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The Tyto Insights for Rhonchi Detection is a prescription-use artificial intelligence (AI) enabled decision support software system used in the evaluation of lung sounds in adults and pediatrics (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA 510k cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Rhonchi" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional's advice is required to understand the meaning of the Tyto Insights for Rhonchi Detection result. Healthcare providers should consider the device result in conjunction with recording and other relevant patient data.

The Tyto Insights for Rhonchi Detection is a web-based AI-enabled software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Rhonchi is detected within the recorded sound data. The Tyto Insights for Rhonchi Detection Software is intended to process recordings from the FDA-cleared compatible Tyto Stethoscope (Tyto Stethoscope, K181612). The acquisition of the acoustic data (recordings) is carried out by a professional user in a clinical environment or by a lay- user in a non-medical environment, in compliance with the labeling of the Tyto Stethoscope. The system is composed of the following sub-systems:

1. The Tyto Insights for Rhonchi Detection Application Server (APS) communicates with the Tyto Insights for Rhonchi Detection Algorithm Server (ALS) and implements an application programming interface (API) for communication with the telehealth server.

2. The Tyto Insights for Rhonchi Detection Algorithm Server (ALS) receives an audio file as input and returns an analysis result of positive or negative regarding whether a Rhonchi was detected as output.

3. The Tyto Insights for Rhonchi Detection Web Server (WBS) provides a graphic indication whether a Rhonchi is detected in the recording. It can be utilized both in the patient and clinician side.

All the software subsystems (servers and storage) are hosted in the cloud and communicate through IP network.

The recordings from the compatible Tyto Stethoscope (K181612) are sent by the third-party point of care app to the clinician app through the telehealth server. The telehealth server sends the set of the lung sound recordings to the Tyto Insights for Rhonchi Detection web server using its dedicated API. The AI enabled algorithm runs automatically and returns a response for each audio file with the indication of rhonchi to the telehealth server which sends a response to both the clinician side and the patient side.

Here's a breakdown of the acceptance criteria and study details for the Tyto Insights for Rhonchi Detection, based on the provided FDA 510(k) clearance letter:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

Study Details

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

• Sample Size: 400 recordings (100 Rhonchi positive and 300 negative) from 400 patients.
• Data Provenance: Retrospective validation dataset composed of recordings obtained from the real-world use of the Tyto Care FDA-cleared compatible Tyto Stethoscope (K181612). The country of origin is not explicitly stated, but Tyto Care Ltd. is based in Israel, suggesting possible international data acquisition or a mix.

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

• Number of Experts: Three.
• Qualifications of Experts: Blinded experienced Pulmonologists. Specific years of experience are not mentioned.

4. Adjudication method for the test set

• Adjudication Method: Majority vote (2+1) of the three blinded Pulmonologists. The binary ground truth was determined if at least two out of the three experts agreed.

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

• An MRMC study was performed comparing the device's AUC to that of clinical readers (non-Pulmonologists).
• Effect Size: The difference in AUC (Tyto Insights for Rhonchi Detection – clinical readers) was 0.16 (0.13–0.21). This indicates that the device itself performed better than the clinical readers (non-Pulmonologists) in detecting rhonchi, establishing non-inferiority with a positive margin. The study did not evaluate how much human readers improve with AI assistance (i.e., human-in-the-loop performance), but rather compared standalone AI performance to standalone human reader performance.

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

• Yes, a standalone performance evaluation was done. Table 3 explicitly provides "The stand-alone accuracy of the Tyto Insights for Rhonchi Detection" with Sensitivity, Specificity, PPV, and NPV.

7. The type of ground truth used

• Type of Ground Truth: Expert consensus. Specifically, a majority vote from three experienced Pulmonologists.

8. The sample size for the training set

• The document does not explicitly state the sample size for the training set. It only mentions the retrospective validation dataset of 400 recordings. The PCCP section mentions "Re-training of the ML model with additional data," which implies a training set was used to develop the initial model, but its size is not provided in this document.

