Search Results

The Ava Fertility Tracker is intended to measure and display physiological parameters (body temperature, resting pulse rate, heart rate variability, and breathing rate) as an aid in ovulation prediction to facilitate conception (not to be used for contraception).

The Ava Fertility Tracker aids women in ovulation prediction and to facilitate conception. The Ava Fertility Tracker is a non-invasive device made up of the following components:
The Ava bracelet incorporating hardware with electronics and embedded software
A mobile application running on smartphones (iOS and Android)
A backend server software, including algorithms running on remote servers
The Ava bracelet is worn by women at night and tracks the following physiological parameters with built-in sensors:
Temperature sensor - provides information on skin temperature
Photoplethysmography (PPG) sensor – measures the interbeat interval (IBI) providing information on pulse rate (HR), heart rate variability (HRV), breathing rate (BR) and perfusion. Only HR, HRV, and BR are used by the algorithms for prediction of the fertile window. Perfusion information is used to assess the quality of the PPG sensor data.
Accelerometer provides information on movement and sleep duration and phases
The user synchronizes the bracelet to the mobile app each morning. The mobile app receives the raw datasets via Bluetooth Low Energy (BLE) and transfers this data to the backend server. The algorithm is run on the physiological parameters collected and the prediction of ovulation and the fertile window is determined. This information is transferred and displayed in the mobile app. The mobile app will also display a single mean value for HR, temperature, HRV ratio, BR, and sleep duration from the prior night.

The mobile application has three modes:
Trying to Conceive Mode - The application shows the user the predicted day of ovulation plus five predicted fertile days leading up to the predicted day of ovulation. Users receive the prior night summary of measured parameters displayed in graphs. Users can track additional information on their cycle, such as sexual intercourse or cervical fluid (this information does not feed into the algorithm).
Cycle Tracking Mode– For users not wanting to conceive but wanting to track their cycle. These users receive the same information provided to Trying to Conceive Mode users.
Pregnancy Mode - Users receive the prior night summary of measured parameters displayed on graphs. They can also track additional information as relates to their pregnancy, such as their weight or their daily water intake. For each week of their pregnancy, a different piece of informational content gets displayed in the application, such as typical height and weight of a baby at this stage of their pregnancy.

Here's a breakdown of the acceptance criteria and study information for the Ava Fertility Tracker, based on the provided document:

Acceptance Criteria and Device Performance

Study Details for Clinical Performance:

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

   • Test Set Sample Size: The final analysis was performed on data from 61 women and 154 cycles.
   • Data Provenance: The study was a single center, prospective clinical study. The country of origin is not explicitly stated, but Ava AG is based in Zürich, Switzerland, and Ava Science Inc. in San Francisco, USA. The study design ("single center, prospective") indicates primary data collection for this purpose.

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

   • The document does not specify the number or qualifications of experts used to establish ground truth.

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

   • The document does not specify an adjudication method.

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

   • No, an MRMC comparative effectiveness study involving human readers (as typically seen in image-based diagnostics) was not performed.
   • The study compared the device's performance against a reference method (urinary LH tests) and a predicate device (Lady-Comp). It was not structured to assess human improvement with or without AI assistance in interpretation.

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

   • Yes, the clinical study essentially assessed the standalone performance of the Ava Fertility Tracker algorithm in predicting ovulation day, using "urinary LH tests as a reference." The device runs its algorithms on collected physiological parameters to determine predictions which are then displayed to the user.

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

   • The primary ground truth for ovulation prediction was urinary LH tests.
   • For the secondary endpoint (temperature shifts), the comparison was against the Lady-Comp device's basal-body temperature readings.

7. The sample size for the training set:

   • The document does not provide information regarding the sample size for the training set used for the Ava Fertility Tracker's algorithms.

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

   • The document does not provide information on how the ground truth for the training set was established.

Ask a specific question about this device

The Fertility Focus OvuSense Fertility Monitor (Fertility Focus OvuSense Fertility Monitor Starter Kit M009-US, which includes Reader M010-US and Personal Sensor M011) is intended for measuring and recording basal body temperature (BBT) as an aid in ovulation prediction to aid in conception (not to be used for contraception).

