Digestive motility · Esophageal manometry
Read the pressure. Recognize the pattern.
AI‑driven identification, classification and reporting of esophageal motility patterns in high resolution esophageal manometry according to Chicago Classification 4.0.
HREM · SWALLOW SEQUENCE LIVE ANALYSIS
01 · Intended use
AI assistance for complex esophageal pressure data.
Smart Esophagus® enhances the detection and differentiation of the most relevant esophageal motility patterns in high resolution esophageal manometry.
The platform is designed to make interpretation more consistent and help extend access to HREM beyond specialized reference centers.
AI
The clinical challenge
Complex pressure data can limit access to confident interpretation.
HREM is central to esophageal functional assessment, yet its availability remains limited and analysis can be technically demanding. Pattern interpretation may vary between observers and clinical settings.
“The opportunity is to make specialized motility interpretation more consistent and more accessible.”
02
How it works
One continuous path from examination to report.
The interface follows the same logic as the technology: information progressively resolves as it moves through the analysis.
HREM acquisition
High resolution esophageal manometry pressure data enters the analysis workflow.
Signal preparation
The examination is organized into clinically relevant phases and pressure channels.
Pattern detection
The AI identifies disorders of esophagogastric junction outflow and peristalsis across the examination.
Pattern classification
Findings are differentiated using standardized esophageal motility criteria.
Clinical review
Structured results are presented for expert validation and diagnostic reporting.
AI capabilities
Designed for consistent esophageal motility interpretation.
94.2%
Accuracy reported for EGJ outflow disorder detection
Automatic pattern detection
Identifies relevant patterns of esophagogastric junction outflow and peristalsis in HREM examinations.
Motility differentiation
Supports consistent differentiation of the most relevant esophageal motility patterns.
Chicago 4.0 classification
Organizes examination findings within the standardized Chicago Classification framework.
Accessible expert support
Helps extend advanced esophageal manometry interpretation beyond reference centers.
Structured data review
Transforms complex pressure data into focused information for clinician validation.
03
Scientific validation
Clinical evidence for automatic motility pattern detection.
Artificial Intelligence Driven Diagnosis of Motility Patterns in High Resolution Esophageal Manometry: A Multicentric Multidevice Study
Clinical and Translational Gastroenterology · 2025 · Multicenter and multidevice validation
Read publication ↗Clinical benefits
More consistent analysis. Broader clinical access.
01
Automatic detection and differentiation of esophageal motility patterns
↗02
More consistent interpretation of complex HREM pressure data
↗03
Reduced interobserver variability through standardized analysis
↗04
Greater availability of esophageal manometry interpretation across clinical settings
↗Smart Esophagus®
Bring intelligent pattern recognition to esophageal manometry.
Talk to our team ↗The products and technologies showcased are part of our advanced research and development pipeline and may be pending regulatory approval in your market.