Search Results

The Canary Tibial Extension (CTE) with Canary Health Implanted Reporting Processor (CHIRP) System is intended to provide objective kinematic data from the implanted medical device during a patient's total knee arthroplasty (TKA) post-surgical care. The kinematic data are an adjunct to other physiological parameter measurement tools applied or utilized by the physician during the course of patient monitoring and treatment postsurgery.

The device is indicated for use in patients undergoing a cemented TKA procedure that are normally indicated for at least a 58mm sized tibial stem extension.

The objective kinematic data generated by the CTE with CHIRP System are not intended to support clinical decision-making and have not been shown to provide any clinical benefit.

The CTE with CHIRP System is compatible with Zimmer Persona® Personalized Knee Svstem.

The Canary Tibial Extension is a physical implant component that is attached to the Zimmer Biomet Persona® tibial baseplate (K113369) to form the patient's tibial knee prosthesis. Like a traditional tibial extension, the CTE provides additional stability to the replacement knee joint. In addition, the software and electronics embedded within the CTE collect the patient's functional movement and gait parameter information post-surgery. The CTE is provided sterile via Ethylene Oxide (EtO).

The CHIRP system collects unprocessed 3D accelerometer and 3D gyroscopic sensor data over the course of a day.

The electronic and other unique elements incorporated within the CTE implant include an antenna, X-ray ID, printed circuit assembly, three-axis gyroscope, three-axis accelerometer, and a Lithium Carbon Mono-Fluoride (CFx) battery.

The CTE with CHIRP system is composed of external base station units with embedded firmware that facilitate communication with the CTE implant. The main function of the base station units is to act as a conduit to receive and transmit encrypted raw kinematic data from the CTE to the Cloud Based software system.

The Operating Room (OR) Base Station (BS1) subsystem consists of a laptop computer with the customized OR Application (OR App) software to initialize the CTE implant and record implant and procedural information, an OR base station unit, a bar code reader to incorporate TKA component and CTE serial number information, and USB cables to attach the OR base station unit and bar code reader to the computer.

The Home Base Station (BS2) subsystem is located in the patient's home, is set up by the patient prior to the date of surgery, and is used to transmit patient's gait and activity information collected by the CTE. BS2 consists of a Home Base Station unit, a USB power and data cable, and a power adapter. These items are used in concert with a USB-enabled personal computer and the patient's home wireless Internet connection.

The Cloud subsystem is intended to receive and store all healthcare professional (HCP) and patient data for pre-operative, day of operation, and post-operation activities, including unprocessed, patient kinematic data from the CTE implant. The post-operation processed, patient Canary Medical Gait Parameter (CMGP) data will be used by HCPs to monitor the patient's post-TKA procedure function as an adjunct to other physiological parameter measurement tools. The Cloud is accessible through a browser-based web application.

Manual Instruments and Accessories: Impaction Sleeve, Canary Tibia Cut Guide (5 DEGREE - L/R), Canary Drill Bit, CTE Provisional, CTE Template.

The provided text is a De Novo classification request for the Canary Tibial Extension (CTE) with Canary Health Implanted Reporting Processor (CHIRP) System. It details the device, its intended use, background, and various non-clinical/bench studies conducted to demonstrate its safety and performance.

However, the document does not contain information about acceptance criteria and a study that specifically proves the device meets those acceptance criteria in the context of an AI/ML algorithm's performance on a test set, expert ground truth establishment, or human reader improvement with AI assistance (MRMC study).

The "PERFORMANCE TESTING - BENCH" section describes various engineering and design validation tests (e.g., mechanical, electrical, IMU performance, cadaver studies, gait parameter validation), but these are primarily focused on the device's physical and functional integrity, data accuracy against a "gold standard" motion capture system, and surgical usability, rather than the performance of an AI/ML component on a distinct test set with expert-adjudicated ground truth.

Specifically, the "Gait Parameters Design Validation" section describes a study comparing the device's kinematic measurements (walking speed, cadence, stride length, Knee ROM, Tibia ROM) to a "gold standard" kinematic gait measurement system. This is the closest to a performance study mentioned, but it's measuring the accuracy of sensor data processing, not an AI/ML diagnostic or classification output.

Therefore, for the requested information regarding AI/ML acceptance criteria and a study proving it meets them, this document does not provide the necessary details. There is no mention of:

• A table of AI/ML acceptance criteria and reported device performance against those criteria.
• Sample sizes for an AI/ML test set (only for the gait validation study and bench tests).
• Data provenance for an AI/ML test set.
• Number/qualifications of experts for AI/ML ground truth.
• Adjudication methods for AI/ML ground truth.
• MRMC comparative effectiveness study for AI assistance.
• Standalone AI algorithm performance.
• Type of ground truth for an AI/ML model (beyond the "gold standard" motion capture for kinematic data validation).
• Training set size or ground truth establishment for an AI/ML model.

The document focuses on the hardware, embedded firmware, and system-level functional performance. The "Canary Medical Gait Parameters (CMGP)" application is mentioned as calculating kinematic gait parameters from raw sensor data, but its design validation is based on comparing its output to a motion capture system, not an AI/ML classification task with an independent test set and expert ground truth in the way typically seen for diagnostic AI.

Conclusion: The provided text does not contain the information required to answer the prompt regarding AI/ML acceptance criteria and a study proving the device meets them. The device described appears to be a sensor-based measurement system where the "performance" relates to the accuracy and reliability of its kinematic data collection and processing, not an AI/ML diagnostic or classification system as implied by the prompt's detailed questions on expert adjudication, MRMC studies, and training/test sets for an AI model.

Ask a specific question about this device