Search Results

The TetraGraph Neuromuscular Transmission (NMT) Monitor is indicated for monitoring the relaxation of the patient when neuromuscular blockade is administered.

The TetraGraph Neuromuscular Transmission (NMT) Monitor (TetraGraph) is a portable, batteryoperated EMG-based neuromuscular transmission monitor for use perioperative and in recovery and critical care environments following or during the application of Neuromuscular block. TetraGraph undertakes this function by electrical stimulation of the peripheral nerve and directly measuring the evoked response of the muscles (Muscle Action Potential (MAP)), thus providing a quantitative and automatic measurement of muscle response to a stimulus using electromyography (EMG). The TetraGraph is a prescription-only medical device and is indicated for use in hospitals. TetraGraph consists of the following main components: TetraGraph Monitor, TetraSens Electrode, TetraSens Pediatric Electrode (new accessory), Philips Interface (new and optional accessory), and Pole clamp kit (optional accessory).

The provided text describes the 510(k) premarket notification for the Senzime AB TetraGraph Neuromuscular Transmission Monitor, specifically for the addition of new accessories: the TetraSens Pediatric electrode and the Philips Interface. The submission aims to demonstrate substantial equivalence to a legally marketed predicate device (TetraGraph Neuromuscular Transmission Monitor, K190795).

Based on the provided document, here's an analysis of the acceptance criteria and the study that proves the device meets them:

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

The document does not explicitly present a table of acceptance criteria with corresponding performance results in a clear, summarized format. Instead, it refers to generalized performance testing.

However, it implicitly states that performance testing was conducted for the TetraGraph with the new TetraSens Pediatric electrodes and that "all of the acceptance criteria for this device" were met. These criteria are noted to be "the same or very similar to the predicate device's specifications."

The types of performance testing mentioned are:

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 sizes used for any of the performance tests mentioned (biocompatibility, electrode testing, EMG detection, tensile strength, shelf life, software, electrical, EMC).

The data provenance is not explicitly stated in terms of country of origin or whether it was retrospective or prospective. It implies internal testing conducted by the manufacturer or their designated testing facilities.

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 tests described are largely bench-top and engineering performance tests, which typically do not involve experts to establish ground truth in the same way clinical studies or image-based diagnostics would.

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

This information is not applicable/not provided as the tests described are technical performance tests rather than clinical evaluations requiring adjudication of subjective outcomes.

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 type of study is not applicable and was not conducted. The device is a neuromuscular transmission monitor, not an AI-assisted diagnostic tool that aids human readers. The document explicitly states: "There was no clinical testing required to demonstrate that TetraGraph with the new TetraSens Pediatric electrodes is substantial equivalent to the predicate device as the predicate has similar technological characteristics."

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

The device itself is a measurement and monitoring device, an "algorithm only" or "standalone" performance would refer to its accuracy and reliability in measuring neuromuscular transmission. The performance testing (EMG evoked response detection, compliance with standards) serves this purpose by demonstrating the technical capabilities of the device in isolation, even though it's used by humans. The document confirms that "performance testing made for the device" was completed and met acceptance criteria.

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

For the described performance tests, the "ground truth" would be established by:

• Scientific Standards: For biocompatibility (ISO 10993-1) and electrode testing (ANSI/AAMI EC12: 2000), the ground truth is defined by the requirements and test methods outlined in these international and national standards.
• Engineering Specifications: For EMG evoked response detection, electrode tensile strength, and other performance tests, the ground truth is based on the device's design specifications and expected technical performance against which the measured results are compared.

8. The sample size for the training set:

This information is not applicable/not provided. The TetraGraph is a measurement device and the data provided does not suggest it uses machine learning or AI models that require a "training set" in the conventional sense. The submission focuses on hardware accessories and their technical performance.

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

This information is not applicable/not provided for the same reasons as in point 8.

