(292 days)
This monitor is intended to be used for monitoring, storing, reviewing, recording, and generating alarms for multiple physiological parameters including ECG, respiration (RESP), temperature (TEMP), functional arterial oxygen saturation (Sp02), pulse rate (PR), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), expired C02, cardiac output (C.O.) and anesthetic gas (AG)of adults, pediatrics and neonates in hospital environments. The monitor is equipped with alarms that indicate system faults (such as loose or defective electrodes), physiologic parameters that have exceeded the limits set by the operator, or both.
This monitor is suitable for use in hospital environments including but not limited to OR, PACU, ICU and neonate intensive care room.
The PM-2000M Patient Monitor can perform long-time continuous monitoring of multiple physiological parameters. Also, it is capable of storing, displaying, analyzing and controlling measurements, and it will indicate alarms in case of abnormities happen.
The PM-2000M realizes the monitoring of physiological parameters by configuration with different parameter modules which include Sp02 (pulse oxygen saturation, pulse rate and Sp02 plethysmogram) with EDAN Sp02 module or Nellcor SP02 module, NIBP (systolic pressure, diastolic pressure, mean pressure and pulse rate), TEMP, ECG, RESP, C02, IBP, C.O. and AG.
The above is the maximum configuration for elite VB, the user may select different monitoring parameters in according with the requirement.
The PM-2000M is configured with a 17-inch touch screen and build-in Lithium-ion battery, Besides, and supports software upgrade online and networking
This document is a 510(k) summary for the PM-2000M Patient Monitor. It focuses on demonstrating substantial equivalence to a predicate device, rather than providing detailed acceptance criteria and a study report as typically seen for novel devices that require extensive performance validation against a defined set of criteria.
Therefore, the requested information, particularly regarding specific acceptance criteria, detailed study designs (sample size, data provenance, expert ground truth, adjudication, MRMC, or standalone performance), and ground truth establishment for novel algorithms, is not explicitly available in the provided text.
Here's an analysis based on the information provided and what can be inferred:
1. A table of acceptance criteria and the reported device performance
The document does not provide a table of
specific, quantitative acceptance criteria for each physiological parameter (ECG, SpO2, NIBP, etc.) or a corresponding reported performance from a study. The "Test Summary" lists general categories of testing:
- Software testing
- Hardware testing
- Safety testing
- Environment testing
- Risk analysis
- Final validation
This implies that the device underwent validation to ensure it meets general performance and safety standards for patient monitors, likely including accuracy and reliability benchmarks commonly applied to such devices (e.g., ISO or AAMI standards for specific physiological measurements). However, the specific metrics and thresholds are not detailed.
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 general nature of the "Test Summary" does not include details about specific test sets, their size, or the provenance of any data used for validation.
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. The document does not describe studies that would require expert-established ground truth in the way a diagnostic AI device would (e.g., for image interpretation). Patient monitors typically rely on physical measurement standards or highly accurate reference devices for ground truth during testing.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided. Adjudication methods are typically relevant for studies involving human interpretation or subjective assessments, which are not detailed here for this patient monitor.
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, an MRMC comparative effectiveness study was not done or at least not reported in this document. This type of study is usually conducted for AI-powered diagnostic aids where human readers interact with the AI. The PM-2000M is a patient monitor, and its primary function is direct physiological measurement, not aiding human readers in interpretation tasks in the same way an AI diagnostic tool would.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The document implies that standalone testing of the device's functions (measurements, alarms) was performed as part of "Software testing," "Hardware testing," and "Final validation." However, explicit details of these standalone performance metrics (e.g., accuracy of ECG measurement compared to a reference, alarm detection rates) are not provided. The focus is on substantial equivalence to a predicate device, suggesting performance was assessed against established standards for patient monitors rather than novel algorithm-specific benchmarks.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The document does not explicitly state the type of ground truth used. For patient monitors, ground truth typically involves:
- Reference devices: Highly accurate, calibrated medical devices (e.g., a reference ECG machine, a calibrated blood pressure simulator, a SpO2 simulator) that provide the true physiological values.
- Physical standards: For environmental and safety testing, compliance with relevant industry standards (e.g., for electromagnetic compatibility, temperature ranges).
8. The sample size for the training set
This information is not applicable / not provided. Patient monitors like the PM-2000M typically rely on established physics-based algorithms and signal processing techniques for physiological parameter measurement, rather than machine learning algorithms that require a "training set" of data in the common sense of AI/ML devices. Therefore, the concept of a training set of data for a "novel" algorithm is not relevant here based on the device description.
9. How the ground truth for the training set was established
This information is not applicable / not provided for the same reason as point 8.
§ 870.1025 Arrhythmia detector and alarm (including ST-segment measurement and alarm).
(a)
Identification. The arrhythmia detector and alarm device monitors an electrocardiogram and is designed to produce a visible or audible signal or alarm when atrial or ventricular arrhythmia, such as premature contraction or ventricular fibrillation, occurs.(b)
Classification. Class II (special controls). The guidance document entitled “Class II Special Controls Guidance Document: Arrhythmia Detector and Alarm” will serve as the special control. See § 870.1 for the availability of this guidance document.