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The GMC Upper Arm Automatic Blood Pressure Monitor, Model X3, is a non-invasive blood pressure measurement device that is used for measuring systolic and diastolic blood pressure and pulse rate using the oscillometric method for adults at home.

The device has an irregular heartbeat (IHB) indicator. The device detects the appearance of an irregular heartbeat during measurement, and displays an IHB symbol on the LCD with the reading once the irregular heartbeat is detected.

The GMC Upper Arm Automatic Blood Pressure Monitor, Model X3, measures systolic and diastolic blood pressure and pulse rate of an adult individual. The method used to define blood pressure is similar to the auscultatory method but uses an electronic pressure sensor rather than a stethoscope and mercury manometer. The device utilizes the oscillometric method whereby the electronic pressure sensor converts variation in cuff pressure to electrical signals. The electrical signals are analyzed and used to define the systolic and diastolic measurements and determine the pulse rate. An irregular heart beat (IHB) indicator is displayed when there is more than a 25% deviation from the averaged pulse rate measurements.

Here's an analysis of the acceptance criteria and study proving the device meets them, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size for Test Set: 85 patients (39 males and 46 females).
• Data Provenance: The document does not explicitly state the country of origin or whether the study was retrospective or prospective. However, clinical validation studies for a new device are typically prospective.

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

• The document implies that the ground truth for blood pressure measurements was established using the standard auscultation method. It does not specify the number of experts (e.g., clinicians, physicians) performing the auscultation, nor their specific qualifications (e.g., "radiologist with 10 years of experience"). It's standard practice for trained medical professionals to perform auscultation, but their specific experience level is not detailed here.

4. Adjudication Method for the Test Set:

• The document states: "Blood pressure measurements were repeated alternatively with the device and auscultation in the same arm according to the sequence in #3-122 ISO 81060-2 Second edition 2013-05-01 Non-invasive sphygmomanometers - Part 2: Clinical validation of automated measurement type."
• This suggests a direct comparison method between the device and the auscultation reference. The specific adjudication method (e.g., 2+1, 3+1) is not detailed. However, ISO 81060-2 has specific requirements for the number of observers and how their readings are handled to establish criteria for ground truth.

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:

• No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed for this device. This is a blood pressure monitor, not an AI-powered diagnostic imaging device that would involve human readers interpreting cases. The study focuses on the accuracy of the automated measurement against a reference method.

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

• Yes, the clinical testing described is primarily a standalone performance evaluation of the device's algorithm. The "GMC Upper Arm Automatic Blood Pressure Monitor, Model X3" is an automated device, meaning its algorithm determines the blood pressure readings without direct human interpretation of a raw signal, other than possibly initiating the measurement. The clinical study validates the accuracy of these automated readings against a standard reference.

7. The Type of Ground Truth Used:

• The ground truth used was expert auscultation measurements. The document states, "Standard auscultation method was used as the reference blood pressure monitor measuring in the left arm." Auscultation by a trained professional is considered a clinical gold standard for blood pressure measurement in this context.

8. The Sample Size for the Training Set:

• The document does not provide information regarding a training set. This is typical for a device like a blood pressure monitor, which relies on established oscillometric principles and calibration, rather than a machine learning model that requires a distinct training phase.

9. How the Ground Truth for the Training Set was Established:

• As no training set is mentioned or implied, the document does not provide information on how ground truth for a training set was established.

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It is a device intended to measure the systolic, diastolic blood pressure and pulse rate of an adult individual by using a non-invasive oscillometric technique in which an inflatable cuff (available sizes: 22cm44cm (8.7in17.3in)) is wrapped around the single upper arm.

Arm automatic blood pressure monitor is based on pressure vibration method. Blood pressure cuff use the air pump to inflate, then the arteries are extruded by the cuff with pressure. Pressure sensor collects the pressure in the cuff, and then converts it to digital signal to the CPU. Then the software calculates the systolic and diastolic blood pressure and pulse rate.

This device is an Arm automatic blood pressure monitor, and the provided text describes its substantial equivalence to a predicate device, rather than presenting a standalone study with acceptance criteria and performance metrics in the typical sense of AI/ML device studies. This document is a 510(k) summary from the FDA.

However, I can extract the relevant "acceptance criteria" for blood pressure measurement accuracy based on the provided specifications, and then infer how it meets these based on the comparison to the predicate device and the referenced standard.