Ask a specific question about this device

The BeneVision N12N15/N17/N19/N22 patient monitors are intended for monitoring, displaying, storing, alarming, and transferring of multiple physiological parameters including ECG (3-lead, 5-lead or 12-lead selectable, Arrhythmia Detection, ST Segment Analysis, QT Analysis, and Heart Rate (HR)), Respiration Rate (Resp), Temperature (Temp), Pulse Oxygen Saturation (SpO2), Pulse Rate (PR), Non-invasive Blood Pressure (NIBP), Invasive Blood Pressure (IBP), Pulmonary Artery Wedge Pressure (PAWP), Cardiac Output (C.O.), Continuous Cardiac Output (CCO), Mixed/Central Venous Oxygen Saturation (SvO2/ScvO2), Carbon Dioxide (CO2), Oxygen (O2), Anesthetic Gas (AG), Impedance Cardiograph (ICG), Bispectral Index (BIS), Respiration Mechanics (RM), Neuromuscular Transmission Monitoring (NMT), Electroencephalograph (EEG), and Regional Oxygen Saturation (rSO2). The system also provides an interpretation of resting 12-lead ECG.

All the parameters can be monitored on single adult, pediatric, and neonatal patients except for the following:

• · BIS, RM, CCO, SvO2/ScvO2, PAWP, NMT monitoring, PNP, and PNC are intended for adult and pediatric patients only. CCO using FloTrac is intended for adult patients only;
• · C.O. monitoring and A-Fib are intended for adult patients only;
• · ICG monitoring is intended for only adult patients who meet the following requirements: height: 122 to 229cm, weight: 30 to 155kg.
• · rSO2 monitoring is intended for use in individuals greater than 2.5kg.

The monitors are to be used in healthcare facilities by clinical professionals or under their guidance. They should only be used by persons who have received adequate training in their use. The BeneVision N12/N15/N17/N19/N22 monitors are not intended for helicopter transport, hospital ambulance, or home use.

The BeneVision N1 Patient Monitor is intended for monitoring, reviewing, storing, alarming, and transferring of multiple physiological parameters including ECG (3-lead, 5-lead or 12-lead selectable, Arrhythmia Detection, ST Segment Analysis, and Heart Rate (HR)), Respiration (Resp), Temperature (Temp), Pulse Oxygen Saturation (SpO₂), Pulse Rate (PR), Non-invasive Blood Pressure (NIBP), Invasive Blood Pressure (IBP), Pulmonary Artery Wedge Pressure (PAWP), Carbon Dioxide (CO2) and Oxygen (O2). The system also provides an interpretation of resting 12-lead ECG.

All the parameters can be monitored on single adult, pediatric, and neonatal patients except for the following:

• PAWP, PNP, and PNC are intended for adult and pediatric patients only;
• A-Fib is intended for adult patients only;

The BeneVision N1 monitor is to be used in healthcare facilities. It can also be used during patient transport inside and outside of the hospital environment, whereas N1 configured with WMTS technology can be used inside the hospital only. It should be used by clinical professionals or under their guidance. It should only be used by persons who have received adequate training in its use. It is not intended for home use.

The subject BeneVision N Series Patient Monitors includes six monitors:

• . BeneVision N12 Patient Monitor
• BeneVision N15 Patient Monitor
• BeneVision N17 Patient Monitor ●
• BeneVision N19 Patient Monitor ●
• BeneVision N22 Patient Monitor ●
• BeneVision N1 Patient Monitor

Mindray's BeneVision N Series Patient Monitors provide a flexible software and hardware platform to meet the clinical needs of patient monitoring.

This document is a 510(k) Summary for the Mindray BeneVision N Series Patient Monitors, which focuses on demonstrating substantial equivalence to a previously cleared predicate device (K202405).

The information provided primarily details the device's technical specifications and comparisons to a predicate device, rather than a full study proving the device meets acceptance criteria for a specific medical condition or AI diagnostic output.

Therefore, I cannot fully answer all parts of your request as the document does not contain the detailed clinical study results (like sample sizes for test sets, number of experts for ground truth, adjudication methods, MRMC studies, or specific AI performance metrics) that would typically be found for a device requiring those types of studies (e.g., an AI-powered diagnostic tool).

However, I can extract the relevant information regarding the device's functional and technical performance as demonstrated in this 510(k) submission.

Here's a breakdown of what can be inferred and what is missing:

Acceptance Criteria and Reported Device Performance

The "acceptance criteria" in this context are related to meeting the performance specifications of the predicate device and relevant consensus standards. The "reported device performance" is demonstrated through functional and system-level testing, ensuring the device meets its accuracy specifications for the various physiological parameters it monitors.

