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The Gastric Alimetry System is intended to record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various gastric disorders.

The Gastric Alimetry System is indicated for patients 12 years and older.

The Gastric Alimetry System is an electrogastrography (EGG) device, used for non-invasively measuring the myoelectrical activity of the stomach at the surface of the abdomen. The Gastric Alimetry System is intended to record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various gastric disorders.

The device is used to acquire and digitize gastric myoelectrical data and movement artifacts using the Alimetry Reader connected to a single use Gastric Alimetry Array which includes electrodes on an adhesive patch used for recording the myoelectrical data from the skin surface. The Gastric Alimetry App runs on an iPad mini and is used to set up the device and capture patient-reported symptom data. The Gastric Alimetry Report is provided to the clinicians at the end of the test and includes myoelectrical signal data for manual analysis, together with computed data summaries and plots. A Supplementary Report is also routinely available to clinicians that includes signal data from all 64 channels on the array. The Alimetry Cloud acts as a secure website portal for physicians to access Gastric Alimetry Reports. The Gastric Alimetry Dock (Accessory) is used to guide alignment of the Array and Reader during the setup procedure and charge the Reader.

The Gastric Alimetry System is non-invasive and used in healthcare facilities.

The provided text is a 510(k) Summary for the Gastric Alimetry system. It details modifications made to an already cleared device (K232925, Gastric Alimetry) and argues for substantial equivalence. The summary emphasizes that the changes are minor and do not significantly impact the safety or performance of the device.

Here's an analysis of the acceptance criteria and study information, based only on the provided text. It's important to note that this document is a summary and therefore may not contain all the detailed information of the full 510(k) submission.

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly present a table of acceptance criteria or reported device performance in the typical format of a standalone clinical study. Instead, it asserts substantial equivalence to a predicate device (K232925) based on the minimal nature of the modifications and the applicability of previously performed bench testing.

The device's intended use and indications for use are considered the primary "performance" criteria for comparison to the predicate.

• Updating Amplitude plot to BMI-adjusted Amplitude plot.
• Updating spectral analysis section to include normative ranges.
• Updating the Gut-Brain Wellbeing survey responses presentation and adding a total score.
  These updates are stated to "not impact the performance or safety of the device." |
  | Safety Features: Biocompatibility, software, system checks, skin preparation, instructions to patient, sterilization. | Same as the predicate. |
  | Compliance with Standards: ANSI/AAMI EC12:2000, IEC 60601-1, IEC 60601-1-2. | Same as the predicate. |

2. Sample Size for Test Set and Data Provenance:

The document explicitly states: "The modifications to the device since the prior clearances, namely additional Symptom Summary panel, Symptom Correlation Analysis panel, additional Gut-Brain Wellbeing questions, and an update to the Reader's enclosure, were minimal and did not significantly impact the safety or performance of the device as reflected in the previously performed bench testing submitted in the prior 510(k) notice remains applicable."

This implies that no new test set (clinical data) was used or required for this specific 510(k) submission (K240946) due to the nature of the modifications. The submission relies on the existing performance data of the predicate device (K232925).

Therefore, specific sample size, country of origin, or retrospective/prospective nature for a new test set are not provided in this document. The decision is based on asserting that the changes do not warrant new clinical performance data.

3. Number of Experts and Qualifications for Ground Truth:

Not applicable for this submission. As stated above, no new clinical test set was presented or required to demonstrate performance for these minor modifications. The modifications relate to presentation of existing data (BMI-adjusted amplitude, normative ranges, survey presentation) and an expanded age indication supported by a systematic review of literature and real-world data, rather than a new performance claim verified by expert interpretation of new cases.

4. Adjudication Method for Test Set:

Not applicable for this submission, as no new clinical test set was presented.

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

No MRMC study was done for this submission. The provided text does not mention any comparative effectiveness study, with or without AI assistance, or any effect size of human reader improvement. The focus of this 510(k) is on the safety and performance of the device as a diagnostic aid, specifically justifying minor changes and an expanded age indication based on existing data and prior clearance.

6. Standalone (Algorithm Only) Performance:

The document describes the device as a "diagnostic aid" that records, stores, views, and processes data for clinicians to analyze. It mentions "manual analysis" alongside "computed data summaries and plots." This suggests that the device's outputs are intended for interpretation by a clinician, rather than providing a definitive automated diagnosis (standalone performance).

