Multi-Sensor Gesture Detection for Automated Medication Delivery
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Solution Overview
Problem
Existing medication delivery systems, such as insulin infusion devices, struggle to account for variations in patient insulin response due to daily activities and meal consumption, leading to manual errors and reduced therapy effectiveness.
Innovation Solution
A gesture-informed patient management system that utilizes primary and secondary sensing arrangements to predict patient events and automatically adjust medication delivery based on detected physical movements and ancillary data, enhancing accuracy and reducing patient workload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual bolus administration is used to mitigate postprandial hyperglycemia, then patient can control insulin delivery, but manual errors occur such as miscounting carbohydrates or failing to initiate bolus in a timely manner
Solution Approach 1:
The system automatically detects meal events through sensor data (accelerometer, gyroscope, microphone, camera) and triggers insulin bolus delivery without requiring manual patient input. The device serves itself by autonomously monitoring patient behavior, predicting meal consumption, and adjusting medication delivery, thereby eliminating manual errors while reducing patient workload.
2Adaptability or versatility
If patient manually monitors and adjusts insulin therapy based on daily activities, then therapy can be customized, but patient burden increases and errors occur
Solution Approach 1:
The system continuously collects sensor data from multiple sources (motion sensors, audio sensors, visual sensors) and uses this feedback to automatically adjust insulin delivery parameters. The feedback loop enables the device to adapt therapy to patient's actual activities and meal consumption patterns without requiring manual patient input, thereby maintaining therapy customization while reducing patient burden.
Solution Approach 2:
The patent replaces manual mechanical monitoring and adjustment processes with automated electronic sensing and control systems. Sensors detect patient activities and meal events, and the control system automatically adjusts insulin delivery, substituting the mechanical manual operations with electronic automation to reduce patient burden while maintaining adaptability.
3Measurement precision
If single sensor arrangement is used for gesture detection, then device complexity is reduced, but measurement accuracy decreases leading to false event predictions
Solution Approach 1:
The system merges multiple sensor arrangements (accelerometer, gyroscope, microphone, camera) into a unified monitoring system that collectively detects patient activities and meal events. By combining data from multiple sensors, the system achieves high measurement precision for event detection while managing complexity through integrated processing and fusion algorithms.
Data Source
AI summary
Gesture-informed patient management systems and related medical devices and operating methods are provided. A method of operating a medical device capable of influencing a physiological condition of a patient involves obtaining first sensor measurement data from a sensing arrangement associated with a first location on a body of the patient and capable of detecting physical movement by the patient, obtaining second sensor measurement data from a second sensing arrangement having a second location different from the first location, predicting an occurrence of an event based at least in part on the first sensor measurement data in a manner that is influenced by the second sensor measurement data, resulting in a predicted occurrence of the event, and automatically configuring operation of the medical device to influence the physiological condition of the patient in a manner that is influenced by the predicted occurrence of the event.