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The INFINITY Modular Monitors are intended for multi-parameter patient monitoring. The devices will produce visual and audible alarms if any of the physiological parameters monitored vary beyond preset limits and timed or alarm recordings will be produced. These devices will connect to an R50 Bedside recorder, either directly or via the INFINITY Network.

The INFINITY Modular monitors are capable of monitoring:

• Heart rate .
• Respiration rate .
• Invasive pressure .
• Non-invasive pressure .
• Arrhythmia .
• Temperature .
• Cardiac output .
• Arterial oxygen saturation .
• Pulse rate .
• Apnea .
• ST Segment Analysis ●
• 12-Lead ST Segment Analysis
• tcn02/tcp(02 .
• EEG signals .
• FiQ2 .

The SCIO and MultiGas/MultiGas+ modules sample breathing gases from adults and pediatrics. The gas modules continuously measure and produce real time and derived gas information of CO2, NO, O2 and one of the anesthetic agents, halothane, isoflurane, Enflurane, Sevoflurane and Desflurane in any mixture and communicates real time and derived gas information to the INFINITY monitors.

With etCO2 the monitors can measure end tidal carbon dioxide, inspired carbon dioxide, and respiration with etCO2 and instream or side-stream measurement mode; and with etCO2+Respiratory Mechanics, spirometry and carbon dioxide can be monitored.

The monitors can interface with specific third party devices via an MIB protocol converter.

The devices are intended to be used in the environment where patient care is provided by Healthcare Professionals, i.e. Physicians, Nurses, and Technicians, who will determine when use of the device is indicated, based upon their professional assessment of the patient's medical condition.

The devices are intended to be used on Adult, Pediatric and Neonatal populations, with the exception of the parameter Cardiac Output, ST Segment Analysis, and arrhythmia which are intended for use in the adult population only, and tcpO2 which is to be used in the neonatal population only when the patient is not under gas anesthesia.

The INFINITY Modular monitor VF4 software release includes a modification in support of the Scio gas module for dual-anesthetic agent display.

The provided document describes a Special 510(k) Notification for modifications to the INFINITY Modular MonitorsVF4 software release, specifically in support of the Scio gas module for dual-anesthetic agent display. This is a modification to an existing, legally marketed device, and the submission primarily focuses on demonstrating that the modified device is as safe and effective as the previous versions.

Therefore, the document does not contain information about the development and testing of a new AI/ML device that would typically involve acceptance criteria, performance metrics, ground truth establishment, or clinical studies involving human readers. Instead, it describes a verification and validation study to ensure that the modifications to the existing software and hardware do not introduce new safety or efficacy issues.

Here's an analysis based on the information provided, recognizing that the scope is for device modification rather than a new AI/ML product:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics in the format of a table. Instead, it refers to:

The implicit acceptance criterion is that the modified device performs similarly to or better than the predicate device without introducing any new safety or efficacy concerns. The "reported device performance" is a qualitative statement of conformity.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify the sample size for any test set or the data provenance. It generally states that "verification and validation testing of VF4 software" was performed. Given this is a software modification for an existing monitor, the testing would likely involve simulation, bench testing, and potentially some form of in-house functional testing using synthetic or recorded physiological data, but no details are provided.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This is not applicable to the type of submission described. "Ground truth" in the context of device performance, especially for AI/ML, refers to a definitive correct answer for a given input. For this type of physiological monitoring device modification, the "ground truth" would be the known physiological parameters (e.g., gas concentrations) used during testing, established by calibrated reference equipment, not by human experts.

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

Not applicable. Adjudication methods like 2+1 or 3+1 are typically used in studies where human readers interpret data, and there's a need to resolve discrepancies. This submission pertains to software and hardware modifications to a physiological monitor, not diagnostic image interpretation.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is relevant for AI-powered diagnostic aids where human interpretation is involved. The INFINITY Modular Monitors are physiological monitors that directly display parameters. The modifications relate to displaying dual-anesthetic agents.

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

The document implies that the device's performance (i.e., its ability to monitor and display physiological parameters) was assessed independently through "verification and validation testing." However, it does not explicitly use the term "standalone performance" in the context of an algorithm. The device itself, as a monitor, operates in a "standalone" fashion by measuring and displaying data, and the software modifications were tested to ensure this function remains effective.

