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The eKuore Stethoscope Touch is intended to be used as a part of a physical assessment of a patient by healthcare professionals for diagnostic decision support in clinical settings.

The eKuore Stethoscope Touch is intended for use on pediatric and adult patients. It can electronically filter and transfer sounds to a compatible software application.

It can be used to record heart sounds and cardiac murmurs, bruits, respiratory sounds, and abdominal sounds during physical examination in normal patients or those with suspected diseases of the cardiac, vascular, pulmonary or abdominal organ systems.

eKuore Stethoscope Touch is formed by eKuore Stethoscope Touch device, eKuore Medical Devices App and eKuore Touch Android Engine.

The eKuore Stethoscope Touch device introduces three different models:

• . ES001 is the basic version of the electronic stethoscope for general purposes.
• . ES002 is an electronic stethoscope designed for people with hearing problems and enable hearing aids connection.
• ES003 is an electronic stethoscope that can connect to third-party software ● using an Android Library.

The primary purpose of the eKuore Stethoscope Touch device is to detect and amplify heart, lung, arteries, veins, and internal sounds using selective frequency organ ranges.

The design of eKuore Stethoscope Touch lets the user change the chestpiece attached between different sizes depending on the patient to be auscultated.

The primary purpose of the eKuore Medical Devices App is to get the acoustic signals from the eKuore Stethoscope Touch device. Once the device is turned on, the smartphone/tablet could detect a Bluetooth device.

After the connection, the eKuore Medical Devices App displays the acoustic signal as a phonogram in real-time, on the monitor screen, there is a record button. When it is pressed, the recording start, a record maximum duration of 30 seconds is defined. To stop the record, the recording button must be pressed again. Recordings are stored in *.wav file format in the internal memory of the connected smartphone/tablet. Each recording is stored named with the date and time of the moment of the record.

eKuore Medical Devices App has a management screen where it is possible to play, remove and edit a recording. Only the length and the name of the record file could be edited. Also, the eKuore Medical Devices App lets the user share the records.

eKuore Touch Android Engine enable third party companies to connect eKuore Stethoscope Touch model ES003 to obtain the audio from the device and use it in their own software. Audio is transmitted without modifications or processing.

The provided text describes a 510(k) premarket notification for the eKuore Stethoscope Touch. This submission seeks to demonstrate the device's substantial equivalence to a legally marketed predicate device (eKuore Pro Series, K203007).

The document details the device's purpose, characteristics, indications for use, and a comparison to the predicate device. However, it does not contain specific acceptance criteria or the details of a study proving the device meets those criteria, as typically seen with performance metrics like sensitivity, specificity, or F1-score for AI-driven devices.

Instead, the submission focuses on demonstrating equivalence in terms of intended use, technological characteristics, and compliance with general medical device standards. The "study" mentioned is a "Summary discussion of non-clinical data," which outlines various tests and standards met, rather than a clinical performance study with predefined acceptance criteria for diagnostic accuracy.

Therefore, many of the requested items cannot be extracted directly from the provided text.

Here's a breakdown of what can be inferred or explicitly stated:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not explicitly provided in the format of acceptance criteria and performance metrics for diagnostic accuracy. The document states "Device signal acquisition accuracy and acoustic transmission disturbance have been evaluated successfully, presenting in all devices with similar acoustic characteristics" as a general outcome of non-clinical testing. This indicates performance was compared to the predicate, implying similar performance is the "acceptance criterion" for these aspects, but no quantitative thresholds are given.

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

• Sample size for test set: Not specified.
• Data provenance: Not specified (since it's a non-clinical "acoustic performance comparison" rather than a clinical study with patient data).

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

Not applicable. The study mentioned is an "acoustic performance comparison" and non-clinical testing, not a diagnostic accuracy study requiring expert-established ground truth.

4. Adjudication method for the test set

Not applicable. No expert-driven ground truth establishment or adjudication process is described for this non-clinical comparison.

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

No, an MRMC comparative effectiveness study was not done. The eKuore Stethoscope Touch is an electronic stethoscope that facilitates sound recording and transfer, but it is not explicitly stated to be an AI-assisted diagnostic device that would involve "human readers improve with AI vs without AI assistance." Its indication is for "diagnostic decision support," but this appears to be through improved sound quality and digital record-keeping rather than an AI interpretation. The document explicitly focuses on demonstrating substantial equivalence to a predicate electronic stethoscope through non-clinical performance and safety data.

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

Not applicable. As noted above, the device is an electronic stethoscope producing amplified and filtered sounds, and it's not described as having a standalone diagnostic algorithm for interpretation without human intervention. The "eKuore Medical Devices App" displays the acoustic signal (phonogram), allows recording, and basic editing/sharing, but not AI-driven interpretation.

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

Not applicable. The "acoustic performance comparison" for the non-clinical data would likely compare the device's output to a known, calibrated acoustic standard or the output of the predicate device, not a diagnostic ground truth like pathology for AI performance evaluation.

8. The sample size for the training set

Not applicable. The document does not describe the development of an AI algorithm or a training set for machine learning.

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

Not applicable. No AI algorithm or training set is described.

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