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

• The document does not explicitly describe how the ground truth for the training set was established. It only details the ground truth establishment method for the validation dataset (majority vote by three pulmonologists). It's reasonable to infer a similar method might have been used for the training data, but it's not stated.

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The Tyto Insights for Crackles Detection is an over-the-counter artificial intelligence (AI) enabled decision support software system used in the evaluation of lung sounds in adults and pediatrics (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA 510k cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Crackle" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional’s advice is required to understand the meaning of the Tyto Insights for Crackles Detection result. Healthcare providers should consider the device result in conjunction with recording and other relevant patient data.

The Tyto Insights for Crackles Detection is a web-based (AI) enabled software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Crackle is detected within the recorded sound data. The Tyto Insights for Crackles Detection Software is intended to process recordings from the FDA-cleared compatible Tyto Stethoscope (Tyto Stethoscope, K181612). The acquisition of the acoustic data (recordings) is carried out by a professional user in a clinical environment or by a lay- user in a non-medical environment, in compliance with the labeling of the Tyto Stethoscope. The system is composed of the following sub-systems:

• The Tyto Insights for Crackles Detection Application Server (APS) communicates with 1. the Tyto Insights for Crackles Detection Algorithm Server (ALS) and implements an application programming interface (API) for communication with the telehealth server.
• The Tyto Insights for Crackles Detection Algorithm Server (ALS) receives an audio file 2. as input and returns an analysis result of positive or negative regarding whether a Crackles was detected as output.
• The Tyto Insights for Crackles Detection Web Server (WBS) provides a graphic 3. indication whether a Crackles is detected in the recording. It can be utilized both in patient and clinician side.
  All the software subsystems (servers and storage) are hosted in the cloud and communicate through IP network.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) summary for "Tyto Insights for Crackles Detection":

Product Information:

• Trade/Device Name: Tyto Insights for Crackles Detection
• Regulation Number: 21 CFR 868.1900
• Regulation Name: Diagnostic Pulmonary-Function Interpretation Calculator
• Regulatory Class: Class II
• Product Code: PHZ
• Intended Use/Indications for Use: An over-the-counter AI-enabled decision support software system for evaluating lung sounds (adults and pediatrics 2+ years) recorded by the compatible Tyto Stethoscope. It identifies recordings where "Crackle" is suspected. It is not intended to detect other abnormal/normal lung sounds. Requires a licensed healthcare professional's advice to interpret results, which should be considered with other patient data.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The acceptance criteria for Sensitivity and Specificity (LCI > 0.6279 and LCI > 0.9668, respectively) are specifically laid out in the "Predetermined Change Control Plan (PCCP)" section for modifications to the device. For the initial submission, the primary endpoint focused on the non-inferiority of the device's AUC compared to clinical readers. The reported standalone sensitivity and specificity are actual performance metrics from the validation study.

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

• Test Set Sample Size: 446 recordings (120 Crackles positive, 326 Crackles negative). This corresponded to a total of 445 patients.
• Data Provenance: Retrospective validation dataset. Recordings were obtained from the real-world use of the Tyto Care FDA-cleared compatible Tyto Stethoscope (K181612). The document does not specify the country of origin for the data.

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

• Number of Experts: Three (3) blinded experienced Pulmonologists.
• Qualifications: "Experienced Pulmonologists" are specified. Further details on years of experience or specific board certifications are not provided in the summary.

4. Adjudication Method for the Test Set

• Adjudication Method: Binary ground truth was determined by a majority vote of the three blinded Pulmonologists. This is a form of 3+ Consensus.

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

• MRMC Study Done?: A comparative effectiveness study was done comparing the device (AI) performance to "clinical readers" (Physicians non-Pulmonologists). However, this was an AI-only vs. human-only comparison, not a "human reading with AI assistance vs. human reading without AI assistance" MRMC study.
• Effect Size of Human Improvement with AI: This study did not assess how much human readers improve with AI assistance. It directly compared the AI algorithm's performance to human clinical readers.
  • Device AUC: 0.97 (0.95–0.98)
  • Clinical Readers AUC: 0.77 (0.73–0.8)
  • Difference in AUC (Device - Clinical Readers): 0.2 (0.17–0.23). This indicates the AI algorithm significantly outperformed the clinical readers in this specific comparison, establishing non-inferiority (and superiority) based on the defined margin.

