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The GALILEO Gold ventilator is intended to provide positive pressure ventilatory support to adult, pediatric, infant, and neonatal patients. The device is intended for use in the hospital and institutional environment where healthcare professionals provide patient care, including use at the patient bedside and for intrafacility transport, provided compressed gas is supplied. The device is not intended for transportation outside the hospital or for use in the home environment.

The GALILEO Gold is an electronically controlled pneumatic intensive care ventilation system. It uses oxygen and air to ventilate adult, pediatric, infant, and neonatal patients. It is powered by ac with battery backup to protect against power failure or unstable power and to facilitate intrahospital transport. The GALILEO Gold's pneumatics deliver gas, and its electrical systems control pneumatics, monitor alarms, and distribute power. The user interface consists of a LCD-display with touch screen, keys, and a press-and-turn knob. The GALILEO Gold provides audible and visual patient- and ventilator-related alarms.

The provided text describes the HAMILTON MEDICAL GALILEO Gold ventilator, but it does not contain the detailed information necessary to complete a table of acceptance criteria and the study that proves the device meets those criteria, as typically required for AI/machine learning device submissions.

The document is a 510(k) summary for a continuous ventilator, which is a hardware medical device rather than an AI/ML-driven software device. Therefore, the information provided focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics and nonclinical performance (waveform testing), rather than on specific acceptance criteria and detailed study results for an AI algorithm's performance.

Here's a breakdown of why the requested information cannot be fully provided based on the input:

• Acceptance Criteria and Device Performance: The document states "The ventilator was subject to wave-form performance testing as described in the standard F1100 - 90. The data provided from these tests, were shown to be substantially equivalent to a legally marketed device." It does not list specific numerical acceptance criteria (e.g., accuracy, sensitivity, specificity) or the quantitative reported performance of the device against such criteria.
• Sample Size for Test Set and Data Provenance: No information on a "test set" in the context of AI/ML performance evaluation is provided. The testing mentioned is "wave-form performance testing," which likely involves engineering tests rather than patient studies for algorithm validation.
• Number of Experts and Qualifications: Not applicable to this type of device submission.
• Adjudication Method: Not applicable.
• MRMC Comparative Effectiveness Study: Not applicable, as this is a hardware ventilator, not an AI-assisted diagnostic tool.
• Standalone Performance: While the device has standalone performance in terms of its ventilation capabilities, it's not a standalone algorithm in the AI/ML sense.
• Type of Ground Truth: Not applicable in the context of AI/ML. The "ground truth" for a ventilator would be its physical performance against engineering standards.
• Sample Size for Training Set & How Ground Truth for Training Set was Established: Not applicable, as this is not an AI/ML device.

In summary, the provided 510(k) for the GALILEO Gold ventilator is for a traditional medical device and does not include the type of AI/ML performance acceptance criteria, study details, or ground truth methodologies that your request anticipates. The approval is based on substantial equivalence to predicate devices and nonclinical performance testing against industrial standards (like F1100-90) for its ventilation functions and safety.

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The GALILEO Gold ASV ventilator is intended to provide positive pressure ventilatory support to adults, pediatrics, and infants. The device is intended for use in the hospital and institutional environment where healthcare professionals provide patient care, including use as a patient bedside for intra-facility transport, provided compressed gas is supplied. The device is not intended for transportation outside the hospital or for use in the home environment.

The GALILEO Gold N is a software modified version of the legally marketed device GALILEO Gold (K040574). The GALILEO Gold SV is a full-functioned intensive care ventilator. It can ventilate adult, pediatric and infant patients. The GALILEO Gold*ASV offers a full spectrum of modalities, from the conventional to the new included Adaptive Support Ventilation, ASV.

ASV is designed to maintain at least the minute ventilation set by the clinician. ASV does this without exceeding a preset plateau pressure. ASV provides full ventilation in apnea or low-drive conditions, then automatically returns control to the patient as spontaneous ventilation begins. ASV works automatically by continuous repetition of 3 steps:

• 1. Assess the patient breath-by-breath.
• 2. Calculate an optimal breath pattern based on the minimal work of breathing method by Otis (J Appl Physiol 1950: 592-607).
• 3. Approach the target by automatically adjusting mandatory rate and inspiratory pressure.

The provided document focuses on the Hamilton Medical GALILEO GoldASV ventilator and its substantial equivalence to predicate devices, rather than an AI-powered diagnostic device. Therefore, a direct application of the requested acceptance criteria and study details for an AI-powered device is not fully applicable.

However, I can extract the relevant information regarding the performance and safety assessment of the GALILEO GoldASV ventilator, specifically its new ASV mode, and structure it as closely as possible to your request for an AI device, by interpreting "acceptance criteria" as the demonstration of safety and effectiveness.

