Literature DB >> 32079351

Avoiding 3D Obstacles in Mixed Reality: Does It Differ from Negotiating Real Obstacles?

Bert Coolen1, Peter J Beek1, Daphne J Geerse1, Melvyn Roerdink1.   

Abstract

Mixed-reality technologies are evolving rapidly, allowing for gradually more realistic interaction with digital content while moving freely in real-world environments. In this study, we examined the suitability of the Microsoft HoloLens mixed-reality headset for creating locomotor interactions in real-world environments enriched with 3D holographic obstacles. In Experiment 1, we compared the obstacle-avoidance maneuvers of 12 participants stepping over either real or holographic obstacles of different heights and depths. Participants' avoidance maneuvers were recorded with three spatially and temporally integrated Kinect v2 sensors. Similar to real obstacles, holographic obstacles elicited obstacle-avoidance maneuvers that scaled with obstacle dimensions. However, with holographic obstacles, some participants showed dissimilar trail or lead foot obstacle-avoidance maneuvers compared to real obstacles: they either consistently failed to raise their trail foot or crossed the obstacle with extreme lead-foot margins. In Experiment 2, we examined the efficacy of mixed-reality video feedback in altering such dissimilar avoidance maneuvers. Participants quickly adjusted their trail-foot crossing height and gradually lowered extreme lead-foot crossing heights in the course of mixed-reality video feedback trials, and these improvements were largely retained in subsequent trials without feedback. Participant-specific differences in real and holographic obstacle avoidance notwithstanding, the present results suggest that 3D holographic obstacles supplemented with mixed-reality video feedback may be used for studying and perhaps also training 3D obstacle avoidance.

Entities:  

Keywords:  HoloLens; mixed-reality headset; mixed-reality video feedback; obstacle avoidance; walking adaptability

Year:  2020        PMID: 32079351     DOI: 10.3390/s20041095

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  3 in total

1.  A Wearable Mixed Reality Platform to Augment Overground Walking: A Feasibility Study.

Authors:  Emily Evans; Megan Dass; William M Muter; Christopher Tuthill; Andrew Q Tan; Randy D Trumbower
Journal:  Front Hum Neurosci       Date:  2022-06-09       Impact factor: 3.473

2.  C-Gait for Detecting Freezing of Gait in the Early to Middle Stages of Parkinson's Disease: A Model Prediction Study.

Authors:  Zi-Yan Chen; Hong-Jiao Yan; Lin Qi; Qiao-Xia Zhen; Cui Liu; Ping Wang; Yong-Hong Liu; Rui-Dan Wang; Yan-Jun Liu; Jin-Ping Fang; Yuan Su; Xiao-Yan Yan; Ai-Xian Liu; Jianing Xi; Boyan Fang
Journal:  Front Hum Neurosci       Date:  2021-03-22       Impact factor: 3.169

3.  Quantifying Spatiotemporal Gait Parameters with HoloLens in Healthy Adults and People with Parkinson's Disease: Test-Retest Reliability, Concurrent Validity, and Face Validity.

Authors:  Daphne J Geerse; Bert Coolen; Melvyn Roerdink
Journal:  Sensors (Basel)       Date:  2020-06-05       Impact factor: 3.576

  3 in total

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