Table of "Acceptance Criteria" (Implied Specifications) and "Reported Device Performance" (Conformance):

Detailed Study Information (Based on Document Content):

1. Sample sizes used for the test set and the data provenance:

   • The document states that "functional and system level testing" and "bench testing" were conducted.
   • However, no specific sample sizes for test sets (e.g., number of patients, number of data recordings) are provided for any of the performance evaluations.
   • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). The tests described are generic "bench testing" to ensure compliance with technical specifications and standards, not clinical studies.

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

   • Not applicable / Not provided. This document describes engineering and bench testing against pre-defined technical specifications and industry standards for physiological measurement accuracy. It does not describe a clinical study involving human experts establishing ground truth for diagnostic interpretation (e.g., for an AI algorithm interpreting medical images).

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

   • Not applicable / Not provided. Same reason as above.

4. 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. This device is a patient monitor. It detects physiological parameters and provides alarms, and some interpretations of ECG (e.g., 12-lead ECG interpretation, arrhythmia detection). It is not an AI-assisted diagnostic device in the sense of image interpretation for which MRMC studies are typically performed. The document details that "optimized auditory ALARM SIGNALS" and "alarm highlight" were added, suggesting improvements to the human-device interface, but not a formal MRMC study on diagnostic improvement.

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

   • The document implies that algorithms for ECG (Mindray or Mortara algorithm for arrhythmia and ST-segment analysis) are embedded in the device. The listed accuracy specifications for these measurements (e.g., HR, ST, QT) reflect the standalone performance of these measurement algorithms and sensors against established benchmarks. However, a formal "standalone study" with detailed methodology, distinct from the general bench testing, is not specifically described or provided with separate results. The performance data listed (e.g., accuracy for HR, ST, QT) serves as the "standalone" performance verification for these integrated functionalities.

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

   • For physiological measurements (ECG, SpO2, NIBP, etc.), the "ground truth" would typically refer to reference measurement devices or calibrated simulators used during bench testing to verify the accuracy of the monitor's readings against a known, accurate value.
   • For the ECG interpretation (e.g., 12-lead ECG interpretation, arrhythmia detection), the ground truth for the algorithms would have been established during their development and previous clearance processes (Mindray or Mortara algorithms). This document focuses on demonstrating that the integration and revised features maintain that established accuracy rather than re-proving the core algorithms.

7. The sample size for the training set:

   • Not provided. This document pertains to the 510(k) clearance of updates to an existing patient monitor series. It does not detail the development or training of new AI/ML algorithms, which would typically involve substantial training datasets. The ECG algorithms (Mindray or Mortara) were presumably "trained" (or developed and validated) previously as part of their initial predicate clearances.

8. How the ground truth for the training set was established:

   • Not provided. (See point 7). For existing algorithms like Mortara or Mindray ECG algorithms, ground truth for their original development would likely have been established using large, diverse ECG databases with expert cardiologist interpretations and/or correlation with clinical outcomes where relevant. This particular 510(k) document is concerned with demonstrating equivalence and continued performance with minor changes, not the original algorithm development.

Ask a specific question about this device

Onera STS measures and records multiple physiological parameters from a sleep study which are used by clinicians to make a decision on the diagnosis of sleep disorders.

Onera STS is intended to be used on a patient, who has been prescribed a sleep study by a healthcare professional. The device is designed to be used under the direction of a physician or trained technician but applied by a layperson.

The recorded data will be made available to a healthcare professional to assist in the diagnosis of sleep disorders.

The device is intended to be used for adults.

Onera STS is a wearable system for measuring (physiological) signals during a sleep study. The device can be used in home (Home Healthcare Environment) as well as Professional Healthcare Facilities, to perform the sleep study.

Onera STS consists of four sensors applied on the forehead, upper chest area, abdominal and lower leg area.

The sensors measure EEG, EOG, EMG, ECG, bioimpedance based respiratory effort, bioimpedance based respiratory flow, cannula based respiratory flow, oxygen saturation, activity, position, and sound pressure level.

The study preparation and data retrieval are done in a professional/clinical environment by a dedicated trained operator.

