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Wireless Smart Thermometer is intended to be used at home for the intermittent measurement and monitoring of human body temperature orally, rectally, and under the arm. The devices are reusable for the adult and pediatic patient population (not suitable for neonates).

Wireless Smart Thermometer (Model: FDTH3400, FDTH3401, FDTH3402, FDTH3403, FDTH3404, FDTH3405, FDTH3406, FDTH3407, FDTH3408, FDTH3409, FDTH3410, FDTH3411, FDTH-V0-13, FDTH-V0-4) utilizes a modular design method and consists of six main modules:

• Buzzer module: Control the product buzzer to produce audible notifications;
• Display module: Display driver content through notifications, and combine to produce various display interfaces;
• Battery voltage management module: Detect the battery power of the product and output the battery power level;
• Temperature measurement module: After collecting the electrical signal of the external temperature sensor through AD, it is restored to the temperature value through various algorithms
• Button module: This module is used to identify whether the product button is active;
• Wireless function module: Transfer the measurement data to the mobile device.

The provided text describes the Wireless Smart Thermometer (models FDTH3400, FDTH3401, FDTH3402, FDTH3403, FDTH3404, FDTH3405, FDTH3406, FDTH3407, FDTH3408, FDTH3409, FDTH3410, FDTH3411, FDTH-V0-13, FDTH-V0-4) and its substantial equivalence to a predicate device. While it mentions performance criteria and clinical testing, it does not detail specific acceptance criteria values or the results of a statistically powered clinical study to "prove" the device meets them in the way typically expected for a full clinical study report. Most of the information provided refers to compliance with standards.

Here's an attempt to extract the requested information based on the provided text, with significant limitations due to the nature of the document (a 510(k) summary, not a detailed study report):

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

The document primarily references compliance with standards rather than specific acceptance criteria values and reported performance figures. It lists the measuring accuracy as:

• For FDTH3400~FDTH3405 and FDTH-V0-13: ±0.10°C between 35.00°C42.00°C (±0.18°F between 95.00°F107.60°F), and ±0.20°C (or ±0.36°F) outside this range.
• For FDTH3406~FDTH3411 and FDTH-V0-4: ±0.3°C between 34.0°C42.0°C (±0.6°F between 93.2°F107.6°F), and ±0.4°C (or ±0.8°F) outside this range.

The document states: "The results showed the accuracy of the subject device is within acceptable scope specified in ISO 80601-2-56." This implies that the device's measured accuracy performance meets the acceptance criteria defined by the ISO 80601-2-56 standard for clinical thermometers, which generally defines the maximum permissible error for different temperature ranges. However, the specific measured performance values from the clinical study are not provided in this summary.

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

• Sample Size for Test Set (Clinical Study): 105 patients.
• Data Provenance: Not explicitly stated regarding country of origin. The study appears to be prospective, as it states "105 patients participated in the subjects were volunteer to take part in the clinical study, all the subjects completed the clinical study without any adverse events."

3. 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 document. The text refers to "clinical validation data" and states results were "within acceptable scope specified in ISO 80601-2-56," but does not mention experts establishing ground truth or their qualifications. For thermometer accuracy validation, ground truth is typically established by high-precision reference thermometers rather than expert consensus on images.

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

This information is not applicable/not provided. Adjudication methods like 2+1 or 3+1 are typically used in studies involving expert review of medical images or other subjective interpretations to establish ground truth. For a clinical thermometer, the accuracy is validated against a reference standard, not through expert adjudication of results.

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

This information is not applicable/not provided. The device is a "Wireless Smart Thermometer" and not an AI-powered diagnostic imaging tool that would typically involve human readers or an MRMC study. It measures body temperature.

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

Yes, a standalone performance assessment was conducted. The clinical testing evaluates the device's accuracy in measuring body temperature, which is a standalone function of the thermometer. The "Wireless function module" transfers data to a mobile device, but the core temperature measurement capability is inherent to the device itself, making it a standalone functional assessment.

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

The ground truth for the clinical study would be established by high-precision reference thermometers or validated methods of core body temperature measurement, implicitly adhering to the requirements of ISO 80601-2-56. The document mentions "water bath" in relation to measurement time, but for clinical accuracy, more direct human body temperature references are used.

8. The sample size for the training set

This information is not applicable/not provided. The device is a clinical electronic thermometer, not a machine learning or AI algorithm in the context that would typically require a "training set" of data to develop its core functionality. While there might be internal calibration data or algorithm fine-tuning, the concept of a "training set" as in AI/ML development does not apply here in the way it would for image analysis algorithms.

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

This information is not applicable/not provided for the same reasons as #8.

