Closed-Loop Algorithm Signal Processing

The Brain of AID Systems

Closed-loop algorithms are the intelligence behind automated insulin delivery systems.

Core Functions

Data Analysis

• Process raw CGM signals
• Filter noise and artifacts
• Identify true glucose trends

Prediction

• Forecast future glucose levels
• Anticipate meals and activity
• Calculate time-to-target

Insulin Adjustment

• Increase basal for rising trends
• Decrease or suspend for falling trends
• Deliver correction boluses (in advanced systems)

Signal Processing Techniques

Noise Filtering

• Remove sensor artifacts
• Smooth erratic readings
• Identify and handle compression lows

Trend Analysis

• Calculate rate of change
• Identify inflection points
• Distinguish true trends from noise

Algorithm Types

Reactive Algorithms

• Respond to current glucose values
• Simpler but slower response
• Less aggressive, more conservative

Predictive Algorithms

• Anticipate future glucose
• Pre-emptive insulin adjustments
• More aggressive, tighter control

Challenges

The Lag Problem

Algorithms must compensate for:

• CGM physiological lag (5-15 min)
• Insulin absorption delay (15-30 min)
• Combined delay can exceed 30 minutes

Safety Constraints

• Maximum insulin delivery limits
• Minimum glucose thresholds for delivery
• Fail-safe behaviors for lost signal