Search Results

Fora Care Blood Pressure Monitoring System is a system designed to measure the systolic and diastolic blood pressure and pulse rate by using a non-invasive technique in which an inflatable cuff is wrapped on the upper arm. It is intended for individuals age 18 and above use at home and in clinical settings. The device is not to be used for the diagnosis of hypertension or for testing on newborns.

Fora Care Blood Pressure Monitoring System (Model: P80) can be operated by the device itself or with the TDLink BP App. TDLink BP App is designed to assist in blood pressure testing, recording, tracking and monitoring in easy.

Here's a breakdown of the acceptance criteria and study information for the Fora Care Blood Pressure Monitoring System, Model P80, based on the provided 510(k) summary:

Acceptance Criteria and Device Performance:

The 510(k) summary explicitly states that the Fora Care Blood Pressure Monitoring System (Model P80) "meets the same performance specifications as the predicate device" and that "the accuracy has been demonstrated in the predicate 510(k) submission according to the requirements of ANSI/AAMI SP10:2002."

Therefore, the acceptance criteria and reported device performance are derived from the predicate device (U-RIGHT TD-3128 Blood Pressure Monitoring System, K112216) as required by ANSI/AAMI SP10:2002. While the exact numerical acceptance criteria are not provided in this document, the standard typically requires that the device's blood pressure measurements be within a certain mean difference and standard deviation compared to reference measurements.

Study Details:

1. Sample Size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • Sample Size: Not explicitly stated for the subject device (Fora Care Blood Pressure Monitoring System). The submission leverages the performance data of the predicate device (U-RIGHT TD-3128), which would have had its own test set size to meet ANSI/AAMI SP10:2002.
   • Data Provenance: Not specified for the subject device or the predicate's original study.

2. 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):

   • Not specified. For blood pressure monitors tested against ANSI/AAMI SP10, ground truth is typically established using simultaneous auscultatory measurements by trained observers.

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

   • Not specified, but for ANSI/AAMI SP10, it's common to have at least two trained observers taking simultaneous readings, with a third if there are significant discrepancies.

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. This device is a standalone blood pressure monitor, not an AI-assisted diagnostic tool for human readers.

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

   • Yes, a standalone performance assessment was conducted, or rather, the performance of the algorithm (oscillometric method) embedded in the device was demonstrated through its substantial equivalence to a predicate device that had undergone such testing. The document states: "No clinical study was performed using the subject device since the subject device's blood pressure monitoring capability was duplicated from the predicate, K11216 submitted by TaiDoc." This means the standalone performance is inherited from the predicate.

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

   • The ground truth for blood pressure monitors adhering to ANSI/AAMI SP10:2002 is typically established through auscultatory measurements performed by trained observers (experts) using a mercury sphygmomanometer or validated reference device.

7. The sample size for the training set:

   • Not applicable as this is a blood pressure monitor based on a physical measurement principle (oscillometric method) rather than a machine learning algorithm requiring a separate training set. The algorithm itself
     is a well-established method.

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

   • Not applicable for the reason stated above. The "training" for the oscillometric method's development would have historically involved extensive empirical data collection and validation against auscultatory readings.

Ask a specific question about this device