Adaptive Patient Data Transmission via Signal Quality Analysis
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Solution Overview
Problem
Conventional physiologic monitoring systems face challenges in maintaining critical information transmission due to interference and congestion, leading to gaps in data and poor user-perceived signal quality, especially in shared network environments where bandwidth is limited, resulting in incomplete or lost data that can disrupt monitoring and alerting processes.
Innovation Solution
A network communication optimization system that includes a transceiver, signal quality analyzer, and transmission controller to detect network congestion and latency, selectively reduce data transmission based on a data type hierarchy, and buffer omitted data for later transmission, ensuring higher priority data is maintained and gaps are filled once signal quality improves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional systems transmit all data continuously, then data completeness is improved, but network bandwidth consumption increases causing congestion and packet loss
Solution Approach 1:
The system dynamically adjusts the data transmission rate based on real-time signal quality measurements. The transmission controller modifies the number of data points transmitted per cycle according to the measured signal quality, creating a dynamic adaptation mechanism that balances data completeness with network bandwidth efficiency under varying network conditions
Solution Approach 2:
The system changes the transmission parameter (number of data points) based on signal quality thresholds. When signal quality falls below a threshold, the system reduces the number of data points transmitted; when signal quality improves, the system increases transmission. This parameter change approach resolves the contradiction by adjusting transmission volume to match available network capacity
2Productivity
If the system reduces data transmission during congestion, then network bandwidth efficiency is improved, but data completeness deteriorates due to gaps in monitoring data
Solution Approach 1:
The system performs preliminary actions by buffering data locally when network conditions are poor, then transmitting the buffered data when signal quality improves. This ensures that data transmission resumes without gaps once network conditions allow, maintaining data completeness while having reduced transmission during congestion periods
Solution Approach 2:
The system maintains continuous monitoring by buffering data during congestion periods and then continuing transmission once signal quality improves. The useful action of data collection continues uninterrupted, just the transmission timing is adjusted, ensuring both bandwidth efficiency during congestion and data completeness overall
3Loss of information
If the system shuts down connection completely during poor signal quality, then data loss is minimized, but monitoring continuity deteriorates due to connection reestablishment breaks
Solution Approach 1:
The system applies partial action by reducing rather than completely shutting down data transmission during poor signal quality. It transmits only the essential data or reduced data sets rather than stopping entirely, thereby maintaining monitoring continuity while minimizing data loss through selective transmission
4Reliability
If dedicated bandwidth is allocated for physiologic monitoring, then data transmission reliability is improved, but network resource consumption increases
Solution Approach 1:
The system uses universal network infrastructure for physiologic monitoring without requiring dedicated bandwidth. It adapts to shared network conditions by adjusting transmission rates based on signal quality, allowing the same network resources to serve multiple functions while maintaining reliable data transmission through adaptive rather than dedicated allocation
Data Source
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AI summary
When transmitting patient data over a hospital network, data types are prioritized into a data type hierarchy (26) that is employed to rank data types in order of criticality for transmission during periods of diminished signal quality. As signal quality decreases, less critical data types are omitted from transmission and stored to a gap data buffer for later transmission. As signal quality recovers, the less critical data types are restored to current data transmissions. Once all data types are restored during current transmission, previously omitted gap data is transmitted to fill in the gaps in a receiving device such as a network server to ensure that a complete data set is provided to the network and/or other devices coupled thereto.