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The Ear Thermometer is intended to measure human body temperature of people over three months from surface of eardrum. It applies to both professional use and home use.

The ear thermometer is a handheld device that displays the temperature of the measured patient by measuring the thermal radiation of the eardrum. Measurement unit: °C or °F. The results can be displayed on LCD. The thermometers are powered by 1.5V×2 (AAA or AA) alkaline batteries, which can be used for people over three months. A thermopile sensor is employed to detect or monitor the infrared thermal energy emitted from the eardrum, which is converted into temperature measurement with the unit of °C or °F. All the models share the same critical components, intended use, working principle and similar product design, and compose of a sensor, PCB, buttons, LCD display and housing. Functions include temperature measurement, memory reading recall, unit switch, low battery detection and high temperature indicator.

The FDA 510(k) clearance letter and accompanying 510(k) Summary for the Ear Thermometers (EAR-E101, EAR-E102, EAR-E103) provide information on acceptance criteria and supporting studies.

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to a predicate device (Jiangsu Yuyue Medical Equipment & Supply Co., Ltd, Infrared Ear Thermometers YHT101 and YHT200, K203583). Thus, the "acceptance criteria" are largely framed as demonstrating equivalence or adherence to relevant standards. The performance data is presented in comparison to the predicate and overall compliance with standards.

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

• Non-clinical Data (Bench Testing): The document does not specify a "sample size" in terms of number of devices for bench testing. It states that "The device has been tested according to the following standards," implying tests were performed on representative samples to ensure compliance.
• Clinical Data: The summary states, "The clinical testing has been conducted per ISO 80601-2-56 Medical electrical equipment—Part 2-56: Particular requirements for basic safety and essential performance of clinical thermometers for body temperature measurement." However, the specific sample size (number of patients/measurements) and data provenance (e.g., country of origin, retrospective/prospective) for this clinical study are NOT provided in the given document.

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

• Clinical Data: The document does not specify the number of experts or their qualifications for establishing ground truth in the clinical study. As it's an ear thermometer, the "ground truth" would typically come from a reference temperature measurement method (e.g., rectal thermometry) rather than expert interpretation of an image or signal.

4. Adjudication method for the test set:

• Clinical Data: Given that the device measures a quantitative value (temperature), an adjudication method in the context of expert consensus (like multiple readers for an image) is generally not applicable. The comparison would be between the device's reading and the reference method's reading. The document does not describe any specific adjudication method for the clinical test set.

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 type of study (MRMC) is relevant for diagnostic imaging devices where human interpretation plays a significant role, sometimes aided by AI. This document is for an ear thermometer, a direct measurement device, not an AI-assisted diagnostic tool.

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

• Yes, a standalone performance was done for the ear thermometer. The device itself is designed to provide temperature readings directly, without requiring human interpretation or input to calculate the core measurement. The bench and clinical testing described aim to quantify this standalone performance in terms of accuracy and adherence to standards.

7. The type of ground truth used:

• Clinical Data: While not explicitly stated, for a clinical thermometer, the ground truth for performance testing is typically established by comparison against a standardized, highly accurate reference thermometer (e.g., a rectal thermometer or an oral thermometer with known accuracy) or a specialized blackbody calibrator in a controlled environment as specified by standards like ISO 80601-2-56. The document mentions "clinical accuracy test" and "performance test," strongly implying such a comparative methodology.

8. The sample size for the training set:

• Not applicable / Not provided. The device is an ear thermometer, which is a sensor-based measurement tool, not an AI/machine learning algorithm that requires a "training set" in the conventional sense. The device's performance is determined by its design, calibration, and adherence to physical principles and engineering specifications, which are validated through bench and clinical testing.

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

• Not applicable. As noted above, the concept of a "training set" and its associated ground truth establishment is not relevant for this type of medical device submission.

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The Wrist Blood Pressure Monitor is intended to measure the systolic pressure and diastolic pressure, as well as the pulse rate of adult person via non-invasive oscillometric technique by an inflatable cuff wrapped around the wrist at medical facilities or at home.

The Wrist Blood Pressure Monitor is designed as a battery driven automatic non-invasive blood pressure monitor. It can automatically complete the inflation, deflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult person at wrist within its claimed range and accuracy via the oscillometric technique. The result will be displayed in the international unit mmHg or Kpa.

All the models included in this submission follow the the same intended use, same measurement principle, same blood pressure core algorithm and similar product design. All the models can be used with one cuff size 13.5~19.5 cm (5.3-7.7inches).

The main differences are appearance, Dimensions and some specifications which will not affect the safety and effectiveness of the device.

The provided FDA 510(k) clearance letter and associated summary pertain to a Wrist Blood Pressure Monitor, which is a medical device for measuring blood pressure and pulse rate. It is not an AI/Software as a Medical Device (SaMD). Therefore, many of the typical acceptance criteria and study designs associated with AI/SaMD (such as multi-reader multi-case studies, ground truth establishment by experts, training set details, or effect sizes of AI assistance) are not applicable to this device.

The acceptance criteria and study details provided are tailored to the performance of a non-invasive blood pressure measurement system (hardware device), focusing on accuracy, safety, and effectiveness.

Here's a breakdown of the requested information based on the provided document, addressing the device's specific characteristics as a hardware blood pressure monitor:

Acceptance Criteria and Device Performance (Wrist Blood Pressure Monitor)

1. Table of Acceptance Criteria and Reported Device Performance

As per the 510(k) summary, the device's accuracy is a key performance metric. The acceptance criteria are based on the international standard ISO 81060-2 Third edition 2018-11 [Including AMD1:2020].