Inference from the text:

The device is an automatic blood pressure monitor that uses an oscillometric technique. The "acceptance criteria" are implied by the accuracy specification listed in the comparison table and the adherence to the IEC 80601-2-30 standard, which defines accuracy requirements for automated sphygmomanometers.

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

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

• Sample Size for Test Set: The document explicitly states: "Therefore repeated clinical test in accordance with the standard IEC 80601-2-30:2009 & A1:2013 is unnecessary." This indicates that no new clinical test set was used for the subject device to re-evaluate its accuracy for blood pressure measurement. Instead, substantial equivalence was established based on the technical similarity to the predicate device, which would have undergone clinical testing to meet the IEC 80601-2-30 standard. The IEC 80601-2-30 standard typically requires a clinical validation study with a specified number of subjects (e.g., at least 85 subjects for validation, including sufficient numbers in different blood pressure ranges). However, the specific sample size for the predicate is not provided in this document.
• Data Provenance: Not applicable for a new clinical test set for the subject device because it was deemed unnecessary. For the predicate device's validation (which the subject device is relying upon for clinical accuracy), the provenance is not detailed in this document.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable as no new clinical test set was performed for the subject device. For the predicate device's validation, the IEC 80601-2-30 standard requires a specific methodology for reference measurements, typically involving trained observers using a mercury sphygmomanometer or auscultation, but the exact number and qualifications of experts for the predicate's original study are not specified here.

4. Adjudication method for the test set:

• Not applicable as no new clinical test set was performed for the subject device. For the predicate device's validation, the IEC 80601-2-30 standard details the requirements for obtaining reference blood pressure measurements (ground truth), which often involves multiple observers and a consensus or averaging approach.

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

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

• Yes, implicitly. The device is an "automatic blood pressure monitor" that uses an "oscillometric technique" and "software calculates the systolic and diastolic blood pressure and pulse rate." This is a standalone algorithm (device) performance measurement. The accuracy criteria (Pressure: ±3mmHg, Pulse: ±5%) are for this standalone performance. The document states that because the technical aspects influencing blood pressure measurement were identical to the predicate, a repeated clinical test was unnecessary, meaning the standalone performance of the subject device is considered to meet the same accuracy standards as the predicate, which would have been established through a standalone clinical validation.

7. The type of ground truth used:

• For the clinical validation implied by adherence to IEC 80601-2-30, the ground truth for blood pressure measurements is typically established through auscultation by trained observers using a reference standard like a mercury sphygmomanometer. This involves direct physiological measurement.

8. The sample size for the training set:

• Not applicable in the context of typical AI/ML training sets. This device uses a "pressure vibration method" and a "software algorithm" for calculation, but the document does not describe it as an AI/ML device that requires a distinct "training set" for model development in the machine learning sense. The algorithm would have been developed and fine-tuned based on engineering principles and potentially clinical data, but not referred to as a "training set."

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

• Not applicable, as no described training set in the AI/ML sense. The algorithm's development would follow standard medical device software engineering practices, with performance validated against reference physiological measurements based on established medical standards (e.g., auscultation).

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It is a device intended to measure the systolic, diastolic blood pressure and pulse rate of an adult individual by using a non-invasive oscillometric technique in which an inflatable cuff (available sizes: 22cm44cm (8.7in17.3in)) is wrapped around the single upper arm.

Arm automatic blood pressure monitor is based on pressure vibration method. Blood pressure cuff use the air pump to inflate, then the arteries are extruded by the cuff with pressure. Pressure sensor collects the pressure in the cuff, and then converts it to digital signal to the CPU. Then the software calculates the systolic and diastolic blood pressure and pulse rate.

This document is a 510(k) Summary for a medical device called an "Arm automatic blood pressure monitor" (various models). The purpose of this summary is to demonstrate that the new device is substantially equivalent to a legally marketed predicate device.

Here's an analysis of the acceptance criteria and study information provided, extracting the requested details:

Acceptance Criteria and Device Performance

The acceptance criteria for accuracy are based on the ANSI/AAMI/ISO 81060-2:2009 standard for non-invasive sphygmomanometers. While the document mentions that a repeated clinical test for the subject devices was "unnecessary" due to technical similarity with the predicate, the predicate device's performance, which the subject devices claim substantial equivalence to, is detailed in a comparison table.

