Auxiliary Means to Improve Motion Guidance Memorability in Extended Reality

Gebhardt, Patrick; Weiß, Maximilian; Huszár, Pascal; Yu, Xingyao; Achberger, Alexander; Zhang, Xiaobing; Sedlmair, Michael

doi:10.1109/vrw58643.2023.00187

Cited by 1 publication

(4 citation statements)

References 2 publications

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“…ConImp: Implicit representation of desired motions requiring interpretation, which updates throughout the motion when trainees satisfy the postural accuracy. Commonly used with motion trajectories, where concrete postures are interpreted as the boundaries between completed and uncompleted parts [17,20,52,53,59].…”

Section: Continuousmentioning

confidence: 99%

“…This allows trainees to promptly identify any errors in their performance and make timely corrections, thereby creating a rapid learning feedback loop. Examples include showing mismatches in postures [55] and the immediate highlight of movement errors [20].…”

Section: When: Temporalitymentioning

confidence: 99%

“…Color can not only serve as an intuitive indicator of movement accuracy (e.g., green denoting correctness and red denoting errors [48,53]), but also enable the representation of the extent of deviations by interpolating color hues. For instance, a higher intensity of red signifies a higher magnitude of movement error [20].…”

Section: How: Presentationmentioning

confidence: 99%

“…For instance, the length of the connecting line between body joints of the trainee and feedforward directly visualizes the deviation distance [59]. Building upon this, Gebhardt et al [20] replaced this line with a pair of opposing cones, encoding both their heights and base widths in terms of deviation distance between body joints, and eventually presented the movement error by the volume of the cones.…”

Section: How: Presentationmentioning

confidence: 99%

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

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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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