Research & Roadmap
Behavioral audio awareness, privacy-first design, and clinically informed development.
Purpose
This page is intended for research partners, clinical collaborators, and grant reviewers.
SnapHabit LLC, the company behind AwareFlow™, is developing a system for detecting subtle behavioral signals and translating them into real-time awareness.
The work aligns with priorities in digital health, behavioral science, and human-computer interaction.
AwareFlow is not a medical device and does not provide diagnosis or treatment. The research described here reflects areas of investigation, not clinical claims.
Problem & Opportunity
Subtle habits such as sniffing, throat clearing, or other repetitive sounds are common and often unconscious. These behaviors can impact focus, relationships, and perceived social tension, particularly in contexts such as misophonia.
- They often occur without awareness
- They may reflect nervous-system load or stress
- They can create disproportionate impact on others
There is currently no widely adopted tool that provides real-time awareness of these patterns without recording or storing audio.
Scientific Foundations
AwareFlow builds on established concepts across behavioral science and digital health.
-
Behavioral signal patterns
Short, repetitive actions can reflect internal physiological or emotional state.
-
Contextual modulation
Fatigue, environment, and emotional load influence frequency and intensity.
-
Pattern analysis
Using timing, frequency, and pattern data instead of raw recordings to derive insight.
The central premise: these behaviors are not noise. They are meaningful patterns.
Research Aims
-
Safe pattern recognition
Develop on-device models that identify short behavioral sounds without storing audio.
-
Context modeling
Explore relationships between behavior, time, environment, and subjective state.
-
Awareness-driven feedback
Design interventions that support noticing without inducing pressure or compliance behavior.
Approach
- On-device processing instead of cloud-based audio collection
- Pattern-level abstraction instead of raw data storage
- User-controlled feedback rather than automated correction systems
This approach reduces privacy risk while preserving meaningful behavioral insight.
Development Roadmap
-
Phase 1
Sniff and throat-clear awareness with personalized calibration (current)
-
Phase 2
Expansion to additional behavioral sound classes
-
Phase 3
Context-aware insights incorporating environment and temporal patterns
-
Future work
Clinical partnerships and formal validation studies
Research and Grant Aspirations
AwareFlow began as a personal project and has grown into a mission with wider reach. We are pursuing trademark protection, patent pathways, and federal research funding to expand the science and accessibility of gentle habit awareness.
Grants from agencies such as NIH and NSF would allow us to study subtle auditory habits at scale (sniffing, throat clearing, pen clicking) and eventually extend the technology to spoken patterns such as filler words and emotional tone shifts.
These resources would help AwareFlow mature into a broader behavioral-wellness platform, supporting real-world research while giving individuals tools to understand themselves with compassion rather than shame.
Privacy & Ethics
The system is designed around strict privacy constraints.
- No raw audio storage
- No passive cloud collection
- Explicit, opt-in participation for any research sharing
The aim is to enable behavioral insight without compromising personal boundaries.
Collaboration
We are open to collaboration with researchers, institutions, and funding partners.
For inquiries or partnership discussions:
Read about how the listening system works: How AwareFlow Works
Read about our privacy approach: Privacy Policy