The "modifications to the report" include "normative reference intervals" and "BMI-Adjusted Amplitude plot," which are tools to aid clinician interpretation, not to replace it with a standalone algorithmic decision.

7. Type of Ground Truth Used:

For the justification of the expanded age indication (12 years and older), the document states: "Systematic review of the extensive general medical literature, together with real-world and structured research evaluations specific to the Gastric Alimetry System, show comparable device performance in adolescents with no new questions of safety and efficacy."

This suggests that the "ground truth" for affirming comparable performance in the adolescent population was based on:

• Systematic review of general medical literature: Implies accepted medical knowledge and established diagnostic criteria.
• Real-world and structured research evaluations specific to the Gastric Alimetry System: This would likely involve data from previous deployments or studies, where clinical outcomes or established diagnostic methods would serve as ground truth for evaluating the device's measurements. However, no specifics are provided in this summary.

For the changes to reporting features (BMI-adjusted amplitude, normative ranges, Gut-Brain Wellbeing survey), the ground truth is implicitly related to accepted physiological measurements and clinical utility in presenting information to clinicians.

8. Sample Size for Training Set:

The document does not provide details of a training set sample size for this specific submission because it's focused on modifications to an already cleared device. Any training data would have been part of the original K232925 submission.

9. How Ground Truth for Training Set was Established:

Not specified in the provided text, as this submission focuses on modifications to an existing device rather than initial development and training. This information would refer to the predicate device's initial development.

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The Gastric Alimetry System is intended to record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various qastric disorders.

The Gastric Alimetry System is an electrogastrography (EGG) device, used for non-invasively measuring the myoelectrical activity of the stomach at the surface of the abdomen. The Gastric Alimetry System is intended to record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various gastric disorders. The device is used to acquire and digitize gastric myoelectrical data and movement artifacts using an array with recording electrodes on an adhesive patch, which is used for recording the myoelectrical data from the skin surface. An App is used to set up the device and capture patient-reported symptom data. A report is provided to the clinicians at the end of the test which includes myoelectrical signal data for manual analysis, together with computed data summaries and plots. A Supplementary Report is also routinely available to clinicians that includes signal data from all 64 channels on the array.

This FDA 510(k) clearance document for the Gastric Alimetry System states that no new clinical studies were required for this submission. The submission relies on prior clearances and bench testing, as the modifications introduced were considered minimal and did not significantly impact safety or performance.

Therefore, the document does not contain the detailed information usually found in a study proving a device meets acceptance criteria, such as:

• A table of acceptance criteria and reported device performance (for a new study).
• Sample size used for a test set or data provenance.
• Number of experts or their qualifications for ground truth establishment.
• Adjudication methods.
• MRMC comparative effectiveness study details.
• Standalone algorithm performance.
• Type of ground truth used (for a new study).
• Training set sample size or how its ground truth was established.

Based only on the provided document, here's what can be inferred / what is explicitly stated:

The document primarily focuses on demonstrating substantial equivalence to a previously cleared predicate device (Gastric Alimetry System, K223398) due to minor modifications.

Here's a breakdown of the requested information, referencing the document's content:

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

   • No specific acceptance criteria table for this submission's performance study is provided. The document states: "The modifications to the device since the prior clearances... were minimal and did not significantly impact the safety or performance of the device as reflected in the previously performed bench testing, the testing submitted in the prior 510(k) notice remains applicable."
   • The "Technological Characteristics / Substantial Equivalence" table (pages 5-6) compares the subject device to the predicate across various parameters (e.g., sampling frequency, number of channels, power source, software features). For almost all parameters, the "Subject Device" and "Primary Predicate Device" columns state identical characteristics, followed by "Same as the predicate." This implicitly means the performance characteristics are expected to be the same as the predicate and were deemed acceptable based on the predicate's clearance.
   • For "Symptom Outputs", the subject device adds visualizations without removing or altering existing outputs, and the addition of gut-brain wellbeing questions does not impact device performance.

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

   • Not applicable. No new clinical "test set" was used for this 510(k) submission. "No clinical studies were required."

