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The SmartMonitor® 2 Professional Series Infant Apnea Monitor is intended for use in the continuous monitoring of respiration, heart rate, and SpO2 of infant patients in a hospital or home environment. The monitor detects and alarms for periods of central apnea, high or low heart rate, and high or low saturation.

The SmartMonitor 2PS is a microprocessor-based, software-controlled device intended for use as an infant apnea monitoring system.

The SmartMonitor 2PS is designed to analyze and record physiologic signals (ECG, respiration, SpO2 and pulse rate) acquired from infant patients during sleep. Its primary function is to analyze the physiologic signals and generate visual and audible alarm indications upon detection of physiologic events such as central apnea, bradycardia, and high or low SpO2. The portable design of the device facilitates its use in a hospital or in a home environment.

ECG and respiration signals are acquired via a single transducer set attached to the patient and directly connected to the monitor. The measurement method used to derive the respiration signal is Transthoracic Impedance. SpO2 and plethysmographic pulse rate acquired via an oximeter finger sensor. The acquired physiologic signals are classified and stored for use at a later time.

A Host PC may interface to the SmartMonitor 2PS via a direct serial connection for the purpose of downloading the monitor's previously stored data and/or retrieving the monitor's real time data.

The SmartMonitor 2PS is a compact, lightweight unit. Two front panel connectors are provided for the patient sensor input. The sensor connectors and associated sensor plugs are individually keyed to prevent improper insertion.

The SmartMonitor 2 is approximately 7.4 inches wide, 10 inches deep and 2.5 inches high. It weighs approximately 2 pounds.

The enclosure for the monitor is constructed of plastic injection molded materials. Components and assemblies are securely mounted inside. The enclosure design is resistant to the entrance of liquids and other foreign materials.

The provided text describes the SmartMonitor 2 Professional Series (SmartMonitor 2PS), an infant apnea monitor with an internal oximeter. It is a 510(k) submission seeking to extend the existing claims of the monitor to include an internal pulse oximeter.

However, the provided text does not contain the detailed information required to fill out all sections of your request regarding acceptance criteria and the study proving the device meets those criteria. Specifically, it lacks:

• A table of acceptance criteria and reported device performance.
• Details about sample size, data provenance, number or qualifications of experts for ground truth, adjudication methods, or specific study designs (MRMC or standalone).
• Information on the training set or how its ground truth was established.

The text primarily focuses on:

• The product's proprietary and common name, classification, and predicate devices.
• The reason for submission (additional or expanded indications).
• Device description and its intended use (Indications for Use).
• General statements about design verification testing, IEC 60601-1 and 60601-2 testing, and a Risk Traceability Matrix to assure safety and mitigate hazards.

Based on the information available, here's what can be provided:

Acceptance Criteria and Device Performance Study Information

The document mentions that the functionality of the design was verified through "design verification testing" and safety was assured by "IEC 60601-1 and 60601-2 testing" and a "Risk Traceability Matrix." However, it does not provide specific acceptance criteria or the reported device performance from these tests. It focuses on demonstrating substantial equivalence to predicate devices (Respironics SmartMonitor 2 and Masimo SET Pulse Oximeter) rather than a detailed performance study proving specific acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance

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

This information is not provided in the document. The text broadly mentions "design verification testing" but does not specify the sample size of patients or data used, nor its provenance (country, retrospective/prospective).

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 information is not provided in the document. The submission focuses on device functionality and safety standards compliance, not on expert-adjudicated ground truth for a test set.

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

This information is not provided in the document.

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

This information is not applicable/provided. The SmartMonitor 2PS is an apnea monitor with an internal oximeter, not an AI-assisted diagnostic tool for human readers. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this device's description.

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

The context suggests the device operates as a standalone monitor, analyzing physiological signals and generating alarms. The entire device essentially represents the "standalone" performance, as it directly monitors and alarms without "human-in-the-loop" performance for its primary function of detecting and alarming. However, the text does not detail specific algorithm-only performance studies with metrics; it broadly states "design verification testing."

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

This information is not explicitly provided in the document. For an apnea monitor, ground truth would typically involve independently confirmed physiological events (e.g., using polysomnography or other gold-standard monitoring) against which the device's detections are compared. The text only mentions "analyzing physiologic signals and generating visual and audible alarm indications upon detection of physiologic events."

8. The sample size for the training set

This information is not provided in the document. The device is microprocessor-based and software-controlled; while software likely involves development and testing, typical "training sets" as seen in machine learning contexts are not mentioned.

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

This information is not provided in the document.

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