The device is not a life supporting physiological monitor

Here's an analysis of the acceptance criteria and the study that proves the device meets the acceptance criteria, based on the provided FDA 510(k) summary for the Onera Sleep Test System (K210593):

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary primarily focuses on demonstrating substantial equivalence to a predicate device rather than explicitly stating pre-defined "acceptance criteria" in a quantitative table format for all parameters. However, we can infer some key performance metrics and their proven results:

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

• SpO2 Accuracy Validation:
  • Sample Size: 10 healthy volunteers.
  • Data Provenance: Not explicitly stated regarding country of origin, but described as a controlled study meeting ISO standards. It is a prospective study as it involved active data collection from subjects for the purpose of validating the device.
• Comparative Sleep Study Testing (Primary Clinical Test Set):
  • Sample Size: 32 patients.
  • Data Provenance: Not explicitly stated regarding country of origin or if it was retrospective or prospective. However, the description states "concurrently applied to 32 patients undergoing a routine sleep study," which implies a prospective, clinical data collection for the validation purpose.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• SpO2 Accuracy Validation: The ground truth for SpO2 accuracy is typically established using a reference oximeter that has been calibrated and validated according to specific standards (e.g., arterial blood gas measurements). The document does not specify the number or qualifications of experts involved in the direct "ground truth" establishment, as it's a technical parameter validated against a standard reference.
• Comparative Sleep Study Testing:
  • Number of Experts: Not explicitly stated. The document mentions "Studies were scored blinded by a qualified sleep professional." This phrasing suggests at least one, but possibly more, qualified sleep professionals were involved.
  • Qualifications: "Qualified sleep professional." Specific details like years of experience or board certification (e.g., diplomate of the American Board of Sleep Medicine) are not provided.

4. Adjudication Method for the Test Set

• SpO2 Accuracy Validation: No explicit adjudication method is mentioned, as SpO2 validation against a reference is a direct measurement comparison.
• Comparative Sleep Study Testing: The scoring was done "blinded" by a qualified sleep professional. It's not explicitly stated if multiple professionals scored and then adjudicated differences (e.g., 2+1, 3+1). The wording "a qualified sleep professional" might suggest single-reader scoring relative to the predicate device, or it might be a simplification of a more complex process. More specific adjudication methods (e.g., consensus, expert panel review) are not described.

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

• No explicit MRMC comparative effectiveness study involving human readers improving with AI vs. without AI assistance was described. This study is focused on the device's ability to record and process physiological parameters similarly to a predicate device, and the sleep staging/scoring is done by a human professional based on the device's output. The device itself is not described as providing AI-assisted interpretations that then improve human reader performance. Its purpose is to provide the raw data for such interpretation.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• The study is essentially a standalone performance evaluation of the device's data collection and preliminary processing capabilities, compared against a predicate device. The "scoring" is done by a human, but the device provides the signals for that scoring. Therefore, the device's performance in generating these signals is evaluated independently of a human's final diagnostic decision. The agreement metrics (Cohen's kappa, accuracy, sensitivity, specificity, correlation) reflect the device's ability to produce data that leads to similar scores as the predicate device.

7. Type of Ground Truth Used

• SpO2 Accuracy Validation: The ground truth for SpO2 was based on a reference standard (likely a co-oximeter or another highly accurate method) as per ISO 80601-2-61:2019, generally derived from arterial blood gas measurements.
• Comparative Sleep Study Testing: The ground truth was established by comparing the Onera STS data to the data from the predicate device (Embletta MPR), with both sets of data scored by a "qualified sleep professional." This means the ground truth for sleep staging and physiological scoring is expert scoring of data from a legally marketed device. It is not stated to be pathology or direct outcomes data, but rather a comparative performance to a widely accepted clinical standard.

8. Sample Size for the Training Set

• The provided document does not mention a specific "training set" or its size for the Onera STS device. This implies that the device's underlying algorithms (if any, separate from standard signal processing) were not developed using a distinct, large, and formally defined training dataset in the way a deep learning AI model would be. The focus is on the device's performance in measuring and recording parameters, and the comparison to an existing predicate device.

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

• Since a dedicated "training set" is not described, the method for establishing its ground truth is also not applicable or not provided in this document. The device appears to rely on established physiological measurement principles and signal processing, validated against a predicate device and relevant standards.

Ask a specific question about this device

Hypotension Decision Assist is indicated to acquire, process and display arterial pressure and other key cardiovascular characteristics of adult patients who are at least eighteen years of age that are undergoing surgery where their arterial pressure is being continuously monitored by a vital-signs monitor. It is indicated for use to assist anesthesia healtheare professionals manage the blood pressure, hemodynamic stability and the cardiovascular system during such surgery.

