Multi-Sensor Armband for Non-Invasive Glycemic Event Prediction
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Solution Overview
Problem
Current methods for monitoring glucose levels in diabetes patients rely on invasive continuous glucose monitors (CGMs), which are expensive and only prescribed to a limited number of patients, and lack effective non-invasive solutions for predicting glycemic events such as hypoglycemia and hyperglycemia.
Innovation Solution
A wearable multi-sensor armband device that combines non-invasive sensors like photoplethysmography (PPG), bioimpedance (BioZ), single-sided electrocardiogram (SS-ECG), electrodermal activity (EDA), and temperature sensors, along with an accelerometer and gyroscope, to predict glycemic events by analyzing physiological signals and using machine-learning algorithms to provide early alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive continuous glucose monitors (CGMs) are used to monitor glucose levels, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical/invasive CGM system with a non-invasive optical sensing system. Multiple optical sensors (PPG, multi-wavelength spectroscopy) detect physiological changes in skin and underlying tissues to infer glucose levels without penetration or injection, thereby maintaining measurement capability while eliminating invasiveness and reducing device complexity.
Solution Approach 2:
The wearable device integrates multiple sensing modalities (optical, electrical, thermal) that can simultaneously monitor glucose levels, detect hypoglycemic events, and track other physiological parameters. This multi-functional approach consolidates what would otherwise require separate devices into a single universal monitoring system.
2Reliability
If invasive CGMs are deployed, then reliability of glycemic event detection is improved, but ease of operation deteriorates
Solution Approach 1:
By replacing the invasive mechanical insertion required by CGMs with non-invasive optical sensing through the skin, the system eliminates pain, infection risk, and wearability issues. Patients can wear the device continuously without discomfort, significantly improving ease of operation and long-term compliance while maintaining reliable detection of glycemic events.
3Reliability
If multiple non-invasive sensors are combined, then reliability of prediction is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple independent sensing modalities (photoplethysmography, multi-wavelength optical spectroscopy, electrical sensors, thermal sensors) into a single integrated wearable device. The sensors are physically combined in one unit and their data streams are processed together through machine learning algorithms, achieving reliable prediction while managing complexity through unified design.
Solution Approach 2:
The system uses multiple optical wavelengths to create redundant measurement pathways, similar to copying information across different channels. This redundancy allows cross-validation of signals and improves prediction reliability while the shared processing architecture manages the complexity of handling multiple sensor inputs.
4Ease of operation
If non-invasive sensors are used, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent combines multiple non-invasive sensing modalities that individually provide limited information but collectively deliver accurate glucose level measurement. By merging optical absorption data at different wavelengths with physiological signal processing, the system achieves precision comparable to invasive methods while maintaining non-invasive ease of operation.
Solution Approach 2:
The system varies multiple parameters simultaneously - using different optical wavelengths, different sensor positions on the body, and different processing algorithms - to extract glucose information from complex tissue interactions. This multi-parameter approach compensates for the inherent limitations of non-invasive measurement and achieves high accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The device offers a non-invasive, cost-effective solution for predicting glycemic events with high accuracy, reducing the need for invasive monitoring and improving patient safety by providing timely alerts for both hypoglycemia and hyperglycemia.
Implementation Method 1
a photoplethysmography sensor
Implementation Method 2
a bioimpedance and electrodermal activity sensor
Implementation Method 3
a single-sided electrocardiography sensor
Implementation Method 4
a bioimpedance and electrodermal activity sensor
Implementation Method 5
temperature sensors
Data Source
AI summary
A wearable multi-sensor device for measuring physiological properties includes a plurality of non-invasive sensors, such as a single-sided electrocardiography sensor, a bioimpedance and electrodermal activity sensor, a skin temperature sensor, and a photoplethysmography sensor. The device is configured to secure a skin-facing side of the sensors to exposed skin of a user and includes a communication module configured to receive signals from the plurality of non-invasive sensors and output data from the device, the being suitable for use in predicting glycemic events in the user.