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

• Standalone Study Done?: Yes.
• Performance Metrics:
  • Sensitivity: 0.72 (0.63-0.79)
  • Specificity: 0.99 (0.97–1.00)
  • Positive Predictive Value (PPV): 0.63 (0.4-0.87)
  • Negative Predictive Value (NPV): 0.99 (0.98-0.99)

7. The Type of Ground Truth Used

• Type of Ground Truth: Expert Consensus. Specifically, a majority vote of three blinded experienced Pulmonologists on the presence or absence of "Crackle" in the lung sound recordings.

8. The Sample Size for the Training Set

• The document does not specify the exact sample size for the training set. It mentions that the device utilizes a CRNN (Convolutional Recurrent Neural Network) model and that "Each network is trained based on the target clinical class." However, it only provides details for the retrospective validation dataset.

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

• The document does not explicitly describe how the ground truth for the training set was established. It primarily focuses on the ground truth establishment for the validation set used for performance evaluation. It's generally assumed that similar expert-driven annotation methods would be used for training data, but this is not detailed in the provided summary.

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The Tyto Insights for Wheeze Detection is an over the-counter artificial intelligence (Al) enabled decision support software system used in the evaluation of lung sounds in adults and pediatrics (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Wheeze" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional's advice is required to understand the meaning of the Tyto Insights for Wheeze Detection result. Healthcare providers should consider the device result in conjunction with recording and other relevant patient data.

The Tyto Insights for Wheeze Detection is a web-based (AI) enabled software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Wheeze is detected within the recorded sound data.

The Tyto Insights for Wheeze Detection Software is intended to process recordings from the FDA-cleared compatible Tyto Stethoscope (Tyto Stethoscope, K181612). The acquisition of the acoustic data (recordings) is carried out by a professional user in a clinical environment or by a lay- user in a non-medical environment, in compliance with the labeling of the Tyto Stethoscope. The system is composed of the following sub-systems:

• 1. The Tyto Insights for Wheeze Detection Application Server (APS) communicates with the Tyto Insights for Wheeze Detection Algorithm Server (ALS) and implements an application programming interface (API) for communication with the telehealth server.
• 2. The Tyto Insights for Wheeze Detection Algorithm Server (ALS) receives an audio file as input and returns an analysis result of positive or negative regarding whether a wheeze was detected as output.
• The Tyto Insights for Wheeze Detection Web Server (WBS) provides a graphic 3. indication whether a wheeze is detected in the recording. It can be utilized both in patient and clinician side.

All the software subsystems (servers and storage) are hosted in the cloud and communicate through IP network.

Here's a breakdown of the acceptance criteria and study details for the "Tyto Insights for Wheeze Detection" device, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" as a pass/fail threshold, but rather focuses on comparing the device's performance to its predicate and demonstrating non-inferiority. The key performance metrics are sensitivity, specificity, and Area Under the Curve (AUC).

Conclusion regarding acceptance criteria: The device met the primary endpoint of non-inferiority to the predicate device based on AUC, as the lower bound of the 95% CI for the difference in AUCs (0.0289) was well above the non-inferiority margin of -0.05.

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

• Sample Size for Test Set: 371 recordings, corresponding to 359 patients. (86 recordings were Wheeze positive and 285 negative).
• Data Provenance: Retrospective validation dataset sourced from real-world use of the FDA cleared compatible Tyto Stethoscope. The country of origin is not explicitly stated, but Tyto Care Ltd. is based in Israel.

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

• Number of Experts: Three blinded experienced Pulmonologists.
• Qualifications of Experts: Described as "experienced Pulmonologists." Specific details like years of experience are not provided.

