Search Results

The Probe Covers for Thermometers are intended for use as barriers between thermometers and oral cavities or users' rectum. The subject devices are used as accessories for digital thermometers and intended for single use only.

The Probe Covers for Thermometers, which made of PE and EVA, are used for thermometers as barriers during oral or rectal temperature measurements. The Probe Covers are suitable for varied thermometers and non-sterilized packaging. A sandwich structure which is formed by the top and back paper and middle films.

The provided text is a 510(k) Premarket Notification for "Probe Covers for Thermometers" and outlines the device's characteristics and its substantial equivalence to a predicate device. It defines the device, its intended use, and its comparison to an existing device (Yu Long Sheng Disposable Thermometer Sheath, K102508).

However, the document does not describe a study that involves an AI/ML device, expert ground truth establishment, sample sizes for training/test sets, or detailed performance metrics like sensitivity, specificity, or AUC as one would expect for an AI diagnostic device. Instead, it describes compliance with engineering and biocompatibility standards for a physical medical accessory.

Therefore, I cannot extract the information required to populate the table and answer the subsequent questions about an AI/ML study. The provided text is solely about the regulatory clearance of a non-AI/ML medical device accessory.

Here's why I cannot fulfill your request based on the provided text:

• No AI/ML Device: The device is "Probe Covers for Thermometers," a physical accessory. It does not involve any artificial intelligence or machine learning component.
• No Diagnostic Performance Study: The "performance" section refers to compliance with ASTM E1104-98 (Standard Specification for Clinical Probe Covers and Sheaths) and ISO 10993 (Biocompatibility). These are standards for physical properties (leakage, toxicity, compatibility) and material safety, not for diagnostic accuracy or algorithmic performance.
• No "Ground Truth" as related to AI: Ground truth in an AI/ML context typically refers to validated medical conditions (e.g., presence or absence of a disease) established by experts, pathology, or outcomes for a machine to learn from or be tested against. For a thermometer probe cover, "ground truth" relates to physical specifications and material safety.
• No Human Reader Study (MRMC): There is no mention of human readers or comparative effectiveness studies with or without AI assistance, as the device is not a diagnostic tool that assists human interpretation.

Therefore, I must state that the provided document does not contain the information requested in your prompt regarding acceptance criteria and a study proving an AI/ML device meets them.

If you have a document describing an AI/ML medical device and its corresponding studies, please provide that, and I would be happy to help.

Ask a specific question about this device

The Digital Thermometer is intended to measure oral temperature of human body. It can be used in home environment or at a doctor's clinic. It is indicated for use by people of all ages.

The Digital Thermometer consists two parts. The thermometer probe part is a compact, small, light-weight, and battery-powered unit with thermometer sensor for oral temperature measurements. The thermometer probe must be connected to a compatible mobile phone device through its headphone jack for displaying measured temperatures.

The mobile application could be conducted for operation and display temperature measurement when the Digital Thermometer connects with mobile device. The mobile application can be conducted on iOS operating system and Android operating system of mobile device.

The mobile application could perform the functionality on mobile device screen including measurement activity, historical data activity, trend activity, basic setting and initial setting activity.

The provided text describes a digital thermometer, Model 2180, and its substantial equivalence to a predicate device, the Basal Digital Thermometer (K141505). The information primarily focuses on the device's characteristics, intended use, and compliance with various standards.

Here's an analysis of the acceptance criteria and the study information as requested, based only on the provided text:

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

The document lists several standards and requirements that the Digital Thermometer complies with, implying these act as acceptance criteria. The reported performance is that the device "complies" or "met the endpoints."

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

The document does not explicitly state the sample size used for any specific test set, nor does it mention data provenance (e.g., country of origin, retrospective/prospective). It generally states that the device was "verified and validated" or "complies" with standards.

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

This information is not provided in the document. The document refers to compliance with established standards (e.g., ASTM E1112-00 for accuracy), which inherently have their own defined test methodologies, but details about specific expert involvement in this device's testing ground truth establishment are absent.