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

   • Not applicable. No new clinical "test set" for which ground truth needed to be established for this submission.

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

   • Not applicable. No new clinical "test set" for this submission.

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 study was not done for this submission. The device (Gastric Alimetry System) is an electrogastrography (EGG) device intended to "record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various gastric disorders." It provides "myoelectrical signal data for manual analysis, together with computed data summaries and plots." It is not described as an "AI assistance" device for human readers in the context of interpretive diagnostic imaging.

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

   • Not explicitly stated for this submission. The device provides data for "manual analysis" by clinicians. The document focuses on the equivalence of the data acquisition and reporting features, not on a standalone diagnostic algorithm's performance.

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

   • Not applicable for this submission. No new clinical study was conducted where such ground truth would be established. The device is an EGG system, aiding in diagnosis by presenting myoelectrical activity data. The "ground truth" for its function would relate to how accurately it records and processes these physiological signals, which is addressed through technical and bench testing described in previous submissions, not a comparative diagnostic outcome study in this document.

8. The sample size for the training set:

   • Not applicable for this submission. This document describes minor modifications to an already cleared device and does not detail a new AI model with a training set. The "Minor Algorithm fixes" mentioned on page 5 suggests iterative improvements, but no new large-scale training is implied or detailed.

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

   • Not applicable. See point 8.

In summary, the provided document explicitly states, "No clinical studies were required," for this 510(k) clearance due to the minor nature of the changes. The acceptance criteria and performance proof are based on the prior clearance of the predicate device (K223398) and repeated bench testing for specific components (array electrical performance).

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The Gastric Alimetry System is intended to record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various gastric disorders.

The Gastric Alimetry System is an electrogastrography (EGG) device, used for non-invasively measuring the myoelectrical activity of the stomach at the surface of the abdomen. The Gastric Alimetry System is intended to record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various gastric disorders.

The device is used to acquire and digitize gastric myoelectrical data and movement artifacts using an array with recording electrodes on an adhesive patch. which is used for recording the myoelectrical data from the skin surface. An App is used to set up the device and capture patient-reported symptom data. A report is provided to the clinicians at the test which includes myoelectrical signal data for manual analysis, together with computed data summaries and plots. A Supplementary Report is also routinely available to clinicians that includes signal data from all 64 channels on the array.

In the modified Gastric Alimetry System, the following minor updates are introduced in order to provide additional data summaries within the Report:

• Addition of four post-processing data summary metrics:
  • Principal Gastric Frequency showing the frequency of myoelectrical activity o occurring within the gastric range
  • 'BMI-Adjusted Amplitude' calculated amplitude for BMI up to the recommended O device limit (BMI

Based on the provided text, the Gastric Alimetry System is an electrogastrography (EGG) device. The performance data section focuses on demonstrating the substantial equivalence of four newly added data summary metrics to equivalent metrics in a Reference Device (Medtronic Polygram NET EGG System), rather than establishing new acceptance criteria for the entire device.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Reported Device Performance

The acceptance criteria here aren't typical performance thresholds (like achieving a certain sensitivity or specificity for a diagnostic claim). Instead, the "acceptance criteria" for the newly added metrics in the modified Gastric Alimetry System appear to be demonstrating high correlation with equivalent metrics from a legally marketed Reference Device. The aim is to prove substantial equivalence, meaning these minor updates do not raise new questions of safety or effectiveness.

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The Gastric Alimetry System is intended to record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various gastric disorders.

The Gastric Alimetry is an electrogastrography (EGG) device, used for non-invasively measuring the myoelectrical activity of the stomach at the surface of the abdomen. The Gastric Alimetry System is intended to record, store, view and process gastric myoelectrical activity as an aid in the diagnosis of various gastric disorders.

The device is used to acquire and digitize the myoelectrical data and movement artifacts through an array with recording electrodes on an adhesive patch which is used for recording the myoelectrical data from the skin surface. An App used to set up the device and capture patient-reported symptom data.

A report is provided to the clinicians at the end of the test which displays myoelectrical data.

The provided text describes the Gastric Alimetry System, an electrogastrography (EGG) device. However, it does not explicitly state specific acceptance criteria (e.g., a specific sensitivity or specificity threshold) for the device's performance. Instead, it concludes that the device's performance is "equivalent" or "comparable" to a predicate device and manual marking of artifacts.