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Arm Blood Pressure Monitor/Automatic Wireless Smart Blood Pressure is intended to measure the blood pressure and pulse rate of adults and children at least 12 years of age, at household or medical center. with the left upper arm according to the instruction in the user's guide manual(Cuff size 220 ~ 420 mm).

Arm Blood Pressure Monitor/Automatic Wireless Smart Blood Pressure Monitor (Model:FDBP-A7B、FDBP-A7BL、FDBP-A7BT、FDBP-A7BLT、FDBP-A8B、 FDBP-A8BL、FDBP-A8BT、FDBP-A8BLT、FDBP-A9B、FDBP-A9BL、FDBP-A9BT、 FDBP-A9BLT、FDBP-A10B、FDBP-A10BL、FDBP-A10BT、FDBP-A10BLT) includes utilize modular design method. It consists of nine main modules: power-on self-test module, system initialization module,sampling data processing and pressure, pulse rate calculation module, display processing module, power detection processing module, data storage module, key scanning processing module, sampling processing module, , wireless function module, and each module communicates through a message queue. The blood pressure monitor controls the pneumatic flow control module through singlechipped microcomputer to pressurize the cuff module in order to exceed the lower pressure of patients, the blood being pushed against the artery walls; Pneumatic Flow Control Module being directed to release the pressure, while the pressure detection module collect pulse pressure signal and amplify filter; amplified filter signal being read by single-chipped microcomputer for pressure and pulse signal,through unique algorithm to obtain the systolic and diastolic pressure with pulse; Single-chipped microcomputer will control the inflation/deflation module to release the pressure after receive measurements; in the meanwhile, display the measurements results then stored the values with memory module.

The provided text describes the 510(k) submission for the Famidoc Technology Company Limited Arm Blood Pressure Monitor/Automatic Wireless Smart Blood Pressure Monitor. This document is a premarket notification to the FDA to demonstrate substantial equivalence to a legally marketed predicate device. The information below is extracted from the provided text to fulfill the request.

1. Table of Acceptance Criteria and Reported Device Performance

The device's performance, particularly its clinical accuracy, is evaluated against the standards outlined in ISO 81060-2.

The document states: "The results showed the accuracy of the subject device is within acceptable scope specified in ISO 81060-2."

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

• Sample Size: 85 patients (43 males)
• Data Provenance: The document does not explicitly state the country of origin but implies a clinical study was performed. It also does not specify if the study was retrospective or prospective, but clinical studies are generally prospective in nature.

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

The document mentions "manual Mercury Sphygmomanometer was used as a reference sphygmomanometer." It does not specify the number of experts or their qualifications for establishing the ground truth, but implicitly, trained medical professionals would be operating the reference device.

4. Adjudication method for the test set

The document states, "Same arm sequential method was adopted during the clinical study." This refers to how measurements were taken, not an adjudication method for conflicting readings. No explicit adjudication method for the test set is described.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance

This is an automated blood pressure monitor, not an AI-assisted diagnostic device for human readers. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not applicable and was not performed.

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

Yes, the device operates as a standalone automated blood pressure monitor. Its performance was tested directly against a reference standard in a clinical setting. The clinical study details describe the device's performance in measuring blood pressure and pulse rate without human-in-the-loop assistance in the measurement process itself, beyond initiation and observation.

7. The type of ground truth used

The ground truth for blood pressure and pulse rate measurements was established using a manual Mercury Sphygmomanometer. This is considered a clinical reference standard.

8. The sample size for the training set

The document does not provide a specific sample size for a training set. This is typical for medical devices that rely on established physical measurement principles (oscillometric method) and are validated against existing standards rather than necessarily "training" a machine learning algorithm in the same way an AI diagnostic tool would. If an algorithm within the device was developed using data, that information is not detailed here.

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

As no explicit training set is mentioned in the context of machine learning, the ground truth establishment for such a set is not described. The device's underlying principles are based on oscillometric measurements, for which the fundamental accuracy is validated against clinical standards like mercury sphygmomanometers.

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FDBP A series Upper Arm Blood Pressure Monitor is intended to measure the blood pressure and pulse and children at least 12 years of age, at household or medical center. (Not suitable for neonate, pregnancy or pre-eclampsia). with the cuff around the left upper arm according to the instruction in the user's guide manual.

