Search Results

The Philips Medical Systems Integrated Patient Monitoring System (IPMS) is intended to monitor the heart rhythm and other vital signs for a patient undergoing an MRI procedure and to provide signals for synchronization for the MRI scanner.

The Philips Medical Systems Integrated Patient Monitoring System (IPMS) is a significant modification of the Invivo Research Omni-Trak™ 3150/3155 Series Patient Monitoring System. This device has been integrated into the Philips Physiotrak patient gurney used with the Philips MRI System. The Philips Medical Systems Integrated Patient Monitoring System is intended to monitor the heart rhythm and other vital signs for a patient undergoing an MRI procedure and to provide signals for synchronization for the MRI scanner. The IPMS works on DC (battery) power supplies and monitors ECG, non-invasive blood pressure, SPO2, respiration and temperature. This information can be displayed either at the monitor or remotely. The monitor sounds an alarm if any monitored parameter falls outside the range indicated by the alarm limits. The alarm limits is programmable either manually or programmally based on the current value of the parameter(s). This monitoring system is MRI-compatible. It utilizes technology from the Invivo Research Omni-Trak™ 3150/3155 Series Patient Monitoring System and the Invivo Research Millennia Patient Monitor. The IPMS consists of three major component parts; the MCB (Patient Connector Box), MEB (Monitoring Electronics Box), and MDCU (Monitoring Display and Control Unit) which are integrated into the Phillips Physiotrak patient gurney.

The provided text describes the acceptance criteria and a summary of performance testing for the Philips Medical Systems Integrated Patient Monitoring System (IPMS). However, it does not include a detailed study description with information like sample sizes for test and training sets, data provenance, number or qualifications of experts, adjudication methods, or MRMC comparative effectiveness studies. This document is a 510(k) summary, which typically focuses on demonstrating substantial equivalence to a predicate device rather than providing full clinical study details.

Here's the information that can be extracted from the provided text based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not specified in the document. The document states "Validation and Verification Testing confirmed that this device operates as designed and intended," but does not provide details on the number of subjects or test cases.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not specified.

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

• Not applicable/Not specified. This device is a physiological patient monitor, and its performance is typically evaluated against calibrated reference instruments or simulated physiological signals, not human expert interpretation.

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

• Not applicable/Not specified.

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 not an AI-assisted diagnostic device. It's a physiological monitoring system.

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

• Yes, performance testing as described in the "Summary of Performance Testing" table is inherently standalone device performance. The device's accuracy for various parameters (Heart Rate, NIBP, SpO2, Respiration, Temperature) is specified.

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

• The ground truth would be based on calibrated reference standards and established physiological benchmarks. For example, heart rate accuracy would be compared against an ECG simulator or directly measured heart rate from a known source; blood pressure against a calibrated sphygmomanometer; SpO2 against a co-oximeter in controlled studies; temperature against a calibrated thermometer.

8. The sample size for the training set

• Not applicable/Not specified. This device is not described as utilizing a machine learning algorithm that requires a training set in the conventional sense. Its design and performance are based on engineering principles and established physiological measurement techniques.

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

• Not applicable.

Ask a specific question about this device