BracyInsight™ Computational Physiology Platform — Bracy Analytics
Technology Platform
BracyInsight™ — Computational
Physiology Platform
A hardware-agnostic computational framework that transforms multimodal physiological signals into continuous estimates of pulmonary status using advanced signal processing, computational physiology, and physics-informed artificial intelligence.
The innovation is the software, the algorithms, and the physiology — not the sensing hardware.
Platform Architecture
Three integrated layers
BracyInsight™ is organized into three distinct layers. Each layer has a clear responsibility — and together they form a complete pipeline from raw physiological signals to clinical decision support.
Multimodal Physiological Sensing
The hardware-agnostic sensing layer. BracyInsight™ is designed to accept input from any combination of physiological sensors — future sensors plug in without changes to the core platform. The innovation is not the hardware.
Capabilities
- Electrical Impedance Tomography (EIT)
- ECG & cardiac monitoring
- PPG & peripheral oxygen saturation (SpO₂)
- Respiratory rate & effort monitoring
- Motion sensing & artifact detection
- Hardware-agnostic sensor abstraction layer
Computational Physiology Engine
The intellectual property — and what NSF is funding. This layer transforms raw multimodal signals into continuous, clinically meaningful estimates of pulmonary status using physics-informed AI and advanced signal processing.
Capabilities
- Signal quality assessment & validation
- Motion artifact correction & noise rejection
- Physiological feature engineering
- Multi-sensor data fusion
- Physics-informed AI modeling
- Pulmonary state estimation
- Confidence scoring & uncertainty quantification
Clinical Decision Support
Clinically actionable outputs delivered to the point of care. This layer translates computational physiology estimates into decision support that clinicians and systems can act on — regardless of the clinical environment.
Capabilities
- Continuous pulmonary assessment
- Respiratory deterioration detection
- Risk scoring & triage prioritization
- Clinical decision support alerts
- Remote monitoring & data transmission
Design Principles
Built on first principles
Hardware-Agnostic by Design
The platform is not tied to any specific sensor or device form factor. The computational physiology engine accepts inputs from any validated sensor combination — enabling deployment across wearables, bedside monitors, and future hardware.
Physics-Informed AI
Unlike black-box ML models, BracyInsight™ embeds physiological knowledge directly into the model architecture. This improves generalizability, reduces training data requirements, and produces outputs that are interpretable to clinicians.
Edge-First Architecture
The computational physiology engine is designed to run on resource-constrained hardware without cloud dependency. Full functionality in austere environments — no connectivity required for core assessment.
NSF SBIR Validated
The scientific merit and commercial potential of the platform has been validated by the National Science Foundation, which invited Bracy Analytics to submit a Phase I SBIR proposal for continued development.
Consulting Technology Stack
Tools & platforms we deliver with
Our consulting practice leverages industry-standard platforms across GIS, analytics, cloud, and AI — delivering solutions that integrate with your existing infrastructure.
GIS & Spatial
- ArcGIS Enterprise
- ArcGIS Online
- QGIS
- PostGIS
- Esri StoryMaps
- GeoPandas
Analytics & Statistics
- SAS
- R
- Python
- SQL
- CDISC / ADaM / SDTM
- Jupyter
Cloud & BI
- Microsoft Azure
- AWS
- Power BI
- Tableau
- Databricks
- Snowflake
AI & Machine Learning
- Machine Learning
- Predictive Analytics
- LLM Integration
- TensorFlow / PyTorch
- Scikit-learn
- MLflow
Ready to explore a partnership?
We are seeking technology partners, clinical advisors, and investors who understand the opportunity in computational medicine and clinical AI.