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

• Sample Size for Test Set (Clinical Accuracy Study):
  • Three groups of clinical accuracy research were conducted. Each group included 100 subjects, for a total of 300 subjects across the 13 models.
  • Group 1: 100 subjects (47 Male, 53 Female)
  • Group 2: 100 subjects (54 Male, 46 Female)
  • Group 3: 100 subjects (44 Male, 56 Female)
  • Minimum subjects for each group was 85, as per ISO 81060-2.
• Data Provenance: The document does not explicitly state the country of origin for the clinical data. However, the manufacturer is "Shenzhen AOJ Medical Technology Co., Ltd." in Shenzhen, Guangdong, China. It is highly probable the data was collected in China.
• Retrospective or Prospective: The clinical accuracy study, designed to meet ISO 81060-2, is typically conducted prospectively to collect new data for device validation. The wording "clinical accuracy research" and "clinical accuracy test report and data analysis followed the requirements" implies a prospective study.

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

• This question is not directly applicable in the context of this device because "ground truth" for a blood pressure monitor's accuracy is established against a reference standard, not through expert consensus on interpretations of images or signals (as would be the case for AI/SaMD).
• For blood pressure monitors, the "ground truth" or reference measurement is typically taken by trained medical professionals using a standardized reference sphygmomanometer (e.g., mercurial or auscultatory method), as per the ISO 81060-2 standard. The document states "The Same Arm Sequential Method was chosen for all studies," which is a standard procedure comparison method against a reference device. The qualifications of the individuals performing these reference measurements would be trained clinicians (e.g., physicians, nurses).

4. Adjudication Method for the Test Set

• This question is not applicable for a blood pressure monitor's accuracy testing. Adjudication methods (like 2+1 or 3+1) are used to resolve discrepancies in human expert interpretations, especially in image-based diagnostics.
• For blood pressure accuracy, deviations are quantified statistically between the device reading and the reference measurement, not through an adjudication process among multiple "readers."

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, this was not done. This type of study is relevant for AI/SaMD devices where AI assists human interpretation and is a key component for assessing the AI's clinical utility. The Wrist Blood Pressure Monitor is a standalone hardware device that provides a measurement; it does not involve human "readers" interpreting data or AI assistance.

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

• Yes, in essence. The entire clinical accuracy study described in Section 8 ("Clinical data") evaluates the device's performance (which incorporates its internal oscillometric algorithm) in a standalone manner against a reference standard. The "algorithm" here refers to the embedded software that processes the oscillometric signals to derive blood pressure and pulse rate. The study directly assesses how accurately the device (with its integrated algorithm) measures blood pressure readings compared to the reference.
• Performance Metrics: The evaluation was based on the "mean error and standard deviation of differences for systolic, diastolic pressure" as per ISO 81060-2.

7. The Type of Ground Truth Used

• The ground truth for the clinical accuracy testing was established through concurrent measurements using a standardized reference method (e.g., auscultatory method with a mercurial sphygmomanometer or another validated reference device) on the same arm, sequentially with the test device. This is the standard for blood pressure monitor validation as per ISO 81060-2.
• It is not "expert consensus" in the sense of subjective medical interpretation, but rather an objective, standardized measurement performed by trained personnel using a calibrated reference instrument.

8. The Sample Size for the Training Set

• This concept is not applicable to this type of medical device clearance. The Wrist Blood Pressure Monitor is a hardware device with an embedded algorithm (oscillometric technique) that is based on established physiological principles. It doesn't use machine learning or deep learning in a way that requires a separate "training set" of patient data for an AI model to learn from, as would be the case for AI/SaMD devices. The device's "training" (development and calibration) would involve engineering principles and laboratory testing, rather than a data-driven machine learning process.

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

• As the concept of a "training set" in the context of machine learning is not applicable here (see point 8), the establishment of ground truth for such a set is also not applicable. The device's underlying measurement principle is well-established oscillometric technology. Development and calibration rely on physical models and engineering validation.

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The Arm Blood Pressure Monitor is intended to measure the systolic and diastolic blood pressure as well as the pulse rate of adult person via non-invasive oscillometric technique in which an inflatable CUFF is wrapped around the upper arm at medical facilities or at home.

The Arm Blood Pressure Monitor is designed as a battery driven automatic non-invasive blood pressure monitor. It can automatically complete the inflation, deflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult person at upper arm within its claimed range and accuracy via the oscillometric technique. The result will be displayed in the international unit mmHg or Kpa.

The device has the data storage function in order for data reviewing, including the systolic pressure, diastolic pressure, pulse rate and measurement time. The device also has low voltage indication, which will be triggered when the battery is low.

The FDA 510(k) clearance letter for the Arm Blood Pressure Monitor does not explicitly state acceptance criteria in a quantitative table or the specific performance metrics achieved in a typical "device performance" section as one might expect for a software-based or diagnostic device. Instead, it refers to compliance with established medical device standards, particularly ISO 81060-2:2018 (and its amendment from 2020) for clinical accuracy.

However, based on the context of the clinical data and the requirements of ISO 81060-2, we can infer the acceptance criteria for accuracy.

Here's a breakdown of the requested information based on the provided document:

Implied Acceptance Criteria and Reported Device Performance

The device's performance is demonstrated by its adherence to the clinical accuracy requirements of ISO 81060-2 Third edition 2018-11 (including AMD1:2020).