The Fertility Focus OvuSense Fertility Monitor is intended for measuring and recording core body temperature intra-vaginally on a nightly basis during the non-menstruating phases of the monthly female reproductive cycle. The Fertility Focus OvuSense Fertility Monitor consists of two components made of silicone - a Personal Sensor, which collects the data, and a Reader (with LCD display), which establishes a communication link to the Personal Sensor whereupon the data is transferred to the Reader. Electromagnetic induction communications hardware transmits the stored temperature data from the Personal Sensor to the receiving device, the Reader, activated when the Sensor is placed on the Reader cradle and the Reader's dedicated download button is pressed. The microprocessor based Reader filters the overnight data, then calculates and stores the 25th percentile value, representative of the average basal (lowest) overnight temperature. The Reader then displays these nightly temperature readings on a graph using a relative scale - the kev information for necessary calculations being the temperature changes relative to other recorded temperatures within a cycle for a particular user, and not absolute temperature value. At the start of the next cycle, indicated by the User inputting first day of the bleeding in the cycle, the Reader algorithm calculates the date of ovulation in the prior cycle, and uses this to predict the fertile period for the cycle which has just started. The Reader then displays fertility information in a verbal summary, including: An indication of the day ovulation occurred in the prior cycle, or if ovulation was not detected it displays this information instead. An indication whether the cycle length was within the expected normal parameters.

Here's a summary of the acceptance criteria and the study details for the Fertility Focus OvuSense Fertility Monitor, based on the provided text:

Acceptance Criteria and Device Performance

The provided text focuses on demonstrating substantial equivalence to predicate devices rather than defining specific, quantifiable acceptance criteria. However, it does state an overall conclusion regarding the device's performance relative to the gold standard.

Study Details

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

   • Sample Size: 19 women, measuring 81 cycles.
   • Data Provenance: Prospective study. The country of origin is not explicitly stated, but the applicant and official correspondent are based in the UK and USA respectively, suggesting the study likely took place in one of these regions.

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

   • The document implies that "ultrasound" was used as the gold standard for ovulation detection. It does not specify the number or qualifications of experts involved in interpreting the ultrasound results and establishing this ground truth.

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

   • The document does not describe any specific adjudication method for the ground truth.

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

   • No MRMC comparative effectiveness study was done. This device is a standalone monitor for ovulation prediction, not an AI-assisted tool for human readers.

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

   • Yes, a standalone study was conducted. The clinical investigation directly assessed the performance of the OvuSense Fertility Monitor system (algorithm only) in detecting ovulation.

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

   • The ground truth used was ultrasound detection of ovulation ("gold standard detection of ovulation using ultrasound").

7. The sample size for the training set:

   • The text does not explicitly mention a separate "training set" or its sample size. The clinical investigation appears to be a validation study (test set) for the established algorithm.

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

   • Since a separate training set is not described, the method for establishing its ground truth is not provided. The algorithm's development or initial training phase is not detailed in this 510(k) summary.

Ask a specific question about this device

The DuoFertility Monitor is intended for measuring, and recording basal body temperature (BBT) as an aid in ovulation prediction to aid in conception (not to be used for contraception).

The DuoFertility system is a computerized basal body temperature thermometer with the following features:

• 1. A temperature Sensor with integrated data logger to monitor temperature throughout sleep and store the temperature readings
• 2. Measuring accuracy within +/- 0.05 deg C
• 3. Adhesive patches to hold the temperature Sensor against the users skin
• 4. Radiofrequency communications hardware to transmit the stored temperature data to a receiving device
• 5. Microprocessor based Reader to process and display temperature readings and fertility information.

The DuoFertility system is a computerized basal body temperature thermometer intended for measuring and recording basal body temperature (BBT) as an aid in ovulation prediction to aid in conception.

Here's an analysis of its acceptance criteria and the study that proves its performance:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Clinical Test Set Sample Size: Data from 21 menstrual cycles was analyzed. The number of individual subjects is not explicitly stated, but it would be at least 21 women if each provided only one cycle, or fewer women if some provided multiple cycles.
• Data Provenance: The data was collected through a prospective clinical study. The country of origin is not explicitly stated for the clinical study, but the submitter (Cambridge Temperature Concepts Ltd) is based in the United Kingdom.

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

The document does not mention the use of experts to establish ground truth for the clinical test set. The comparison was made against a predicate device (Lady-Comp), implying that the "ground truth" for ovulation prediction was derived from the performance of the predicate device, or implicitly, from the accepted method of BBT interpretation for ovulation as performed by both devices.

4. Adjudication Method

No adjudication method is described for the clinical test set. The "ground truth" for comparison was the performance of the predicate device, Lady-Comp.

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

No MRMC study was performed or described. This device is a direct measurement and interpretation system, not an AI-assisted diagnostic aid that human readers would use. The clinical study compared the device's performance to a predicate device, not human readers with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance study was done for the device's core functionality. The "Clinical tests" section describes the device comparing its temperature readings and derived ovulation prediction to a predicate device (Lady-Comp) without human intervention in the interpretation process of the DuoFertility system itself beyond the initial instructions for use. The device itself is designed to process and display fertility information.