4. Adjudication Method for the Test Set

• Adjudication Method: Binary ground truth was determined by a majority vote of the three blinded Pulmonologists. This implies a "3+1" approach where if at least two out of three experts agreed on the presence or absence of wheeze, that was considered the ground truth.

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

• There is no indication of a Multi-Reader Multi-Case (MRMC) comparative effectiveness study being performed with human readers with and without AI assistance. The study focused on the stand-alone performance of the AI algorithm and its non-inferiority to a predicate device's algorithm, not on the improvement of human readers with AI assistance.

6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) was Done

• Yes, a standalone study was done. The performance evaluation section explicitly states: "For the characterization of the stand-alone accuracy, the automated binary result of the software has been compared to ground truth and specificity and sensitivity were calculated." and "The primary end point was area under the Curve (AUC) for the detection of wheezes by the proposed device compared to the TytoCare Lung Sounds Analyzer (K221614)".

7. The Type of Ground Truth Used

• Type of Ground Truth: Expert consensus. Specifically, the binary ground truth was determined by a majority vote of three blinded experienced Pulmonologists.

8. The Sample Size for the Training Set

• The sample size for the training set is not explicitly provided in the document. The text states: "The AI Algorithm was trained with recordings acquired by the real-world use of the compatible Tyto Stethoscope."

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

• The document states that the AI algorithm was "trained with recordings acquired by the real-world use of the compatible Tyto Stethoscope." However, it does not explicitly detail how the ground truth for this training set was established. It can be inferred that a similar expert labeling process might have been used, but this is not confirmed in the provided text.

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The TytoCare Lung Sounds Analyzer is an over-the-counter decision support software system used in the evaluation of lung sounds in adults and children (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Wheeze" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional's advice is required to understand the meaning of the TytoCare Lung Sounds Analyzer result. Healthcare provider should consider the device result in conjunction with recording and other relevant patient data.

The TytoCare Lung Sounds Analyzer is a web-based software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Wheeze is detected within the recorded sound data.

The TytoCare Lung Sounds Analyzer Software is intended to process recordings from the FDA-cleared compatible Tyto Stethoscope (Tyto Stethoscope, K181612). The acquisition of the acoustic data (recordings) is carried out by a professional user in a clinical environment or by a lay- user in a non-medical environment, in compliance with the labeling of the Tyto Stethoscope.

The system is composed of the following sub-systems:

• 1. The TytoCare Lung Sounds Analyzer Application Server (APS) communicates with the TytoCare Lung Sounds Analyzer Algorithm Server (ALS) and implements an application programming interface (API) for communication with the telehealth server.
• 2. The TytoCare Lung Sounds Analyzer Algorithm Server (ALS) receives an audio file as input and returns an analysis result of positive or negative regarding whether a wheeze was detected as output.
• 3. The TytoCare Lung Sounds Analyzer Web Server (WBS) provides a graphic indication whether a wheeze is detected in the recording. It can be utilized both in patient and clinician side.

All the software subsystems (servers and storage) are hosted in the cloud and communicate through IP network.

Here's a breakdown of the acceptance criteria and the study details for the TytoCare Lung Sounds Analyzer, based on the provided document:

Acceptance Criteria and Device Performance

Study Details

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

   • Sample Size: 371 recordings (86 Wheeze positive, 285 negative) from 359 patients.
   • Data Provenance: Retrospective validation dataset of Tyto Stethoscope recordings sourced from real-world use of the Tyto Care FDA cleared Tyto Stethoscope. The dataset included recordings from patients with known pre-existing conditions (COPD or Asthma) (7.28%).

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

   • Number of Experts: Three.
   • Qualifications: Blinded experienced Pulmonologists. Specific years of experience are not mentioned.

3. Adjudication method for the test set:

   • Adjudication Method: Majority vote of the three blinded Pulmonologists ("binary ground truth was determined by majority vote of these three Pulmonologists"). This is a 3-reader consensus method.