4. Adjudication method for the test set

The document does not describe any adjudication method (e.g., 2+1, 3+1) for establishing ground truth for a 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

This is not applicable as the device is a digital thermometer, not an AI-assisted diagnostic tool involving human readers. No MRMC study was mentioned.

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

The device is a standalone digital thermometer that provides a temperature reading. Its performance criteria (e.g., accuracy) were assessed in this context. The "software validation" mentioned indicates evaluation of the algorithm within the device and mobile application, which can be seen as a standalone performance assessment for its accuracy and functionality.

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

For the performance of the thermometer, the "ground truth" would be established by reference standards or calibrated equipment used in accordance with the specified testing methodologies of standards like ASTM E1112-00. The text does not detail the specifics of such "ground truth" generation for its internal testing beyond stating compliance with the standard.

8. The sample size for the training set

This information is not applicable. The device is a digital thermometer, not a machine learning model that requires a training set in the conventional sense.

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

This information is not applicable, as there is no "training set" for this type of device.

Ask a specific question about this device

The Basal Digital Thermometer is intended to measure the human body temperature for children and adults, especial for woman. It has precise digital display and be used in household environment and doctor in clinics as reference.

Not Found

This document is a 510(k) clearance letter for a "Basic Digital Thermometer, Model KD-2160." It formally states that the device is substantially equivalent to legally marketed predicate devices.

However, the provided text does not contain any information regarding specific acceptance criteria, study details, or performance data for the device itself. It is a regulatory approval letter, not a study report. Therefore, I cannot fulfill the request to describe the acceptance criteria and the study that proves the device meets them based on the provided input.

To answer your request, I would need a document detailing the performance study, such as a summary of safety and effectiveness, or a clinical study report submitted to the FDA during the 510(k) process.

Ask a specific question about this device

The Ultrasonic Nebulizer is intended to transform liquid medications into aerosol form for patient inhalation. The device can be used by adult or pediatric patients for respiratory treatment in the home, hospital or healthcare environment.

The Ultrasonic Nebulizer is a small, compact, and battery powered potable nebulizer which transforms liquid medicines into aerosol form and delivers directly to patient for inhalation. It makes patient's respiratory treatment easier and more convenient.

Here's an analysis of the K-jump® Ultrasonic Nebulizer based on the provided text, focusing on acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not contain a specific table of "acceptance criteria" for performance that would typically be found in a detailed validation study. Instead, the document focuses on demonstrating substantial equivalence to a predicate device by comparing technological characteristics and compliance with general safety and performance standards.

However, we can infer some performance characteristics and compliance requirements:

Important Note: The document emphasizes "similar performance" and "compliance with equivalent safety standards" rather than showing specific quantitative performance targets met by the K-jump device and then presenting raw data to prove those targets were met. This is typical for a 510(k) submission where substantial equivalence to a legally marketed predicate device is being demonstrated.

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

The provided document does not specify a sample size for a "test set" in the context of clinical or performance data for this device. The submission relies on demonstrating compliance with recognized standards and similarity in technological characteristics to a predicate device.

• Sample size for test set: Not specified/applicable in this document's context.
• Data Provenance: The document does not describe patient or clinical data that would have a provenance (e.g., country of origin, retrospective/prospective). The data presented for the K-jump device are engineering specifications and compliance declarations.

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

Not applicable. The document does not describe a study involving expert-established ground truth for a test set. This type of submission focuses on engineering specifications and regulatory compliance, not typically on diagnostic accuracy or interpretation by human experts.

4. Adjudication Method for the Test Set

Not applicable. There is no mention of a test set requiring adjudication in this 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

Not applicable. This device is an ultrasonic nebulizer, not an AI-powered diagnostic tool. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is outside the scope of this submission.

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

Not applicable. This device is a medical apparatus, not an algorithm, so "standalone" algorithm performance is not relevant.

7. The Type of Ground Truth Used

Not applicable. The "ground truth" concept (e.g., pathology, outcomes data) is not relevant for this type of device submission, which focuses on device functionality, safety, and equivalence to a predicate. The "truth" here is established through engineering testing and compliance with recognized standards.