Hypotension Decision Assist (HDA) is a clinical decision support Software as a Medical Device (SaMD) that is installed upon a medically-rated touch-screen computer. HDA connects to a multi-parameter patient monitor supplied by other manufacturers, from which it acquires vital signs data continuously including the arterial blood pressure waveform and cardiovascular-related numeric parameters.

HDA continually processes this data to display, in graphical charts and numeric format, vital signs data and derived variables including mean arterial pressure (MAP), heart rate, systolic and diastolic blood pressure, cardiac output and systemic vascular resistance. HDA compares MAP to user set targets to indicate when MAP is above or below the target range. It allows the user to mark the administration of vasopressors and volume challenges to the MAP trend.

Here's a breakdown of the requested information based on the provided text, focusing on the acceptance criteria and the study that proves the device meets them:

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

The document primarily focuses on demonstrating substantial equivalence to a predicate device and meeting various technical and safety standards, rather than defining specific numerical performance acceptance criteria for clinical outcomes. However, it does highlight areas of verification.

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

• Sample Size for Test Set: Not explicitly stated as a number of patients or cases for clinical performance assessment. The "test set" primarily refers to hardware and software testing.
• Data Provenance: "Patient data sets obtained from internationally recognized databases" were used for the original system verification and "bench testing performed to compare the performance of HDA to the predicate device." The data was "representative of the range of data input and signal quality that will be encountered in the intended use population and environment of use of the device." No specific countries of origin or whether the data was retrospective or prospective are mentioned beyond being from "internationally recognized databases."

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

Not applicable. The document states that "Clinical studies were not performed." Therefore, there was no expert consensus or ground truth established by human experts for a clinical test set in the traditional sense. The "ground truth" for the bench testing was derived from established standards (e.g., IEC 60601-2-34) and comparison to predicate/reference device measurements.

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

Not applicable. Since no clinical studies were performed, there was no adjudication of clinical outcomes by multiple experts.

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 MRMC comparative effectiveness study was not performed. The device is a clinical decision support software, not an AI for image interpretation that would typically involve human readers. Clinical studies involving human users were not performed.

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

Yes, in a sense. The "Performance Data" section describes "Measurement accuracy verification," "Artefact Detection Verification," and "Predicate comparison testing" which evaluate the algorithm's direct output and processing capabilities against established standards or predicate device outputs. This represents a standalone performance evaluation of the algorithms and software functionality, rather than human-in-the-loop performance.

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

The ground truth for the device's technical performance verification (e.g., measurement accuracy) was established through:

• Bench testing methodologies derived from recognized standards (e.g., IEC 60601-2-34).
• Comparison to predicate or reference devices' established performance for specific parameters (e.g., cardiac output, SVR events, physiological parameter derivation).
• Pre-defined specifications for artifact detection and power interruption tolerance.

For claims of "clinical decision support" or "assisting healthcare professionals," the ground truth implicitly relies on the widely accepted understanding that accurate display and processing of vital signs aid clinical decision-making, rather than a specific clinical outcome study being performed with this device.

8. The sample size for the training set

The document does not explicitly mention a "training set" in the context of machine learning or AI model development. The device is described as "clinical decision support software" that "continually processes this data." If machine learning was used implicitly, no details are provided about its training data. The "patient data sets obtained from internationally recognized databases" were used for "original system verification" and "bench testing," which might imply they were used for validation or testing, but not necessarily for training a model.

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

Not applicable, as a clear "training set" and its ground truth establishment are not described in the provided text. The device's functionality appears to be primarily based on processing established physiological parameters and rules, rather than learning from a labeled training dataset in the AI sense.

Ask a specific question about this device

The indications for use of the BeneVision Central Monitoring System include:

• · Real time viewing of patient clinical data and alarms
• · Storage and Historical review of patient clinical data and alarms
• · Printing of real time and historical patient data
• · Configuration of local settings as well as synchronizing settings across the network to a remote device
• · Transfer of patient clinical data and settings between several CentralStations

The Bene Vision Central Monitoring System is a networked patient monitoring system intended for use in a fixed location, installed in professional healthes to provide clinicians remote patient monitoring. The network connections between the various devices can be any combination of Ethernet (Wireless WIFI (WLAN), and Wireless WMTS. The Bene Vision Central Monitoring System supports one or more Mindray compatible physiological monitors and will display, store, print, and transfer information received from the compatible monitors; The Bene Vision Central Monitoring System supports bi-directional configuration of the compatible monitors. No data processing is done by the BeneVision Central Monitoring System for data received from compatible monitors.