4. If a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done:

   • Yes, a comparative study was done. The clinical performance section compares the device's AUC to that of "clinical readers (Physicians non-Pulmonologists)."
   • Effect size of how much human readers improve with AI vs. without AI assistance: The study primarily focused on the device's accuracy being non-inferior to human readers, rather than human readers with AI assistance. The reported AUC for the device (0.91) was higher than the AUC for clinical readers (0.83), with a difference of 0.09. This suggests the device performs better than the un-assisted clinical readers. The study did not test human readers with AI assistance, so an effect size for human improvement with AI assistance cannot be determined from this document.

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

   • Yes, a standalone accuracy assessment was performed. Table 3 explicitly presents "The stand-alone accuracy of the TytoCare Lung Sounds Analyzer" with sensitivity and specificity results.

6. The type of ground truth used:

   • Type of Ground Truth: Expert consensus. Specifically, a majority vote of three blinded experienced Pulmonologists.

7. The sample size for the training set:

   • The document does not provide the sample size for the training set. It only mentions the validation dataset.

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. It only describes the ground truth establishment for the validation dataset.

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The Tyto Thermometer is a non - contact clinical infrared thermometer intent determination of human body temperature from the center of the forehead on people of all ages. The Tyto Thermometer is intended for use by both adult lay users and clinicians. It can be used both at home and in clinic environments.

The Tyto Thermometer is a non-contact infrared thermometer that enables measuring of the human body temperature for persons of all ages. The device is a hand-held infrared thermometer that, when positioned within 2 inches of a patient's forehead, measures the infrared energy emitted from the surface of the skin and converts it to a Core body temperature scale (Celsius, Fahrenheit) as represented on the oral body site. The device is designed for use by professional as well as lay users in clinical or nonclinical environments. The device can optionally be connected wirelessly to a user's mobile phone for use with a dedicated app (TytoCare App). Measurement results are displayed on the device LCD screen and in parallel on the mobile phone. Results of temperature recordings can be stored on the Tyto Server.

The Tyto Thermometer is a non-contact infrared thermometer intended for intermittent determination of human body temperature from the center of the forehead on people of all ages.

Here's an analysis of its acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: 124 subjects.
  • Group 1: Up to 1 year (Sub-group 1a: up to 3 months, Sub-group 1b: 3 months up to 1 year)
  • Group 2: 1 to 5 years
  • Group 3: Older than 5 years
• Data Provenance: Not explicitly stated regarding country of origin. The study was conducted in accordance with ASTM E1965-98 (R 2009) and ISO 80601-2-56 (2009), which are international standards for clinical thermometers. The study is described as a "clinical validation study," implying it was prospective data collection.

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

This information is not provided in the given text. The ground truth was established by a "reference gold standard Welch Allyn contact thermometers," but details about the operators or experts using these reference thermometers are not included.

4. Adjudication Method for the Test Set

This information is not provided in the given text.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned or performed as part of this submission for the clinical validation. The study focused on the device's accuracy and repeatability against a reference standard, not on comparing human reader performance with and without AI assistance.

6. Standalone (Algorithm Only) Performance Study

The clinical validation study described is a standalone performance study of the Tyto Thermometer itself, measuring its accuracy and repeatability against a reference standard. The device has an "infrared sensor" and uses "predictive algorithms to estimate the body temperature," which constitutes the algorithm-only performance being evaluated.

7. Type of Ground Truth Used

The ground truth for the clinical validation study was established using reference gold standard Welch Allyn contact thermometers.

8. Sample Size for the Training Set

The document does not specify a separate training set or its sample size. The "predictive algorithms" are mentioned as part of the device's functioning, implying they were developed and potentially trained, but details of this process are not provided in the 510(k) summary.

9. How Ground Truth for Training Set Was Established

This information is not provided in the document.

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The Tyto Stethoscope is an electronic stethoscope that enables transmission of auscultation sound data, whereby a clinician at one location on an IP network can listen to the auscultation sounds of a patient on site or at a different location on the IP network with the signal carried on an IP connection between the two locations. The Tyto Stethoscope is intended to be used by professional users in a clinical environment or by lay users in a nonclinical environment. The device is for medical diagnostics purposes only. The device is not intended for self-diagnosis.