Implied Acceptance Criteria of ISO 81060-2:2018 (and AMD1:2020):

The ISO 81060-2 standard consists of two parts for accuracy assessment:

• Criterion 1 (Mean Difference and Standard Deviation):
  • The mean difference between the device and the reference measurement for both systolic and diastolic blood pressure shall be $\leq \pm 5$ mmHg.
  • The standard deviation of these differences shall be $\leq 8$ mmHg.
• Criterion 2 (Cumulative Percentage of Differences):
  • For each subject, the absolute difference between the device and the reference measurement should be calculated.
  • The cumulative percentage of devices should have absolute differences within certain thresholds:
    • $\leq 5$ mmHg for at least 65% of measurements.
    • $\leq 10$ mmHg for at least 85% of measurements.
    • $\leq 15$ mmHg for at least 95% of measurements.

Table of Acceptance Criteria and Reported Device Performance (Inferred from ISO 81060-2)

Note: The document explicitly states, "All data's mean error and standard deviation of differences for systolic, diastolic pressure is not over the limits of ISO 81060-2 Third edition 2018-11 [Including AMD1:2020]." This confirms the device met the numerical precision requirements of the standard for mean difference and standard deviation. While it doesn't provide the exact numbers for each group, it confirms compliance with the key statistical thresholds.

Study Details

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

   • Total Sample Size: The 28 models were grouped into 7 categories for clinical accuracy testing. Each of these 7 groups had a test set of 100 subjects, except for Group 7, which had 92 subjects.
     • Group 1: 100 subjects
     • Group 2: 100 subjects
     • Group 3: 100 subjects
     • Group 4: 100 subjects
     • Group 5: 100 subjects
     • Group 6: 100 subjects
     • Group 7: 92 subjects
   • Male/Female Distribution: Each group had a participant distribution of at least 30% male and at least 30% female.
   • Age Range: Subjects were "adult person" with an age range of "> 12 years old," specifically noted ranges from 15 to 80 years old across the groups.
   • Data Provenance: The document does not explicitly state the country of origin for the clinical data. It also does not explicitly state if the study was retrospective or prospective, but clinical accuracy studies adhering to ISO 81060-2 are typically prospective and involve simultaneous, sequential measurements.

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

   • The document does not specify the number or qualifications of experts (e.g., radiologists) for establishing ground truth in this context. For blood pressure monitors, "ground truth" is typically established by trained technicians or clinicians using a validated reference method (e.g., mercury sphygmomanometer) following a rigorous protocol (like the auscultatory method per ISO 81060-2). The standard requires independent observers for reference measurements.

3. Adjudication Method for the Test Set:

   • The document states, "The clinical accuracy test report and data analysis followed the requirements of the ISO 81060-2 Third edition 2018-11 [Including AMD1:2020]. The Same Arm Sequential Method was chosen for all studies."
   • ISO 81060-2 outlines a specific method for ground truth establishment for blood pressure. It typically involves multiple independent observers (at least two trained observers) who simultaneously or sequentially measure blood pressure using a validated reference device. Discrepancies between these observers are resolved in accordance with the standard, which usually involves specific rules for averaging or discarding measurements based on predefined variability criteria, rather than a formal "adjudication panel" in the sense of image interpretation.

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

   • No, an MRMC comparative effectiveness study was not done. This type of study is specifically relevant for diagnostic imaging AI devices where human readers interpret medical images with and without AI assistance. For a non-invasive blood pressure monitor, the study focus is on the device's measurement accuracy against a reference standard, not on how it assists human interpretation.

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

   • Yes, in essence, a "standalone" or "algorithm only" performance was evaluated. The device (Arm Blood Pressure Monitor) is an automated system that measures blood pressure. Its clinical accuracy study measures its direct output (systolic and diastolic pressure) against a reference standard. There isn't a "human-in-the-loop" component in the operational measurement process that would affect its core accuracy, as it's an automated device.

6. The Type of Ground Truth Used:

   • The ground truth was established by comparison with a validated reference measurement method, as prescribed by ISO 81060-2. This typically involves the auscultatory method using a mercury sphygmomanometer or an equivalent validated reference device, with measurements performed by trained observers.

7. The Sample Size for the Training Set:

   • Not applicable / Not provided. This device is a hardware-based blood pressure monitor that uses an oscillometric technique and a "blood pressure core algorithm." It is not described as a machine learning or AI algorithm that requires a separate "training set" in the conventional sense of deep learning. Its performance is based on its engineering design and the embedded validated algorithm.

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

   • Not applicable / Not provided. As mentioned above, there isn't a "training set" in the common understanding for a typical medical AI device. The core algorithm is likely developed and validated internally by the manufacturer through engineering principles and extensive testing, not necessarily through a separate clinical "training set" with ground truth in the AI context. The clinical data presented is for validation (test set) of the final device, demonstrating its accuracy.

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The Arm Blood Pressure Monitor is intended to measure the systolic and diastolic blood pressure, as well as the pulse rate of adult person via non-invasive oscillometric technique in which an inflatable CUFF is wrapped around the upper arm at medical facilities or at home.

Arm blood pressure monitor, models(models ARM-30H, ARM-30J, ARM-30K and AOJ-90B), are designed as a battery driven automatic no-invasive blood pressure monitor. It can automatically complete the inflation, deflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult person at upper arm within its claimed range and accuracy via the oscillometric technique. The result will be displayed in the international unit mmHg or Kpa. All the models included in this submission follow the similar software, same measurement principle and same specifications. All the models can be used with one cuff size 2242 cm (8.616.5 inches). AOJ90B has extra 4G network except for other models.

Here's an analysis of the provided FDA 510(k) clearance letter to extract information on acceptance criteria and the study proving device performance:

Summary of Device and Context:

The submission K250116 concerns several models of Arm Blood Pressure Monitors (ARM-30H, ARM-30J, ARM-30K, ARM-90B) manufactured by Shenzhen AOJ Medical Technology Co., Ltd. These devices are intended for non-invasive oscillometric measurement of systolic and diastolic blood pressure and pulse rate in adults, for both medical facilities and home use. The predicate device is the Arm Blood Pressure Monitor, model AOJ-30B (K222125).

