Bio-Potential ECG Electrodes for HRV-Based Hypoglycemia Detection
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Solution Overview
Problem
Existing glucose monitoring devices suffer from false positive alarms and lack of accurate prediction of hypoglycemic events due to reliance on surrogate biomarkers like continuous glucose monitoring (CGM) with lag times and poor specificity, while autonomic nervous system (ANS) tests are not routinely conducted and are cumbersome, limiting the detection of autonomic dysfunction.
Innovation Solution
A system combining heart rate variability (HRV) analysis with biomarker sensors to predict and detect adverse events, such as hypoglycemia, by integrating electrocardiogram (ECG) electrodes with insulin delivery devices to adjust insulin infusion rates automatically based on real-time heart rhythm and glucose levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous glucose monitoring (CGM) is used to detect hypoglycemic events, then glucose levels can be monitored continuously, but false positive alarms occur due to lag times and poor specificity
Solution Approach 1:
The patent introduces heart rate variability (HRV) as an intermediary biomarker to validate CGM readings. HRV serves as a mediator that confirms whether a CGM-detected glucose drop represents a true hypoglycemic event or a false alarm, thereby improving alarm reliability without sacrificing detection accuracy
Solution Approach 2:
The system implements feedback by using HRV measurements to verify CGM alerts. When CGM detects a potential hypoglycemic event, the system checks HRV patterns to confirm the event's真实性, creating a feedback loop that reduces false positives while maintaining sensitive detection
2Reliability
If autonomic nervous system (ANS) tests are conducted routinely, then autonomic dysfunction can be detected early, but the tests are cumbersome and not routinely performed
Solution Approach 1:
The patent combines ANS assessment with routine ECG monitoring. By integrating HRV analysis into standard cardiac monitoring protocols, the system makes autonomic dysfunction detection as convenient as routine heart monitoring, eliminating the need for separate cumbersome ANS tests
Solution Approach 2:
The ECG device serves multiple functions: it monitors cardiac rhythm and simultaneously assesses autonomic nervous system function through HRV analysis. This multi-functionality allows routine cardiac monitoring to also detect autonomic dysfunction, improving accessibility without requiring specialized equipment or procedures
3Manufacturing precision
If insulin delivery is adjusted based on real-time glucose levels, then glycemic control can be improved, but hypoglycemic events may still occur due to lag times in detection
Solution Approach 1:
The system performs preliminary action by detecting hypoglycemic trends through HRV changes before glucose levels actually drop. By identifying autonomic nervous system alterations that precede hypoglycemia, the system can alert patients and adjust insulin delivery in advance, preventing severe hypoglycemic events
Solution Approach 2:
The system dynamically adjusts insulin delivery based on real-time integration of CGM and HRV data. By continuously monitoring both glucose levels and autonomic nervous system state, the system can adaptively modify insulin rates to prevent hypoglycemia while maintaining tight glycemic control, reducing the time loss associated with reactive adjustments
Data Source
AI summary
An insulin delivery device includes an insulin injection device in communication with a controller for controlling the insulin injection device. The controller is configured to receive a heart signal from one or more heart sensors, and a blood glucose signal from one or more blood glucose sensors. The controller is further configured to analyze changes in the heart rhythm of the subject based on the heart signal and determine, based on the changes in the heart rhythm and the blood glucose signal, whether the subject is and/or will be experiencing an adverse event. Upon determination that the subject is or will be experiencing an adverse event, the controller determines one or more parameters of delivery of insulin to be delivered to the subject. Finally, the controller is configured to control the injection device to deliver insulin to the subject in accordance with the determined one or more parameters of delivery.