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The Hewlett-Packard Viridia Component Monitoring System, (M1175A/76A/77A), and Viridia 24/26 (M1205A) Rev.K with EASI™ ST segment Monitoring is indicated for: Assessment of real time ST segment analysis in adult patients. Assessment is indicated for the

The new device consists of a software enhancement enabling the CMS system to accommodate an electrode placement pattern allowing signals for deriving the 12-lead electrocardiogram from the 5-lead EASI™ electrode system. The EASI™ capability is fully compatible with the existing HP ECG frontend modules M1001A/B or M1002A/B.

The provided text is a 510(k) summary for the Hewlett-Packard Viridia Component Monitoring System with EASI™ ST Segment measurement. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study proving performance against specific acceptance criteria for a novel device. As such, much of the requested information regarding detailed study design, ground truth establishment, expert involvement, and sample sizes for training/test sets is not explicitly present in the provided document.

However, I can extract what is available and indicate where information is missing based on the document.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics from a specific study comparing the new device against such criteria. Instead, it relies on the concept of "substantial equivalence" to a predicate device, implying that its performance is comparable.

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

This information is not provided in the document. The 510(k) focuses on the technological equivalence and intended use rather than a detailed clinical validation study with a specified test set.

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

This information is not provided in the document. Since a detailed test set and ground truth establishment methodology are not described, the involvement of experts for this purpose is also absent from the summary.

4. Adjudication Method for the Test Set

This information is not provided in the document. Without a described test set and ground truth establishment, an adjudication method is not mentioned.

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

This information is not provided in the document. The submission is about a software enhancement to a monitoring system, not a diagnostic aid that would typically involve human readers. Therefore, an MRMC study is not relevant to this type of device and is not mentioned.

6. If a Standalone (Algorithm Only) Performance Study Was Done

The document describes a "software enhancement enabling the CMS system to accommodate an electrode placement pattern allowing signals for deriving the 12-lead electrocardiogram from the 5-lead EASI™ electrode system." It also states that "monitoring technology identical to that used in the predicates." This implies that the core ST segment measurement algorithm is either the same as or very similar to the predicate and that the focus is on the EASI™ electrode system's ability to provide signals for this existing algorithm. However, a standalone performance study with specific metrics for the algorithm itself (isolated from the entire monitoring system) is not explicitly detailed in this summary. The "study" here is more about demonstrating that the EASI™ technology can provide equivalent input for the existing ST segment measurement.

7. The Type of Ground Truth Used

Given the nature of the device (ST segment monitoring via ECG), the ground truth for such a device, if a study were conducted, would typically be a clinically accepted standard for ECG interpretation (e.g., expert cardiologists' readings of standard 12-lead ECGs obtained simultaneously, or sometimes correlational studies with other diagnostic tests). However, the document does not explicitly state the type of ground truth used for any performance evaluation, as it relies on substantial equivalence.

8. The Sample Size for the Training Set

This information is not provided in the document. As the device is an enhancement to an existing system, and the technology is described as "identical to that used in the predicates," it's possible that no "training set" in the context of a new machine learning algorithm was used. If a training set was used for the original development of the ST segment algorithm, that information is not part of this 510(k) summary.

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

This information is not provided in the document, for the reasons outlined in point 8.

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The Hewlett-Packard Viridia Component Monitoring System is intended for use in monitoring, recording, and alarming of multiple physiological parameters. The devices are indicated for use in health care facilities by health care professionals whenever there is a need for monitoring the physiological parameters of adult, neonatal, and pediatric patients.

The modification is a software based change that combines software in the HP Clinical Monitoring System product line (M1175A, M1176A and M1177A, M100B/M1002B ECG/RESP) with the software in the HP Component Transport System Viridia, (M1205A), the devices are to be known collectively as the HP Viridia Component Monitoring System. The combination system will allow for shared future functionality capabilities in HP patient monitoring systems.

The provided text is a 510(k) summary for the Hewlett-Packard Viridia Component Monitoring System. It describes a software-based change that combines existing software within HP's clinical monitoring product lines. The document primarily focuses on establishing substantial equivalence to previously cleared predicate devices rather than directly detailing a study that proves the device meets specific acceptance criteria.

Therefore, much of the requested information regarding acceptance criteria, study design, sample sizes, expert involvement, and ground truth establishment cannot be found in the provided text. The document does not describe a clinical performance study with specific acceptance criteria that the device was tested against.

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

1. Table of Acceptance Criteria and Reported Device Performance

Not available in the provided text. The document focuses on showing substantial equivalence based on intended use, technological characteristics, and software changes rather than a new performance study with benchmarked acceptance criteria.

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

Not available in the provided text. No information is given about a test set or its data provenance, as a dedicated performance study is not described.

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

Not available in the provided text. Since no test set or ground truth establishment is described, this information is absent.

4. Adjudication Method for the Test Set

Not available in the provided text. No adjudication method is mentioned as a specific test set is not detailed.

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

Not available in the provided text. The document does not mention any MRMC study or the effect size of human readers improving with AI assistance. The device in question is a patient monitoring system, not primarily an AI-driven diagnostic tool in the sense of image interpretation.

6. Standalone (Algorithm Only) Performance Study

Not available in the provided text. While the change is software-based, the document doesn't detail a standalone performance study of the algorithm in isolation. It describes the integration of existing software components.

7. Type of Ground Truth Used

Not available in the provided text. Since no specific performance study is detailed, no information on the type of ground truth used is provided.

8. Sample Size for the Training Set

Not available in the provided text. No training set is mentioned, as the submission describes combining existing software from legally marketed predicate devices, implying prior validation rather than de-novo algorithm training for this specific submission.

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

Not available in the provided text. As no training set is discussed, information on ground truth establishment for it is also absent.

In summary, the provided 510(k) notification focuses on the regulatory pathway of substantial equivalence for a software-based combination of existing monitoring systems. It does not contain the detailed clinical study information typically found when a new device's performance against specific acceptance criteria is being proven.

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