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for Test Set (Clinical Studies)

• Clinical Study for ARM-90B:

  • Sample Size: 100 adult subjects (61 females, 39 males)
  • Age Range: 19 to 77 years
  • Data Provenance: Not explicitly stated (e.g., country of origin). Since Shenzhen AOJ Medical Technology Co., Ltd. is based in China, it's highly probable the study was conducted there, but this is not confirmed in the provided text. The study method was prospective, as subjects were enrolled for the purpose of the study.

• Clinical Study for ARM-30H:

  • Sample Size: 100 adult subjects (54 females, 46 males)
  • Age Range: 18 to 80 years
  • Data Provenance: Not explicitly stated. Likely prospective, similar to ARM-90B.

3. Number of Experts and Qualifications for Ground Truth

The document does not provide information on the number of experts used to establish ground truth or their specific qualifications (e.g., "radiologist with 10 years of experience"). For blood pressure monitor clinical studies, ground truth is typically established by trained technicians or clinicians using validated reference devices, but the specific details are not present.

4. Adjudication Method for Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1). For blood pressure studies following ISO 81060-2, the ground truth measurements are usually taken by trained observers using mercury sphygmomanometers or other validated reference methods. The standard itself outlines the procedures for taking these measurements, which inherently involves multiple measurements and comparisons, but not necessarily a formal adjudication process in the sense of resolving conflicting interpretations of images or complex diagnostic results. The "Same Arm Sequential Method" was chosen for both studies, indicating a direct comparison of the device's readings against reference readings on the same arm of the subject.

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

No MRMC comparative effectiveness study was done.
This type of study is typically relevant for interpretative devices (e.g., AI in radiology) where human readers are making diagnoses. For a blood pressure monitor, the device provides a direct measurement, not an interpretation that a human would then refine. The clinical studies directly evaluate the device's accuracy against a recognized reference standard.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance study was done for the device. The clinical studies performed according to ISO 81060-2 directly assess the performance of the device itself (the algorithm within the device) against a reference standard without human intervention in interpreting the device's output. The device is the algorithm in this context, automatically performing inflation, deflation, and measurement.

7. Type of Ground Truth Used

The ground truth used for the clinical studies was established by comparison with a reference method defined by ISO 81060-2. This standard outlines precise procedures for obtaining reference blood pressure measurements (typically using a mercury sphygmomanometer or other validated reference devices operated by trained observers) against which the automated device's readings are compared. The criteria state "mean error and standard deviation of differences for systolic, diastolic pressure is not over the limits of ISO 81060-2," which implies the ground truth is based on reference measurements adhering to this international standard.

8. Sample Size for the Training Set

The document does not provide information on the sample size for the training set.
510(k) submissions typically focus on the performance of the final device, not the details of its development or training data for its internal algorithms, unless the device explicitly uses machine learning algorithms that are updated or adapt. For a standard oscillometric blood pressure monitor, the algorithm is generally fixed and designed based on established physiological principles and extensive validation, rather than being "trained" on a dataset in the modern sense of machine learning.

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

As with the training set sample size, the document does not provide information on how the ground truth for any potential training set was established. Given the nature of a blood pressure monitor, the "training" (if it occurs in a machine learning context) would likely involve extensive data collection with reference ground truth from validated sphygmomanometers, similar to the clinical validation studies, but specifically for internal algorithm development and refinement. However, this is speculative as the document does not detail the development process.

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The pulse oximeter is a reusable device and intended for spot-checking of oxygen saturation and pulse rate for use with the finger of adult patients in home and healthcare environments. And it is not intended to be used under motion or low perfusion scenarios.

The Pulse Oximeter is a battery powered device in measuring and displaying functional oxygen saturation of arterial hemoglobin (SpO2) and pulse rate (PR). The Pulse Oximeter works by applying a sensor to a pulsating arteriolar vascular bed. The sensor contains a dual light source and photo detector. The one wavelength of light source is 660 m, which is red light; the other is 905 nm, which is Infrared light. Skin, bone, tissue, and venous vessels normally absorb a constant amount of light over time. The photodetector in finger sensor collects and converts the light into electronic signal which is proportional to the light intensity. The arteriolar bed normally pulsates and absorbs variable amounts of light during systole and diastole, as blood volume increases. The ratio of light absorbed at systole and diastole is translated into an oxygen saturation measurement. This measurement is referred to as SpO2. The device mainly composed of PCB board, On/Off button, mode button, OLED&LED screen, battery compartment, Bluetooth® module and plastic shell. There are five models AOJ-70A, AOJ-70C, AOJ-70E. Only AOJ-70E. Only AOJ-70D have wireless connection function via Bluetooth®. The device is a spot-check pulse oximeter and does not intended for life-supporting or life-sustaining.

The provided text is a 510(k) summary for a Pulse Oximeter (AOJ-70A-E). It describes the device, its intended use, and comparative testing to show substantial equivalence to a predicate device. However, it does not provide a table of acceptance criteria with reported device performance or information regarding a typical "AI/algorithm" study (e.g., sample sizes for training/test sets, expert adjudication, MRMC studies, types of ground truth, etc.). This document primarily focuses on regulatory compliance for a medical device (pulse oximeter), not an AI/ML-based diagnostic or assistive technology.

Therefore, I cannot fulfill the request as the necessary information (acceptance criteria table, detailed study design for an AI/ML model, expert data, ground truth establishment for AI/ML) is not present in the provided text. The text only mentions "software verification and validation testing" and "clinical data is referenced to K221039" for SpO2 accuracy, which refers to a standard medical device clinical trial for a pulse oximeter, not an AI/ML performance study.

