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Indications for Use for SureSigns VS3 Vital Signs Monitor

The SureSigns VS3 vital signs monitor is for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The SureSignsVS3 is for monitoring, recording and alarming of multiple physiological parameters in healthcare environments for patient types listed below. Additionally, the monitor may be used in transport situations within a healthcare facility.

Parameter (patient types): NBP (Adult, Pediatric, Neonatal); SpO2 (Adult, Pediatric, Neonatal); Temperature (Adult, Pediatric, Neonatal)

Contraindications: Not for transport outside the healthcare facility

Indications for Use for SureSigns VS4 Vital Signs Monitor

The SureSigns VS4 vital signs monitor is for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The SureSigns VS4 is for monitoring, recording and alarming of multiple physiological parameters in healthcare environments for patient types listed below. Additionally, the monitor may be used in transport situations within a healthcare facility.

Parameter (patient types): NBP (Adult, Pediatric, Neonatal); SpO2 (Adult, Pediatric, Neonatal); Temperature (Adult, Pediatric. Neonatal); CO2 (Adult, Pediatric. Neonatal); RRa (Adult, Pediatric); SpHb (Adult, Pediatric)

Contraindications: Not for transport outside the healthcare facility

The subject VS3 and VS4 will be modified with the current QuickAlert to include On-device multi-parameter configurable Modified Early Warning Scores (MEWS).

The provided text describes a 510(k) premarket notification for Philips SureSigns VS3 and VS4 Vital Signs Monitors. This document asserts substantial equivalence to previously cleared devices rather than providing a detailed study proving the device meets specific acceptance criteria with new clinical trials.

The modifications to the devices (VS3 and VS4) involve adding "On-device multi-parameter configurable Modified Early Warning Scores (MEWS)" to the existing QuickAlert functionality. The document states that there are no additions, deletions, or changes to the current measurements or alarming, nor any specification changes to the current SureSigns VS3 or SureSigns VS4 monitors.

Therefore, the information you requested regarding acceptance criteria and a study proving the device meets those criteria, particularly in the context of new clinical performance outcomes, is not explicitly detailed in this 510(k) summary. The summary focuses on demonstrating that the modified devices function as intended without adverse impact on safety or effectiveness and are substantially equivalent to their predicate devices.

However, I can extract information related to the verification, validation, and testing activities mentioned, which implicitly served to meet the acceptance criteria for the added MEWS functionality and device safety/performance.

Here's a breakdown of the available information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a formal table of explicit acceptance criteria with quantitative performance metrics for the added MEWS functionality. It generally states:

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

The document states: "Testing involved system level tests, performance tests and tests according risk assessment." It does not specify the sample size for the test set (e.g., number of patients or data points) or the data provenance (e.g., country of origin, retrospective or prospective). Given the nature of a 510(k) for a modification to a vital signs monitor primarily focused on a new scoring algorithm, the testing likely involved a combination of simulated data, historical patient data for algorithm validation, and/or in-house testing, rather than a large prospective clinical study.

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

This information is not provided in the document. For a MEWS system, ground truth would typically involve clinical experts determining actual patient deterioration or risk, but the document does not elaborate on how the MEWS algorithm's performance was validated against expert judgment.

4. Adjudication Method for the Test Set

This information is not provided in the document.

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

A MRMC comparative effectiveness study was not performed or reported in this 510(k) summary. The document focuses on the technical verification of the device and its software modification, not a study evaluating human reader improvement with or without AI assistance.

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

The document implies that "performance tests" were conducted, which would likely include testing the MEWS algorithm's output in a standalone manner. However, it does not explicitly describe a dedicated standalone study with specific metrics for the algorithm's performance independent of user interpretation or intervention. The MEWS is "On-device," suggesting it provides scores for healthcare professionals to act upon, but its isolated performance metrics are not detailed.

