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Ageless Health Medical Digital Thermometers are intended for the measurement and monitoring of human body temperature by doctor or consumers in the hospital or home. lt can be used for axillary measurement, oral measurement and rectal measurement.

Ageless Health Medical Digital Thermometers comprises a thermistor for getting temperature signal, a reference resistor for comparing the resistance of the thermistor, a buzzer for sounding effect, an ASIC for processing the target temperature digitally, and a LCD for displaying the temperature result. The design principle of thermometer is based on thermos sensor and ASIC technology. A thermistor is used as thermos sensor. The ASIC gets the sensor's signal from human body, then processes the signal and calculates the result, after that displays the temperature result by a LCD.

The provided document is a 510(k) summary for the "Ageless Health Medical Digital Thermometer." It details the device's characteristics and compares it to predicate devices to establish substantial equivalence.

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

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the device are largely based on adherence to recognized standards and specific performance metrics, particularly measurement accuracy and range.

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

The document states that the device's safety and performance were evaluated by "lab bench testing" according to a list of standards. However, it does not provide details on the sample size used for these tests. There's also no explicit information on data provenance in terms of country of origin or whether the tests were retrospective or prospective, beyond being "lab bench testing." It is implied that these tests were conducted as part of the device development and verification process.

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

The document does not mention the use of experts to establish ground truth for a test set. The validation appears to be based on engineering and performance testing against established standards for temperature measurement devices.

4. Adjudication method for the test set

Since there is no mention of experts or a subjective assessment test set, there is no adjudication method described. The evaluation is against objective engineering and performance standards.

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 type of study is not applicable to a digital thermometer. The device is a direct measurement tool, not an AI-assisted diagnostic device requiring human interpretation of complex data. Therefore, an MRMC comparative effectiveness study was not performed, nor is there any mention of AI assistance.

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

The device is inherently a standalone measurement tool. Its performance is evaluated purely on its ability to accurately measure temperature according to the specified standards, without human intervention in the measurement process itself. So, in a sense, a "standalone" performance evaluation was done on the device's core function.

7. The type of ground truth used

The ground truth used for this type of device is established by:

• Reference standards and calibrated equipment: The "lab bench testing" implicitly relies on highly accurate and traceable reference thermometers and controlled environmental conditions as the ground truth for temperature measurement.
• Biological evaluation standards: ISO 10993-5 (in vitro cytotoxicity) and ISO 10993-10 (irritation and skin sensitization) involve standardized biological assays where the "ground truth" is determined by the absence or presence of adverse biological reactions as defined by the standards.

8. The sample size for the training set

The concept of a "training set" is not applicable here as this is a traditional medical device (digital thermometer) and not an AI/machine learning device. The device's operation is based on fixed physical principles and programmed logic, not learned from data.

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

As there is no training set for this device, this question is not applicable. The device's functionality is designed and verified against established engineering and medical standards, not by training on a dataset.

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AGE Automatic Upper Arm Blood Pressure Monitor is intended for use by medical professionals or at home to monitor and display diastolic, systolic blood pressure and pulse rate on adult each time, with the cuff around the left upper arm according to the instruction in the user's guide manual.

AGE Automatic Upper Arm Blood Pressure Monitor is a battery driven automatic non-invasive blood pressure meter. It can automatically conduct the inflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult at arm within its claimed range and accuracy via the Oscillometry technique. The device also has low voltage indication, which will be triggered when the battery is low.

The provided text describes a 510(k) submission for an Automatic Upper Arm Blood Pressure Monitor. It focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving the device meets specific acceptance criteria based on a clinical trial.

Therefore, many of the requested details about acceptance criteria, study design, expert ground truth, and human-in-the-loop performance are not available in this document, as they are typically associated with performance validation studies for AI/ML devices or new diagnostic methods, not blood pressure monitors seeking 510(k) clearance based on substantial equivalence to an existing device.

However, I can extract the relevant information regarding performance standards and comparisons that are mentioned:

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

The document references the standard AAMI / ANSI / ISO 81060-2 Second Edition, Non-Invasive Sphygmomanometers - Part 2: Clinical Validation Of Automated Measurement Type as the key performance standard.

While explicit acceptance criteria are not listed in a table, the standard itself defines accuracy requirements for blood pressure monitors. The device claims the following accuracy, which would implicitly be the performance criteria it aims to meet based on the standard:

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

The document states that the device was evaluated for "safety and performance by lab bench testing" and refers to "Clinical Validation Of Automated Measurement Type" according to ISO 81060-2.