The closest information found is the clinical study for SpO2 accuracy performance of the pulse oximeter itself, not an AI/ML component. Here's what is available regarding that:

Study on SpO2 Accuracy Performance (Not an AI/ML study):

• Study Name/Reference: Referenced to K221039.
• Location: Sir Run Run Shaw Hospital, Zhejiang University School of Medicine.
• Methodology: Conducted in accordance with ISO 14155-1, ISO 80601-2-61:2017, and FDA Guidance Document for Pulse Oximeters. Evaluated SpO2 accuracy performance during stationary (non-motion) conditions over a wide range of arterial blood oxygen saturation levels compared to arterial blood CO-Oximetry (which served as ground truth).
• Sample Size: 11 healthy adult volunteer subjects (ages 21-47yr, with skin tones varying from Fitzpatrick 2-6) were included.
• Ground Truth: Arterial blood CO-Oximetry.
• Reported Performance: The SpO2 accuracy performance results showed that the subject device had an ARMS (Accuracy Root Mean Square)

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The Infrared thermometer is intended to measure human body temperature of people over three months old from the eardrum or forehead. It is indicated to be used in homecare and healthcare environments.

The Infrared thermometer is a handheld device, which can measure human body's temperature either via the eardrum or the forehead for clinical or home use. The results can be displayed on LCD and can also be transmitted to a non-device APP to record and display through Bluetooth.
There are two models AOJ-20A and AOJ-20Y. Both models share the same construction except differences on product enclosure,PCB layout and button designs.

The provided text describes a 510(k) premarket notification for an Infrared Thermometer (AOJ-20A; AOJ-20Y). It details the device, its intended use, and the non-clinical testing performed to establish substantial equivalence to predicate devices.

However, the document does not contain the level of detail typically found in a clinical study report or a more comprehensive validation plan. Specifically, it lacks:

• Explicit acceptance criteria in a tabular format with corresponding performance results.
• Specific sample sizes for test sets beyond general statements of testing being conducted.
• Data provenance (country, retrospective/prospective) for clinical data.
• Number and qualifications of experts for ground truth.
• Adjudication methods.
• Information on Multi-Reader Multi-Case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance details.
• Specific details on the type of ground truth (e.g., pathology, outcomes data) beyond "performance effectiveness."
• Training set sample size and ground truth establishment for training.

The document primarily focuses on non-clinical performance data to support the substantial equivalence claim, rather than a clinical study demonstrating acceptance criteria met in a real-world setting with human subjects. The tests mentioned are:

• Biocompatibility testing: Cytotoxicity, Skin Sensitization, Skin Irritation per ISO 10993-1.
• Electrical safety and electromagnetic compatibility (EMC): Compliance with IEC 60601-1, IEC 60601-1-11, and IEC 60601-1-2.
• Bench Testing: Compliance with ISO 80601-2-56 for performance effectiveness.
• Software Verification and Validation Testing: Conducted as per FDA's "Content of Premarket Submissions for Device Software" guidance, with the device considered "Basic" documentation level.

Given these limitations in the provided text, I can only extract the general types of tests and the standards they comply with, rather than specific acceptance criteria values and the device's measured performance against them. The information on "study that proves the device meets the acceptance criteria" is limited to the types of non-clinical tests conducted.

Therefore, direct answers to many of your questions cannot be provided from the given document as it does not contain clinical study data or a detailed validation report with specific performance metrics against acceptance thresholds.

Based on the provided text, here is what can be inferred and what is explicitly stated:

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

The document references compliance with ISO 80601-2-56 for "performance effectiveness" in bench testing. This standard likely specifies accuracy and precision requirements for clinical thermometers. However, the specific numerical acceptance criteria (e.g., ±0.2°C) and the actual measured performance values of the device against these criteria are not provided in this summary.

Inferred/General:

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: Not specified. The document states "Bench testing was conducted on the thermometer device, consisting of all the system." This suggests testing of the physical devices, but no numerical sample count (e.g., number of thermometers tested, number of measurements taken) is given.
• Data provenance: Not specified. The tests are non-clinical bench and lab tests, not clinical human subject data.

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

• Not applicable as the testing described is non-clinical/bench testing, not involving human expert interpretation for ground truth.

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

• Not applicable.

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 is a medical device (thermometer), not an AI imaging or diagnostic algorithm used by human readers.

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

• The document describes the performance of the device itself (sensor, electronics, software) in a standalone manner via bench testing, but not an "algorithm only" in the sense of a standalone AI model. The device's function is temperature measurement.

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

• For "performance effectiveness," the ground truth (or reference standard) would typically be calibrated reference thermometers or temperature sources compliant with the ISO standard used for test and measurement, not clinical outcomes or expert consensus.
• For biocompatibility, the ground truth is the chemical and biological assays.
• For electrical safety and EMC, the ground truth is the measurement against standard limits using appropriate test equipment.

8. The sample size for the training set

• Not applicable, as this is a traditional medical device (thermometer), not an AI/machine learning model requiring a training set for its core function. The "software verification and validation testing" refers to standard software engineering practices, not machine learning model training.

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

• Not applicable for the same reasons as point 8.

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The Arm Blood Pressure Monitor is intended to measure the systolic pressure and diastolic pressure, as well as the pulse rate of adult person via non-invasive oscillometric technique at medical facilities or at home.