Table of Acceptance Criteria and Reported Device Performance

Study Information:

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

   • The document states that a repeated clinical test for the subject devices was unnecessary because the subject devices are identical to the predicate device from a technical point of view, and the differences (Power Source, Weight, Size, Broadcast Function) do not relate to blood pressure measurement technology. Therefore, no new clinical test data for the subject devices is provided in this summary.
   • The provenance of the data for the predicate device's clinical validation (which established the acceptance criteria for these equivalence claims) is not detailed in this document. It is implied that the predicate device (K151258) met the ANSI/AAMI/ISO 81060-2:2009 standard, but the specific details of that study are not provided in this submission.

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)

   • Since a new clinical test for the subject device was deemed "unnecessary," there would be no new ground truth established for the subject device in this submission. The ground truth for the predicate device's accuracy would have been established during its original clinical validation against the ANSI/AAMI/ISO 81060-2:2009 standard, which typically involves comparing automated measurements to those taken by trained observers using a reference sphygmomanometer. Details on the number or qualifications of these "experts" (trained observers) are not provided in this document.

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

   • No new clinical test was performed for the subject device, so no adjudication method is mentioned for its test set. The ANSI/AAMI/ISO 81060-2 standard outlines procedures for obtaining reference blood pressure measurements, often involving multiple observers to minimize bias, but the specific method used for the predicate device's validation is not detailed here.

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

   • This is not applicable. The device is an automatic blood pressure monitor, not an AI-assisted diagnostic tool that would involve human "readers" or an MRMC study.

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

   • The core functionality of an "Arm automatic blood pressure monitor" is inherently standalone. It uses an oscillometric technique to calculate blood pressure and pulse rate without human intervention during the measurement process. The comparison tables indicate the subject device and predicate device "use the same oscillometric method within the software algorithm to determine the systolic and diastolic blood pressure and pulse rate." This implies a standalone algorithm performance.

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

   • For blood pressure monitors, the "ground truth" during clinical validation (following standards like ANSI/AAMI/ISO 81060-2) is typically established by simultaneous auscultatory measurements performed by trained observers using a calibrated reference sphygmomanometer. This is considered an expert comparison or reference measurement.

7. The sample size for the training set

   • This document does not specify a training set as it focuses on demonstrating substantial equivalence rather than detailing the development and initial validation of the algorithm itself. The oscillometric method used is a well-established technique for blood pressure measurement, and any "training" (e.g., development of the algorithm's parameters) would have occurred during the initial design and validation of the predicate device's core technology, which is not described here.

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

   • As no training set is explicitly discussed in this document for the subject device, the method for establishing its ground truth is not provided. For oscillometric devices, the algorithm's parameters are typically derived and refined based on clinical data where the device's readings are compared against standard reference measurements.

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It is a device intended to measure the systolic, diastolic blood pressure, pulse rate of an adult individual by using a non-invasive oscillometric technique in which an inflatable cuff (available sizes: 22cm to 44cm (8.7in to 17.3in)) is wrapped around the single upper arm.

Arm automatic blood pressure monitor is based on pressure vibration method. Blood pressure cuff uses the air pump to inflate, and then the arteries are extruded by the cuff with pressure. Pressure sensor collects the pressure in the cuff, and then converts it to digital signal to the CPU. Then the software calculates the systolic, diastolic blood pressure and pulse rate.

The provided document is a 510(k) summary for the Shenzhen Pump Medical System Co., Ltd.'s Arm Automatic Blood Pressure Monitor, Models BE6034 and BE6134. It details the device's substantial equivalence to a predicate device but does not contain a standalone clinical study on the subject device (BE6034, BE6134) for blood pressure measurement accuracy with defined acceptance criteria and reported performance.

Instead, the document states: "The subject device, Model BE6034, BE6134 is from the technical point of view, identical to the predicate blood pressure monitor. Model BF1112, BF1113 and BF1115. The differences between them do not relate to blood pressure measurement technology, so the clinical accuracy in terms of blood pressure detection will not be affected. Therefore repeated clinical test in accordance with the standard IEC 80601-2-30:2009 & A1:2013... is unnecessary."

