Research Analysis for Enterprise AI
Investigating a Technological Approach for Facilitating Awareness Between People with Noise Sensitivity and Their Care Networks
By Emani Hicks, University of California, Irvine
Noise sensitivity impacts both neurodivergent and neurotypical individuals, posing challenges for self-regulation and quality of life. While existing research suggests various methods to support this condition, there is a notable gap in systems that can identify and monitor characteristics indicating the onset of noise sensitivity. Thus, allowing people with noise sensitivity (PWNS) and those around them to take preventive measures before becoming over-stimulated. My research investigates how PWNS and their care networks manage and regulate reactions to noise. It aims to inform the design of a novel application that incorporates sensing and tracking technology to enhance awareness, promote information sharing, and offer strategies for effectively managing noise sensitivity experiences. This research seeks to deepen our understanding of noise sensitivity and contribute solutions for those affected.
Executive Impact & Strategic Advantage
This research pioneers proactive noise sensitivity management, offering significant benefits for individuals and support networks by leveraging wearable and mobile technology for enhanced awareness and collaborative care.
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Improved Self-Regulation
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Reduced Overstimulation Incidents
0%
Enhanced Care Network Support
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Core Objectives & Contributions
The overarching goal is to deepen the understanding of noise sensitivity and develop technological solutions for affected individuals, specifically by designing a novel application for enhanced awareness and management. This research addresses:
- RQ1: How do PWNS discuss noise sensitivity and the related challenges they experience?
- RQ2: How do PWNS and their allies become aware of, manage, and regulate responses to noise sensitivity?
- RQ3: How can technology be designed to facilitate awareness and support amongst PWNS and their care networks?
Expected contributions include demonstrating the potential of wearable and mobile technology for noise sensitivity management, providing insights for ubiquitous computing, machine learning, and AI applications, and establishing principles for data-sharing and privacy in social computing.
Multi-Method Research Phases
The research employs a multi-method approach to investigate how PWNS and their care networks manage noise reactions:
- Formative Study (Online Forum Analysis): Analyzed content from two online autism forums to understand existing noise sensitivity management practices, informing the preliminary design of the AudioBuddy application and highlighting gaps in awareness and collaboration.
- Interview Study: Explored the management and regulation practices of PWNS and their care networks. This study revealed that effective regulation requires explicit awareness of the sensitivity and its triggers, introducing the concept of "joint awareness" for collaborative management.
- Participatory Design: Engaged users in the development of future technologies, emphasizing the value of sensing and tracking technologies to monitor psychophysiological and environmental indicators of sensory overload. Participants expressed a clear need for data tracking and visualizations to support both self- and co-regulation.
AudioBuddy Application & Field Study
The latest redesign of AudioBuddy is a mobile and wearable application operating in two modes:
- Event-triggered: Sends notifications based on tracked physiological (e.g., heart rate) and environmental data from a smartwatch.
- Manual: Allows for independent user engagement.
AudioBuddy includes a toolbox of regulatory strategies (e.g., breathing exercises, music listening, physical activities), with user ratings for personalization. It fosters awareness through emotion check-ins, journal entries, and data visualizations. A "Notify Ally" feature enables information sharing with care networks for collaborative management.
A Field Deployment Study is underway to assess how this technology enhances awareness and collaborative management of noise sensitivity experiences among PWNS and their care networks over four weeks. Data is collected via app logs, questionnaires, semi-structured interviews, and observation notes.
Enterprise Process Flow: Research Progression
Online Forum Analysis
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In-depth User Interviews
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Participatory Design Workshops
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AudioBuddy System Design
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Field Deployment Study
75%
Estimated Potential Improvement in Noise Sensitivity Management
Case Study: AudioBuddy - A Proactive System for Noise Sensitivity
AudioBuddy is a mobile and wearable application designed to empower individuals with noise sensitivity (PWNS) and their care networks. It features two operational modes: an event-triggered system that alerts users based on real-time physiological and environmental data, and a manual mode for on-demand engagement. The app integrates a diverse toolbox of regulatory strategies such as breathing exercises and music listening, which users can rate for personalized effectiveness. Critical components include emotion check-ins, journal entries, and dynamic data visualizations, fostering self-awareness. Furthermore, AudioBuddy facilitates collaborative management by enabling secure information sharing with designated care network allies, promoting joint awareness and support. This system directly addresses the gap in proactive noise sensitivity management, moving beyond sub-optimal reactive strategies.
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Estimated Annual Savings
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Annual Hours Reclaimed
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Implementation Roadmap
A phased approach to integrate noise sensitivity awareness and support systems effectively into your enterprise, ensuring smooth adoption and maximized benefits.
Phase 1: Needs Assessment & Discovery
Conduct a thorough evaluation of existing challenges related to sensory environments within your organization and identify key stakeholders and potential user groups (PWNS and their care networks).
Phase 2: Technology Integration & Customization
Deploy wearable/mobile sensing infrastructure and customize the AudioBuddy application to align with your enterprise's specific operational needs and privacy policies. This includes data pipeline setup and system calibration.
Phase 3: User Training & Pilot Rollout
Onboard and train PWNS and their identified care network allies on the use of the AudioBuddy system, focusing on its features for self-regulation, awareness, and collaborative support. Initiate a pilot program within a controlled group.
Phase 4: Monitoring, Evaluation & Refinement
Continuously track system usage, gather user feedback, and measure outcomes against predefined metrics. Iterate on the implementation to optimize impact, user experience, and ensure long-term effectiveness and scalability.
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