AOJ-33series arm blood pressure monitor is designed as a battery driven automatic non-invasive blood pressure monitor. It can automatically complete the inflation, deflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult person at upper arm within its claimed range and accuracy via the oscillometric technique. The result will be displayed in the international unit mmHg or Kpa. The device has the data storage function in order for data reviewing, including the systolic pressure, diastolic pressure, pulse rate and measurement time. The device also has low voltage indication, which will be triggered when the battery is low. The proposed device is intended to be used in medical facilities or at home. And the effectiveness of this sphygmomanometer has not been established in pregnant (including pre-eclamptic) patients. The product is provided non-sterile, and not to be sterilized by the user prior to use. All the models included in this submission follow the same software, same measurement principle and same specifications. The main differences are color of the face shell and keys, which will not affect the safety and effectiveness of the device. AOJ-33B include the Bluetooth transmission functionality which can transfer data for Application in the external instruments, and the measuring data, including systolic diastolic pressures and pulse rate can be displayed, stored and reviewed by the Application in the external instruments without any control feature, therefore, no interoperability happened. This function is not available for AOJ-33A.

The provided text describes the acceptance criteria and the study that proves the Arm Blood Pressure Monitor, models AOJ-33A and AOJ-33B, meets these criteria.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The core performance acceptance criteria for blood pressure monitors are typically defined by international standards like ISO 81060-2. The document states that the device was tested to ISO 81060-2:2018.

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

• Sample Size: 100 adult subjects (49 female, 51 male).
• Data Provenance: The document does not explicitly state the country of origin. It indicates it was a clinical validation study performed on AOJ-33A, implying it was a prospective study conducted for regulatory submission.

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

The document refers to a "Same Arm Sequential Method" clinical validation study in accordance with ISO 81060-2:2018. This standard typically involves multiple trained observers (experts) taking sequential measurements using a reference sphygmomanometer. However, the document does not specify the exact number of experts or their qualifications.

4. Adjudication method for the test set

The document states "The Same Arm Sequential Method was chosen." This method, as described in ISO 81060-2, involves comparing the automated device measurements to those taken by trained observers using a reference manual sphygmomanometer on the same arm. While it implies a comparison against expert readings, the document does not explicitly detail an adjudication method (e.g., 2+1, 3+1). The standard outlines procedures for obtaining reference measurements, which inherently involve a form of expert consensus or highly standardized measurement to establish 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

This question is not applicable as the device is an automated blood pressure monitor and not an AI-assisted diagnostic tool for human readers. It directly measures and displays blood pressure and pulse rate.

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

Yes, a standalone performance evaluation was done. The clinical validation study described is for the device (AOJ-33A) functioning independently to measure blood pressure and pulse rate, without human interpretation or assistance during the measurement process.

7. The type of ground truth used

The ground truth for the clinical study was established by comparison with established reference measurements, likely from a manual sphygmomanometer operated by trained observers, as per the ISO 81060-2:2018 standard for non-invasive sphygmomanometers. This effectively represents a validated, expert-derived measurement.

8. The sample size for the training set

The document does not specify a separate training set sample size. The clinical data mentioned (100 adult subjects) refers to the testing or validation set for the device's performance against the standard. For medical devices like blood pressure monitors, the "training" (i.e., calibration and algorithm development) often occurs internally during the device design phase, and explicit "training set" data for regulatory submission in the same way as an AI algorithm is typically not detailed.

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

As there is no explicit mention of a separate "training set" in the context of data for regulatory submission (beyond the device's inherent design and calibration), this information is not provided in the document. The general principle for developing such devices involves engineering and clinical testing to ensure accurate readings, which implicitly leverages previous data and established hemodynamic principles to calibrate the oscillometric algorithm.

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The Infrared thermometer is intended to measure human body temperature of people over three months old from the eardrum or forehead. It is indicated to be used in homecare and healthcare environments.

The AOJ-20 series Infrared thermometer is a handheld device, which can measure human body's temperature either via the eardrum or the forehead, for clinical or home use. The results can be displayed on LCD. The device operates in adjusted mode, and the reference body site of output temperature is oral. The measurement distance for forehead mode is 0 cm ~ 3 cm. The thermometers are powered by AAA 1.5V×2 alkaline batteries. A thermopile sensor is employed to detect or monitor the infrared thermal energy emitted from the eardrum or the surface of the skin of forehead, which is converted to the equivalent oral temperature with the unit of °C or ºF. All the models share the similar design and the same critical components. The major differences include: - Mechanical changes and the corresponding hardware adjustment happened to AOJ-20A, AOJ-20B, AOJ-20C, AOJ-20D, AOJ-20E, AOJ-20F, AOJ-20H, AOJ-20M, AOJ-20T, AOJ-20R and AOJ-20Y - In the measurement function, two measurement modes are distinguished between children and adults for AOJ-20B and AOJ-20E.

The provided text describes the regulatory clearance of an Infrared Thermometer (AOJ-20 series) and includes detailed performance testing against acceptance criteria. Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The device is an Infrared Thermometer, and its primary performance criterion is accuracy. The relevant standard for accuracy is ISO 80601-2-56.

The text explicitly states: "The system complies with the ISO 80601-2-56 Medical electrical equipment — Part 2-56: Particular requirements for basic safety and essential performance of clinical thermometers for body temperature measurement for performance effectiveness." and "Clinical accuracy validation was carried out on people over three month indicated in the instructions for use. The number of subjects in each age group met the minimum number requirements."

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

The "test set" in this context refers to the clinical study subjects for accuracy validation.

