Surgical Device Identification via Signal Frequency Analysis
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Solution Overview
Problem
Existing systems struggle to accurately identify and control a wide variety of surgical devices in medical and surgical environments, especially in environments that are not conducive to maintaining signal fidelity.
Innovation Solution
A system and method that uses a control console to identify surgical devices by analyzing the frequency of an identification signal, allowing the console to tailor its operation to match the specific device configuration, even in noisy environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional identification methods are used in noisy surgical environments, then device identification may fail or be inaccurate, but implementing robust frequency-based identification increases system complexity
Solution Approach 1:
The system changes the parameter used for device identification from simple signal presence to frequency characteristics. By measuring the frequency of identification signals over time and comparing against stored frequency ranges for different device types, the system achieves reliable device identification even in noisy environments where signal fidelity may be compromised.
Solution Approach 2:
The system implements feedback by continuously monitoring the frequency of identification signals and using this information to determine device type. The controller measures frequency over a predetermined time period, compares it to stored reference frequencies, and adjusts its device configuration accordingly, creating a closed-loop identification process that improves reliability.
2Adaptability or versatility
If the control console is designed to support a wide variety of surgical devices, then versatility is improved, but the complexity of managing different device configurations increases
Solution Approach 1:
The control console is designed with universal functionality to support multiple device types through a single identification interface. The system uses a standardized frequency-based identification method that works across different device configurations, allowing one system to universally identify and adapt to various surgical devices without requiring device-specific identification hardware for each device type.
Solution Approach 2:
The system manages device configuration complexity by changing the identification parameter to frequency characteristics, which provide a compact and distinguishable signature for each device type. By storing frequency ranges for different device types and comparing measured frequencies against these ranges, the system efficiently manages multiple device configurations without requiring complex identification protocols for each device.
3Reliability
If signal frequency is measured over a longer predetermined time to improve accuracy, then identification reliability improves, but the time required for device identification increases
Solution Approach 1:
The system applies partial action by measuring frequency over a predetermined time period that is sufficient to achieve reliable identification without being excessively long. This optimized measurement duration balances the need for accurate frequency determination with the requirement for quick device identification, capturing enough signal cycles to filter out noise while minimizing identification time.
Data Source
AI summary
A surgical device controlled by a control console includes a device body, an identification circuit in connection with the device body, and a communication interface. The communication interface is configured to communicatively connect the identification circuit to the control console. In response to receiving an energization signal from the control console via the communication interface, the identification circuit activates an identification signal at a fixed frequency for a predetermined period of time and communicates the identification signal to the control console via the communication interface.