7. Type of Ground Truth Used

• For temperature measurement accuracy, the ground truth was "known temperatures, by immersion in a calibrated, computer-controlled waterbath."
• For clinical performance (ovulation prediction), the performance of the Lady-Comp predicate device served as the comparative "ground truth." The study evaluated if DuoFertility was "at least equivalent in performance" to Lady-Comp.

8. Sample Size for the Training Set

The document does not specify a sample size for a training set. This suggests that the device's algorithm for ovulation prediction might be based on established physiological models of BBT, or if any machine learning was used, the training data details are not provided in this summary.

9. How Ground Truth for the Training Set Was Established

As no training set is described for a machine learning model, there is no information on how its ground truth was established. The device likely relies on conventional BBT interpretation rules rather than a learned model requiring a distinct training set with established ground truth.

Ask a specific question about this device

Lady-Comp® USA is intended for measuring and recording basal body temperature (BBT) as an aid in ovulation prediction to facilitate conception (not to be used for contraception).

Lady-Comp® USA is a computerized basal body temperature thermometer with the following functions:

1. Alarm clock function for measuring temperature at a consistent time.
2. Measuring accuracy within +/- 0.05°C (0.09°F).
3. Displaying the measured temperature.
4. Generating the measurement completion signal.
5. Memory Capacity of data for 180 days.
6. Transferring the stored data to an external instrument.

I am sorry, but the provided text does not contain detailed information about the acceptance criteria and the study that proves the device meets the acceptance criteria. It primarily focuses on the 510(k) summary for the Lady-Comp® USA device, including its description, intended use, and substantial equivalence to a predicate device.

The document states:

• Measuring accuracy within +/- 0.05°C (0.09°F). This is the only explicit performance characteristic mentioned that could be considered an acceptance criterion for the temperature measurement function. However, no study details are provided to demonstrate how this criterion was met.

There is no information regarding:

• A table of acceptance criteria and reported device performance.
• Sample sizes, data provenance, or study design for testing.
• Number of experts, qualifications, or adjudication methods for establishing ground truth.
• Multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance studies.
• Type of ground truth used (e.g., pathology, outcomes data).
• Sample size for the training set or how ground truth for the training set was established.

The core of the document is a regulatory submission demonstrating substantial equivalence to a predicate device, not a detailed performance study report.

Ask a specific question about this device

The Microlife Digital Basal Thermometer is a device intended for measuring, and aiding in the monitoring and tracking of basal body temperature (BBT) as an aid in ovulation prediction to aid in conception (not to be used for contraception).

The Microlife Digital Basal Thermometer, which uses the Basal Temperature method can be used for helping in family planning in healthy adults by understanding their menstrual cycle and ovulation and interpreting basal temperature changes. This Thermometer provides easy, quick and highly accurate readings over the body temperature range. The body temperature is measured by the thermistor (inside the probe tip) and displayed as numbers on the LCD (liquid crystal diplay) through microprocessor of IC. The basic principle of this thermometer is that change of thermistor resistance, caused by changes of temperature, are converted to changes of frequency of R-C oscillator circuit. Therefore, temperature can be given by measuring the frequency of oscillator. For a given time period by applying to R-C oscillator circuit, changes of temperature will correspond to changes of pulse number.

The provided text describes the Microlife Digital Basal Thermometer and its 510(k) submission, confirming its substantial equivalence to a predicate device. However, it does not contain the detailed acceptance criteria or the specifics of a study that proves the device meets those criteria in the way requested by the prompt.

The document states:

• "Controlled human clinical studies were conducted using the Microlife Digital Basal Thermometer MT1921 for measurement and accuracy."
• "Compliance to applicable voluntary standards includes ASTM E1112, as well as IEC60601-1 and IEC60601-1-2 requirements."
• "Guidance documents included the "FDA Guidance on the Content of Premarket Notification 510(K) Submissions for Clinical Electronic Thermometers."

While these statements indicate that testing was performed and standards were met, the actual acceptance criteria values and the results of those tests are not provided in the summary. Therefore, directly filling out most of the requested fields is not possible from the given input.

Based on the provided text, here's what can be extracted and what cannot:

1. Table of acceptance criteria and the reported device performance:

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

• Sample size: Not specified.
• Data provenance: "Controlled human clinical studies were conducted," but country of origin and retrospective/prospective nature are not specified.