The Tyto Stethoscope (OTC) is designed for use by professional as well as lay users in clinical or non-clinical environments. It enables four types of stethoscope exams: Heart, Lungs, Heart Rate and Audio (Audio is for clinician only). The operation process of the Tyto Stethoscope uses four (4) primary functional elements: (1) The Tyto Stethoscope (composed of a Stethoscope Tip and a Base Unit – Tyto Device and supported with proprietary software). (2) A mobile device (e.g., a smartphone, not part of the Tyto Stethoscope device, not supplied by TytoCare, on which the proprietary TytoCare App is running), (3) The Tyto Server platform (composed of server hardware not part of the Tyto Stethoscope device, not supplied by TytoCare, on which the proprietary server software is running). (4) A clinician receiving platform located in a clinical environment (e.g., a PC at the clinic, not part of the Tyto Stethoscope device, not supplied by TytoCare, on which the proprietary Clinician App is running).

The provided text is a 510(k) summary for the Tyto Stethoscope (OTC). It mostly focuses on establishing substantial equivalence to predicate devices and does not contain detailed information about specific acceptance criteria or a study that rigorously proves the device meets those criteria in a quantitative sense as typically seen for AI/ML devices.

However, based on the general information provided about performance testing, we can infer some "acceptance criteria" through the lens of device specifications and the types of tests mentioned.

Here's an attempt to answer the questions based on the available text, acknowledging that much of the detailed study information is not present in this summary.

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

Based on the provided text, the "acceptance criteria" are broad and relate to meeting specifications and demonstrating similar performance and safety to predicate devices. The text doesn't provide specific quantitative "reported device performance" metrics against numeric acceptance thresholds, as it relies on the device being technologically identical to a previously cleared device.

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

The document states, "A testing plan was developed and performed in order to verify that the Tyto Stethoscope (K160401) meets its specifications and demonstrates, based on comparable characteristics, similar performance and safety as compared to its predicate devices". It then lists categories of performance testing.

• Sample Size for Test Set: Specific sample sizes for any of the listed tests (e.g., stethoscope performance, pseudo clinical, heart rate measurement) are not provided in this summary.
• Data Provenance: Not explicitly stated. Given the device is an electronic stethoscope and the context is regulatory, it's highly likely that the performance testing involved simulated scenarios, physical measurements, and potentially human subjects for usability or sound perception. The original clearance (K160401) would contain more details.

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 510(k) summary. The summary refers to "pseudo clinical" and "stethoscope performance" testing, which would typically involve expert assessment, but no details are given.

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

This information is not provided in the 510(k) summary.

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

The Tyto Stethoscope (OTC) is described as an electronic stethoscope for transmitting auscultation sounds to a clinician. It enables the transmission of raw sound data for human clinicians to interpret. There is no indication in this summary that it incorporates AI for interpretation or diagnosis, nor is there any mention of an MRMC comparative effectiveness study involving AI assistance.

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

Since there is no mention of an AI algorithm performing diagnosis or interpretation, this question is not applicable. The device's function is to transmit data for a human clinician.

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

Given the device's function (electronic stethoscope for sound transmission and heart rate), the "ground truth" for performance testing would likely involve:

• For Stethoscope Performance: Comparison to established acoustic standards, reference stethoscopes, or expert audiologist/physician assessments of sound quality.
• For Heart Rate Measurement: Comparison to ECG, manual palpation, or other validated heart rate measurement devices.
• For Pseudo Clinical: Likely comparison to expert clinical assessment of scenarios or validated simulated patient sounds.

However, the specific type of ground truth used for each test is not detailed in this summary.

8. The sample size for the training set

The provided text describes performance testing for an electronic stethoscope, not an AI/ML algorithm that requires training data in the traditional sense. Therefore, the concept of a "training set" as it relates to AI models is not applicable here. The device's functionality is based on hardware and software for sound acquisition and transmission, not data-driven learning.

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

As explained in point 8, the concept of a "training set" for an AI/ML algorithm is not applicable to this device as described.