8. The Sample Size for the Training Set

Not applicable. The K-jump Ultrasonic Nebulizer is a physical medical device, not an AI or machine learning algorithm. Therefore, there is no "training set."

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

Not applicable, as there is no training set for this device.

Ask a specific question about this device

The Non-contact Thermometer is intended to measure the human body temperature for children and adults without contact to human body. It can be used by consumers in household environment and doctor in clinics as reference.

The Non-contact Thermometer is a compact, small and light-weight device, which is powered by a battery and can be connected to a smartphone through headphone jack, for detecting body temperature without contact to human body. The measured temperature will be displayed on the screen of a smartphone.

The provided document describes a 510(k) premarket notification for a Non-contact Thermometer (K120711). The primary method for proving the device meets acceptance criteria is through demonstrating substantial equivalence to a predicate device (K102947) and compliance with recognized standards.

Here's an analysis of the acceptance criteria and the study (or lack thereof) that proves the device meets them, based on the provided text:

Acceptance Criteria and Reported Device Performance

The acceptance criteria are primarily derived from the predicate device's performance specifications and industry standards.

Detailed Study Information (Based on provided text)

The document primarily relies on design validation and compliance with established standards rather than a specific clinical study with human subjects for novel performance claims.

1. Sample size used for the test set and data provenance:
   This information is not provided in the document. The filing states the device "complies" and is "verified and validated," but it does not detail the specific test set size (e.g., number of temperature measurements, number of subjects) or the provenance (e.g., country of origin, retrospective/prospective) of any data collected to demonstrate compliance with ASTM E1965-98, which would typically involve testing on physical samples.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
   This information is not provided. The document does not describe a clinical study relying on expert-established ground truth. Compliance with ASTM E1965-98 would typically involve metrology experts and calibrated reference devices, but specific details are absent.

3. Adjudication method for the test set:
   This information is not provided. As there's no mention of a clinical study with multiple observers, adjudication methods like 2+1 or 3+1 are not applicable here.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance:
   No, an MRMC comparative effectiveness study was not done. This device is a standalone thermometer, not an AI-assisted diagnostic tool for human readers.

5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
   The entire premise of this submission is for a standalone device (a thermometer). The "performance" described is the standalone performance of the device itself (its accuracy, operating range, etc.) in meeting established standards. There's no separate "algorithm only" component vs. "human-in-the-loop," as the human interacts directly with the device to take a measurement. The "study" (or validation) conducted would have been to verify the device's accuracy against a known reference temperature source during testing, as per ASTM E1965-98.

6. The type of ground truth used:
   The ground truth for performance (specifically temperature accuracy) would have been established through calibrated reference standards and laboratory testing in accordance with ASTM E1965-98. For safety and EMC, the ground truth is adherence to the technical specifications and test methodologies defined in the respective IEC/ANSI/AAMI standards.

7. The sample size for the training set:
   This information is not applicable/not provided. This device is a hardware product with embedded firmware/sensors for a direct physical measurement. It is not an AI/machine learning device that requires a "training set" in the conventional sense.

8. How the ground truth for the training set was established:
   This information is not applicable/not provided, as there is no "training set" for this type of device.

Ask a specific question about this device

K-jump Health Co, Ltd. Digital Forehead Thermometers, Model KD-2201 & KD-2210, are intended to measure the human body temperature using the forehead as measurement site. They can be used with adult or pediatric patients.

The Digital Forehead Thermometers, Model KD-2201 & KD-2210, consist of a probe with thermister sensor and stainless steel plate, a PC board with ASIC circuits, a LCD display, a plastic main body, an ON/OFF power key, a buzzer and two AAA type batteries for the determination of human body temperature.

The acceptance criteria and study proving device performance are as follows:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Size for the Test Set and Data Provenance:
The document does not explicitly state the sample size used for the test set in terms of the number of measurements or subjects. Rather, it refers to compliance with voluntary standards.
The provenance of data is not specified in terms of country of origin or whether it was retrospective or prospective, as clinical trials were deemed unnecessary.

