Anqi Chen’s research while affiliated with Beihang University and other places

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Publications (3)


MEM-Box employs randomly generated virtual scenes that simulate everyday scenarios. We use devices in a to present virtual environments and collect HRV and GSR signals. Virtual scenes fall into two distinct thematic categories: b the living room theme and c the bedroom theme (one of its iterations). b illustrates the exploration mode designed to help users become familiar with interactions in VR. c Shows the working memory training and evaluation mode, wherein users are required to find and select objects in a specific sequence based on a list provided. Their performance will serve as the basis for the evaluation of their working memory. d the collected subjective scales and the physiological analysis
Schematic representation of the overall experiment procedure
Physical and cognitive workload participants experienced during the MEM-Box and the PC-based training
Comparison of sense of the presence participants experienced during the MEM-Box training and the PC-based training. *Indicates a significance level less than 0.05
Left: Stroop test result (reciprocal of the average reaction time for a correct answer) of participants before and after MEM-Box training. Right: variation of MEM-Box evaluation of participants before and after MEM-Box training

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Mem-Box: VR sandbox for adaptive working memory evaluation and training using physiological signals
  • Article
  • Publisher preview available

June 2024

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79 Reads

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1 Citation

The Visual Computer

Anqi Chen

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Ming Li

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Working memory is crucial for higher cognitive functions in humans and is a focus in cognitive rehabilitation. Compared to conventional working memory training methods, VR-based training provides a more immersive experience with realistic scenarios, offering enhanced transferability to daily life. However, existing VR-based training methods often focus on basic cognitive tasks, underutilize VR’s realism, and rely heavily on subjective assessment methods. In this paper, we introduce a VR Sandbox for working memory training and evaluation, MEM-Box, which simulates everyday life scenarios and routines and adaptively adjusts task difficulty based on user performance. We conducted a training experiment utilizing the MEM-Box and compared it with a control group undergoing PC-based training. The results of the Stroop test indicate that both groups demonstrated improvements in working memory abilities, with MEM-Box training showing greater efficacy. Physiological data confirmed the effectiveness of the MEM-Box, as we observed lower HRV and SDNN. Furthermore, the results of the frequency-domain analysis indicate higher sympathetic nervous system activity (LFpower and LF/HF) during MEM-Box training, which is related to the higher sense of presence in VR. These metrics pave the way for building adaptive VR systems based on physiological data.

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Citations (3)


... Additionally, users generally had lower average GSR values when interacting with Elder agents, consistent with the higher trust levels observed in the interaction effects. Previous research have similar findings, as lower GSR levels indicate reduced emotional responses and cognitive load [9,21,26]. ...

Reference:

Trust in Virtual Agents: Exploring the Role of Stylization and Voice
Mem-Box: VR sandbox for adaptive working memory evaluation and training using physiological signals

The Visual Computer

... Limitations included the need for hard-to-obtain DT parameters, custom adaptations for real-time robot data, and a lack of physical workstation feedback control. Li et al. [35] introduced an integrated AR framework that combined real-time multi-material simulation with efficient hand gesture interaction. They used an RGBD camera for 3D data acquisition, enabling real-time gestures in simulations and expanding AR applications. ...

Real-time Physics-based Interaction in Augmented Reality
  • Citing Conference Paper
  • March 2023

... The tuning of models and their parameters for better performance through AI iterations has been achieved, and therefore the authors wish to emphasize the importance of datasets rather than the models themselves. (5) 3D vertigo is an important flaw in the VR experience [25] that can reduce the sense of presence in the VR experience [95]. To best avoid the effect of 3D vertigo symptoms, we applied strategies to minimize the effects, such as selecting participants who self-reported "no" 3D vertigo for this study, and we did not find significant 3D vertigo symptoms for other participants during the experiment process. ...

Analysis of Emotional Tendency and Syntactic Properties of VR Game Reviews
  • Citing Conference Paper
  • March 2022