The acceptance criteria and reported device performance for blood pressure measurement accuracy are inferred from the predicate device's specifications, as no new clinical study was conducted for the subject devices on this aspect.

Here's a breakdown of the requested information based on the provided text, with the understanding that clinical accuracy data is based on the predicate and not a new study of the subject device in isolation:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not applicable for a new clinical test on the subject device's blood pressure accuracy, as none was performed. The determination of device accuracy for blood pressure measurement was based on the predicate device's performance.
• Data Provenance: Not applicable for a new clinical test on the subject device's blood pressure accuracy.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not applicable, as no new clinical study was performed for the subject device's blood pressure accuracy. The ground truth for the predicate device's original clinical validation would have been established according to the relevant standard (IEC 80601-2-30:2009 & A1:2013, which substituted ANSI/AAMI SP10). These standards typically involve simultaneous readings by trained observers (experts) using a reference sphygmomanometer.

4. Adjudication method for the test set

• Not applicable, as no new clinical study was performed for the subject device's blood pressure accuracy.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This device is an automatic blood pressure monitor and does not involve human readers interpreting results in the context of AI assistance.

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

• A standalone performance assessment for the subject devices (BE6034, BE6134) explicitly demonstrating blood pressure accuracy was not done or required by the FDA. The justification provided is that the "subject device... is from the technical point of view, identical to the predicate blood pressure monitor... The differences between them do not relate to blood pressure measurement technology, so the clinical accuracy in terms of blood pressure detection will not be affected." Therefore, the clinical performance of the subject device is considered equivalent to the predicate device.

7. The type of ground truth used

• For blood pressure monitors, the ground truth for clinical validation (as would have been applied to the predicate device) is typically established by simultaneous measurements by trained observers using a reference method (e.g., auscultation with a mercury or aneroid sphygmomanometer). This is a common requirement for validating blood pressure measurement accuracy according to standards like IEC 80601-2-30 (which substituted ANSI/AAMI SP10).

8. The sample size for the training set

• Not applicable to this device, as it is a medical device for vital signs measurement, not an AI model that requires a training set in the conventional sense of machine learning for image analysis or diagnostics. The software calculates blood pressure based on a pressure vibration method and an algorithm, but it's not described as an adaptive learning system.

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

• Not applicable (see point 8).

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It is intended for measuring adult blood pressure and pulse rate over-the-counter.

Arm automatic blood pressure monitor is based on pressure vibration method. Blood pressure cuff use the air pump to inflate, then the arteries are extruded by the cuff with pressure. Pressure sensor collects the pressure in the cuff, and then converts it to digital signal to the CPU. Then the software calculates the systolic and diastolic blood pressure and pulse rate.

The arm automatic blood pressure monitor BF1112, BF1112, BF1113 and BF1115 have the same basic principles, main function, performance and intended use, and they are consistent in product structure and material.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Reported Device Performance

Study Details

• 1. Sample size used for the test set and the data provenance:

  • Sample Size: The document states that the clinical study was "evaluated according to ANSI/AAMI SP10." However, the exact sample size for the test set is not explicitly mentioned in the provided text. ANSI/AAMI SP10 is a standard for blood pressure measuring devices, and it outlines requirements for clinical validation, including sample sizes (typically a minimum of 85 subjects for accuracy assessment). Without further information, we cannot confirm the precise number of subjects used in this specific study.
  • Data Provenance: The document does not specify the country of origin of the data or whether the study was retrospective or prospective. It only mentions that the applicant is from Shenzhen, China, and the predicate device manufacturer is Omron Healthcare, Inc.

• 2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

  • This information is not provided in the text. For blood pressure monitors, ground truth is typically established by trained observers taking manual auscultatory measurements using a mercury manometer or a validated oscillometric device, but the number and qualifications of such observers are not detailed here.

• 3. Adjudication method for the test set:

  • This information is not provided in the text.

• 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. This is a blood pressure monitor, not an AI-assisted diagnostic device typically evaluated with MRMC studies comparing human readers. The device is standalone.

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

  • Yes. The device is an "Arm automatic blood pressure monitor" and operates as a standalone device, providing blood pressure and pulse rate measurements directly. The clinical study evaluated the device's performance against a standard, implying a standalone assessment of its accuracy.