3. Number of Experts and Qualifications for Ground Truth:
Not applicable. The ground truth was established through compliance with recognized performance standards (ASTM E 1112-00 and EN 12470-3), not through expert consensus derived from a clinical test set.

4. Adjudication Method for the Test Set:
Not applicable, as there was no expert adjudication process for establishing ground truth in this non-clinical performance evaluation.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
No, an MRMC comparative effectiveness study was not performed. The device is a standalone thermometer, and the evaluation focused on its intrinsic accuracy against standards rather than its performance with or without AI assistance for human readers.

6. Standalone Performance Study (Algorithm Only Without Human-in-the-Loop):
Yes, a standalone performance evaluation was conducted. The devices were tested for compliance with recognized performance standards (ASTM E 1112-00 and EN 12470-3). These standards typically involve testing the device's accuracy and other performance characteristics under controlled conditions, without human interpretation as part of the core performance metric.

7. Type of Ground Truth Used:
The ground truth was established by recognized performance standards for clinical electronic thermometers: ASTM E 1112-00 and EN 12470-3. These standards define the acceptable limits for accuracy and other performance parameters.

8. Sample Size for the Training Set:
Not applicable. The document describes a medical device (a thermometer), not an AI/machine learning algorithm, and therefore there is no "training set" in the context of machine learning.

9. How the Ground Truth for the Training Set Was Established:
Not applicable, as there is no training set for an AI/machine learning algorithm.

Ask a specific question about this device

Non-Contact Infrared Thermometer, Model KI-8280, can measure body temperature for infants and adults without contact to human body. It can be used by consumers in household environment and doctor in clinic as reference.

The Non-Contact Infrared Thermometer, Model KI-8280, uses infrared sensor (thermopile) to detect the radiated infrared energy emitted by the objects, solid, liquid or gas. The intensity of the emitted energy depends on the temperature of the object and the infrared sensor can recognize it to transfer to the proper electronic signal. The electronic signal can be processed in the subject device to convert to the temperature reading. Therefore, the subject device is able to measure the temperature of a person by the energy the person emits. The predicate device, JXB Thermoflash, use the same detection principle to measure the patient's temperature. The subject device also use the focusing design to collect the infrared emitted from nearby area of object surface. This mechanism make the subject device have the ability to detect the object surface temperature in the distance of 3-8cm. The subject device intended to detect the temperature of patients. The temperature is converted to the oral temperature. The temperature reading shown in the device display after measuring is the patient's oral temperature. The compact, small and light-weight design, the K-jump Health Co, Ltd. Non-Contact Infrared Thermometer, Model KI-8280, enables to provide safe and reliable results and offers a very good clinical accuracy for human body temperature measurement.

Here's a breakdown of the acceptance criteria and the study details for the Non-Contact Infrared Thermometer, Model KI-8280, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

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

   • The document states that the clinical performance test protocol and data analysis followed the requirements of ASTM E 1965. However, it does not explicitly state the specific sample size used for the test set of patients.
   • Data Provenance: Not explicitly stated, but clinical testing was conducted. It's common for such tests to be prospective, but this is not explicitly confirmed. The company is based in Taiwan, so it's possible testing occurred there or in another location appropriate for clinical studies.

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

   • This information is not provided in the summary. The study refers to comparing the device's readings with a "digital thermometer," implying this was the reference standard, but details on how the ground truth was established for the digital thermometer readings (e.g., expert interpretation) are absent.

3. Adjudication Method for the Test Set:

   • This information is not provided. The study focused on the difference between the device's readings and a digital thermometer, rather than using an adjudication process for subjective assessments.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No, an MRMC comparative effectiveness study was not explicitly mentioned or performed. This type of study is more common for diagnostic imaging devices where human interpretation is a key component. This device is a direct measurement tool.

