Movement Guidance using a Mixed Reality Mirror

Zhou, Qiushi; Irlitti, Andrew; Yu, Difeng; Gonçalves, Jorge; Velloso, Eduardo

doi:10.1145/3532106.3533466

Cited by 16 publications

(3 citation statements)

References 47 publications

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“…Start set B contains prominent publications (over 100 citations on Google Scholar) that fit our scope: Just Follow Me [58], ShadowGuides [18], LightGuide [51], YouMove [1] and Physio@Home [53]. Start set C contains publications within the past 5 years on XR-based motion guidance across a broad research spectrum, including: Kodama et al [32] on training using virtual co-embodiment, Zhou et al [61] on motion guidance with an MR mirror, Lilija et al [39] on correction on virtual hand avatar movements, Yu et al [59] on the influence of perspective in motion guidance, and Dürr et al [14] on the virtual appearance of feedforward.…”

Section: Methodology Of Literature Reviewmentioning

confidence: 99%

“…Feedforward can be overlaid on a reflection of the trainee's own body viewed on a (virtual) mirror. Depending on the technological setup, the appearance of such reflections may be consistent with their real bodies (screen-based [53] or MR mirror [61]), or an avatar [55]. The mirror perspective naturally allows the trainee to see their entire body and the feedforward all at once.…”

Section: Viewing Perspectivementioning

confidence: 99%

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Design Space of Visual Feedforward And Corrective Feedback in XR-Based Motion Guidance Systems

Yu,

Lee,

Sedlmair

2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Figure 1: Schematic representations of motion feedforward. The leftmost column shows the complete motion sequence and its critical postures at four critical moments (Start, Point1, Point2, and End). The remaining columns show how the feedforward of this motion can be represented using different configurations of level of indirection (explicit, implicit and abstract) and interactive update strategy (discrete, continuous and autonomous). The visualizations in blue represent the feedforward; while the the black glyphs show the trainee's four moments during training from top to bottom (Start, reach Point 1, between Point 1 and Point 2, and between Point 2 and End); the green parts visualize the completed parts of a motion when using Implicit guidance (column 4 and 5). Discrete guidance (column 2, 4 and 6) presents cues for the next critical posture, which updates only when that posture is satisfied. Continuous guidance (column 3, 5 and 7) presents cues for the next frame in the motion sequence at all times. Autonomous guidance is not shown as it operates independently of the trainee's actions.

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Section: Methodology Of Literature Reviewmentioning

confidence: 99%

Section: Viewing Perspectivementioning

confidence: 99%

Design Space of Visual Feedforward And Corrective Feedback in XR-Based Motion Guidance Systems

Yu,

Lee,

Sedlmair

2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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“…Training and support for motion-based tasks can be done using Augmented Reality (AR) and Virtual Reality (VR) [5,6,23,24]. However, to enable workers to achieve the required precision in movement and timing, the effect of visual guidance on continuous movement needs to be carefully explored.…”

Section: Introductionmentioning

confidence: 99%

AR Guidance Design for Line Tracing Speed Control

Ceyssens,

van Deurzen,

Ruiz

et al. 2023

2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)

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Offistretch: camera-based real-time feedback for daily stretching exercises

Adolf,

Kán,

Feuchtner

et al. 2024

Vis Comput

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In this paper, we present OffiStretch, a camera-based system for optimal stretching guidance at home or in the workplace. It consists of a vision-based method for real-time assessment of the user’s body pose to provide visual feedback as interactive guidance during stretching exercises. Our method compares the users’ actual pose with a pre-trained target pose to assess the quality of stretching for a number of different exercises. We utilize angular and spatial pose features to perform this comparison for each individual exercise. The result of this pose assessment is presented to the user as real-time visual feedback on an "augmented mirror" display. As our method relies simply on a single RGB camera, it can be easily utilized in everyday training scenarios. We validate our method in a user study, comparing users’ performance and motivation in stretching when receiving audio-visual guidance on a TV screen both with and without our live feedback. While participants performed equally well in both conditions, feedback boosted their motivation to perform the exercises, highlighting its potential for increasing users’ well-being. Moreover, our results suggest that participants preferred stretching exercises with our live feedback over the condition without the feedback. Finally, an expert evaluation with professional physiotherapists reveals that further work must target improvements of the feedback to ensure correct guidance during stretching.

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Movement Guidance using a Mixed Reality Mirror

Cited by 16 publications

References 47 publications

Design Space of Visual Feedforward And Corrective Feedback in XR-Based Motion Guidance Systems

Design Space of Visual Feedforward And Corrective Feedback in XR-Based Motion Guidance Systems

AR Guidance Design for Line Tracing Speed Control

Offistretch: camera-based real-time feedback for daily stretching exercises

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