7. Type of Ground Truth Used

The document does not specify the type of ground truth used for evaluating the MEWS functionality. For a risk-scoring system like MEWS, common ground truths might include subsequent clinical events (e.g., ICU admission, cardiac arrest, death), expert clinical assessment, or established clinical criteria for deterioration.

8. Sample Size for the Training Set

The document does not specify the sample size for any training set. It's common for MEWS algorithms to be based on established clinical scoring systems rather than de novo machine learning models requiring extensive training data. If machine learning was used for the "configurable" aspect, the training set size is not disclosed.

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

Since no training set is mentioned, the method for establishing its ground truth is also not provided.

In summary, this 510(k) notification emphasizes the substantial equivalence of the modified vital signs monitors to their predicate devices, particularly concerning the addition of configurable MEWS. It mentions verification and validation testing to ensure the device performs as specified and meets safety and effectiveness standards, but it lacks detailed quantitative data on clinical performance, sample sizes, expert involvement, or ground truth methodologies that would typically be found in a comprehensive clinical study report.

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The SureSigns VS3 vital signs monitor is for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The SureSignsVS3 is for monitoring, recording and alarming of multiple physiological parameters in healthcare environments for patient types listed below. Additionally, the monitor may be used in transport situations within a healthcare facility.

The SureSigns VS4 vital signs monitor is for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The SureSigns VS4 is for monitoring, recording and alarming of multiple physiological parameters in healthcare environments for patient types listed below. Additionally, the monitor may be used in transport situations within a healthcare facility.

The subject devices are SureSigns VS3 and SureSigns VS4 multi-parameter patient monitors. Modifications include adding connectivity to IntelliVue GuardianSoftware (IGS), adding Temporal Temperature measurement to VS3, and other enhancements such as additional title bar indicators, expanded patient records pane, display patient name or primary ID, expanded QuickCapture entries, default CO2 setting alignment (VS4 only), temperature high and low alarms color change, increased SpO2 alarm delay defaults, option to prevent inadvertently clearing NBP programs, and RFID patient ID entry.

This document describes the Philips SureSigns VS3 and VS4 Vital Signs Monitors, which are multi-parameter patient monitors. The submission is a 510(k) premarket notification for modifications to previously cleared devices.

Here's an analysis of the acceptance criteria and study information provided, focusing on what can be extracted from the text:

1. Table of Acceptance Criteria and Reported Device Performance

The document broadly states that "Pass/Fail criteria were based on the specifications cleared for the subject device." However, it does not explicitly list specific numerical acceptance criteria for performance metrics (e.g., accuracy ranges for NBP, SpO2, Temperature, CO2). Instead, it confirms that the device reportedly meets these implicit criteria.

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

The document does not provide details on the sample size used for the test set.
It also does not specify the data provenance (e.g., country of origin, retrospective or prospective). The testing appears to be internal validation by Philips Medical Systems.

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

This information is not provided in the document. The testing described is verification, validation, and performance testing, which typically involves comparing device outputs to a known reference standard (e.g., calibration equipment, established measurement methods) rather than human expert-established ground truth in a clinical scenario.

4. Adjudication Method for the Test Set

This information is not provided. Given the nature of the device (monitoring physiological parameters), "adjudication" in the sense of resolving discrepancies between human experts for a diagnostic task is unlikely to be relevant here. The testing would involve comparing device readings against a gold standard or reference measurement.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of Human Improvement

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is typically for diagnostic imaging devices where human readers interpret images with and without AI assistance. The SureSigns VS3 and VS4 are vital signs monitors, not diagnostic imaging devices designed for human interpretation of complex data patterns in the same way. The modifications focus on software connectivity, a new temperature measurement accessory, and feature enhancements.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The document describes "system level tests, performance tests, and safety testing from hazard analysis." This strongly implies that standalone performance testing was done for the device's functions (e.g., accuracy of NBP, SpO2, Temperature measurements). The software verification and validation, along with compliance to specific standards for temperature measurement, suggest testing of the algorithms and hardware in a standalone capacity against reference standards. However, "standalone" in the context of an AI algorithm is typically for diagnostic or predictive AI, which this device, in its described modifications, does not appear to be. It's a measurement device.

