Surgical Dataflow Rebalancing for Erroneous Sensor Inputs
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Solution Overview
Problem
Surgical procedures are often disrupted due to erroneous data transmission from smart devices, which can lead to patient safety issues and the need to pause or cancel procedures.
Innovation Solution
A surgical computing system uses sensor data from a second smart device to generate control data for a first smart device, allowing the procedure to continue without interruption by rebalancing the dataflows and adjusting output characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a smart device transmits erroneous sensor data during a surgical procedure, then patient safety is compromised and the procedure must be paused or cancelled, but continuing with reduced smart devices or replacing the failed device causes procedural interruption and loss of time
Solution Approach 1:
The surgical computing system acts as an intermediary that receives sensor data from multiple smart devices, processes it centrally, and generates control data. When one device fails, the intermediary can substitute data from another device, preventing procedural interruption and maintaining continuous operation without requiring direct device-to-device communication
Solution Approach 2:
The system establishes redundant dataflow paths and alternative sensor data sources before failure occurs. When erroneous data is detected, pre-configured alternative dataflows are immediately activated, cushioning against the impact of device failure and eliminating the need for procedural pauses or device replacements
2Productivity
If the system uses sensor data from a second smart device to generate control data for a first smart device, then continuous operation is maintained, but the system complexity increases due to multiple dataflow management requirements
Solution Approach 1:
The surgical computing system is designed with universal data processing capabilities that can handle sensor data from multiple different smart device types through a unified interface. This multi-functionality allows the same system to process data from various devices without requiring device-specific processing logic, managing complexity through standardization
Solution Approach 2:
The system dynamically changes operational parameters by switching between different dataflow configurations based on device status. When a device fails, the system alters its data processing parameters to utilize alternative data sources, maintaining productivity through adaptive parameter adjustment rather than structural complexity
Data Source
AI summary
Systems, methods, and/or instrumentalities disclosed herein may augment dataflows to rebalance the number of unknowns and dataflows. The device may be configured to receive a first dataflow from a first surgical element. The first dataflow may be associated with a physiological parameter of a patient. The device may determine that the first dataflow from the first surgical element is erroneous. The device may determine a second dataflow associated with a second surgical element. The determination of the second dataflow may be based on an indication of a relational link associated with the second dataflow of the second surgical element, control data for the first surgical element, and/or the physiological parameter of the patient. The device may generate control data for the first surgical element based on the second dataflow. The control data may indicate an adjustment to an output characteristic associated with the first surgical element.