FDBP A series Upper Arm Blood Pressure Monitor (Model:FDBP-A8,FDBP-A11,FDBP-A12,FDBP-A14 )includes utilize modular design method, It consists of nine main modules: power-on self-test module, system initialization module,sampling data processing and pressure, pulse rate calculation module, display processing module, power detection processing module, data storage module, key scanning processing module, sampling processing module, voice broadcast processing module, and each module communicates through a message queue. The blood pressure monitor controls the pneumatic flow control module through singlechipped microcomputer to pressurize the cuff module in order to exceed the lower pressure of patients, the blood being pushed against the artery walls; Pneumatic Flow Control Module being directed to release the pressure, while the pressure detection module collect pulse pressure signal and amplify filter; amplified filtersignal being read by single-chipped microcomputer for pressure and pulse signal,through unique algorithm to obtain the systolic and diastolic pressure with pulse; Single-chipped microcomputer will control the inflation module to release the pressure after receive measurements; in the meanwhile, display the measurements results then stored the values with memory module.

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

1. Table of Acceptance Criteria and Reported Device Performance

Study Proving Acceptance Criteria:

The studies conducted for the FDBP A Series Upper Arm Blood Pressure Monitor are divided into "Non-Clinical Data" and "Clinical Data."

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

• Non-Clinical Data:
  • The document does not explicitly state the sample size for individual biocompatibility, electrical safety, EMC, or bench testing. However, it indicates these tests were conducted on "all the modules and accessories in the system" and "all the patient contracting materials."
  • Data Provenance: Not specified, but given the manufacturer is Famidoc Technology Company Limited (China), it's highly probable the testing was conducted in China or by labs contracted by the Chinese manufacturer. The document doesn't specify if it's retrospective or prospective for non-clinical testing.
• Clinical Data:
  • The document states: "Clinical testing is conducted per ISO 81060-2: 2013 Non-invasive sphygmomanometers -Part 2: Clinical validation of automated measurement type."
  • ISO 81060-2: 2013 typically requires a specific number of subjects for clinical validation. While the exact number is not provided in this document, the standard generally mandates a minimum of 85 subjects for validation in a mixed population.
  • Data Provenance: Not explicitly stated, but likely from a clinical study conducted either within China or a region where compliance with ISO 81060-2 is standard. The document doesn't specify if it's retrospective or prospective, but clinical validation studies are inherently prospective.

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

• For the clinical validation (per ISO 81060-2):
  • ISO 81060-2 requires that the reference blood pressure measurements (the "ground truth") be obtained by at least two trained observers using a mercury sphygmomanometer or an equivalent validated reference device.
  • Qualifications of Experts: These observers must be specifically trained and certified to perform accurate auscultatory blood pressure measurements, adhering to strict protocols outlined in the standard. The document does not provide specific details on the individual qualifications of the "two trained observers" used in this particular study, but it is a prerequisite of the standard cited.

4. Adjudication Method for the Test Set:

• For the clinical validation (per ISO 81060-2):
  • The standard dictates a specific methodology where simultaneous (or near-simultaneous) measurements are taken by the device under test and the two trained observers. The average of the two observers' measurements typically serves as the reference (ground truth). Discrepancies between the observers' measurements might trigger re-measurements or specific rules for reconciliation, but a formal "adjudication" in the sense of a third expert resolving disagreements is not always explicitly a primary step unless the initial agreement criteria are not met. The document does not specify the exact adjudication method (e.g., 2+1, 3+1) beyond compliance with ISO 81060-2.

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 an automated blood pressure monitor for direct blood pressure measurement, not an AI-assisted diagnostic imaging device or an interpretation tool involving human "readers." Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not relevant to this type of medical device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

• Yes, this is a standalone device. The FDBP A Series Upper Arm Blood Pressure Monitor is an automated device designed to measure blood pressure without human intervention in the measurement process (once the cuff is applied and the device activated). The "algorithm only" performance is the core function of such a device. The clinical validation conducted under ISO 81060-2 is precisely a standalone performance evaluation against a human-read auscultatory reference.

7. The Type of Ground Truth Used:

• Expert Consensus (Auscultatory Reference): For the clinical validation, the ground truth for blood pressure measurements is established by trained human observers using the auscultatory method (typically with a mercury sphygmomanometer or a validated equivalent), following the protocols defined in ISO 81060-2. This is considered an "expert consensus" in the context of blood pressure measurement.

8. The Sample Size for the Training Set:

• Not applicable/Not explicitly stated. As an automated blood pressure monitor, the device's core functionality relies on a pre-defined oscillometric algorithm rather than a "training set" in the context of machine learning or AI models. While the algorithm itself would have been developed and refined using data (which could be loosely considered "training"), the document does not provide details on such a training dataset or its size. The primary validation focuses on its clinical performance against expert-derived ground truth.

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

• Not applicable/Not explicitly stated. Similar to point 8, the document does not detail a "training set" for an AI algorithm. If an algorithm development process involved data, the ground truth for that development would likely have been established through a combination of simulated data, data from calibration devices, and potentially earlier validation studies against auscultatory measurements. However, the document does not provide these specifics.

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