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KD-7962 Fully Automatic Electronic Blood Pressure Monitor is for use by medical professionals or at home and is a non-invasive blood pressure measurement system intended to measure the diastolic and systolic blood pressures and pulse rate of an adult individual by using a non-invasive technique in which an inflatable cuff is wrapped around the wrist. The cuff circumference is limited to 6.1023 inches to 9.8425 inches.

KD-7962 Fully Automatic Electronic Blood Pressure Monitor is for use by medical professionals or at home and is a non-invasive blood pressure measurement system intended to measure the diastolic and systolic blood pressures and pulse rate of an adult individual by using a non-invasive technique in which an inflatable cuff is wrapped around the wrist. The cuff circumference is limited to 6.1023 inches to 9.8425 inches. It is designed and manufactured according to ANSI/AAMI SP10--- manual, electronic or automated sphygmanometers. The operational principle is based on oscillometric and silicon integrate pressure sensor technology, the result will be shown on a LCD with an electronic interface module, the result can also be classified and displayed by the function of blood pressure classification indicator, the memory capability is 2×90 times. If any irregular heartbeat is detected, it can be shown on the LCD. The LCD backlight, the touch key button and the voice function make it more convenient to use. It also has the function of averaging the last three measurements.

The provided text describes a 510(k) summary for the KD-7962 Fully Automatic Electronic Blood Pressure Monitor. However, it does not contain explicit details about acceptance criteria, specific study results demonstrating device performance against those criteria, or the methodology of such a study.

The document primarily focuses on establishing substantial equivalence to a predicate device (KD-7961) by comparing technological characteristics and conformity to standards.

Here's an attempt to answer your questions based on the available information, noting where information is not present in the provided text:

Acceptance Criteria and Device Performance for KD-7962 Fully Automatic Electronic Blood Pressure Monitor

The provided 510(k) summary indicates that the KD-7962 device conforms to the ANSI/AAMI SP10 standard for manual, electronic, or automated sphygmomanometers. This standard dictates the performance requirements for blood pressure monitors. While the specific numerical acceptance criteria from AAMI SP10 are not detailed in this document, the device's conformance to this standard implies it meets those criteria.

The submission claims that any differences in performance parameters (cuff pressure range, overpressure limit) between the KD-7962 and its predicate KD-7961 "do not raise any new questions of safety and effectiveness," suggesting that the new device's performance is acceptable.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The actual numerical acceptance criteria for blood pressure and pulse rate accuracy as defined by AAMI SP10 (e.g., mean difference ≤ ±5 mmHg with a standard deviation ≤ 8 mmHg) are not explicitly stated in this 510(k) summary, nor are the specific numerical performance results of the KD-7962.

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

• Sample Size for Test Set: This information is not provided in the document.
• Data Provenance: This information is not provided in the document.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not provided in the document. For blood pressure monitors, ground truth is typically established by trained technicians or clinicians using a reference sphygmomanometer (e.g., a mercury sphygmomanometer or an auscultatory method) alongside the device under test.

4. Adjudication Method for the Test Set

This information is not provided in the document.

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

• Was an MRMC study done? No, this type of study is not relevant for a fully automated blood pressure monitor like the KD-7962, which does not involve human interpretation of medical images or complex data where AI assistance would be applicable to improve human reader performance.
• Effect size of human reader improvement with AI vs. without AI assistance: Not applicable.

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

Yes, a standalone performance study must have been conducted to demonstrate conformity to the AAMI SP10 standard. The device is a "Fully Automatic Electronic Blood Pressure Monitor," implying its primary function is standalone measurement without continuous human expert intervention for each reading. The document states, "the test in this submission provides demonstration that these small differences do not raise any new questions of safety and effectiveness." This implicitly refers to performance testing that would have included evaluation against the AAMI SP10 standard.

7. Type of Ground Truth Used

Based on the nature of blood pressure monitors, the ground truth would typically be established using reference blood pressure measurements obtained simultaneously with expert observers (e.g., trained clinicians or technicians using a validated auscultatory method or a calibrated reference sphygmomanometer). This is the standard methodology for validating automated blood pressure devices according to AAMI SP10.

8. Sample Size for the Training Set

• Training Set Sample Size: This information is not provided in the document. For a traditional oscillometric blood pressure monitor, there typically isn't a "training set" in the machine learning sense. Instead, the device's algorithms are developed and calibrated based on physiological principles and then validated against a test set.

9. How Ground Truth for the Training Set Was Established

• Ground Truth for Training: This information is not provided and is largely not applicable in the context of traditional, non-machine learning blood pressure monitors. The device's internal algorithms are based on established oscillometric principles and calibrated during development, rather than "trained" on a dataset with ground truth in the way an AI model would be. Calibration and development would likely involve testing against reference measurements performed by experts, but this isn't typically referred to as "training set ground truth."

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