• Sample Size: The document does not explicitly state the sample size (number of subjects/measurements) used for the clinical validation. ISO 81060-2 typically specifies minimum patient numbers (e.g., 85 subjects for validation). Without the full study report, the exact sample size cannot be determined from this document.
• Data Provenance: Not explicitly stated. Clinical validation studies for such devices typically involve prospective data collection from human subjects. The document does not specify the country of origin.
• Retrospective/Prospective: Clinical validation according to ISO 81060-2 is inherently prospective, involving live measurements on human subjects.

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

For blood pressure monitor validation (ISO 81060-2), ground truth is established by simultaneous auscultatory measurements performed by trained observers (commonly two, with a third if disagreements arise) using a reference sphygmomanometer. These are not "experts" in the sense of radiologists interpreting images, but rather trained technicians or clinicians. The document does not specify the exact number of observers or their specific qualifications, but the standard mandates specific training and performance for these observers.

4. Adjudication method for the test set

The ISO 81060-2 standard typically employs an adjudication method for reconciling reference blood pressure measurements. Commonly, two trained observers simultaneously measure, and if their readings differ by more than a predefined threshold, a third observer might be used, or the measurements are discarded and re-taken. This is inherent to the standard's methodology, though not explicitly detailed in this summary document.

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, an MRMC study was not done. This type of study is relevant for diagnostic devices, particularly those involving human interpretation, often with AI assistance (e.g., radiology AI). This device is an automatic blood pressure monitor, not an interpretive diagnostic system.

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

Yes, in essence. The primary performance evaluation for an automatic blood pressure monitor is its standalone accuracy against a reference method (auscultation). The device itself is designed to operate automatically, without continuous human intervention during the measurement cycle for interpretation. The reported accuracies (±3 mmHg for pressure, ±5% for pulse) reflect this standalone performance.

7. The type of ground truth used

The ground truth for non-invasive blood pressure monitors typically involves simultaneous auscultatory measurements performed by trained observers using a mercury or an equivalent validated reference sphygmomanometer. This is the "gold standard" for clinical validation of automated blood pressure devices as per ISO 81060-2.

8. The sample size for the training set

This document does not specify a separate "training set" sample size. For traditional medical devices like blood pressure monitors, there isn't typically a distinct "training set" in the machine learning sense. The device's algorithm (oscillometric method) is developed based on physiological principles and engineering, not "trained" on a large dataset of patient readings in the way an AI algorithm learns. The validation is done on a "test set" or clinical study population.

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

As there isn't a "training set" in the AI/ML sense, this question is not applicable. The device's internal algorithms are based on established oscillometric principles for blood pressure determination. Their accuracy is then validated (tested) against the clinical ground truth described in point 7.

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AGE Automatic Upper Arm 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 blood pressures and pulse rate of an adult individual by using a non-invasive technique in which an inflatable cuff is wrapped around the upper arm. The cuff circumference is six sizes.

AGE Automatic Upper Arm Blood Pressure Monitor is intended for use by medical professionals or at home to monitor and display diastolic, systolic blood pressure and pulse rate on adult each time, with an air cuff buckled around one's arm according to the instruction in the user's guide manual.

AGE Automatic Upper Arm Blood Pressure Monitor is a battery driven automatic non-invasive blood pressure meter. It can automatically conduct the inflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult at arm within its claimed range and accuracy via the Oscillometry technique. The device also has low voltage indication, which will be triggered when the battery is low.

This document is a 510(k) Premarket Notification from the U.S. Food and Drug Administration (FDA) for a blood pressure monitor. It serves as a regulatory approval and states that the device is "substantially equivalent" to legally marketed predicate devices, meaning it has met the necessary safety and effectiveness standards.

Here's an analysis 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

The acceptance criteria for the AGE Automatic Upper Arm Blood Pressure Monitor are primarily established by compliance with recognized standards for safety and performance. The document explicitly states the required accuracy for pressure and pulse measurements.

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

The document explicitly states that the device's safety and performance were evaluated by "lab bench testing" and "clinical validation" according to ISO 81060-2.

• Sample Size: The document does not specify the precise sample size used for the clinical validation. ISO 81060-2, the standard followed, dictates specific subject requirements for clinical validation of automated sphygmomanometers (e.g., specific age groups, blood pressure ranges, and a minimum number of subjects, typically at least 85 subjects with appropriate distribution). However, the number of subjects used in this specific study is not provided in the excerpt.
• Data Provenance: The document does not explicitly state the country of origin of the data or whether the study was retrospective or prospective. Given it's a 510(k) submission for a device manufactured in China, it's plausible the clinical study was conducted in China or another region that uses ISO standards, likely a prospective study to collect human blood pressure measurements.

