Designing a Multisensory VR Game Prototype for Older Adults - the Acceptability and Design Implications

VR Medical Training & RehabilitationFitness Tracking & Physical Activity MonitoringPhysical Therapists & Rehabilitation SpecialistsElderly Care Workers

Title of the Paper

Designing a Multisensory VR Game Prototype for Older Adults - the Acceptability and Design Implications

Paper Information

  • Research Area: Virtual Reality, Multisensory Interaction Design, Health Intervention Technologies
  • Keywords: VR games, older adults, acceptability, dynamic visual acuity (DVA), mental workload, motivation, physical ability, cognitive ability

Research Background and Problem

  • Issues and Challenges:
    Older adults commonly experience declines in visual functions (dynamic visual acuity), cognitive abilities (e.g., multitasking), and physical functions (e.g., balance). These declines significantly impact independence and quality of life. Existing designs often focus on single or dual channels (cognitive or physical functions), neglecting the potential of dynamic vision and its synergy with other abilities.

  • Significance of the Research:
    Dynamic visual acuity is closely related to the decline in cognitive and physical functions. Comprehensive design targeting this area can contribute to goals such as balance and healthy aging. Integrating multisensory channels (dynamic vision, cognition, and physical abilities) into digital health interventions may yield synergistic health benefits.

  • Motivation and Related Work:
    While many VR-based health intervention designs have explored cognitive and physical stimulation, no research has comprehensively integrated dynamic visual acuity. By combining dynamic vision training with cognitive and physical channels, this study aims to fill a critical gap in VR health interventions.

Proposed Solution

  • Proposed Method:
    The authors designed the first multisensory VR game prototype based on cognitive psychology theories, integrating the following elements:

    1. Cognitive channel: Based on multitasking and Go/No-Go tasks.
    2. Physical channel: Full-body movements, including limb exercises and balance training.
    3. Dynamic visual channel: Dynamic vision training through horizontal, vertical, and forward-backward eye movements.
  • Innovations:

    1. Proposed a method to integrate multisensory channels (dynamic vision, cognition, physical abilities) to synergistically enhance health and engagement for older users.
    2. Designed a VR game incorporating dynamic visual acuity tasks, addressing a gap in traditional health intervention designs that overlook dynamic vision decline.
    3. Provided empirical data comparing different age groups and task types to support the applicability of VR technology for older adults.
  • Implementation Steps and Key Technologies:

    1. System prototype design: Created a simple VR game, optimizing dynamic visual parameters to meet the needs of older adults.
    2. User testing: Conducted experiments to evaluate the game's acceptability, including dimensions such as cybersickness, mental workload, motivation, presence, and game experience.
    3. Experimental design: Used a crossover design comparing traditional PC tasks with VR tasks, covering multi-scenario experiments in seated and standing positions.

Research Outcomes

  • Specific Findings:

    1. Experimental results showed that older users accepted the multisensory VR game well, with no significant cybersickness issues, regardless of seated or standing positions.
    2. The VR game's mental workload did not exceed that of traditional PC tasks, while being more engaging and valuable.
    3. The game's design, integrating three channels, demonstrated synergistic benefits in full-body movement, cognitive training, and dynamic vision enhancement.
  • Advantages Compared to Existing Solutions:

    1. Improved comprehensive health intervention effects for older adults, particularly in dynamic visual acuity.
    2. Provided a deeper sensor fusion experience, enhancing presence and long-term user engagement.
    3. Offered both seated and standing modes, better accommodating older users with varying physical conditions.
  • Experiment and Evaluation Results:

    • Multidimensional measurements of user experience (e.g., NASA-TLX, IMI, PQ, PENS) indicated high motivation and active participation among older adults in the VR game.
    • User feedback suggested that the VR game was not only enjoyable but also incorporated elements of physical health.
    • Comparisons revealed a stronger preference for standing gameplay among older adults, who perceived it as offering greater freedom and physical benefits.
  • Limitations and Future Directions:

    • The current prototype lacks additional gamification elements, such as reward mechanisms and dynamic difficulty adjustments. Future plans include improving the system design to enhance long-term engagement.
    • Only short-term experience testing was conducted; further evaluation of long-term health intervention effects is needed, such as multi-month field experiments.
    • Exploration of the specific impact of dynamic visual parameters on cybersickness and applicability across broader age groups is necessary.

Design Insights

  • Develop dynamic visual task parameters optimized for older adults to enhance their visual information processing.
  • Game design should prioritize integration with physical movements and include posture flexibility to enable comprehensive physical training.
  • Incorporate real-time player position feedback to enhance older adults' sense of safety and enjoyment in the game.
  • Leverage the synergistic benefits of the three channels to alleviate cognitive resource strain caused by single-channel designs and enhance user perceptual experiences.

By integrating dynamic vision, cognitive, and physical abilities through a multisensory design, this study highlights the potential for comprehensive health interventions for older adults. It provides valuable references for future interactive health designs using VR technology for aging populations.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/chi/146682/2024

AdRecommended

Learn AI Coding at CodeNow

open_in_newOpen DOI Link
DOI: https://doi.org/10.1145/3613904.3642948
At a Glance

Paper Snapshot

fact_check
dataset
Source
CHI
calendar_month
Year
2024
emoji_events
Award
No award tagged
group
Authors
6 authors
sell
Subtopics
VR Medical Training & Rehabilitation, Fitness Tracking & Physical Activity Monitoring
work
Professions
Physical Therapists & Rehabilitation Specialists, Elderly Care Workers
article
Content Status
Full text indexed
hub
Related Papers
4 related papers