Collaboration and Assistive Technology: Facilitating Joint Awareness for Noise Sensitivity

Paper Title

Collaboration and Assistive Technology: Facilitating Joint Awareness for Noise Sensitivity

Publication Info

• Topic area: Assistive technology for noise sensitivity and collaborative care
• Keywords: Noise sensitivity, assistive technology, joint awareness, self-regulation, mobile applications, wearables, psychophysiological monitoring, collaborative care, sound awareness, data-driven reflection

Background and Problem

• Problem / challenge: Existing systems for people with noise sensitivity (PWNS) lack features to identify and monitor noise sensitivity experiences, limiting the ability of PWNS and their companions to understand and manage the condition collaboratively.
• Significance: Noise sensitivity affects 2–6% of the general population and up to 45% of autistic individuals, causing challenges in daily life, such as sensory overload and fatigue, which can impact education, work, and social interactions.
• Motivation and related work: Prior research has focused on individual self-regulation using wearables and mobile apps but has not adequately addressed collaborative care or joint awareness. Existing sound awareness systems primarily target the D/deaf and hard-of-hearing (DHH) community, leaving a gap in solutions for PWNS.

Solution

• Proposed approach: AudioBuddy, a mobile and smartwatch application, facilitates awareness of noise sensitivity experiences through data tracking, mood logging, coping strategies, and ally notifications.
• Novelty:
  1. Integration of self-awareness, others’ awareness, and joint awareness in a single system.
  2. Use of data-driven reflection to support understanding of environmental and psychophysiological impacts.
  3. Features for collaborative care, including ally notifications and shared activity reports.
  4. Customizable thresholds for noise and heart rate alerts tailored to individual needs.
• Procedure and key techniques:
  • AudioBuddy tracks environmental noise levels and heart rate via Apple Watch.
  • Users log moods and access coping strategies through the app.
  • Notifications alert users and companions when thresholds are exceeded.
  • Data visualizations and activity reports enable reflection and sharing with companions.

Results

• Concrete findings:
  • PWNS and companions reported increased awareness of environmental triggers and emotional states.
  • Mood logging and data reflection helped participants identify patterns and manage noise sensitivity.
  • Noise alerts validated PWNS experiences and fostered empathy among companions.
• Advantage over baselines: AudioBuddy uniquely combines individual self-regulation tools with features for collaborative care, addressing gaps in existing solutions for noise sensitivity.
• Experiments / evaluation:
  • Field deployment with 11 PWNS (ages 11–62) and 7 companions (ages 29–62) over two weeks.
  • Data collected through interviews, mood check-ins, and app usage logs.
  • Validated misophonia and hyperacusis scales used to assess participants’ noise sensitivity.
• Limitations and future work:
  • Current hardware cannot capture specific sound characteristics (e.g., pitch, rhythm).
  • Manual data sharing limits real-time joint awareness.
  • Notify Ally feature was underutilized due to environmental restrictions and social dynamics.
  • Future work should explore intelligent sound recognition, privacy-preserving data sharing, and extending joint awareness to secondary supporters.

Summary

This study introduces AudioBuddy, a mobile and wearable system designed to enhance self-awareness, others’ awareness, and joint awareness for people with noise sensitivity (PWNS) and their companions. Through a two-week deployment, participants reported improved understanding of environmental and emotional triggers, supported by data-driven reflection and personalized alerts. While the system successfully facilitated awareness and empathy, limitations in sound detection and manual data sharing highlighted areas for improvement. Future systems should incorporate intelligent sound recognition, privacy-sensitive data sharing, and multi-stakeholder awareness to enable comprehensive collaborative care for PWNS.