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

  • The ground truth for blood pressure monitor validation, as per ANSI/AAMI SP10, typically involves manual auscultatory measurements performed by trained observers using a reference standard (like a mercury sphygmomanometer). While not explicitly stated as "expert consensus," this method relies on expert human measurement.

• 7. The sample size for the training set:

  • This information is not provided in the text. For traditional medical devices like this, there isn't typically a distinct "training set" in the sense of machine learning algorithms. The device's underlying algorithm is developed and calibrated, and then its performance is validated against a separate test set. The document only mentions "Laboratory testing" for specification validation.

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

  • As there isn't a "training set" described in the machine learning sense, the method for establishing ground truth for a training set is not applicable here. The device's design and calibration would have been based on established physiological principles and engineering practices, likely involving various test conditions and reference measurements during development, but this is distinct from a machine learning training set.

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The Accumed Upper Arm Automatic Blood Pressure Monitor, Model AAE-701, is a non-invasive blood pressure measurement device that is used for measuring systolic and diastolic blood pressure and pulse rate using the oscillometric method for adults at home.

The device has an irregular heartbeat (IHB) indicator. The device detects the appearance of an irregular heartbeat during measurement, and displays an IHB symbol on the LCD with the reading once the irregular heartbeat is detected.

The Accumed Upper Arm Automatic Blood Pressure Monitor, Model AAE-701, measures systolic and diastolic blood pressure and pulse rate of an adult individual. The method used to define blood pressure is similar to the auscultatory method but uses an electronic pressure sensor rather than a stethoscope and mercury manometer. The device utilizes the oscillometric method whereby the electronic pressure sensor converts variation in cuff pressure to electrical signals. The electrical signals are analyzed and used to define the systolic and diastolic measurements and determine the pulse rate. An irregular heart beat (IHB) indicator is displayed when there is more than a 25% deviation from the averaged pulse rate measurements.

Here's a breakdown of the acceptance criteria and the study information derived from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document refers to meeting established standards, rather than defining specific numerical acceptance criteria within the 510(k) summary itself. The reported device performance is that it met these standards.

(Note: ANSI/AAMI SP10 is the standard for non-invasive sphygmomanometers, covering accuracy requirements for blood pressure devices. The IEC/EN 60601 series covers medical electrical equipment safety. The specific numerical accuracy criteria are contained within the ANSI/AAMI SP10 standard, but are not explicitly listed in this 510(k) summary.)

Missing Information: The document does not explicitly state the numerical acceptance criteria from ANSI/AAMI SP10, nor does it provide the exact performance metrics (e.g., mean difference and standard deviation) for blood pressure measurements and pulse rate as specified in that standard. It only states that the device "meets all applicable requirements."

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "Bench testing was conducted" and refers to meeting standards, but does not provide details on the number of subjects or measurements included in these tests for accuracy evaluation.
• Data Provenance: Not explicitly stated. It's likely prospective data collected during the bench testing, but the country of origin is not mentioned.

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

This information is not provided in the document. For blood pressure monitors, ground truth is typically established against a reference method (e.g., auscultatory method with a trained observer using a mercury sphygmomanometer) and not usually by "experts" in the sense of radiologists.

4. Adjudication Method for the Test Set

This information is not provided and is generally not applicable to the performance testing of an automated blood pressure monitor. Accuracy is assessed by comparing the device's readings against a validated reference measurement, not through expert adjudication of images or diagnoses.

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

• No, a MRMC comparative effectiveness study was not done. This type of study is typically used for diagnostic imaging devices where human readers interpret results, often with and without AI assistance, to assess the impact of AI on reader performance. This device is an automated blood pressure monitor.
• Effect Size of Human Readers Improvement with AI vs. without AI Assistance: Not applicable.

6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• Yes, in essence, a standalone performance study was done. The "Bench testing" against ANSI/AAMI SP10 (which includes clinical validation protocols) assesses the algorithm's performance in automatically measuring blood pressure and pulse rate without human intervention beyond device operation. The device is designed to operate autonomously to produce readings.

7. The Type of Ground Truth Used

The ground truth used for the performance testing (specifically, for conforming to ANSI/AAMI SP10) would be a validated reference measurement method, such as the auscultatory method performed by trained observers using a reference sphygmomanometer (e.g., mercurial or laboratory-grade aneroid manometer). This is implied by the reference to the ANSI/AAMI SP10 standard.

