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The Aware™ Transport Monitor System (includes Aware POD and Aware Transport Monitor) is intended for use under the direct supervision of a licensed healthcare practitioner, or by personnel trained in proper use of the equipment in a professional medical facility, such as a hospital, clinic, surgical center or doctor's office. It can be used in multiple areas such as operating room (OR), post anesthesia care unit (PACU), emergency department (ED), critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care.

The Aware POD is intended to provide uninterrupted acquisition of physiologic parameter data on adult, pediatric and neonatal patients during non-transport/bedside and transport patient care episodes. Physiological parameter data acquired by the Aware POD includes ECG, invasive blood pressure, non-invasive blood pressure, pulse oximetry, temperature, and respiration. This device acquires, processes and stores information for all aforementioned parameters and transmits this information to a transport or bedside central processing unit for viewing and alarm surveillance purposes.

The Aware Transport Monitor is intended for use as part of a transport monitoring system for intra-healthcare facility transport. When used with the Aware POD or the TRAM acquisition module, this device is intended to provide uninterrupted monitoring of physiologic parameter data for adult, pediatric, and neonatal patients during transport from one area of the healthcare facility to another. Physiological parameter data includes ECG, invasive blood pressure, non-invasive blood pressure, pulse oximetry, temperature, and respiration. Both the Aware POD and TRAM acquisition module acquire, process and store information for all aforementioned parameters.

The Aware™ Transport Monitor System is a complete, high-acuity patient monitoring system composed of two main parts: the Aware POD and Aware Transport Monitor.

The Aware™ Patient Observation Device (POD) is an acquisition module that measures and processes a patient's physiological parameters. Physiological parameter data acquired by the Aware POD includes 12 Lead ECG, respiration, up to four invasive blood pressure channels (as options), non-invasive blood pressure, Masimo SpO2, dual temperature and cardiac output (optional).

The Aware™ Transport Monitor is designed to be lightweight, rugged, and provide continuous monitoring capability when coupled with a compatible acquisition module. The Aware Transport Monitor is designed to facilitate quick, simple connection of either the Aware POD or TRAM 2001 module (K011000). The Aware Transport Monitor provides a means to alert the clinician of limit violations via audible and visual alarms.

Acceptance Criteria and Device Performance Study for Aware™ Transport Monitor System

This document outlines the acceptance criteria and a summary of the study used to demonstrate that the Aware™ Transport Monitor System meets these criteria, based on the provided 510(k) summary.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly present a table of specific numerical acceptance criteria. Instead, it broadly states that the device "complies with the voluntary standards as detailed in Section 9 of this submission" and that "The results of these measurements demonstrated that the Aware Transport Monitor System is as safe, as effective, and performs as well as the predicate devices."

Based on the information available, the acceptance criteria are implicitly tied to a combination of:

• Compliance with Voluntary Standards: Adherence to established industry and regulatory standards relevant to physiological patient monitors. (Specific standards are not detailed in the provided text.)
• Equivalency to Predicate Devices: Performance characteristics (safety and effectiveness) should be comparable to the legally marketed predicate devices (K011000 TRAM 2001 Module).

Implicit Acceptance Criteria & Reported Performance:

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

The document indicates "Clinical Use Validation" and various levels of testing (unit, integration, final acceptance, performance, safety, environmental). However, it does not specify a distinct "test set" and a corresponding sample size for clinical validation nor does it provide details on the data provenance (e.g., country of origin, retrospective or prospective nature of clinical data). The testing described seems to be more focused on engineering verification and validation rather than a separate clinical performance study with a defined patient cohort.

3. Number of Experts Used to Establish Ground Truth and Qualifications

The provided text does not mention the use of experts to establish ground truth for a test set, nor does it specify their number or qualifications. The clinical validation is mentioned, but the methodology for assessing clinical outcomes or establishing "truth" for the device's physiological parameter measurements is not detailed beyond general testing.

4. Adjudication Method

The document does not describe any adjudication method used for a test set.

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

No MRMC comparative effectiveness study is mentioned. The device is a physiological monitor, not an imaging or diagnostic AI-assisted device where such studies are typically performed to assess human reader improvement. There is no information about AI assistance or human-in-the-loop performance improvement.

6. Standalone (Algorithm Only) Performance Study

Given that the device is a physiological patient monitor, its primary function is data acquisition and display. The concept of "standalone (algorithm only)" performance without a human in the loop is not directly applicable in the same way it would be for an AI diagnostic algorithm. The device's performance is inherently tied to its ability to accurately measure and process physiological parameters, which is implicitly evaluated through the "performance testing" and "clinical use validation." However, a specific standalone performance study report with metrics akin to AI algorithms is not provided.

7. Type of Ground Truth Used

The type of "ground truth" used for validating the accuracy of physiological parameter measurements is not explicitly stated. For physiological monitors, ground truth typically involves comparison against established reference devices or invasive measurements (e.g., arterial line for blood pressure, direct temperature probes, or gold-standard ECG recording systems). The document generally refers to "measurements" and "clinical use validation" without specifying the reference methods.

8. Sample Size for the Training Set

The document does not refer to a "training set" as the device is not described as utilizing machine learning or AI that would require a distinct training phase with a dataset. The development process mentions "Requirements Reviews," "Design Reviews," and various levels of testing, which are standard for medical device engineering but do not imply an AI model training paradigm.

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

As there is no mention of a training set for an AI or machine learning model, the method for establishing ground truth for such a set is not applicable and hence not provided.

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