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SonoMe and SONOFINDER are indicated for examining the adult, pregnant woman, and children. These products are intended for use by, or by the order of, and under the supervision of, a licensed physician who is qualified for direct use of medical devices. An appropriately trained healthcare professionals can have operator qualifications. The device use settings are intended in hospital clinic, and medical office settings. The general clinical applications include fetal/ obstetrics(OB), gynecology(GYN), abdominal, small organ and peripheral vessel imaging.

The SonoMe Wireless Probe Type Ultrasound Scanner (Model: 5C, 5CB, H5C, 10L, 14L, 10LB, H10L, H5C10L) and SONOFINDER Wireless Probe Type Ultrasound Scanner (Model: SF14L25) are a wireless ultrasound system that uses pulsed-echo technology to transmit ultrasound images via wireless communication to a Tablet PC or Mobile Phone that utilizes the iOS, Android OS or Windows System.

The SonoMe Wireless Probe Type Ultrasound Scanner and SONOFINDER Wireless Probe Type Ultrasound Scanner are a portable, general-purpose, software-controlled, hand-held diagnostic ultrasound system that consists of (i) a commercial off-the-shelf iOS, Android OS or Windows System, (ii) the Wireless Probe Type Ultrasound Scanner software that runs as an app on the mobile device, (iii) the battery-operated, hand-held Wireless Probe Type Ultrasound Scanner transducer that communicates wirelessly with Tablet PC or Mobile Phone which supports by iOS, Android OS or Windows System and (iv) User Manual, USB charging cable and Wireless Charger (H5C10L only).

The Wireless Probe Type Ultrasound Scanner software can be downloaded to Tablet PC or Mobile Phone which supports by iOS, Android OS or Windows System and utilizes an icon touch-based user interface.

The provided document is a 510(k) summary for the SonoMe and SONOFINDER Wireless Probe Type Ultrasound Scanners, indicating their clearance by the FDA based on substantial equivalence to predicate devices. It primarily focuses on demonstrating that the new devices meet established safety and performance standards through non-clinical testing and comparison with current ultrasound systems.

Crucially, the document explicitly states in Section 9. "Summary of Clinical Tests":

"The subject of this premarket submission, SonoMe Wireless Probe Type Ultrasound Scanner (Model: 5C, 5CB, H5C, 10L, 14L, 10LB, H10L, H5C10L) and SONOFINDER Wireless Probe Type Ultrasound Scanner (Model: SF14L25), did not require clinical studies to support substantial equivalence."

Therefore, the following information regarding acceptance criteria, study design, and performance metrics for an AI-enabled device's clinical performance, as requested in the prompt, cannot be extracted from this document, because no clinical studies were performed or required for the 510(k) clearance of this ultrasound device. The device is purely a hardware ultrasound scanner, not an AI/ML software.

The document focuses on the equivalence of the device's technical specifications and safety standards (electrical, EMC, biocompatibility, acoustic output) to predicate devices, rather than on the performance of a diagnostic algorithm.

Despite the lack of clinical study information in the provided text, I will answer the questions based on the closest relevant information available regarding the device's characteristics and the general principles of medical device clearance, noting where specific details are not provided.

Acceptance Criteria and Device Performance (Based on provided information)

The acceptance criteria for this device are not framed as specific diagnostic performance metrics (e.g., sensitivity, specificity) derived from a clinical study for an AI algorithm. Instead, they are defined by compliance with recognized electrical, safety, and biocompatibility standards, and substantial equivalence in technical characteristics and intended use to legally marketed predicate ultrasound devices.

The "reported device performance" is implicitly that it successfully passed these non-clinical tests and was found substantially equivalent.

1. Table of acceptance criteria and the reported device performance

Regarding an AI-enabled device's clinical performance, the following answers reflect the absence of such information in this specific 510(k) summary, as it explicitly states clinical studies were not required.

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

• Not Applicable. No clinical test set or diagnostic study was performed. The evaluation was based on non-clinical engineering and bench testing, and comparison to predicate devices' specifications.

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

• Not Applicable. No clinical ground truth was established as no clinical study was performed for this device's clearance.

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

• Not Applicable. No clinical test set requiring adjudication was performed.

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. No MRMC study was conducted, as the device is an ultrasound scanner itself, not an AI-assisted diagnostic software affecting human reader performance.

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

• Not Applicable. This is a hardware ultrasound device, not a standalone diagnostic algorithm.

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

• Not Applicable. No clinical ground truth was used or established for this submission, as per Section 9. The "ground truth" for the device's clearance pertains to its adherence to established electrical, performance, and biocompatibility standards.

8. The sample size for the training set:

• Not Applicable. This is a hardware device; thus, it does not have a "training set" in the context of an AI/ML algorithm.

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

• Not Applicable. As above, this is a hardware device, so there is no training set or ground truth in the AI/ML sense.

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