7. The Type of Ground Truth Used

The ground truth used for these types of physiological parameter monitors would typically involve:

• Reference standard instruments: Highly accurate and calibrated devices used to establish the true value of parameters like NBP, SpO2, and Temperature.
• Known physical inputs: For example, precise temperature probes, blood pressure simulators, or SpO2 simulators with defined oxygen saturation levels.
• Compliance with industry standards: The mention of ISO 80601-2-56 for temperature indicates that the ground truth for temperature measurement accuracy would be established by following the specific protocols and reference measurements outlined in that standard.

The document does not explicitly state "expert consensus" or "pathology" as ground truth, which are more relevant for diagnostic AI applications.

8. The Sample Size for the Training Set

The document does not describe any "training set." This is because the device, based on the provided information, is a vital signs monitor and not an AI/ML-based diagnostic or predictive system that requires a training set for model development. The focus is on measurement accuracy and software functionality.

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

Since there is no mention of a training set, this information is not applicable/provided.

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The SureSigns VS3 vital signs monitor is for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The SureSignsVS3 is for monitoring, recording and alarming of multiple physiological parameters in healthcare environments for patient types listed below. Additionally, the monitor may be used in transport situations within a healthcare facility.

The SureSigns VS4 vital signs monitor is for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The SureSigns VS4 is for monitoring, recording and alarming of multiple physiological parameters in healthcare environments for patient types listed below. Additionally, the monitor may be used in transport situations within a healthcare facility.

The subject devices are multi-parameter patient monitors, specifically the SureSigns VS3 and SureSigns VS4. Modifications to the VS4 include the addition of CO2, SpHb, Respiratory Rate RRa, and Masimo SpO2 measurements. Both VS3 and VS4 have the QuickNBP mode added.

This is a 510(k) summary for Philips SureSigns VS3 and VS4 vital signs monitors, describing modifications to add additional measurement capabilities. The provided text, however, does not contain information about specific acceptance criteria or a detailed study proving the device meets said acceptance criteria with numerical performance data. It broadly states that "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the subject device. Testing involved system level tests, performance tests, and safety testing from hazard analysis. Pass/Fail criteria were based on the specifications cleared for the subject device and test results showed substantial equivalence."

Therefore, I cannot fulfill all parts of your request with the provided information.

However, based on the information available, here's what can be extracted:

• Acceptance Criteria and Reported Device Performance: This information is not explicitly provided in a table or numerical format. The document states that "Pass/Fail criteria were based on the specifications cleared for the subject device and test results showed substantial equivalence," implying that the devices met pre-defined specifications. However, the exact criteria and corresponding performance metrics are not detailed.

• Sample Size for Test Set and Data Provenance: This information is not explicitly stated in the provided text.

• Number of Experts and Qualifications: This information is not mentioned in the provided text.

• Adjudication Method: This information is not mentioned in the provided text.

• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: There is no indication that an MRMC study was done. The device is a vital signs monitor, which typically involves direct measurement rather than interpretation by multiple human readers in the way an AI-assisted diagnostic tool might.

• Standalone (Algorithm Only) Performance Study: The document mentions that the new features are achieved by using OEM modules that are "FDA cleared under Kxxxxxx." This implies that the performance of these modules as standalone components was already established in their respective clearances. For instance, for CO2 measurement, the Oridion microMediCO2 OEM module was cleared under K094012; for SpHb, RRa, and Masimo SpO2, the Masimo Rainbow SET Radical 7R CO-Oximeter was cleared under K100428; and for Temporal Temperature, the Exergen TemporalScanner Thermometer was cleared under K011291. The QuickNBP mode is described as based on the "same algorithm that provides the regular NBP measurements" in the existing devices. Therefore, while not explicitly called a "standalone study," the reliance on previously cleared, established technologies suggests that their standalone performance has been demonstrated.

