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The AbStats Gateway is a compact device with integrated sensor interfaces and embedded computing system (stethoscope) that in conjunction with external sensors constitutes the AbStats system external sensors are placed on the abdomen and identify the vibratory signals associated with digestive processes. This device should be used under the direction of a licensed healthcare when it is required to determine this patient digestive state. The device has not been tested for and it is not intended for pediatric use.

The AbStats Gateway is a compact device with integrated sensor interfaces and embedded computing system (stethoscope) that in conjunction with external sensors constitutes the AbStats system. The Ab-Stats system external sensors are placed on the abdomen and identify the vibratory signals associated with digestive processes.

The AbStats Gateway system is a compact, rapidly deployable unit that is comfortable for subjects and convenient in application. The AbStats Gateway sensor includes a standard microelectronic microphone for measurement of vibration acoustic signals. The components in patient contact are disposable, avoiding the need for cleaning and disinfection. The only material in direct contact with the subject is standard, FDA-approved 3M Tegaderm wound bandage adhesive material.

The AbStats Gateway sensor includes a system that provides usage assurance of proper application to the patient. The AbStats Gateway sensor includes both an electret microphone and a compact vibration source (based on the principle of standard signaling vibration sources in consumer pager and smartphone systems). This small electronic vibration device emits a short duration (50 millisecond length) signal each 2 minutes during usage and alternately from each sensor.

This low amplitude and low frequency (less than 1 kHz) vibration signal is not detectable by the subject. lt propagates between the two AbStats sensors where it is detected by the AbStats device and provides direct assurance of proper application of the two sensors.

The AbStats Gateway sensor includes fine, flexible cables that connect to the AbStats Gateway. The AbStats Gateway is a low voltage device that is similar in size to a tablet computer. The AbStats Gateway monitors the AbStats sensor signals and provides a measurement of intestinal motility with a Motility Rate. The rate is calculated based on rate of arrival of acoustic events detected by AbStats sensors.

The provided text describes the AbStats Gateway, an electronic stethoscope, and its substantial equivalence to a predicate device (RNK PCP-USB Stethoscope K132560). The document focuses on regulatory approval rather than detailed performance metrics. Therefore, some information, such as precise acceptance criteria, specific device performance numbers, and statistical study details, is not explicitly provided.

However, based on the information available, here's a structured summary:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list specific numerical acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, accuracy) that the AbStats Gateway needed to meet. Instead, the "acceptance criteria" are implied by the documented functional tests and the finding of "conformance" or "Pass" for each. The overall acceptance criterion appears to be that the device "performs as intended in the specified use conditions" and "functions in a manner comparable to the predicate device."

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

• Test Set (Functional/Bench Testing): Not explicitly stated. The "Functional Study (Proof of Function)" section refers to "AbStats Operation Test Report (TR-001)" which lists 12 test steps, all of which "Passed." This appears to be a bench testing and software validation test rather than a clinical sensitivity/specificity study.
• Test Set (Clinical): The document references an "IRB Approved Clinical Trial results" in the public domain:
  • Reference: Brennan M R Spiegel, Marc Kaneshiro, Marcia M Russell, Anne Lin, Anish Patel, Vartan C Tashjian, Vincent Zegarski, Digvijay Singh, Samuel E Cohen, Mark W Reid, Cynthia B Whitman, Jennifer Talley, Bibiana M Martinez, William Kaiser, "Validation of an acoustic gastrointestinal surveillance biosensor for postoperative ileus", J Gastrointest Surg 2014 Oct 5;18(10):1795-803.
  • Data Provenance: The k-number refers to the US Food and Drug Administration, implying the clinical trial would likely be conducted in the US, but the country of origin of the data is not specified in the provided text. The study is cited as "postoperative ileus validation," suggesting it is a prospective clinical trial.
  • Sample Size: The sample size for this specific clinical study is not mentioned in the provided FDA submission document. One would need to consult the referenced publication.

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

• This information is not available in the provided document. The clinical study referenced is for "Validation of an acoustic gastrointestinal surveillance biosensor for postoperative ileus." It is likely that ground truth for postoperative ileus would involve clinical diagnosis, potentially with imaging or other clinical parameters, but the number and qualifications of experts involved in establishing this ground truth for the test set (if any specific "experts" were used for ground truth rather than standard clinical diagnosis) are not detailed here.

4. Adjudication Method for the Test Set

• Not specified within the provided text. For the clinical study, the adjudication method for diagnosing postoperative ileus (which would serve as ground truth) is not detailed.

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

• Not explicitly mentioned or described. The document states that the device (AbStats Gateway) functions "comparable to the predicate device" and that clinical data "demonstrate that the AbStats Gateway device functions in a manner comparable to the predicate device that is currently marketed for the same intended use." This comparison is at the device level, not an MRMC study assessing human reader improvement with or without AI assistance. The AbStats Gateway itself is described as a stethoscope system identifying vibratory signals, calculating a "Motility Rate," and providing a measurement of intestinal motility; it's not described as an AI-assisted diagnostic tool for human readers in the traditional MRMC sense.

6. Standalone (Algorithm Only) Performance Study

• Yes, in essence, a standalone functional study was done. The "Functional Study (Proof of Function)" and "AbStats Operation Test Report" describe the device's (algorithm's) ability to boot, set time zones, detect and record sensor data, and compute signal counts. These are tests of the algorithm's direct output and operational integrity.
• The system monitors signals and "provides a measurement of intestinal motility with a Motility Rate. The rate is calculated based on rate of arrival of acoustic events detected by AbStats sensors." This implies a standalone algorithmic output. The clinical trial then validates this output's correlation with postoperative ileus.

7. Type of Ground Truth Used

• Functional/Bench Testing: The ground truth for the functional tests was internal verification against expected system responses and design requirements (e.g., "Welcome Message displayed," "Time Zone Entry Accepted").
• Clinical Study: For the clinical study on postoperative ileus, the ground truth would be the established clinical diagnosis of postoperative ileus as determined by standard medical practice, which the device's "Motility Rate" is validated against. The specific gold standard used in the referenced paper would need to be consulted, but it would typically be based on clinical signs, symptoms, and potentially imaging.

8. Sample Size for the Training Set

• Not specified. The document does not provide details on model training or a training set sample size. Given that the device is described as calculating a "Motility Rate" based on the "rate of arrival of acoustic events," the underlying algorithm may involve signal processing and event detection rather than a complex machine learning model requiring a large labeled training set in the modern AI sense. If machine learning was used for event detection, the training set size is not disclosed.

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

• Not specified. As the document doesn't detail a training set, the method for establishing its ground truth is also not mentioned.

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