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The Belter Infra-red Ear thermometer is an electronic thermometer using an infrared sensor to detect human body temperature from the ear canal on people of all ages for home and professional use.

The Belter Infra-red Ear Thermometer is characterized by measuring human body temperature from the ear canal. It utilizes infrared technology to measure infrared energy emitted from eardrum tissue when making a temperature measurement.

This document describes the acceptance criteria and study results for the Belter Infra-red Ear Thermometer.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance

The document does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It only mentions "bench test report" and "clinical repeatability."

3. Number of Experts and Qualifications

This information is not provided in the document.

4. Adjudication Method

This information is not provided in the document.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not conducted as this device is a thermometer, not an AI-assisted diagnostic tool.

6. Standalone Performance

Yes, a standalone performance assessment was done, evaluating the device's accuracy and repeatability without human intervention. The reported values for laboratory accuracy and clinical repeatability are standalone metrics.

7. Type of Ground Truth Used

The ground truth for accuracy was established against a reference standard in laboratory settings (bench tests) and through clinical repeatability measurements in a clinical setting. The specific method for determining the "true" temperature for comparison during clinical repeatability is not detailed, but it typically involves comparison to another validated thermometer or a set protocol.

8. Sample Size for Training Set

This information is not applicable as this is not an AI/ML device requiring a training set.

9. How Ground Truth for Training Set Was Established

This information is not applicable as this is not an AI/ML device requiring a training set.

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Belter Blood pressure meter is intended to measure the systolic and diastolic blood pressure as well as the pulse rate of adult person. It can be used at medical facilities or at home.

The device detects the appearance of irregular heartbeats during measurement and gives a warning signal with readings.

The Belter Blood pressure meter 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 with arm circumference ranging from 22 cm to 36cm by the oscillometric technique. User can select the blood pressure unit mmHg or KPa.

The device consists of the microprocessor, pressure sensor, operation keys, pump, deflation control valve and LCD. The subject device is powered by four AA alkaline batteries.

The device has a memory function that automatically stores up to 60 sets of the latest measurements. It can also display the latest measurement result.

The subject device embeds a Bluetooth that allows it to transport the measurement data to nearby receiving end.

The device also detects the appearance of irregular heartbeats during measurement. and gives a warning signal with readings.

The "Belter Blood pressure meter, Model: ePA-46B" is intended to measure systolic and diastolic blood pressure and pulse rate in adults, for use in medical facilities or at home, and to detect irregular heartbeats. The study demonstrating its performance and meeting acceptance criteria is based on conformance to regulatory and performance standards.

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

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the Belter Blood pressure meter are defined by the conformance to various international standards, including ANSI/AAMI SP10 for automated sphygmomanometers. The reported device performance metrics are directly against the stated accuracy requirements within these standards.

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

The document states that the ANSI/AAMI SP10 standard (Manual, electronic, or automated sphygmomanometers, 2002/A1:2003) was followed. The EN1060-4 standard (Non-invasive sphygmomanometers - Part 4: Test procedures to determine the overall system accuracy of automated Non-invasive sphygmomanometers, 2004) was also followed.

These standards typically specify subject recruitment criteria and sample sizes for clinical validation studies (e.g., minimum of 85 subjects with specific blood pressure ranges for AAMI SP10). However, the specific sample size used for the test set for the Belter device is not explicitly stated in the provided document. Similarly, the data provenance (e.g., country of origin, retrospective or prospective) is not explicitly stated.

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

Since the study appears to be a clinical validation against established reference methods (auditory auscultation by trained observers often used in these standards), the "ground truth" would be established by these trained observers. However, the exact number of experts and their specific qualifications (e.g., "radiologist with 10 years of experience") are not explicitly stated in this document. Standard practice for AAMI SP10 typically involves two or three trained observers whose measurements are averaged or adjudicated.

4. Adjudication Method for the Test Set

The document does not explicitly state the adjudication method used. However, given the reliance on standards like ANSI/AAMI SP10 and EN1060-4, these standards typically outline methods for comparing automated device readings to reference measurements (e.g., using two or three trained observers whose readings are within a specified tolerance, and if not, a third observer or an adjudication process is used). The document does not specify a "2+1, 3+1, none" adjudication method, but the adherence to the standards implies a structured approach for ground truth determination.

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 done. This type of study is typically associated with imaging diagnostics or other AI-assisted detection tasks where human readers interpret data, and the AI's impact on their performance is measured. For a blood pressure monitor, the performance is assessed against a standard reference method, not by comparing human interpretation with and without AI assistance on complex cases.

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

Yes, a standalone study was done. The performance data presented and the conformance to standards like ANSI/AAMI SP10 and EN1060-4 refer to the device's accuracy in autonomously measuring blood pressure and pulse rate, without human intervention in the measurement process itself. The device is purely algorithmic in its core function of calculating BP from oscillometric data.