The telemetry monitoring systems are designed to acquire and monitor physiological data for ambulating patients within a defined coverage area. The BeneVision Central Monitoring System supports Telemetry Systems: TMS-6016, Telepack-608, TMS60, and TM80.

· The TMS-6016 transmitter is intended for use on Adult and Pediatric patients to monitor ECG and SpO2 physiological data.

· The Panorama Telepack-608 transmitter is intended for use on Adult patients to monitor ECG and SpO2 physiological data.

· The TMS60 transmitter is intended for use on Adult and Pediatric patients over three years old to monitor ECG, SpO2, NIBP and Resp physiological data. The physiological data can be reviewed locally on the display of the transmitter. The CentralStation will support ECG, Heart Rate, SpO2, NIBP, Resp, Pulse Rate, Arrhythmia analysis, QT monitoring, and ST Segment Analysis for the TMS60.

· The TM80 telemetry monitor is intended for use on Adult and Pediatric patients over three years old to monitor ECG, SpO2, NIBP and Resp physiological data. The physiological data can be analyzed, alarmed, stored, reviewed locally on the display of the monitor, and the CentralStation can config and display the physiological parameters from the TM80.

The BeneVision Central Monitoring System is intended for use in professional healthcare facilities under the direct supervision of a licensed healthcare practitioner.

The BeneVision Central Monitoring System is a networked patient monitoring system intended for use in a fixed location, installed in professional healthcare facilities to provide clinicians remote patient monitoring. The network connections between the various devices can be any combination of Ethernet (Wired), Wireless WIFI (WLAN), and Wireless WMTS.

The BeneVision Central Monitoring System supports one or more Mindray compatible physiological monitors and will display, store, print, and transfer information received from the compatible monitors; The BeneVision Central Monitoring System supports bi-directional configuration of the compatible monitors. No data processing is done by the BeneVision Central Monitoring System for data received from compatible monitors.

The BeneVision Central Monitoring System consists of the following components:

• 1. CentralStation
• 2. ViewStation
• 3. WorkStation
• 4. CMSViewer
• 5. Telemetry Systems (TMS 6016. Telepak-608. TMS60. TM80)

Here's an analysis of the acceptance criteria and study information provided, structured as requested.

Acceptance Criteria and Device Performance

The provided document describes modifications to an existing device (BeneVision Central Monitoring System) and aims to demonstrate substantial equivalence to a predicate device (K162607). The document presents a comparison of technological characteristics as the primary proof of meeting acceptance criteria, rather than explicit quantitative acceptance metrics for performance. The "Performance Data" section details types of testing conducted to ensure the device performs as designed and meets relevant standards.

Table of Acceptance Criteria and Reported Device Performance

Since explicit quantitative acceptance criteria with specific threshold values for "device performance" in terms of accuracy, sensitivity, specificity, etc., are not directly stated in the tables for the subject device (as would be common for diagnostic AI), the "Acceptance Criteria" column will reflect the stated functionalities or characteristics of the subject device, and "Reported Device Performance" will indicate if the device meets these in comparison to the predicate. The overall "acceptance criterion" is essentially demonstrating that the changes do not raise new questions of safety and effectiveness and that the device continues to meet relevant standards.

Study Information

The document describes software verification and validation, electromagnetic compatibility, electrical safety, and bench testing to demonstrate substantial equivalence. It is important to note that this is a 510(k) Premarket Notification for a modified device, not a de novo submission or a claim of new clinical efficacy. Therefore, the "studies" outlined are primarily focused on engineering and performance verification of the changes.

1. Sample size used for the test set and the data provenance:

   • The document does not specify sample sizes for test sets in terms of patient data or clinical cases. The testing appears to be focused on functional and system-level verification, as well as conformance to technical standards.
   • Data provenance (e.g., country of origin, retrospective/prospective) is not provided as the focus is on engineering verification.

