Therapeutic Gas Delivery With Predictive Backup Switching
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Solution Overview
Problem
Existing therapy gas delivery systems fail to accurately determine the remaining time before a gas source becomes empty, leading to potential disruptions in treatment and lack of seamless transition to backup systems.
Innovation Solution
A therapeutic gas delivery system with redundant subsystems and algorithms that calculate the run-time-to-empty for multiple gas sources, enabling seamless transition between sources and providing fail-safe protection by automatically switching to a backup when the primary source is low, without interrupting treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single gas source is used in the therapy delivery system, then the device complexity is reduced, but the reliability of continuous gas delivery deteriorates when the gas source becomes empty
Solution Approach 1:
The system performs preliminary actions by calculating run-time-to-empty for multiple gas sources before actual depletion occurs. The algorithm continuously monitors gas consumption rates and predicts when each source will be exhausted, enabling proactive switching to backup sources before the primary source becomes empty, thus ensuring continuous delivery without interruption
Solution Approach 2:
The system implements beforehand cushioning by maintaining redundant gas sources and pre-calculating their availability. When the primary gas source approaches depletion, the system has already identified alternative sources and prepared for seamless transition, cushioning against the potential failure of continuous delivery that would occur with a single source
2Loss of time
If run-time-to-empty calculation is not implemented, then the device complexity is reduced, but the loss of time occurs when treatment must be interrupted to replace gas sources
Solution Approach 1:
The system implements feedback by continuously monitoring gas consumption rates from multiple sources and using this information to dynamically calculate run-time-to-empty predictions. This feedback loop allows the system to adjust predictions as consumption patterns change and to alert operators in advance when sources will be depleted, preventing treatment interruptions
Solution Approach 2:
The algorithm performs preliminary calculations of run-time-to-empty based on current consumption rates and remaining gas volumes. By predicting depletion times in advance, the system allows operators to prepare for source replacement or switching without interrupting ongoing treatment, thus eliminating loss of time
3Loss of information
If manual monitoring of gas source status is used, then the device complexity is reduced, but the loss of information occurs regarding the amount of treatment time remaining
Solution Approach 1:
The system establishes feedback communication channels between gas sources, the delivery system, and the user interface. Sensors continuously monitor gas levels and consumption rates, feeding this information to the run-time calculation algorithm, which then displays real-time predictions of remaining treatment time to operators, eliminating information loss about gas source status
Solution Approach 2:
The system introduces an intermediary computational layer that translates raw sensor data from gas sources into meaningful run-time-to-empty predictions. This intermediary algorithm processes communication between the physical gas sources and the user interface, converting complex technical parameters into actionable information about remaining treatment time
Data Source
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AI summary
Therapy gas delivery systems (100) that provide run-time-to-empty information to a user of the system and methods for administering therapeutic gas to a patient. The therapeutic gas delivery system (100) may include a gas pressure sensor (120) attachable to a therapeutic gas source (116) that communicates therapeutic gas pressure data to a therapeutic gas delivery system controller (129,144,164), a gas temperature (130) sensor positioned to measure gas temperature in the therapeutic gas source (116) that communicates therapeutic gas temperature data to the therapeutic gas delivery system controller (129,144,164), at least one flow controller (144,164) that communicates therapeutic gas flow rate data to the therapeutic gas delivery system controller (129,144,164), at least one flow sensor (146,148) that communicates flow rate data to the therapeutic gas delivery system controller (129,144,164), and at least one display (112) that communicates run-time-to-empty to a user of the therapeutic gas delivery system (100). The therapeutic gas delivery system controller (129,144,164) of the system (100) includes a processor that executes an algorithm to calculate the run-time-to-empty from the data received from the gas pressure sensor (120), temperature sensor (130), flow controller (144,164) and flow sensor (146,148), and directs the result to the display (112).