• Type of Ground Truth Used: Not explicitly stated for the overall device's performance. However, for the OEM modules incorporated, their original clearances would have involved appropriate ground truth methods for each physiological parameter (e.g., direct measurement for temperature, arterial blood gas analysis for SpO2 calibration, etc.).

• Sample Size for Training Set: This information is not applicable as the document describes hardware modifications incorporating existing, cleared OEM modules and leveraging existing algorithms. It does not mention the development or training of new algorithms that would require a distinct training set.

• How Ground Truth for Training Set Was Established: Not applicable given the nature of the device modifications.

In summary, the provided text primarily focuses on the substantial equivalence argument for modifications to existing vital signs monitors by integrating previously cleared OEM modules and leveraging existing algorithms. It does not contain the detailed performance study information with specific acceptance criteria, sample sizes, expert involvement, or adjudication methods that your request entails for a newly developed AI/diagnostic device.

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Indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients.

Standard and optional parameters include:

• · NBP
• SpOz .
• Temperature

Philips SureSigns VS3 Vital Signs Monitor and the SureSigns VS4 Vital Signs Monitor. Common usual name for both the VS3 and the VS4 are multi-parameter patient monitor.

This Philips 510(k) summary does not contain the detailed acceptance criteria or a comprehensive study report with specific performance metrics as requested. The available information primarily focuses on establishing substantial equivalence to a predicate device, rather than providing robust statistical evidence of performance against defined acceptance criteria.

However, based on the provided text, here’s an attempt to extract and infer the closest available information:

1. Table of Acceptance Criteria and Reported Device Performance

Explanation:
The document states, "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the subject device. Testing involved system level tests, performance tests, and safety testing from hazard analysis. Pass/Fail criteria were based on the specifications cleared for the subject device and test results showed substantial equivalence."

This indicates that some acceptance criteria existed, based on the cleared specifications of the predicate device (SureSigns VS3, K082280 and K090483). However, the specific numerical or qualitative acceptance criteria (e.g., accuracy ranges for NBP, SpO2, Temperature) are not detailed in this summary. The reported performance is a general statement of compliance, without specific metrics.

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

This information is not provided in the given text. There are no details regarding the number of test subjects, the type of data (e.g., country of origin, retrospective/prospective), or the specific test protocols followed.

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

This information is not provided in the given text. The testing appears to be device-centric (system level, performance, safety) rather than relying on expert consensus for clinical ground truth.

4. Adjudication Method for the Test Set

This information is not provided in the given text. Adjudication methods like 2+1 or 3+1 are typically used when expert consensus is required for ground truth, which isn't described here.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not mentioned or implied in the provided text. The document focuses on the device's technical performance and safety, not on human reader improvement with or without AI assistance. This device is a vital signs monitor, which typically provides direct measurements rather than interpreting complex medical images or data that would necessitate an MRMC study.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, the testing described appears to be a standalone performance evaluation of the device. The text mentions "system level tests, performance tests, and safety testing from hazard analysis," which are typically conducted to assess the device's internal algorithms and hardware functionality independently. The statement "The subject devices use the same algorithms for the measurements as the predicate devices" further supports that the algorithms themselves were evaluated for performance.

7. The Type of Ground Truth Used

The type of "ground truth" implicitly used for this device would be calibrated reference standards and established physiological measurement techniques. For vital signs monitors, this typically involves:

• For NBP: Comparison against invasive arterial blood pressure measurements or highly accurate non-invasive methods in a controlled setting.
• For SpO2: Comparison against co-oximetry readings of arterial blood samples.
• For Temperature: Comparison against highly accurate reference thermometers.

