997;5(1):54–69.
View Article
Google Scholar

[110] View Article

[111] Google Scholar

[ref34] 34. Alcock L, Galna B, Hausdorff JM, Lord S, Rochester L. Enhanced obstacle contrast to promote visual scanning in fallers with Parkinson’s disease: role of executive function. Neuroscience. 2020;436:82–92. Epub pmid:32222557.
View Article
PubMed/NCBI
Google Scholar

[113] View Article

[114] PubMed/NCBI

[115] Google Scholar

[ref35] 35. Hardeman LES, Kal EC, Young WR, J, Ellmers TJ. Visuomotor control of walking in Parkinson’s disease: Exploring possible links between conscious movement processing and freezing of gait. Behavioural Brain Research. 2020;395:112837. pmid:32739286
View Article
PubMed/NCBI
Google Scholar

[117] View Article

[118] PubMed/NCBI

[119] Google Scholar

[ref36] 36. Vitório R, Lirani-Silva E, Pieruccini-Faria F, Moraes R, Gobbi LTB, Almeida QJ. Visual cues and gait improvement in Parkinson’s disease: Which piece of information is really important? Neuroscience. 2014;277:273–80. pmid:25065625
View Article
PubMed/NCBI
Google Scholar

[121] View Article

[122] PubMed/NCBI

[123] Google Scholar

[ref37] 37. Hunt D, Stuart S, Nell J, Hausdorff JM, Galna B, Rochester L, et al. Do people with Parkinson’s disease look at task relevant stimuli when walking? An exploration of eye movements. Behavioural Brain Research. 2018;348:82–9. pmid:29559336
View Article
PubMed/NCBI
Google Scholar

[125] View Article

[126] PubMed/NCBI

[127] Google Scholar

[ref38] 38. Graham L, Armitage J, Vitorio R, Das J, Barry G, Godfrey A, et al. Visual Exploration While Walking With and Without Visual Cues in Parkinson’s Disease: Freezer Versus Non-Freezer. Neurorehabilitation and Neural Repair. 2023;37(10):734–43. pmid:37772512
View Article
PubMed/NCBI
Google Scholar

[129] View Article

[130] PubMed/NCBI

[131] Google Scholar

[ref39] 39. Latt MD, Lord SR, Morris JG, Fung VS. Clinical and physiological assessments for elucidating falls risk in Parkinson’s disease. Mov Disord. 2009;24(9):1280–9. pmid:19425059
View Article
PubMed/NCBI
Google Scholar

[133] View Article

[134] PubMed/NCBI

[135] Google Scholar

[ref40] 40. Forsyth AL, Paul SS, Allen NE, Sherrington C, Fung VS, Canning CG. Flexed truncal posture in Parkinson disease: Measurement reliability and relationship with physical and cognitive impairments, mobility, and balance. J Neurol Phys Ther. 2017;41(2):107–13. pmid:28263252
View Article
PubMed/NCBI
Google Scholar

[137] View Article

[138] PubMed/NCBI

[139] Google Scholar

[ref41] 41. Magic Leap. Field of View (FOV) | MagicLeap Developer Documentation [Internet]. 2023. Available from: https://developer-docs.magicleap.cloud/docs/guides/device/fov#:~:text=Display%20FOV%E2%80%8B,Headset%20Fit%20for%20more%20information.

Figures

Abstract

Introduction

Methods

Participants

Experimental design and setup

Procedure

Experiment 1: Head orientations for looking at real-world and holographic objects.

Experiment 2: Head orientation and gait speed for interacting with real-world and holographic 2D and 3D objects during walking.

Data and statistical analysis

Results

Experiment 1: Smaller downward orientation for seeing nearby holographic objects with HoloLens 2 than with HoloLens 1

Experiment 2

Smaller initial and constant downward orientations for negotiating a sequence of stepping stones with HoloLens 2 than with HoloLens 1.

Smaller initial orientation and rate of change in downward orientation for negotiating a single 2D stepping target or 3D obstacle with HoloLens 2 than with HoloLens 1.

Gait speeds are slightly slower for negotiating holographic than real-world objects.

Discussion

Supporting information

S1 Table. Data file.

Acknowledgments

References