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

   • This information is not applicable or provided. The document focuses on demonstrating substantial equivalence through technical comparisons and compliance with relevant standards, rather than establishing a clinical "ground truth" derived from expert interpretation of medical images or patient data in a comparative clinical study.

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

   • This information is not applicable or provided. Adjudication methods are typically used in clinical studies involving multiple readers and ground truth evaluation, which is not the focus of this 510(k) summary.

4. 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 MRMC comparative effectiveness study was done or reported. The device (BeneVision Central Monitoring System) is a patient monitoring system which, based on the description, primarily displays, stores, prints, and transfers physiological data and alarms. While it performs some analysis (e.g., arrhythmia, ST segment), it's not described as an AI-powered diagnostic tool requiring a human-in-the-loop performance study in the way an AI-CADx system would. The changes described are enhancements to the monitoring system's capabilities and compliance with updated standards.

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

   • The document implies that elements like the "Mindray ECG algorithm modifications" and "Intelligent arrhythmia alarm" have undergone verification to ensure they perform according to specifications (e.g., "enhanced performance," "same methods employed by the Central Station"). However, a formal "standalone performance study" with typical metrics like sensitivity, specificity, and F1 score against a reference standard on a clinical dataset is not explicitly detailed or quantified in the provided text. The verification likely involved testing against known waveforms and simulated conditions to confirm algorithm accuracy according to engineering specifications.

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

   • Given the nature of the device (a core patient monitoring system), the "ground truth" for its functional performance would typically involve:
     • Reference signals/simulators: For verifying ECG, SpO2, NIBP, RESP parameters against known inputs.
     • Standardized test conditions: For EMC, electrical safety, and alarm system performance.
     • Software testing (unit, integration, system): Using expected outputs for given inputs to verify logic and calculations.
     • Predicate device comparison: The predicate device itself acts as a reference for expected performance in many aspects of substantial equivalence.
   • Specific details about ground truth for individual algorithms (e.g., how the "enhanced performance" of the ECG algorithm was measured against a reference standard) are not provided beyond the general statement of "functional and system level testing."

7. The sample size for the training set:

   • The document does not mention a training set, as these are engineering changes and updates to a non-AI patient monitoring system, not a de novo AI/ML algorithm requiring a distinct training phase.

8. How the ground truth for the training set was established:

   • This section is not applicable, as no training set is mentioned.

Ask a specific question about this device

Indications for Use statement for the MX100 and X3:

The monitor is indicated for use by healthcare professionals whenever there is a need for monitoring the physiological parameters of patients.

The monitor is intended to be used for monitoring and recording of, and to generate alarms for, multiple physiological parameters of adults, pediatrics, and neonates. The monitor is intended for use by trained healthcare professionals in a hospital environment.

The monitor is also intended for use during patient transport inside the hospital environment.

The monitor is only for use on one patient at a time. It is not intended for home use. Not a therapeutic device. The monitor is for prescription use only.

The ECG measurement is intended to be used for diagnostic recording of rhythm and detailed morphology of complex cardiac complexes (according to AAMI EC 11).

ST segment monitoring is intended for use with adult patients only and is not clinically validated for use with neonatal and pediatric patients.

The Integrated Pulmonary Index (IPI) is intended for use with adult and pediatric (1 to 12 years) patients only. The IPI is an adjunct to and not intended to replace vital sign monitoring.

The Masimo rainbow SET measurement is indicated for the noninvasive monitoring of functional oxygen saturation of arterial hemoglobin (SpO2), pulse rate, carboxyhemoglobin saturation (SpCO), methemoglobin saturation (SpMet), total hemoglobin concentration (SpHb), and/or respiratory rate (RRac). The Masimo rainbow SET measurement is indicated for use during both no motion and motion conditions, and for patients who are well or poorly perfused.

Indications for Use statement for the Hemodynamic Extension 867039:

The measurement extension adds physiological measurements to a dedicated host device. It is intended for use by trained healthcare professionals for adult, pediatric, and neonatal patients in a hospital environment and for transport inside hospitals. The measurement extension can only function when it is connected to a dedicated host device.