• Sample Size: The sample sizes vary per model, but generally around 135-138 subjects per model. The specific breakdown is provided in the table:
  • AOJ-20A: 138 subjects
  • AOJ-20B: 136 subjects
  • AOJ-20C: 137 subjects
  • AOJ-20D: 138 subjects
  • AOJ-20E: 137 subjects
  • AOJ-20F: 137 subjects
  • AOJ-20H: 135 subjects
  • AOJ-20M: 137 subjects
  • AOJ-20T: 137 subjects
  • AOJ-20R: 137 subjects
  • AOJ-20Y: 137 subjects
• Data Provenance: The document does not specify the country of origin for the clinical data. It also does not explicitly state whether the study was retrospective or prospective, but clinical accuracy validation per ISO standards is typically done in a prospective manner.

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

This information is not provided in the given document. For clinical thermometers, ground truth for body temperature is typically established using a highly accurate reference thermometer (e.g., rectal or oral thermometer depending on the standard's requirements for reference body site), not necessarily by human experts.

4. Adjudication Method for the Test Set

This information is not provided in the given document. Adjudication methods like 2+1 or 3+1 are more common in studies involving subjective assessments (e.g., image interpretation by radiologists), which is not directly applicable to a thermometer's clinical accuracy validation where objective measurements against a reference are typically performed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned or performed. This type of study is more relevant for diagnostic aids where human interpretation is involved. The document describes clinical accuracy validation of the device itself.

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

The device is an Infrared Thermometer, which is a standalone measurement device. Its performance is inherently standalone. There is no "algorithm only" component separate from human interaction, as a human user operates the device to take a temperature reading. The clinical and bench testing described assess this standalone performance.

7. The Type of Ground Truth Used

The ground truth used for clinical accuracy validation of a thermometer is typically based on a reference body temperature measurement obtained by a highly accurate, calibrated reference thermometer (e.g., a specific type of oral or rectal thermometer). The document states the device "operates in adjusted mode, and the reference body site of output temperature is oral," implying oral temperature is the reference for adjusted readings. The study was conducted "per Section 201.102 of ISO 80601-2-56," which would define the exact method for establishing ground truth.

8. The Sample Size for the Training Set

This information is not applicable and therefore not provided. Infrared thermometers are hardware devices with embedded algorithms, but they are not typically "trained" on large datasets of temperature readings in the way AI/ML models are. The device relies on physical principles of infrared detection and calibrated conversion algorithms, not a training set in the AI sense.

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

This information is not applicable as there is no mention of a "training set" in the context of this infrared thermometer. The device's internal algorithms and calibrations are developed and verified through engineering principles and bench testing, not machine learning training on a ground truth dataset.

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The Arm Blood Pressure Monitor is intended to measure the systolic blood pressure, as well as the pulse rate of adult person via non-invasive oscillometric technique in which an inflatable CUFF is wrapped around the upper arm at medical facilities or at home.

AOJ-30 series Arm blood pressure monitor is designed as a battery driven automatic non-invasive blood pressure monitor. It can automatically complete the inflation, deflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult person at upper arm within its claimed range and accuracy via the oscillometric technique. The result will be displayed in the international unit mmHg or kPa. The device has the data storage function in order for data reviewing, including the systolic pressure, diastolic pressure, pulse rate and measurement time. The device also has low voltage indication, which will be triggered when the battery is low. The proposed device is intended to be used in medical facilities or at home. And the effectiveness of this sphygmomanometer has not been established in pregnant (including pre-eclamptic) patients. The product is provided non-sterile, and not to be sterilized by the user prior to use. All the models included in this submission follow the similar software, same measurement principle and same specifications. The differences existed between different models included in this submission will not affect the safety and effectiveness of the device. AOJ-30A and AOJ-30B include the Bluetooth transmission functionality which can transfer data for Application in the external instruments, and the measuring data, including systolic diastolic pressures and pulse rate can be displayed, stored and reviewed by the Application in the external instruments without any control feature, therefore, no interoperability happened. This function is not available for other models.

The provided text describes the 510(k) submission for the Shenzhen AOJ Medical Technology Co., Ltd. Arm Blood Pressure Monitor (AOJ-30 series). This document focuses on demonstrating the substantial equivalence of the new device to a legally marketed predicate device, rather than proving a device meets specific acceptance criteria in the context of an AI/ML study.

Therefore, many of the requested details, such as those related to AI/ML performance (e.g., sample size for training set, number of experts for ground truth, MRMC study, standalone performance), are not applicable to this document as it pertains to a traditional non-invasive blood pressure monitor.

However, I can extract information related to the performance testing and clinical validation for this type of medical device as presented in the document.

Study Details Proving Device Meets Acceptance Criteria (as per the provided document)

The document describes the performance testing undertaken to demonstrate substantial equivalence to a predicate device, focusing on accuracy, safety, and effectiveness for a non-invasive blood pressure monitor.

1. Table of Acceptance Criteria and Reported Device Performance

The core "acceptance criteria" for a non-invasive oscillometric sphygmomanometer like this are typically defined by international standards for accuracy. The document explicitly references these standards for performance effectiveness.

Note: The performance values (± 3 mmHg for BP, ± 5% for HR) are commonly accepted accuracy requirements for non-invasive oscillometric blood pressure monitors as per standards like ISO 81060-2. The document states the device has this accuracy, implying it meets these criteria.

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

• Sample Size for Clinical Validation: "100 subjects were involved for each study" (for the upgraded AOJ-30A, AOJ-30C, AOJ-30D, and AOJ-30E models).
• Data Provenance: Not explicitly stated regarding country of origin, but the submitting company is Shenzhen AOJ Medical Technology Co., Ltd. in China. The study is described as "clinical testing... conducted per IEC 81060-2: 2013." The nature of the study is prospective clinical validation as it describes involving subjects and conducting tests.