Therefore, the table below will reflect the comparison to the predicate device where performance is discussed, rather than predefined acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size (for Gastric Myoelectrical Frequency Detection Study): 25 patients.
• Data Provenance: Prospective clinical study. The country of origin of the data is not specified.

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

• For Gastric Myoelectrical Frequency Detection: The study was a "simultaneous head-to-head comparison to the predicate," meaning the predicate device itself served as a pseudo-ground truth for comparison, rather than an independent expert panel.
• For Automated Artifact Detection: Ground truth was established by "manual marking of artifacts by clinicians." The number of clinicians and their specific qualifications are not specified in the provided text.

4. Adjudication method for the test set:

• The text does not specify an adjudication method like 2+1 or 3+1. For the gastric myoelectrical frequency detection, it was a head-to-head comparison to the predicate. For artifact detection, it was compared against "manual marking by clinicians," implying those clinicians' markings were the reference, without detailing an adjudication process.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study involving human readers and AI assistance is not described in the provided text. The studies mentioned focus on the standalone performance of the device or its algorithms against a predicate or manual marking.

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

• Yes, the performance studies described are essentially standalone evaluations:
  • The head-to-head comparison with the predicate device evaluates the device's ability to measure gastric myoelectrical frequency.
  • The evaluation of the artifact detection algorithm compares its automated output against manual markings.

7. The type of ground truth used:

• For Gastric Myoelectrical Frequency Detection: The performance of the predicate device (Polygraf ID with POLYGRAM NET ElectroGastroGraphy Application Software) was used as the reference point for comparison.
• For Automated Artifact Detection: "Manual marking of artifacts by clinicians" was used as the ground truth.

8. The sample size for the training set:

• The document does not provide details about a training set or its sample size. The clinical studies described are presented as evaluations of the device's performance, implying they might be test or validation sets.

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

• As no information on a specific training set or its ground truth establishment is provided, this cannot be answered from the given text.

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The intended use for the G-Tech Patch System is to serve as a tool that provides gastrointestinal myoelectrical activity measurements to be used at the discretion of the Physician or Clinical User to aid in the diagnosis and evaluation of gastrointestinal disorders.

The G-Tech System is a non-invasive wireless gastrointestinal monitoring system for use by the physician or staff in the hospital setting, clinic, or physician's office. The device is intended for use while the patient is under direct supervision (e.g., in hospital or clinic) as well as after discharge to home or to intermediate setting. The device is for prescription use only. The device consists of the G-Tech Patch, the G-Tech Patch Monitor, an iOS application, a secure cloud storage server and computer-based data analysis algorithms. The G-Tech Patch is a single use, wearable electrode patch that reads the electrical signals of the gastrointestinal tract from the abdominal skin surface. The Patch transmits the acquired electrical signals via Bluetooth to the G-Tech Patch Monitor. The G-Tech Patch Monitor receives the raw data, encrypts it, and periodically uploads it to a secure cloud server. Additionally, the Patch Monitor has a patient interface to allow the patient to manual enter events such as meals, bowel movements, pain or the taking of medications. Data analysis algorithms process the uploaded data to measure and report myoelectrical activity for the stomach and intestines. These measurements are made available to physicians for aid in clinical evaluation of their patient.

The provided document describes the G-Tech Wireless Patch System (WPS), a non-invasive device for measuring gastrointestinal myoelectrical activity. The information details the device's characteristics, intended use, and substantial equivalence to predicate devices, through various studies. However, the document does not explicitly state acceptance criteria in a quantitative, measurable format with corresponding reported device performance values in a table. It also does not present a traditional "study" in the sense of a clinical trial with a defined test set, ground truth experts, adjudication, or MRMC design for regulatory clearance.

Instead, the submission focuses on demonstrating substantial equivalence through a combination of:

• Bench Performance Study: Functional testing with known signals to assess the system's ability to extract rhythmic motor activity.
• Animal Study: Comparison of G-Tech Wireless Patches with internal electrodes in mini-pigs to show fidelity of surface-measured signals to internal ones.
• Clinical Studies (Primary Evidence): Simultaneous measurements with manometry and Smart Pill to demonstrate concordance in frequency and time of myoelectrical activity with internal measurements. These appear to be more akin to validation or correlation studies rather than a pass/fail performance study against pre-defined acceptance criteria for diagnostic accuracy.
• Supplemental Evidence: Four peer-reviewed publications demonstrating correlation with clinical markers and reproducibility.