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

The document refers to compliance with ISO 81060-2 for clinical validation. This standard typically requires "reference measurements" (ground truth) to be obtained by healthcare professionals using a standardized method (e.g., mercury sphygmomanometry with a stetho-scope).

• Number of Experts: ISO 81060-2 usually requires at least two trained observers (experts) for simultaneous, blind auscultatory measurements to establish the reference blood pressure. The document itself does not specify the exact number of experts.
• Qualifications of Experts: The standard implies that these experts are trained and competent in auscultatory blood pressure measurement. While "radiologist with 10 years of experience" is an example qualification, for blood pressure measurement, the standard would typically require medical professionals trained in auscultatory blood pressure measurement, such as physicians, nurses, or trained technicians, without specifying years of experience in this excerpt.

4. Adjudication Method for the Test Set

For the clinical validation against ISO 81060-2, the ground truth is established by simultaneous auscultatory measurements by two trained observers.

• Adjudication Method: While not explicitly detailed, ISO 81060-2 requires a pre-defined method for handling discrepancies between the two observers' readings. Common methods include:
  • Averaging the two readings if they are within a specific tolerance.
  • Using a third, independent observer if the initial two readings differ by more than a specified amount (e.g., 2+1 methodology).
  • No adjudication is typically not acceptable for establishing ground truth in this type of study; a consensus or defined reconciliation process is necessary to minimize observer bias. The exact method used for this device's validation is not detailed in the provided text.

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, an MRMC comparative effectiveness study was not done. This device is an automatic blood pressure monitor, not an AI-assisted diagnostic imaging device. Therefore, the concept of "human readers improving with AI assistance" is not applicable. The study's purpose was to validate the accuracy of the automated device itself against a human-read reference standard.

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

• Yes, in spirit, a standalone performance study was done. The device itself is an automated system that measures blood pressure. The clinical validation conducted under ISO 81060-2 assesses the accuracy of the device's algorithm (its automated measurement) compared to the "gold standard" of human-observed auscultatory blood pressure. There isn't a "human-in-the-loop" in the operation of the device for each measurement; it's designed to be automated.

7. The Type of Ground Truth Used

• The ground truth for the clinical performance evaluation (per ISO 81060-2) would be expert consensus auscultatory blood pressure measurements, typically performed simultaneously and blindly by two trained observers using a mercury sphygmomanometer or equivalent calibrated device. This is the accepted clinical gold standard for such validations.

8. The Sample Size for the Training Set

• Not applicable / Not provided. This document describes a 510(k) submission for a traditional medical device (an automated blood pressure monitor) that operates based on oscillometric principles, not explicitly on machine learning or deep learning algorithms that require separate "training sets." The device's underlying algorithm is likely fixed and validated, not something that "learns" from a training dataset in the AI sense. Therefore, there's no mention of a "training set" as one would find for an AI/ML medical device.

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

• Not applicable. As explained in point 8, this device does not appear to utilize a machine learning model that would require a "training set" with established ground truth in the context of AI/ML development. Its accuracy is validated against a reference standard in a clinical study.

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Ageless Health Medical Digital Thermometers are intended for use in measuring human body temperature (Armpit or Oral).

Ageless Health Medical Digital Thermometers comprises a thermistor for getting temperature signal, a reference resistor for comparing the resistance of the thermistor, a buzzer for sounding effect, an ASIC for processing the target temperature digitally, and a LCD for displaying the temperature result. The design principle of thermometer is based on thermosensor and ASIC technology. A thermistor is used as thermosensor. The ASIC gets the sensor's signal from human body, then processes the signal and calculates the result, after that displays the temperature result by a LCD.

The provided text is a 510(k) summary for the Ageless Health Medical Digital Thermometer, a medical device. It outlines the device's technical specifications and demonstrates its substantial equivalence to a predicate device. However, this document does not contain the information requested regarding acceptance criteria and the study that proves an AI/ML powered device meets those criteria.

