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Innovations

PSight

Biometric-Informed Nervous System Regulation

Traditional wellness apps treat mental health as disconnected activities—"do some breathing," "log your mood." PSight integrates biometric feedback with regulation state tracking to create a closed-loop therapeutic system.

Your body knows when you're dysregulated before your mind does. PSight listens to your body.

The Polyvagal Foundation

Polyvagal Theory describes how our autonomic nervous system responds to safety and threat. The vagus nerve connects brain to body, regulating heart rate, breathing, digestion, and emotional state.

The "Window of Tolerance" is the zone where we function optimally—neither hyperaroused (fight/flight) nor hypoaroused (freeze/collapse). Trauma, stress, and chronic dysregulation narrow this window.

The insight: What if your wellness app knew whether you needed grounding or activation before you consciously realised you were struggling?

The Window of Tolerance

Different arousal states require different interventions. PSight detects your current state and suggests the right approach.

Fight/Flight

Hyperaroused

Symptoms

Anxiety, panic, rage, hypervigilance, racing thoughts

Interventions

Grounding exercisesSlow breathingCold exposureBilateral stimulation
Optimal

Regulated

Symptoms

Calm alertness, social engagement, clear thinking, emotional flexibility

Interventions

Maintenance practicesSocial connectionCreative activities
Freeze/Collapse

Hypoaroused

Symptoms

Shutdown, dissociation, numbness, fatigue, depression

Interventions

Activation exercisesMovementSensory stimulationSocial engagement

What Makes It Different

Not another mood tracker. A closed-loop system that responds to your physiology in real-time.

Biometric-Informed Interventions

Connects to HRV monitors and EEG devices. When your heart rate variability drops or your nervous system shows signs of dysregulation, it proactively suggests interventions—not waiting for you to realise you're struggling.

Adaptive Exercise Selection

The wrong intervention at the wrong time can make things worse. If you're hyperaroused, it suggests grounding and slow breathing. If you're hypoaroused, it suggests activation exercises. State-aware, not one-size-fits-all.

Pattern Recognition Over Time

Tracks what interventions work for you specifically, at what times, in what contexts. Learns your regulation patterns and personalises recommendations based on your history.

Training Loop Integration

Therapy mode helps regulate now. Training mode builds long-term capacity through EEG neurofeedback. The two systems work together for immediate relief and lasting change.

Biometric Integration

Consumer-grade hardware, research-grade insights.

Heart Rate Variability (HRV)

Primary indicator of parasympathetic nervous system activity. Low HRV often signals stress or dysregulation.

Integrations

Apple Watch, Garmin, Polar, Oura Ring

EEG Brainwave Patterns

Alpha, beta, theta, and delta wave ratios indicate arousal states and cognitive load.

Integrations

Muse, OpenBCI, consumer-grade headbands

Respiratory Rate

Breath patterns correlate with nervous system state. Rapid shallow breathing indicates sympathetic activation.

Integrations

Wearables with respiratory tracking

System Architecture

Explore how PSight detects arousal states and selects interventions. Click on any node for details, and use the flow buttons to trace data through the system.

The Bigger Picture

PSight is part of a broader vision: making nervous system regulation accessible to everyone. Not just those who can afford therapy or have the executive function to maintain complex self-care routines.

Therapy mode handles the now—detecting dysregulation and suggesting immediate interventions. Training mode builds the future—using EEG neurofeedback to expand the window of tolerance over time.

Your body already has the signals. PSight helps you hear them.

Interested in Biometric Wellness?

Whether you want to discuss the Polyvagal Theory implementation or explore how biometric integration could work for your application, I'd love to hear from you.