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

• The document implies ground truth (reference blood pressure measurements) would be established by experts as per the standard ISO 81060-2:2018. This standard typically requires a certain number of qualified observers (e.g., trained healthcare professionals) taking reference measurements. However, the exact number of experts and their specific qualifications are not explicitly detailed in this document. It only states: "Observer preparation, Reference determination, Clinical investigation methods and Data analysis are referred to ISO 81060-2: 2018 without any deviation."

4. Adjudication Method for the Test Set

• The document refers to ISO 81060-2:2018 for "Reference determination" and "Clinical investigation methods." This standard outlines specific methodologies for obtaining simultaneous reference blood pressure measurements (e.g., using a mercury sphygmomanometer or an automated reference device), which inherently involves a form of "ground truth" or reference standard, but it's not an "adjudication method" in the sense of multiple independent readers evaluating images, as would be the case for an AI/ML study.

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

• No, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI/ML devices where human readers' performance with and without AI assistance is evaluated. This document concerns a standalone blood pressure monitor.

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

• Yes, the core of the clinical validation described is a standalone performance test of the device's measurement accuracy against a reference standard. The device itself is an automated blood pressure monitor without human interpretation requirements beyond reading the displayed values. The accuracy values (± 3 mmHg for BP, ± 5% for HR) are standalone performance metrics.

7. The Type of Ground Truth Used

• The ground truth for the clinical validation of blood pressure devices is established through simultaneous, direct measurements by a highly accurate reference method (e.g., auscultatory method with trained observers using a mercury sphygmomanometer, or another validated reference device) conducted according to the specified international standard (ISO 81060-2:2018). This is implied by the statement "Reference determination... referred to ISO 81060-2: 2018 without any deviation." It's essentially "expert consensus" in the sense of adhering to a standardized clinical protocol for reference measurements.

8. The Sample Size for the Training Set

• Not applicable. This document describes the validation of a hardware-based blood pressure monitor (oscillometric technique), not an AI/ML device that requires a "training set" in the machine learning sense. The device's algorithm for blood pressure determination is pre-सेट and does not undergo "training" on a dataset in the way an AI model would.

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

• Not applicable. As above, there is no "training set" for this type of device.

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The thermometer is intended to measure human body temperature of people over one month from surface of forehead. It is a non-sterile, reusable, non-contact and hand-held device. It is indicated to be used in homecare and healtheare environments.

The Forehead thermometer is a handheld device, which can measure human body's temperature from the forehead for clinical or home use. The results can be displayed on LCD. The measurement is non-contact with a distance of 3-5 cm to measure the temperature. The thermometers are powered by AAA 1.5V×2 alkaline batteries, which can be used for people over one month. A thermopile sensor is employed to detect or monitor the infrared thermal energy emitted from the surface skin of the forehead, which is converted to a body temperature with the unit of °C or °F. The reference body site of the output temperature is oral. All the models share the similar design and the same critical components, and compose of a sensor, PCB, buttons, LCD display and housing. Functions include temperature measurement, memory reading recall, voice mute/unmute and unit/mode switch, low battery detection and high temperature indicator.

The provided text describes the acceptance criteria and a study demonstrating that the device meets these criteria. Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size for Clinical Accuracy Validation:
  • AOJ-F101: 153 subjects
  • AOJ-F102: 142 subjects
  • AOJ-F103: 132 subjects
• Data Provenance: The document (K221170) is a 510(k) summary submitted to the FDA by a Chinese company (Shenzhen AOJ Medical Technology Co., Ltd. in Shenzhen, China). The clinical testing was explicitly stated as "Clinical accuracy validation was carried out on people over one month indicated in the instructions for use." While not explicitly stated, clinical studies for FDA submissions typically involve prospective data collection to demonstrate performance. The country of origin for the clinical data is not specified, but usually, it aligns with the manufacturer's location or regions where clinical trials are feasible and recognized for regulatory purposes.

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. For a thermometer, "ground truth" for temperature is typically established using a highly accurate reference thermometer (e.g., a rectal thermometer for core body temperature, used in a clinical setting), rather than expert consensus on interpretation.

4. Adjudication method for the test set:

This information is not provided in the document. Adjudication methods like 2+1 or 3+1 are typically used for subjective assessments where multiple human readers interpret medical images or data. For a thermometer's accuracy, the ground truth is usually a precise measurement from a reference device, making such adjudication unnecessary.

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 is not applicable. The device is a thermometer, a measurement tool, not an AI-assisted diagnostic device that aids human readers in interpreting complex cases. Therefore, an MRMC study comparing human reader performance with and without AI assistance was not conducted.

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

The device itself is a standalone measurement device. The "Clinical data" section describes a clinical accuracy validation study to confirm its performance directly against a clinical reference for body temperature, which is a form of standalone performance evaluation for a thermometer. There is no "algorithm only" in the context of an AI device here, but rather device-only performance for a physical product.

7. The type of ground truth used:

For the clinical accuracy validation, the ground truth for body temperature measurements would have been established using a highly accurate reference clinical thermometer (e.g., an oral or rectal thermometer, depending on the standard protocol for comparison) in a controlled clinical setting. The document specifies that clinical testing was conducted "per Section 201.102 of ISO 80601-2-56," which outlines the requirements for clinical investigations of medical electrical equipment used for body temperature measurement. This standard details how to establish accurate reference temperatures.

8. The sample size for the training set:

This information is not provided in the document. The document describes premarket testing and validation for a physical medical device, not a machine learning model that requires a training set. The "software verification and validation testing" refers to traditional software engineering V&V, not AI model training.

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

This information is not applicable as there is no mention of a training set for a machine learning model. The device is a conventional electronic thermometer.

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