Specifically, the document discusses:

• Device identification: Ageless Health Medical Digital Thermometer.
• Regulatory information: Class II medical device, product code FLL, regulation number 21 CFR 880.2910, 510(k) number K152508.
• Intended Use: Measuring human body temperature (armpit or oral).
• Device Description: It's a digital thermometer using a thermistor, reference resistor, buzzer, ASIC, and LCD display.
• Predicate Device: SHENZHEN PUMP MEDICAL SYSTEM CO., LTD. Electronic thermometer (K131210).
• Test Summary: Mentions lab bench testing according to various IEC, ASTM, and ISO standards (e.g., IEC 80601-2-56 for clinical thermometers, ASTM E1112 for electronic thermometers, ISO 10993 for biocompatibility), but does not provide the results of these tests in detail or the specific acceptance criteria met. It only states that "The same tests on Ageless Health Medical Digital Thermometer and the predicate device demonstrate the substantial equivalence of the two."
• Comparison to Predicate Device: A table comparing various elements, including measurement range, accuracy, ambient temperature, and response time. It notes some differences but concludes substantial equivalence because both comply with relevant performance standards.

Therefore, I cannot fulfill the request to describe the acceptance criteria and the study proving the device meets them based on the provided text, as this information is not present for an AI/ML powered device. The document relates to a traditional digital thermometer and focuses on substantial equivalence based on existing standards and predicate device comparison, rather than a novel AI/ML performance evaluation.

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AGE Automatic Wrist 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 13.5cm~19.5cm.

AGE Automatic Wrist Blood Pressure Monitor is a battery driven automatic non-invasive blood pressure meter. It can automatically conduct the inflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult at wrist within its claimed range and accuracy via the Oscillometry technique. The device also has low voltage indication, which will be triggered when the battery is low.

Here’s a breakdown of the acceptance criteria and study information for the AGE Automatic Wrist Blood Pressure Monitor, models BW-601, BW-602, BW-603, BW-605, BW-606, BW-611, BW-612, and BW-613, based on the provided document:

Acceptance Criteria and Reported Device Performance

Study Information

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

   • The document states that the device was evaluated according to "AAMI / ANSI / ISO 81060-2 Second Edition, Non-Invasive Sphygmomanometers - Part 2: Clinical Validation Of Automated Measurement Type."
   • ISO 81060-2 (which this document specifies compliance with) typically requires a minimum of 85 subjects for clinical validation to demonstrate agreement between the test device and a reference standard (e.g., a trained observer using a stethoscope). The document does not explicitly state the exact sample size used in the clinical study, but it is implied to be sufficient to meet the ISO 81060-2 standard.
   • Data provenance: Not specified in the provided text (e.g., country of origin, retrospective/prospective).

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

   • For clinical validation studies compliant with ISO 81060-2, at least two (and preferably three) trained observers are typically required to obtain simultaneous auscultatory reference measurements. These observers must be trained in the standard auscultatory technique for blood pressure measurement and follow the specified protocol (e.g., using a double stethoscope).
   • Their specific qualifications (e.g., "radiologist with 10 years of experience") are not detailed in this document, but they would be healthcare professionals (e.g., physicians, nurses, or trained technicians) proficient in blood pressure measurement to serve as reference observers.

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

   • Clinical validation studies following ISO 81060-2 use simultaneous measurements with multiple observers. The standard outlines specific procedures for comparing the automated device's readings with those from the trained observers. For example, if two observers' readings differ by more than a specified amount, a third measurement or a re-measurement might be required, or the data point might be excluded. The standard's methodology effectively serves as an adjudication method.

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, an MRMC comparative effectiveness study was not done. This device is a standalone blood pressure monitor, not an AI-assisted diagnostic tool that would typically involve human readers interpreting images or data with and without AI assistance. Therefore, there is no effect size related to human reader improvement with/without AI.

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

   • Yes, a standalone performance study was done. The clinical validation per ISO 81060-2 specifically evaluates the algorithm/device's performance (its automated measurements) against reference measurements taken by trained human observers. The device itself operates as a standalone system to provide blood pressure readings.

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

   • The ground truth for the clinical validation was established through expert auscultatory measurements performed simultaneously with the device's readings. This is the standard "reference measurement" method described in ISO 81060-2.

7. The sample size for the training set:

   • This document describes a premarket notification (510(k)) for a medical device. Blood pressure monitors like this typically use established algorithms based on oscillometric principles, not machine learning that requires a "training set" in the sense of AI models. Therefore, a specific "training set" sample size for an AI algorithm is not applicable here. The underlying algorithms are developed and refined through engineering, calibration, and extensive testing, but not typically "trained" on a dataset in the way an AI model would be.

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

   • As mentioned above, a "training set" in the AI sense is not applicable for this type of device. The accuracy and performance of the oscillometric algorithm are established through rigorous engineering design, mathematical modeling, and validation studies against established reference methods (like auscultation) in accordance with standards like ISO 81060-2.

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