8. Sample Size for the Training Set

This information is not provided. Blood pressure monitors using the oscillometric method rely on algorithms that are developed and validated over time, likely with extensive datasets from various populations. The specific training set for this particular product is not detailed in the summary.

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

This information is not provided. For oscillometric algorithms, the development process generally involves comparing numerous oscillometric waveforms to simultaneous reference blood pressure measurements (established via auscultation or intra-arterial monitoring) across a diverse patient population to train and refine the algorithm's ability to accurately derive systolic and diastolic pressures from the oscillations.

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The Microlife Upper Arm Automatic Blood Pressure Monitor, Model BP-3BTO-1 with Optional Thermal Printer, Model PR 1KA1 is a device intended to measure the systolic and diastolic blood pressure and pulse rate of an adult individual by using a non-invasive technique in which an inflatable cuff is wrapped around the upper arm. This device can be used in connection with the Microlife Thermal Printer.

The Microlife Upper Arm Automatic Blood Pressure Monitor, Model BP-3BTO-1 is designed to measure the systolic and diastolic blood pressure and pulse rate of an individual by using a non-invasive technique in which an inflatable cuff is wrapped around the upper arm. Our method to define systolic and diastolic pressure is similar to the auscultatory method but uses an electronic capacitive pressure sensor rather than a stethoscope and mercury manometer. The sensor converts tiny alterations in cuff pressure to electrical signals, by analyzing those signals to define the systolic and diastolic blood pressure and calculating pulse rate, which is a well - known technique in the market called the "oscillometric method". An optional printer is included as an accessory which can be sold separately in a separate box with the printer user manual.

The provided text describes the Microlife Upper Arm Automatic Blood Pressure Monitor, Model BP-3BTO-1, with Optional Thermal Printer, Model PR 1KA1.

Here's an analysis of the acceptance criteria and the study information:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not explicitly state the sample size (number of subjects) used for the clinical testing in accordance with ANSI/AAMI SP10-1992.
• Data Provenance: Not specified in the provided text (e.g., country of origin, retrospective/prospective).

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

The document refers to the ANSI/AAMI SP10-1992 standard for clinical testing. This standard typically involves comparison of the automated device readings against auscultatory measurements performed by trained observers (experts). However, the specific number of experts and their qualifications (e.g., "radiologist with 10 years of experience") are not explicitly stated in the provided 510(k) summary.

4. Adjudication Method for the Test Set

The document does not explicitly describe the adjudication method (e.g., 2+1, 3+1, none) for the test set. For blood pressure measurement, the ground truth is typically established by trained observers taking multiple readings.

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

A Multi Reader Multi Case (MRMC) comparative effectiveness study was not performed. This type of study is more common for diagnostic imaging devices where human readers interpret results, and the AI's effect on their performance is evaluated. This device is an automated blood pressure monitor, and its performance is assessed against a standard, not in terms of improving human reader effectiveness.

6. Standalone Performance Study

Yes, a standalone study was performed. The entire clinical testing section (Discussion of Clinical Tests Performed) is dedicated to evaluating the device's performance (i.e., algorithm only without human-in-the-loop performance) against the ANSI/AAMI SP10-1992 standard. The statement "The BP-3BTO-1 met all relevant requirements of this standard" confirms the standalone performance evaluation.

7. Type of Ground Truth Used

The ground truth for the clinical testing (per ANSI/AAMI SP10-1992) would typically involve expert auscultatory measurements. These are considered the "expert consensus" or "reference method" in blood pressure measurement testing. The device states its method is "similar to the auscultatory method" in its description.

8. Sample Size for the Training Set

The document does not provide information regarding a specific "training set" sample size. This device relies on an "oscillometric method" and a software algorithm. While the algorithm was developed, the submission focuses on validation against a standard, not on a machine learning training paradigm with a distinct training set. The "fuzzy logic inflation" and "split slope resolution" are algorithmic improvements, but information about a formal "training set" as understood in modern AI development is absent.

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

Since there is no explicit mention of a "training set" in the context of modern machine learning, there is no information on how ground truth for such a set was established. The device uses a well-known "oscillometric method" and algorithmic enhancements, implying that the underlying principles and parameters of the algorithm were likely developed based on established physiological principles and empirical data, rather than a separate, labeled "training set" in the AI sense.

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