Central Control Apparatus for Surgical Device Abnormality Detection
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Solution Overview
Problem
During surgery, medical devices can experience abnormalities that are not promptly identified or addressed due to the lack of centralized control and logging mechanisms, which can lead to unintended settings or operations by users, potentially causing errors.
Innovation Solution
A central control apparatus that communicates with multiple medical devices, records operation information as log data, and extracts relevant information based on predefined extraction conditions to detect and respond to abnormal states, prioritizing log data extraction for maintenance notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a central control apparatus monitors all control target devices during surgery, then device abnormality detection capability is improved, but system complexity and data processing burden increase
Solution Approach 1:
The patent extracts only the necessary log data related to detected abnormalities from the comprehensive log data of multiple control target devices. When an abnormality is detected in a specific device, the system selectively extracts log data from that device and potentially from other devices in the same group, rather than processing all log data from all devices. This extraction approach reduces data processing burden while maintaining reliable abnormality detection capability.
2Loss of information
If log data from all control target devices is recorded and analyzed, then comprehensive diagnostic information is obtained, but data transmission time and processing load increase
Solution Approach 1:
The system selectively extracts only the necessary log data related to detected abnormalities rather than transmitting all recorded log data. When an abnormality is detected, the extraction condition determination unit identifies which log data are relevant based on the abnormality type and device group relationships, extracting only those specific records. This significantly reduces data transmission time while preserving all essential diagnostic information needed for troubleshooting.
Solution Approach 2:
The system performs preliminary classification and organization of log data by device type and group relationships before an abnormality occurs. Extraction conditions are pre-defined for different abnormality types and device groups, allowing the system to quickly retrieve and transmit only relevant log data when an abnormality is detected, rather than processing and filtering large volumes of data in real-time.
3Measurement precision
If extraction conditions are defined for each individual device type, then precise log data extraction is achieved, but configuration complexity increases
Solution Approach 1:
The patent implements device group relationships where multiple device types can be organized into groups with shared extraction conditions. Instead of defining separate extraction conditions for each individual device type, the system allows extraction conditions to be defined at the group level, making them universally applicable to all devices within that group. This reduces configuration complexity while maintaining precise extraction capability through the hierarchical structure of device groups and their associated extraction rules.
Data Source
AI summary
A system controller configured to centrally control control target devices used in surgery includes a communicating device capable of communicating with a plurality of control target devices, an extraction condition memory capable of storing extraction conditions, and a processor including hardware. The processor detects an abnormal state of connected control target devices. The processor performs recording processing for recording operation information relating to operation on the control target devices as log data into a predetermined storage apparatus. When a device abnormality detecting section detects an abnormal state, the processor extracts relevant information related to the abnormal state from log data.