5. Standalone (Algorithm Only Without Human-in-the-Loop) Performance:

   • Yes, the performance reported is for the standalone device. The device measures and displays temperature directly without requiring human interpretation of an output, making its performance inherently standalone. The clinical test evaluated the accuracy of the device's temperature readings.

6. Type of Ground Truth Used:

   • The ground truth was established by readings from a digital thermometer, which is considered a standard clinical reference for temperature measurement.

7. Sample Size for the Training Set:

   • This information is not provided. The summary does not discuss a "training set" in the context of machine learning (which this device pre-dates and doesn't rely on in the typical sense). The performance testing described relates to the final device against a known standard.

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

   • As no training set is discussed in the context of machine learning, this information is not applicable. For the clinical validation, the ground truth was established by comparing the device's readings to those of a digital thermometer.

Ask a specific question about this device

K-jump Health Co, Ltd. Peak Flow Meter, Model KN-9710, is intended for monitoring expiratory-breath function at home under direction of a physician or licensed health care professional. It measures the peak expiratory flow (PEF) and timed forced expiratory volumes over 1 second (FEV1). This device can be used from 6-year-old children to adult patients for monitoring and managing of chronic respiratory conditions, especially asthma and COPD.

The Peak Flow Meter, KN-9710, uses hot wire on the thin film inside the air flow measurement tube. The hot wire will electrically heat up to a constant temperature. As air flow passes through the air flow measuring tube, the wires cool off, requiring extra electrical energy to heat up to the the constant temperature. The air flow sensor will instantly feed back a voltage to maintain temperature. And the proper proportion and evaluation of the peak flow rate and volume will be determined. The KN-9710 is a compact, small and light-weight designed portable handheld device that electronically measures the Peak Expiratory Flow (PEF) as will as the Forced Expiratory Volume in the first second of expiration (FEV1).

Here's an analysis of the acceptance criteria and study detailed in the provided document:

The document describes the K-jump Health Co., Ltd. Peak Flow Meter, Model KN-9710, intended for monitoring expiratory-breath function. The primary performance criteria revolve around the accuracy and precision of its measurements for Peak Expiratory Flow (PEF) and Forced Expiratory Volume in the first second (FEV1), as well as compliance with safety and biocompatibility standards.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document only explicitly states the predicate device's flow and volume accuracy comparison. For the subject device's performance, it broadly states "well within the required ATS (ATS 1994 update) accuracy specification" and "comply with all variability requirements" for both interdevice and intradevice variability. The specific numerical performance of the KN-9710 is not directly provided in the text beyond stating it met the ATS specifications.

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

• Sample Size: The device performance was tested using 24 standard waveforms and 26 flow-time waveforms.
• Data Provenance: The test was conducted at an independent laboratory, LDS Hospital (Salt Lake City, UT), U.S.A. The testing involved comparing the device's measurements against generated values from a precision waveform generator, rather than human patient data. Therefore, the data is prospective in the sense that the test was specifically designed and executed to evaluate the device against established waveforms.

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

This section is not applicable as the ground truth was established by a precision waveform generator, not human experts. The reference standard was the generated values produced by this equipment, which is designed to simulate respiratory patterns with known, precise PEF and FEV1 values.

4. Adjudication Method for the Test Set

This section is not applicable. There was no human adjudication process since the comparison was between the device's output and the known, precisely generated values from a waveform generator.

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 typically involves human readers or operators assessing cases with and without AI assistance. This submission describes a standalone technical performance study of a measurement device.

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

Yes, a standalone study was done. The description explicitly states: "The KN-9710 electronic peak flow meter was tested at an independent laboratory... The peak expiratory (PEF) and forced expiratory volume in one second (FEV1) measurement from the KN-9710 were compared against the generated values." This indicates the algorithm and hardware of the device were tested for their accuracy and precision in measuring PEF and FEV1 without human intervention impacting the measurement itself.

7. The Type of Ground Truth Used

The type of ground truth used was generated values from a precision waveform generator. This is a highly controlled, synthetic "ground truth" designed to emit specific, known respiratory flow and volume patterns.