The new IntelliVue Patient Monitor MX100, Multi-Measurement Module X3, and Hemodynamic Extension 867039 acquire multiple physiological patient signals, display measurement values, waves and trends, generate physiological and technical alarms, provide data recording and support patient data management. The devices offer a monitoring solution optimized for the surgical, cardiac, medical and neonatal care environments. They can be located in the patient vicinity at the bedside or can be used mobile, during patient transport inside hospitals. The measurement sensors are applied at diverse bodily locations, depending on the actual physiological parameters monitored.

The new devices have the same range of functions as the legally marketed predicate devices. They use the same measurement parameters as the predicates.

Whereas the predicate devices optionally provide one invasive pressure, the new devices optionally provide two invasive pressures (dual pressure) that can be measured with one pressure connector.

The MX100 and X3 provide multiple non-invasive and invasive measurements: ECG (including arrhythmia and ST), respiration, SpO2, NBP, dual invasive pressure, temperature, and CO2.

The Hemodynamic Extension 867039 adds optional measurements: dual invasive pressure, temperature, and cardiac output /continuous cardiac output to the host device. The measurement extension can only function when it is connected to a dedicated host device.

Specifications of all measurement characteristics, including measurement principles, methods, algorithms, and all detailed performance specifications and measurement alarm specifications, are the same as those in the predicate devices. The new devices reuse unchanged existing accessories of the predicates.

The new IntelliVue Patient Monitor MX100 and Multi-Measurement Module X3 are compact, rugged, lightweight monitors with built-in measurements. The X3 can be used in two ways: as a multi-measurement module for the Philips IntelliVue family of patient monitors and as a stand-alone monitor.

The MX100 and X3 have a 6.1' TFT flat panel color display with a multi-finger touchscreen as input device.

The MX100 and X3 can interact with the Central Station via LAN or wireless link.

The new Transpac IV Dual IBP Cable 453564588501 is a reusable cable intended to connect two ICU Transpac pressure transducers with one of the new Philips measuring devices (Patient Monitor MX100, Multi-Measurement Module X3, or Hemodynamic Extension 867039). The cable transmits analog voltage signals from the pressure transducers to the Philips device and provides electrical power from the Philips device to the transducers.

Here's a breakdown of the acceptance criteria and study information for the Philips IntelliVue Patient Monitor MX100, Multi-Measurement Module X3, and IntelliVue Hemodynamic Extension 867039, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a specific table of acceptance criteria with corresponding performance metrics in a concise format. Instead, it refers to fulfilling requirements of various recognized consensus standards and device-specific guidance documents. The general statement is:

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

The document does not explicitly state the sample sizes used for various test sets in terms of patient numbers or data records.

• NIBP testing: "minimum of three devices" were compared for intra-device variability.
• Data Provenance: Not specified. The document describes a series of engineering tests and compliance to standards, rather than clinical trials with patient data.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not provided in the document. The studies described are primarily engineering verification and validation against established standards and predicate device specifications, rather than relying on expert ground truth for patient data in the typical sense of a diagnostic AI product.

4. Adjudication Method for the Test Set

This information is not applicable and not provided. The testing described is against defined technical specifications and standards, not a diagnostic task requiring adjudication of expert interpretations.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned or performed. This device is a patient monitor, not an AI-assisted diagnostic tool that aids human readers in interpreting medical images or data. The focus is on the device's accuracy and reliability in measuring and displaying physiological parameters.

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

The device is inherently a "standalone" system in terms of its algorithmic performance for measuring physiological parameters. The studies described (e.g., NIBP accuracy, SpO2 accuracy, respiration rate accuracy) directly assess the device's algorithms and hardware without requiring human intervention in the measurement process itself, though it is intended for use by healthcare professionals.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The ground truth for the performance testing appears to be based on:

• Reference Standards: For parameters like NIBP, a "comparison to the intra-arterial reference standard for mean blood pressure" was used.
• Predicate Device Specifications: The "Pass/Fail criteria were based on the specifications cleared for the predicate devices."
• Consensus Standards: Performance was evaluated against recognized consensus standards (e.g., IEC, AAMI, ISO) which define acceptable limits for accuracy and performance.

8. The Sample Size for the Training Set

This information is not applicable and not provided. The document describes a medical device, not a machine learning or AI model that requires a "training set" in the conventional sense. The device's algorithms are likely based on established physiological principles and engineering design, not data-driven machine learning models that are "trained."

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

This information is not applicable and not provided, as there is no mention of a "training set" for a machine learning algorithm.

Ask a specific question about this device