The document states that "Pass/Fail criteria were based on the specifications cleared for the subject device," which implies these specifications included accuracy ranges against such reference standards. However, the specific methods are not detailed.

8. The Sample Size for the Training Set

This information is not provided in the given text. The document indicates that the devices use "the same algorithms for the measurements as the predicate devices," suggesting that any algorithm training would have occurred during the development of the predicate device, or that the algorithms are based on established physiological principles rather than machine learning requiring a training set in the contemporary sense.

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

This information is not provided in the given text, and the concept of a "training set" in a machine learning context is not directly applicable given the device type and the description provided. If algorithms were "trained" in a broader sense (e.g., fine-tuning parameters), their "ground truth" would likely have been established through controlled studies using calibrated reference measurements, similar to the ground truth for validation, but this is speculative given the lack of detail.

Summary of Limitations in the Provided Text:

The provided 510(k) summary is very high-level and lacks the specific details required to fully address your questions. It focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed performance study with explicit acceptance criteria, sample sizes, expert involvement, or specific ground truth methodologies. For these details, one would typically need to refer to the full testing documentation submitted to the FDA, which is not included in this summary.

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Indications for Use: Indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients.

Intended Use: For monitoring, recording, and alarming of multiple physiological parameters of adults, pediatrics and neonates in healthcare environments. Additionally, the monitor is intended for use in transport situations within a healthcare facility.

The names of the subject devices are the Philips SureSigns VM Series Patient Monitors, the SureSigns VS2 Vital Signs Monitor, and the SureSigns VS3 Vital Signs Monitor. The common usual name is multi-parameter patient monitor. The modification is to replace the currently cleared CAS NBP module with the picoNIBP(non invasive blood pressure) OEM Module (which was cleared in K051366) to the VS2 Vital Signs Monitor, the VS3 Vital Signs Monitor, and the VM Series (VM 4/6/8) Patient Monitors. In addition, this submission includes a change in plastics to Valox and the addition of new SP0- sensors and the disclosure of IPX1 rating for ingress protection to vertical water drops for all subject devices.

Here's an analysis of the provided text regarding the acceptance criteria and study information for the Philips SureSigns VM Series Patient Monitors, SureSigns VS2 Vital Signs Monitor, and SureSigns VS3 Vital Signs Monitor:

Based on the provided K090483 510(k) summary, much of the requested information regarding specific acceptance criteria, detailed device performance metrics, and study methodologies for the modified device is not explicitly stated. The submission focuses on demonstrating substantial equivalence to a predicate device (K052707) rather than providing a detailed de novo performance study with specific criteria.

The key takeaway is that the manufacturer states that "Pass/Fail criteria were based on the specifications cleared for the predicate device" and that testing showed "substantial equivalence." This implies that the acceptance criteria for the modified device are implicitly aligned with those established for the previously cleared predicate device.

Acceptance Criteria and Reported Device Performance

Study Information Table

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Indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. For monitoring, recording, and alarming of multiple physiological parameters of adults, pediatrics and neonates in healthcare environments. Additionally, the monitors may be used in transport situations within a healthcare facility.

The SureSigns VS2 Vital Signs monitor and the SureSigns VM1 are for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. For monitoring, recording, and alarming of multiple physiological parameters of adults, pediatrics and neonates in healthcare environments. Additionally, the monitors may be used in transport situations within a healthcare facility. The addition of the wireless functionality to the predicate VS3 does not change the intended use or indications for use. The subject devices have the same fundamental technological characteristics as the legally marketed predicate devices. The subject devices use the same design as the predict device. The composition of the VS2 and the VM1 materials are different than the predicate device, however are made of a material previously used in other medical devices. The chemical composition of the subject devices has changed but is the same as material used in other predicate devices. The energy source of the subject device the VS2 is an external power supply, while the VM1 will use a power supply that is the same as the predicate device. The VS2 and the VM1 both can run on battery power with batteries similar to the predicate devices.