8. The Sample Size for the Training Set

The document does not specify a sample size for a training set. This is typical for submissions of this nature, as the device is a measurement instrument calibrated against physical standards and engineering specifications, rather than a machine learning algorithm that requires a dataset for training. If the device's internal algorithms involve machine learning, the training set information is not provided in this document.

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

This information is not applicable/not provided. As mentioned above, the document describes the testing and validation of the device, not its development or any potential machine learning training phase.

Ask a specific question about this device

The KP-7770 is intended to measure the systolic and diastolic blood pressure and pulse rate (heart rate) by using an inflating cuff wrapped around the arm. It is indicated for use in adults.

The devices display irregular pulse detection (IPD) icon on LCD screen when irregular pulse is detected during blood pressure measurement.

The device is an electronic blood pressure monitor. The device consists of an inflating cuff, a LCD display, a bellows sensor, an internal air pump, a leakage valve, an exhaust valve, a battery power resource, and keys for operation.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Arm Blood Pressure Monitor Model KP-7770:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific numerical acceptance criteria for the device's performance regarding blood pressure accuracy (e.g., mean difference and standard deviation compared to a reference method). Instead, it states compliance with recognized consensus standards.

Acceptance Criteria (Implied by Compliance with Standards):

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

The document states: "Clinical performance of the modified device is remain unchanged; therefore another clinical trial for this device, KP-7770, is not required."

This indicates that no new clinical test set was used for the KP-7770 model as its clinical performance was deemed unchanged from its predicate. Therefore, information regarding sample size and data provenance for a new test set is not applicable to this specific submission for the KP-7770.

3. Number of Experts and Qualifications for Ground Truth of Test Set

As no new clinical test set was conducted for the KP-7770, this information is not provided. The substantial equivalence argument relies on the predicate device's established performance.

4. Adjudication Method for the Test Set

Not applicable, as no new clinical test set was conducted for the KP-7770.

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

No MRMC comparative effectiveness study was done. Blood pressure monitors are typically evaluated for accuracy against a reference standard in clinical studies, not through MRMC studies which are more common for diagnostic imaging or interpretation tasks.

6. Standalone Performance (Algorithm Only)

The document focuses on the overall device (Arm Blood Pressure Monitor Model KP-7770), which is an integrated system. "Standalone" performance in the sense of an algorithm separate from human interaction isn't directly applicable for this type of device. Its performance is measured as the device's output (systolic, diastolic BP, pulse rate) against a clinical reference. The document states the device "can use MOMI or fuzzy logic method to measure blood pressure," implying the algorithm is intrinsic to the device's operation, and its performance is assessed via compliance with AAMI/ANSI SP10.

7. Type of Ground Truth Used

For devices complying with standards like AAMI/ANSI SP10, the ground truth is typically established by simultaneous measurements by trained observers using a validated reference method (e.g., auscultation with a mercury sphygmomanometer or another validated oscillometric device) in a clinical setting. While not explicitly stated in this document for the KP-7770, compliance with AAMI/ANSI SP10 implies such a methodology was used for the predicate device(s) that established the "unchanged" clinical performance.

8. Sample Size for the Training Set

The document does not provide information on the training set for the KP-7770's algorithms (MOMI or fuzzy logic) or the predicate devices. This type of detail is often proprietary and generally not included in 510(k) summaries unless a novel algorithm is being introduced that requires specific clinical validation. Given the reliance on predicate devices and established methods (fuzzy logic), it's likely the algorithms were developed and validated internally during product development, possibly using simulated data or internal clinical data, but no specifics are given here.

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

Similar to point 8, this information is not provided in the 510(k) summary. For blood pressure measurement algorithms, ground truth for training would typically involve large datasets of reference blood pressure measurements (e.g., from auscultation or highly accurate invasive methods) paired with the corresponding oscillometric waveforms.

Ask a specific question about this device

K-jump Health Co., Ltd. Ultrasonic Nebulizer System includes a DC powered ceramic resonator and a fan that provides a source of mist for home health care use. The device is used with a pneumatic nebulizer to convert certain inhaled drugs into an aerosol form for inhalation by a patient. The device can be used with adult or pediatric patients.

