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510(k) Data Aggregation
(164 days)
For use in cardiac electrophysiology procedures to assist in the diagnosis of complex arrhythmias that may be difficult to identify using conventional mapping systems alone (i.e., linear mapping catheters). The FIRMap Catheter may also be used for delivery of externally generated pacing stimuli.
The catheter is used in cardiac electrophysiology procedures to assist in the diagnosis of complex arrhythmias that may be difficult to identify using conventional mapping systems alone (i.e., linear mapping catheters). The FIRMap Multiple Electrode Recording and Pacing Catheter may also be used for delivery of externally generated pacing stimuli.
The FIRMap catheter is delivered to the heart chamber via an intravascular sheath. After the catheter is positioned the sheath is withdrawn enough to allow the basket to expand and the electrodes to contact the heart wall.
The provided text is a 510(k) Summary for the FIRMap Catheter, which outlines the device's technical characteristics and the performance testing conducted to demonstrate its substantial equivalence to a predicate device. This document describes a medical device, not an AI/ML powered device, and therefore the relevant information for an AI/ML acceptance criteria and study cannot be extracted.
Reasoning for inability to extract AI/ML specific information:
The document describes the FIRMap Catheter, an electrode recording catheter used in cardiac electrophysiology procedures. The testing described is focused on the mechanical integrity and functionality of the catheter's basket subassembly, which are hardware-related aspects (e.g., radial force, spline stiffness, introduction/withdrawal cycling, and in-vivo testing in a "Pancake Atrium").
There is no mention of:
- An algorithm or AI/ML model.
- Data provenance, test sets, or training sets in the context of an AI/ML model.
- Expert interpretation of AI/ML outputs or ground truth establishment for AI/ML.
- Multi-reader multi-case studies related to AI/ML assistance.
- Standalone performance of an algorithm.
The document entirely focuses on the physical device and its mechanical/electrical performance, not on software or AI capabilities.
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