The provided 510(k) summary for the Philips SureSigns VM1 Patient Monitors and SureSigns VS2 Vital Signs Monitor does not contain the detailed information necessary to complete a table of acceptance criteria and reported device performance, nor does it describe a study proving the device meets specific acceptance criteria in the way typically expected for AI/ML device evaluations.

This document is a pre-market notification (510(k)) for physiological monitoring devices, specifically patient monitors, and their modifications. The evaluation for substantial equivalence in such devices often focuses on comparing technical characteristics and performance to legally marketed predicate devices, rather than establishing novel performance metrics against a defined ground truth using a clinical study with a specified sample size and expert review in the context of an algorithm.

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

The document states:
"Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the subject devices with respect to the predicates. Testing involved system level tests, performance tests, and safety testing from hazard analysis. Pass/Fail criteria were based on the specifications cleared for the predicate device, the specifications of the subject device and test results showed substantial equivalence. The results demonstrate that the Philips SureSigns VM1 Patient Monitors and SureSigns VS2 Vital Signs monitor and the modification to the SureSigns VS3 Vital Signs Monitor meet all reliability requirements and performance claims and supports a determination of substantial equivalence."

This indicates that the "acceptance criteria" were essentially the specifications of the predicate device and the subject device, and the "study" was system-level, performance, and safety testing aimed at demonstrating substantial equivalence. However, specific numerical performance metrics are not provided in this summary.

Therefore, many parts of your request cannot be directly answered from the provided text.

1. Table of acceptance criteria and the reported device performance

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

• Sample Size: Not specified. The document mentions "system level tests, performance tests, and safety testing," but does not give a sample size of patients or data records.
• Data Provenance: Not specified. It's likely these tests were conducted internally by Philips Medical Systems (Andover, MA, United States), but the origin of any clinical data (if used) is not detailed. The distinction between retrospective or prospective data is not applicable given the type of testing described (device function/safety rather than algorithm performance on clinical data).

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 type of information (number and qualification of experts establishing ground truth) is typically relevant for studies evaluating an AI/ML diagnostic or prognostic system against a human standard. For a patient monitor, "ground truth" would be established by reference standards or direct physical measurements, not expert consensus on interpretations of images or signals.

4. Adjudication method for the test set

• Not applicable / Not specified. Adjudication methods (like 2+1, 3+1) are used to resolve disagreements among multiple human readers when establishing ground truth. This is not typically part of the testing for a physiological monitor's basic functions.

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 / Not done. This is a physiological monitor, not an AI-assisted diagnostic tool for human readers. Therefore, an MRMC study and AI assistance effect size are not relevant to this device's evaluation.

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

• Not applicable / Not mentioned in this context. While these devices contain algorithms for processing physiological signals (e.g., arrhythmia detection, NIBP calculation), the 510(k) summary does not describe a "standalone" algorithm performance study in the way it's typically understood for AI/ML devices where the algorithm's output is compared to a ground truth independent of human interaction. The testing described focuses on the integrated device's performance.

7. The type of ground truth used

• Likely reference standards and direct physical measurements. For physiological monitors, ground truth for parameters like blood pressure, heart rate, or SpO2 would typically involve highly accurate reference devices or invasive measurements (e.g., arterial line for blood pressure) against which the monitor's readings are compared. The document does not explicitly state this but it's the standard practice for such devices.
• Not pathology, outcomes data, or expert consensus in the context of diagnostic interpretation.

8. The sample size for the training set

• Not applicable / Not specified. These devices are not described as employing machine learning models that require a "training set" in the modern sense. They rely on established signal processing algorithms. If any adaptive algorithms or calibrations exist, the "training" would be internal calibration processes rather than a distinct dataset.

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

• Not applicable. As a traditional physiological monitor, the concept of a "training set" and associated ground truth establishment for a machine learning model is not relevant to the information provided in this 510(k) summary.

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