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The Tyto Stethoscope is an electronic stethoscope that enables transmission of auscultation sound data, whereby a clinician at one location on an IP network can listen to the auscultation sounds of a patient on site or at a different location on the IP network with the signal carried on an IP connection between the two locations. The Tyto stethoscope is intended for use by professional users in a clinical environment or in conjunction with patients or lay users in a non-clinical environment.

The Tyto Stethoscope is designed for use by professional as well as lay users in clinical or nonclinical environments. It enables four types of stethoscope exams: Heart, Lungs, Heart Rate and Audio (Audio is for clinician only). The operation process of the Tyto Stethoscope uses four (4) primary functional elements:

• (1) The Tyto Stethoscope (composed of a Stethoscope Tip and a Base Unit and supported with proprietary software)
• (2) A mobile device (e.g., a smartphone, not part of the Tyto Stethoscope device, not supplied by TytoCare, on which the proprietary TytoCare App is running),
• (3) The Tyto Server platform (composed of server hardware not part of the Tyto Stethoscope device, not supplied by TytoCare, on which the proprietary server software is running)
• (4) A clinician receiving platform located in a clinical environment (e.g., a PC at the clinic, not part of the Tyto Stethoscope device, not supplied by TytoCare, on which the proprietary Clinician App is running).
  Two operational flows are optional for using the Tyto Stethoscope: store-and-forward flow and on-line exam flow. Both flows are essentially similar and share the same fundamental steps: performing one or more measurements using the Tyto Stethoscope, recording the data and sending to a clinician, review of the recorded measurements by the clinician, and user receiving a written summary from the clinician presenting his/her assessment and/or recommendations. While in the store-and-forward flow the user can perform the measurements and send the recorded data to the clinician whenever convenient for him/her, an on-line flow may be executed only when also the clinician is available on-line.

This document provides information about the Tyto Stethoscope, for which a 510(k) premarket notification was reviewed by the FDA. The document summarizes the device's intended use, description, and performance testing, but it does not explicitly state specific acceptance criteria or provide a detailed study that proves the device meets those criteria in the format requested.

Therefore, many of the requested fields cannot be directly extracted from the provided text. However, based on the information given, here's what can be inferred or stated:

Missing Information:
The provided document details the FDA's clearance for the Tyto Stethoscope but does not include:

• A table of specific acceptance criteria and detailed reported device performance.
• Sample size used for the test set or its provenance.
• Number of experts, their qualifications, or adjudication methods for establishing ground truth.
• Whether an MRMC comparative effectiveness study was done or effect size.
• Whether a standalone algorithm-only performance study was done.
• The sample size for the training set or how its ground truth was established.

Information Extracted from the Document:

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

   • Acceptance Criteria: Not explicitly stated in a tabular format. The document generally implies that the device should function as expected and be as safe and effective as predicate devices. The performance testing section lists categories of tests performed.
   • Reported Device Performance: The document states, "Test results indicated that the Tyto Stethoscope functions as expected and is as safe and effective as its predicate devices for its intended use." No specific quantitative performance metrics are provided.

2. Sample size used for the test set and the data provenance: Not mentioned in the provided text.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned in the provided text.

4. Adjudication method for the test set: Not mentioned in the provided text.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not mentioned in the provided text. The device is a "Stethoscope," not an AI diagnostic tool in the sense of image interpretation assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The Tyto Stethoscope is an electronic stethoscope that records and transmits audio. Its "performance testing" likely refers to the fidelity of audio capture, heart rate measurement, and wireless transmission, as opposed to an AI algorithm making a diagnosis. The document does not describe a standalone algorithm-only performance as might be applicable to an AI diagnostic device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not mentioned in the provided text. The testing seems to focus on functional performance (e.g., stethoscope performance, heart rate measurement) and safety rather than diagnostic accuracy against a disease ground truth.

8. The sample size for the training set: Not mentioned in the provided text.

9. How the ground truth for the training set was established: Not mentioned in the provided text.

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