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The EV1000 Clinical Platform and the ClearSight™ Finger Cuffs are indicated for patients over 18 years of age in which the balance between. cardiac function, fluid status, and vascular resistance needs continuous assessment. In addition, the non-invasive system is indicated for use in patients with co-morbidities for which hemodynamic optimization is desired and invasive measurements are difficult. The EV1000 Clinical Platform and the ClearSight™ finger cuffs noninvasively measures blood pressure and associated hemodynamic parameters.

The EV1000 Clinical Platform with ClearSight Finger Cuffs is a non- invasive monitor that enables the continuous assessment of a patient's hemodynamic function based on the scientific method of Peňáz - Wesseling. The device measures continuous non-invasive blood pressure (Systolic, Diastolic, and Mean Arterial Pressure) and pulse rate. Cardiac Output and other hemodynamic parameters are derived from the blood pressure waveform. The EV1000 ClearSight™ System consists of a monitor, a pump-unit, a pressure controller that is worn on the wrist, and ClearSight Finger cuffs. The EV1000 Pump-unit receives incoming signals from the pressure controller and the finger cuffs. The algorithms embedded in the Pump- Unit and the pressure controller process signals from the finger cuffs and provide parameter calculations. The EV1000 Monitor is connected to the Pump-Unit via an Ethernet cable, and the Pump-unit is connected to the pressure controller via a RS485 port. The monitor is a touchscreen panel PC with a graphical user interface (GUI). The monitor displays the measured and calculated parameters from the Pump-Unit.

The provided text describes the EV1000 Clinical Platform with ClearSight™ Finger Cuffs, a non-invasive blood pressure measurement system. The submission focuses on demonstrating substantial equivalence to a predicate device through verification and validation testing, including a clinical study.

Here's an analysis of the acceptance criteria and study details based on the provided text:

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

The document does not explicitly state numerical acceptance criteria in a dedicated table format. Instead, it describes meeting acceptance criteria through a comparison to a predicate device.

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 mentions "a clinical study" was conducted. However, it does not specify the sample size used for this clinical study (test set). It also does not provide information on the data provenance (e.g., country of origin, retrospective or prospective nature).

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)

The document does not provide any information regarding the number of experts used to establish ground truth or their qualifications. Given that the device measures physiological parameters (blood pressure), ground truth would likely be established through a reference measurement method, rather than expert interpretation of images/data.

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

The document does not describe any adjudication method for the test set.

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

The document describes a comparative effectiveness study, but it is not an MRMC study comparing human readers with and without AI assistance. This device is a non-invasive blood pressure monitor, not an AI-assisted diagnostic tool for human readers. The comparative effectiveness study focuses on the device's performance against a predicate device. Therefore, there is no mention of an effect size related to human reader improvement with AI.

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

The device itself is a standalone non-invasive blood pressure monitor that measures and calculates parameters. The "clinical study" would inherently assess the performance of this device in a standalone manner against a reference method or predicate device. The document states "a clinical study demonstrated that the device is substantially equivalent to the cited predicate device." This implies standalone performance was assessed.

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

While not explicitly stated, for a non-invasive blood pressure monitor, the "ground truth" in a clinical study would typically be established by simultaneous measurements from a reference invasive blood pressure monitoring system (e.g., arterial line) or another highly accurate, validated non-invasive method. The document does not specify the exact method used for ground truth.

8. The sample size for the training set

This document describes a medical device seeking 510(k) clearance, not an AI/Machine Learning model that undergoes explicit "training." Therefore, there is no concept of a training set sample size as it would apply to AI. The device's algorithms are embedded and validated through testing, not iterative training on a large dataset in the AI sense.

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

As described in point 8, there isn't a "training set" in the context of an AI model for this device. The device's underlying scientific method (Peňáz - Wesseling) and embedded algorithms are based on established physiological principles and likely validated through extensive engineering and clinical testing, not ground truth labeling for a training set.

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