7. The Type of Ground Truth Used

The ground truth used for validating blood pressure monitors against standards like ANSI/AAMI SP10 and EN1060-4 is typically reference measurements obtained by trained observers using a calibrated auscultatory method (e.g., a mercury sphygmomanometer). This is considered the clinical 'gold standard' for non-invasive blood pressure measurement against which automated devices are compared. It's effectively an "expert consensus" or "expert reference" type of ground truth in a clinical setting.

8. The Sample Size for the Training Set

The document does not provide information regarding a "training set" for the device. Automated blood pressure monitors like the Belter device are typically developed and calibrated based on established oscillometric algorithms and physical principles, rather than being "trained" on a dataset in the way a machine learning model would be. Calibration and internal testing would be part of the development process, but this is distinct from a machine learning training set.

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

As there is no mention of a training set in the context of machine learning, there is no information on how its ground truth would have been established. The device operates based on a pre-defined algorithm derived from established physiological principles of oscillometry and is then validated clinically.

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The Shenzhen Belter Health Measurement and Analysis Technology Co., Ltd. Body Fat Scale SF-371 measures body weight, and estimates body fat, body water, body muscle mass and body bone mass using BIA (bioelectrical impedance analysis). The device is intended to be used by generally healthy people (from age 16 to age 80) who are not ill, feverish, have a chronic or acute disease, or a condition that affects the level of hydration such as pregnancy.

The patient steps on the scale device, where four electrodes are located. The patient must step on the electrodes with bare feet, with normal moisture. Through harmless current stimulation of 500 µA, at 50 kHz, the Shenzhen Belter Health Measurement and Analysis Technology Co., Ltd. Body Fat Scale calculates the body fat percentage. This calculation is done via the Bioelectrical Impedance Method. The current is passed through the body and the impedance of the body determines the body fat. The calculation is based upon electrical impedance, height, weight, age, and gender. The calculation is performed via internal software, which uses the variables programmed in by the user. There are elements of this process that can produce erroneous readings, such as dry feet or improper-programmed data. The User's Manual defines items which could cause erroneous readings.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Body Fat Scale, Model SF-371 (K122976):

The provided 510(k) summary (K122976) for the Shenzhen Belter Health Measurement and Analysis Technology Co., Ltd. Body Fat Scale, Model SF-371, is quite limited in detail regarding specific acceptance criteria and the clinical study. It states that "Clinical testing was used to validate the effectiveness and accuracy of the device. All test results were satisfactory." However, it does not provide specific metrics or outcomes from this clinical testing.

Therefore, much of the requested information cannot be directly extracted from the provided document. I will present what is available, and for missing information, I will explicitly state that it is not provided.

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary states that "Clinical testing was used to validate the effectiveness and accuracy of the device. All test results were satisfactory." However, no specific acceptance criteria or quantitative performance metrics (e.g., accuracy percentages, standard deviations, correlation coefficients) are provided in the document.

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

The document states that "Clinical testing was used to validate the effectiveness and accuracy of the device," but it does not specify the sample size used for this test set.

Data Provenance: The document does not explicitly state the country of origin for the clinical testing data. Given that the submitting company is based in Shenzhen, China, it is plausible the testing was conducted locally, but this is not confirmed. It also does not specify whether the data was retrospective or prospective.

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

The 510(k) summary does not provide any information regarding the number of experts used, their qualifications, or how ground truth was established for the clinical testing.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method used for the clinical testing.

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

The document does not mention any MRMC comparative effectiveness study involving human readers or AI assistance. The device is a "Body Fat Scale," which is a direct measurement device rather than an interpretive imaging or diagnostic system that would typically involve MRMC studies.

6. Standalone (Algorithm Only) Performance

The device itself is a standalone algorithm for calculating body composition based on bioelectrical impedance. The statement "Clinical testing was used to validate the effectiveness and accuracy of the device" implicitly refers to the standalone performance of the device's calculations. However, no specific performance metrics are provided.

7. Type of Ground Truth Used

The document does not specify the type of ground truth used for validation. For body fat scales, common ground truth methods include DEXA (Dual-energy X-ray absorptiometry), hydrostatic weighing, or air displacement plethysmography, but none of these are mentioned.

8. Sample Size for the Training Set

The document does not provide any information regarding a training set sample size. This type of device relies on internal algorithms based on established bioelectrical impedance principles and user-programmed variables, rather than a deep learning model requiring a distinct "training set" in the modern AI sense.

9. How Ground Truth for the Training Set Was Established

Since no training set is described in the context of an AI/machine learning model, this information is not applicable and therefore not provided in the document. The device's calculations are based on bioelectrical impedance method, using electrical impedance, height, weight, age, and gender, likely derived from scientific literature and established physiological models rather than a specific "training set" with ground truth in the typical AI development paradigm.

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