AirRes Mask: A Precise and Robust Virtual Reality Breathing Interface Utilizing Breathing Resistance as Output Modality

Honorable Mention
Full-Body Interaction & Embodied InputImmersion & Presence ResearchBiosensors & Physiological MonitoringUI/UX DesignersHCI Researchers

Title of the Paper

AirRes Mask: A Precise and Robust Virtual Reality Breathing Interface Utilizing Breathing Resistance as Output Modality

Paper Information

  • Subject Area: Human-Computer Interaction Technology, Virtual Reality (VR) Interaction, and Multisensory Stimulation Design
  • Keywords: Virtual Reality, Breathing Interface, Breathing Resistance, Natural Interaction, Virtual Avatar, Environmental Simulation

Research Background and Problem

  • Problems and Challenges:

    • In recent years, breathing has been explored as a novel interaction modality in virtual reality (VR). However, traditional breathing sensing devices, such as respiratory belts, often limit user experience due to motion artifacts.
    • Breathing resistance as a system output modality has not been fully studied, and its ability to express environmental conditions or virtual avatar states remains unclear.
    • Existing devices face significant room for improvement in measurement accuracy, real-time feedback, and user freedom of movement.
  • Significance of the Research:

    • Enhancing multisensory stimulation and interactivity in VR is critical for improving immersion and the user's sense of presence.
    • The introduction of breathing resistance could further enhance the realism of target scenarios and user engagement, which is particularly significant for applications such as training simulations and psychological therapy.
  • Motivation and Related Work:

    • Breathing as an interaction modality has been applied in mindfulness training, therapeutic contexts, and gaming scenarios. However, existing technical solutions (e.g., respiratory belts, head-mounted airflow sensors) still suffer from measurement errors, latency, and movement restrictions.
    • This paper proposes a precise and robust solution to address these issues, employing real-time adjustable breathing resistance to explore the potential of breathing as an output modality.

Solution

  • Methods and Solutions:

    • Developed a head-mounted breathing interface device—AirRes Mask—to accurately capture user breathing and provide application-controlled breathing resistance as feedback.
    • Implemented a "breathing engine" that converts the user's inhalation and exhalation forces into interactive forces within the virtual environment in real time.
  • Innovations:

    • Provided a high-precision, real-time measurement method for inhalation and exhalation, avoiding motion artifacts associated with traditional respiratory belts.
    • Innovatively utilized breathing resistance as a new sensory feedback modality, enabling VR to convey virtual environmental states and virtual avatar conditions through such physical feedback.
    • Allowed users to dynamically interact with VR environments using natural breathing behaviors without movement restrictions.
  • Implementation Steps and Key Technologies:

    • Device Design: Employed precision airflow sensors (Sensirion SFM3300) and fast servo motors to support real-time adjustment of breathing resistance.
    • Breathing Engine: Simulated breathing forces and interactive effects in virtual environments based on the drag equation of airflow.
    • System Safety and Hygiene Design: Prevented complete airflow blockage, supported modular cleaning of hardware, and ensured physical separation between electronic components and airflow paths.

Research Outcomes

  • Specific Results:

    • Developed the AirRes Mask and its accompanying breathing engine, capable of accurately capturing user breathing behaviors in VR.
    • Demonstrated that breathing resistance feedback effectively simulates environmental conditions (e.g., smoke, high temperatures) or virtual avatar states (e.g., low stamina) in virtual scenarios.
    • User studies indicated that AirRes Mask performed well in task completion rates, user experience, and enhancing immersion.
  • Comparative Advantages:

    • Compared to traditional devices (e.g., respiratory belts or game controllers simulating breathing), AirRes Mask showed significant improvements in precision, response time, and freedom of movement.
    • Breathing resistance as a new output modality enhanced users' sense of identification with virtual avatars and their sense of presence in virtual environments.
  • Experiments and Evaluation Results:

    • User studies conducted in "escape room" and "firefighter obstacle course" scenarios showed that AirRes Mask achieved higher immersion and multisensory engagement scores.
    • Users generally reported being able to perceive different levels of pressure adjustments in breathing resistance, which enhanced the realism of the scenario experience.
  • Limitations and Future Directions:

    • Limitations:
      • Noise from the servo motor during breathing resistance adjustments affected the sense of immersion in scenarios.
      • The hardware's weight posed some comfort issues.
      • In certain cases, the feedback from AirRes Mask did not fully align with participants' real-world expectations (e.g., coughing induced by smoke).
    • Future Directions:
      • Optimize hardware design (e.g., reduce weight, lower noise levels).
      • Enhance the modeling accuracy of breathing tasks, supporting differentiation between nasal and oral breathing.
      • Develop better integration of virtual avatar and environmental feedback mechanisms to provide more extensible application scenarios for training simulations, psychological therapy, and game development.

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https://hci.top/en/papers/chi/68729/2022

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DOI: https://dl.acm.org/doi/abs/10.1145/3491102.3502090
At a Glance

Paper Snapshot

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Source
CHI
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Year
2022
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Award
Honorable Mention
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Authors
8 authors
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Subtopics
Full-Body Interaction & Embodied Input, Immersion & Presence Research, Biosensors & Physiological Monitoring
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Professions
UI/UX Designers, HCI Researchers
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Full text indexed
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