The KN-9210 uses the ultrasound vibration technique in which a piezeoelectric ceramic installed as a generator of ultrasound wave when powered key pressed and system been powered on. The medicine solution on the semi-oval cup can be converted to mist through the water medium which propagated the ultrasound from resonator on the device. Then, a mini fan on the device drives the mist or aerosol through the air flow chamber and mouth piece installed on the top cover to the patient. The patient can use this aerosol for his/her respiratory therapy with two-safety valve installed on the mouthpiece which is standed on the top of drug ampoule.

The device consists of a piezeoelectric ceramic, a fan, a plastic body (including a top cover, a main body, a rear cover, an inlet filter, a filter cover, a nebulization chamber and an air-flow chamber), a medicine cup, a printed circuit board with electronic components, a DC socket, an AC adapter power source (or a rechargeable battery assembly as an optional power source), and a key for ON/OFF operation.

The provided submission is for an Ultrasonic Nebulizer System (Model KN-9210), which is a medical device and not an AI/ML software device. Therefore, the requested information regarding acceptance criteria and studies proving the device meets them, especially those related to AI/ML performance, is not directly applicable in the typical sense for this document.

However, based on the provided text, I can extract and infer information relevant to the device's performance characteristics and the non-clinical tests conducted to demonstrate substantial equivalence to predicate devices.

Here's a breakdown of the available information, adapted to the requested structure where possible, but noting the absence of AI-specific details:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a nebulizer, the acceptance criteria relate to its physical performance in delivering medication. The "reported device performance" are the results of the performance testing conducted.

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

• Sample Size for performance tests: Not explicitly stated. The document mentions tests were conducted on "three medicines" (Atrovent, Bricanyl, Pulmicort), implying at least three distinct test cases for the nebulization performance metrics. For biocompatibility and other engineering tests, typical sample sizes are generally smaller and defined by applicable standards.
• Data Provenance: Not explicitly stated, but the testing would have been conducted by or for K-jump Health Co., Ltd., likely in Taiwan (country of origin of the company). The studies are non-clinical, bench-top performance tests, making them prospective in the sense that they were specifically designed and executed to evaluate the device.

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

• This device is a mechanical/electronic medical device (nebulizer), not an AI/ML diagnostic tool requiring expert interpretation for "ground truth." The performance metrics (e.g., particle size, flow rates) are measured objectively by laboratory instruments and protocols, rather than through expert consensus.
• Hence, this criterion is Not Applicable in the context of this device and submission.

4. Adjudication Method for the Test Set

• Again, this criterion is Not Applicable for a hardware device like a nebulizer. Adjudication methods like 2+1 or 3+1 are used in studies where human readers review and provide consensus on findings (e.g., medical images for AI 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 is Not Applicable. An MRMC study is relevant for AI/ML diagnostic tools that assist human readers. The K-jump Ultrasonic Nebulizer System is a therapeutic device that delivers medication; it does not involve human readers interpreting a "case" in the diagnostic sense.

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

• This is Not Applicable. This concept applies to AI/ML algorithms, not a physical medical device like a nebulizer.

7. The Type of Ground Truth Used

• For the performance testing, the "ground truth" would be established by objective measurements from calibrated laboratory equipment according to recognized standards (e.g., for particle size distribution, flow rates).
• For biocompatibility, the "ground truth" is determined by standardized laboratory tests for cytotoxicity, irritation, and sensitization, with results compared against pass/fail criteria from relevant international standards (e.g., ISO 10993).
• For EMC, Electrical, Mechanical, and Environmental Testing, the "ground truth" is compliance with relevant national and international safety and performance standards.

8. The Sample Size for the Training Set

• This is Not Applicable. As a physical medical device, there is no "training set" in the AI/ML sense. Design and development would follow engineering principles, not machine learning training.

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

• This is Not Applicable for the same reason as point 8.

Ask a specific question about this device