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

• Not specified. The document does not describe the establishment of a ground truth by experts for the clinical studies.

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

• Not specified.

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/Not done. This device is a thermometer, not an AI-assisted diagnostic tool that would involve "human readers" or "AI improvement." The study focused on the accuracy of the device itself.

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

• This device is a standalone electronic thermometer. The "controlled human clinical studies" would have assessed the device's performance in human subjects, implying a standalone assessment of the device's ability to measure temperature.

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

• Given it's a thermometer, the ground truth for accuracy would typically be a reference thermometer or a calibrated temperature standard against which the device's readings are compared. This is implied by "measurement and accuracy" testing and compliance with ASTM E1112 (Standard Specification for Electronic Thermometers for Intermittent Determination of Patient Temperature).

8. The sample size for the training set:

• Not applicable/Not specified. This device is a hardware-based electronic thermometer, not an AI/ML algorithm that requires a separate training set. The "human clinical studies" are for validation/testing, not training.

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

• Not applicable. (See #8)

Ask a specific question about this device

For measuring, and recording basal body temperature(BBT) as an aid in ovulation prediction to aid in conception (not to be used for contraception).

This device is the clinical thermometer with memory the following functions.
(1) Alarm clock function for measuring temperature at constant time.
(2) Measuring accuracy within +/-0.05°C(between 35.00°C and 38.00°C) +/-0.1°C(between 34.00°C and 35.00°C, 38.00°C and 40.00°C)
(3) Displaying the measured temperature precisely, generating the measurement completion signal(buzz) and warning of a measuring error by buzzer, in case happened.
(4) Memory capacity of data for 6 menstrual cycles or 210 days.
(5) Displaying the measured temperature value in graph.
(6) Transferring the stored data to an external instrument.

The provided text is a 510(k) summary for the "Petit Sophia, Computerized Basal Body Thermometer, Model No. BT-14E". It focuses on establishing substantial equivalence to a predicate device rather than presenting a detailed study proving the device meets specific acceptance criteria through clinical trials. Therefore, much of the requested information regarding acceptance criteria and a study proving performance cannot be directly extracted as it's not present in this type of submission.

However, I can extract the specific performance characteristics mentioned and the basis for substantial equivalence.

Here's the information based on the provided text, with N/A indicating information not found in the document:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The acceptance criteria for the "Petit Sophia" are primarily based on its substantial equivalence to the predicate device, "L-Sophia, BT-01," described as having "the same general design and performance characteristics." The explicitly stated performance characteristics are a description of the device's features, implicitly suggesting they meet the requirements for a basal body thermometer.

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 (Test Set): N/A (The document does not detail a specific test set or clinical study for the Petit Sophia beyond confirming its performance characteristics through comparison to a predicate device.)
• Data Provenance: N/A

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• N/A (No information on ground truth establishment for a test set is provided as the submission relies on substantial equivalence.)

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

• N/A

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

• N/A (This device is a basal body thermometer, not an AI-assisted diagnostic tool for which an MRMC study would be relevant.)

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

• N/A (This device is a physical thermometer with memory and display functions; "standalone" algorithm performance is not applicable in this context.)

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

• N/A (The document indicates the device's performance is based on its technological characteristics and intended use being similar to the predicate device, rather than a new ground-truth validation study.)

8. The sample size for the training set

• N/A (No training set is mentioned for this type of device.)

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

• N/A

Summary of Device Acceptance and Study Type:

The acceptance of the "Petit Sophia, Computerized Basal Body Thermometer" (K021978) by the FDA is based on a 510(k) Premarket Notification demonstrating substantial equivalence to a legally marketed predicate device, "Nishitomo, L-Sophia, BT-01 (K 901512)".

The document explicitly states: "The Petit Sophia Basal Body Thermometer has the same general design and performance characteristics as the predicate device 'L-Sophia', which is manufactured by the same company Nishitomo Co., Ltd. The main difference is the physical size, shape, weight and temperature display. The Petit Sophia Basal Body Thermometer has the same intended use, general design and incorporates similar materials and components, hence should therefore raise no new questions of safety and effectiveness."

Therefore, the "study" proving the device meets acceptance criteria (which are primarily alignment with the predicate device's characteristics and regulatory standards for clinical thermometers) is not a new clinical trial or performance study. Instead, it is a comparison and justification that the new device's specifications (e.g., accuracy, memory, display) are equivalent to those of the predicate device, which was previously cleared by the FDA. The submission asserts that because of this substantial equivalence, the "Petit Sophia" raises no new questions of safety and effectiveness.

Ask a specific question about this device

Ask a specific question about this device