Wearable Chest Motion Sensor for Opioid Overdose Prediction
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Solution Overview
Problem
Current overdose detection methods for opioids lack timely and accurate detection, particularly for opioid overdoses, which can lead to fatalities if antidotes are not administered quickly enough.
Innovation Solution
A wearable condition detector equipped with a motion sensor to monitor chest wall movement, processing system to analyze breathing patterns, and communication system for real-time alerts, utilizing AI or machine learning algorithms to predict overdoses by analyzing breathing waveforms and adapting to individual user data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional overdose detection methods are used, then device complexity is reduced, but detection precision and timeliness deteriorate
Solution Approach 1:
The detection system is divided into multiple independent components: motion sensor for chest wall movement detection, processing system for waveform analysis, and communication system for alerts. Each component performs a specific function, allowing the system to achieve high detection precision while maintaining manageable complexity through modular design.
Solution Approach 2:
The patent replaces traditional mechanical or manual overdose detection methods with electronic sensing and digital signal processing. The motion sensor converts physical chest wall movement into electrical signals, which are then processed algorithmically to detect breathing patterns indicative of overdose, significantly improving detection accuracy.
2Loss of time
If real-time monitoring is implemented, then response time is improved, but energy consumption increases
Solution Approach 1:
The motion sensor continuously monitors chest wall movement without interruption, ensuring that breathing pattern changes are detected immediately. This continuous monitoring enables real-time overdose detection and rapid response, though it does increase energy consumption compared to periodic sampling.
Solution Approach 2:
The communication system provides immediate feedback by sending alerts to emergency contacts or medical personnel when overdose is detected. This feedback loop ensures that the system responds in real-time, minimizing the loss of time between overdose occurrence and intervention.
3Measurement precision
If individualized detection thresholds are used, then detection accuracy is improved, but device adaptability requirements increase
Solution Approach 1:
The system performs preliminary monitoring during a calibration period to establish baseline breathing patterns for each user before actual overdose detection begins. This preliminary action allows the system to adapt to individual user characteristics, improving subsequent detection accuracy without requiring complex real-time adjustments.
Solution Approach 2:
The detection thresholds and parameters are dynamically adjusted based on individual user data collected during calibration and ongoing monitoring. The system adapts to each user's unique breathing patterns, age, and physiological characteristics, maintaining high detection accuracy while automatically managing the complexity of individualization.
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
Enables timely and accurate detection of opioid overdoses, allowing for immediate intervention and potential automatic adjustment of drug delivery, thereby reducing the risk of fatalities.
Implementation Method 1
The motion sensor may be a chest mountable detector. The motion sensor may be configured for mounting to a human chest, upper abdomen or upper torso. The motion sensor may be configured to determine chest wall movement.
Data Source
AI summary
An overdose detector that includes a motion sensor mounted or mountable on a chest wall and configured to detect chest wall movement, and wherein the overdose detector is configured to detect and/or predict an overdose based on the detected chest wall movement. Also described herein are associated systems, methods and computer program products.