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

The type of "ground truth" for a physiological monitor would typically be measurements from calibrated reference instruments or known physiological states (e.g., a gas mixture with a known concentration of anesthetic agents). The document does not explicitly state how ground truth was established, but it would be part of standard verification and validation procedures for such devices. For example, to test the accuracy of gas measurements, the Scio module would be exposed to precisely mixed gas samples with known concentrations, and the device's readings would be compared to these known values.

8. The sample size for the training set

Not applicable. This is a modification to an existing physiological monitor, not an AI/ML product that undergoes a training phase with a dataset.

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

Not applicable. As above, there is no training set mentioned or implied for this type of device modification.

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The INFINITY Modular Monitors are intended for multi-parameter patient monitoring. The devices will produce visual and audible alarms if any of the physiological parameters monitored vary beyond preset limits and timed or alarm recordings will be produced. These devices will connect to an R50 Bedside recorder, either directly or via the INFINITY Network.

The INFINITY Modular monitors are capable of monitoring:

• Heart rate
• Respiration rate
• Invasive pressure
• Non-invasive pressure
• Arrhythmia
• Temperature
• Cardiac output
• Arterial oxygen saturation
• Pulse rate
• Apnea
• ST Segment Analysis
• 12-Lead ST Segment Analysis
• tcp02/tcpC02
• EEG signals
• FiO2

The SCIO and MultiGas/MultiGas+ modules sample breathing gases from adults and pediatrics. The gas modules continuously measure the content of CO2, N2O, O2 and one of the anesthetic agents, halothane, isoflurane, Enflurane, Sevoflurane and Desflurane in any mixture and communicates real time and derived gas information to the INFINITY monitors.

With etCO2 the monitors can measure end tidal carbon dioxide, inspired carbon dioxide, and respiration rate in either mainstream or side-stream measurement mode; and with etCO2+Respiratory Mechanics, spirometry and carbon dioxide can be monitored. The monitors can interface with specific third party devices via an MIB protocol converter.

The VF4 release of the INFINITY Modular monitors supports the "look and feel" of the Draeger Medical product line, including the Draeger logo, colors, menu structure, and physical form. An alarm indicator has been added to the top center of the device that illuminates in red or vellow for the purpose of displaying both life threatening and serious alarms respectively.

Additional minor software modifications have been implemented that primarily address customer requested enhancements.

The provided text is a 510(k) summary for the INFINITY Modular Monitors with VF4 Modifications. This document describes a modification to an existing medical device and focuses on demonstrating that the modified device is as safe and effective as its predicate device. It does not contain information about the development and testing of a new AI/Machine Learning algorithm for a diagnostic or predictive task.

Therefore, many of the requested criteria related to performance metrics, sample sizes for AI model training/testing, expert consensus for ground truth, and MRMC studies are not applicable to this document as it describes a software and hardware update to a physiological monitor, not an AI-powered diagnostic device.

Here's an analysis of the available information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not specify quantitative acceptance criteria in terms of performance metrics (like sensitivity, specificity, or accuracy) for any particular function. This is because it is a submission for modifications to an existing physiological monitor, not a new diagnostic algorithm. The acceptance "criteria" in this context would be that the modified device remains "as safe and effective" as the predicate device.

Other Requested Information (Not Applicable or Not Provided in this Document)

The following points are largely not applicable to this 510(k) submission, as it focuses on demonstrating equivalence of a modified physiological monitor rather than the performance of a new AI-powered diagnostic or predictive algorithm.

2. Sample size used for the test set and the data provenance: Not applicable. The document refers to "testing in accordance with internal design control procedures" but does not specify sample sizes of patients or data, nor the provenance of such data, as would be expected for an AI performance study.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. There is no mention of expert consensus for ground truth as this is not a diagnostic AI device.
4. Adjudication method for the test set: Not applicable.
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. The device is a physiological monitor, not an AI assistance tool for human readers.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable for a standalone AI algorithm performance, however, the "Verification and validation testing of VF4 software, as well as testing applicable to the hardware modifications" implies standalone testing of the modified device's functionality.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable in the context of a diagnostic ground truth. The "ground truth" would be the expected functional performance of the monitoring parameters based on engineering specifications and validated medical standards.
8. The sample size for the training set: Not applicable. This document does not describe the development of an AI model, and therefore, no training set for an algorithm.
9. How the ground truth for the training set was established: Not applicable.

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