Here's an analysis based on the provided text:

Device: GALILEO GoldASV Ventilator (specifically the new ASV mode)

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Sample Size: Not explicitly stated as a numerical value for a "test set" in the context of an AI study. The document refers to "Performance data of patients with normal lungs and diverse respiratory failures, ventilated with the ASV technology."
• Data Provenance: Not specified, but likely from clinical settings where the ASV technology was used. No country of origin is mentioned, nor is it explicitly stated as retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This concept is not applicable here as the device is a ventilator, not an AI diagnostic system requiring expert-established ground truth for a test set. The efficacy and safety are assessed through engineering tests and clinical observations.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable. The assessment involves performance testing and clinical observation, not expert adjudication of diagnostic outcomes.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable. This is a ventilator, not an AI-assisted diagnostic tool for human readers. The document highlights "User assessments show that the extended ASV mode is as safe, as effective, and performs clinically as well as the predicate devices," suggesting a comparison of the device's performance to existing ones, but not an MRMC study with human readers and AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

The device itself is a standalone ventilator with an automated ASV mode (a closed-loop controller). Its performance was evaluated on its own ("The performance/qualification testing of the new added GALILEO Gold feature ASV has been done on modular, integration and system level"). The ASV mode operates automatically by continuous repetition of steps, implying an algorithm-only function once set up by the clinician.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

The "ground truth" for a ventilator's performance is typically established through:

• Engineering specifications and testing (e.g., meeting flow and pressure targets).
• Physiological outcomes data (e.g., maintained minute ventilation, not exceeding plateau pressure, automatic control return as spontaneous ventilation begins).
• Clinical observations and "no adverse effects, complications or required reintubation" as reported from patient data.

8. The sample size for the training set

Not applicable. This is a medical device, not an AI model trained on a specific dataset. The "training" for the ventilator's algorithm is embedded in its design based on physiological principles (e.g., minimal work of breathing method by Otis).

9. How the ground truth for the training set was established

Not applicable, as it's not an AI training set in the conventional sense. The "ground truth" for the ASV algorithm's behavior is rooted in established physiological models and engineering principles to achieve desired ventilatory support.

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The Galileo Gold ventilator is intended to provide positive pressure ventilatory support to Adults, Pediatrics and Infants. The device is intended for use in the hospital and institutional environment where healthcare professionals provide patient care, including use as a patient bedside or for intra-facility transport, provided compressed gas is supplied. The device is not intended for transport, outside the hospital or for use in the home environment.

The Galileo ventilator is a legally marketed intensive care ventilator (K982910, K001686). The four modifications included in this application are purely software-related and do not change the hardware of the Galleo Gold ventilator. This application is for the following options to the Galileo Gold ventilator: DuoPAP and APRV modes, NIV mode, MMV+ mode, and TRC feature.

Here's a summary of the acceptance criteria and the study information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes modifications to an existing ventilator (GALILEO Gold) rather than a novel device requiring specific clinical performance metrics like sensitivity, specificity, or accuracy for a diagnostic task. Therefore, the "acceptance criteria" here relate to demonstrating substantial equivalence to predicate devices and ensuring the new software features do not introduce safety or effectiveness concerns. The performance is reported in terms of successful testing and comparison to predicate devices.

2. Sample Size Used for the Test Set and Data Provenance:

The document describes software modifications to an existing device, and the testing focuses on functional verification and validation, rather than clinical trials with patient data.

• Test Set Sample Size: Not applicable in the traditional sense of a clinical trial test set. The "test set" consisted of various test cases, scenarios, and configurations for modular, integration, and system testing of the software features. Specific numbers of test cases or their characteristics are not provided in this summary.
• Data Provenance: The testing was conducted internally by Hamilton Medical AG (Switzerland) as part of the device modification and regulatory submission process. It is a prospective test in the sense that custom tests were designed and executed to verify the functionality of the new software. There is no indication of retrospective patient data being used.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

Not applicable in the context of this type of device submission. Ground truth, in this context, would refer to the expected functional behavior and performance defined by engineering specifications, relevant standards (like ASTM F1100-93), and comparisons to legally marketed predicate devices. This is established through engineering design, regulatory standards, and comparison to existing, approved devices, not via expert consensus on clinical findings.

4. Adjudication Method for the Test Set:

Not applicable. The testing described is a verification and validation process against predefined specifications and predicate devices, not subjective clinical assessment requiring adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study assesses how human readers perform with and without an AI assistant, which is relevant for diagnostic or interpretive AI devices. The GALILEO Gold ventilator modification is a software update for a therapeutic device, not a diagnostic AI system.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

Yes, in a sense. The core of the testing involved evaluating the new software features in a standalone capacity (i.e., the algorithm/software's execution and its impact on the ventilator's function) without explicitly human-in-the-loop performance studies as would be conducted for AI diagnostic tools. The "System tests were executed with a complete instrument, i.e. the new software together with the existing Galileo Gold hardware," which assesses the algorithm's performance within the device itself.

7. Type of Ground Truth Used:

The "ground truth" for this submission is based on:

• Engineering Specifications and Design Requirements: The new software features were developed to specific engineering criteria.
• Performance Standards: Compliance with relevant standards, such as ASTM Standard F1100-93 for ventilator performance.
• Functional Equivalence to Predicate Devices: The detailed comparison tables demonstrate that the new features function equivalently and do not introduce significant differences compared to the predicate devices.
• Absence of Deviations: The successful completion of modular, integration, and system testing without observed or documented performance deviations.

8. Sample Size for the Training Set:

Not applicable. This device is a medical ventilator with software modifications, not a machine learning or AI algorithm that requires a training set of data for learning patterns. The software is programmed with specific logic and control algorithms.

9. How the Ground Truth for the Training Set Was Established:

Not applicable, as there is no training set for this type of device. The software's "logic" is established through conventional software engineering and ventilator control algorithms, based on physiological principles and intended clinical functionality.

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