Given the information provided, I will interpret "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of the available data, which focuses on demonstrating substantial equivalence through various aspects of performance and comparison to established methods, rather than a single, pre-defined algorithm performance study with specific cutoffs.

Here's a breakdown of the requested information based on the provided text, with explicit notes where information is not present:

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned, the document does not provide a quantitative table of acceptance criteria with corresponding reported device performance values for the overall device's diagnostic capability (e.g., sensitivity, specificity for a specific disorder). The "acceptance criteria" for this 510(k) submission appear to be implicit and qualitative: demonstrating that the device performs as intended, is safe, and is substantially equivalent to predicate devices.

The "performance" is described broadly:

• G-Tech Patches are reliable and provide consistent electrical measurement devices.
• Data processing algorithms are efficient engines for extracting rhythmic motor activity signals. |
  | Fidelity to Internal Signals | Detectable slow wave signals at the skin surface (stomach, small intestine, colon) with fidelity to internally measured signals in frequency and spectral shape. | Animal Study demonstrated:
• Slow wave signals associated with the three major GI organs (as observed with internal electrodes) are detectable at the skin surface with the G-Tech Wireless Patches.
• Signals have fidelity to the internally measured signals in frequency and spectral shape. |
  | Clinical Concordance | Records signals identifiable as originating from Stomach, Duodenum/Jejunum, and Colon, with concordance to manometry and Smart Pill data. | Clinical Studies (Primary Evidence) demonstrated:
• Non-invasive patch system records signals identifiable as being from the Stomach, Duodenum/Jejunum, and Colon by concordance with frequency and time of spectral analysis of high-resolution manometry data.
• Concordance in frequency and time observed between G-Tech Wireless Patch measurements and Smart Pill measurements. |
  | Clinical Utility/Correlation | (Implicit) Utility in understanding measurement capabilities and potential clinical use; correlation with clinical markers of postoperative recovery; reproducibility; sensitivity to external stimulus. | Clinical Studies (Supplemental Evidence - Peer-Reviewed Publications) demonstrated:
• Correlation between G-Tech Wireless Patch Measurements and clinical markers of postoperative recovery in adult and pediatric populations.
• Reproducibility of the gastric and intestinal myoelectrical profile over multi-year periods.
• Sensitivity of measurements to an external stimulus in specific examples. |
  | Safety | Electrical safety, EMC, biocompatibility, mechanical strength. | Compliance with IEC 60601-1, IEC 60601-1-11, IEC 60601-1-6, IEC 60601-1-2, ANSI C63.27-2017.
  Biocompatibility assessed with ISO 10993-1:2009 (compliant for intact skin up to 30 days).
  Mechanical strength testing (wear adhesion, tensile, impact, drop, shock, vibration) demonstrates performance as intended and safety. |
  | Software Performance | Software acquires and processes myoelectrical signals, generates reports as intended. | Software documentation developed in consideration of "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" and "Content of Premarket Submissions for the Management of Cybersecurity in Medical Devices". (Implies verification and validation were done to meet these guidelines). |

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

The document does not explicitly define a "test set" in the context of an AI/ML model for a diagnostic study, but rather describes various validation/correlation studies.

• Bench Performance Study: Known signals were applied to the system, but the specific number/type of signals is not quantified as a "sample size."
• Animal Study: Data from "a study" undertaken to compare measurements in "adolescent Yucatan mini-pigs." The number of animals is not specified. Data provenance: likely laboratory/research setting (not specified country).
• Clinical Studies (Primary Evidence): Describes "simultaneous measurements between G-Tech Wireless Patches and antroduodenal and colonic manometry" and "concordance... between G-Tech Wireless Patch measurements and Smart Pill measurements." The number of human subjects/patients involved in these "primary evidence" studies is not specified. Data provenance: "IRB-approved studies and well-documented case histories," implying prospective or retrospective for specific cases. Country of origin is not specified, but the applicant is US-based.
• Clinical Studies (Supplemental Evidence - Peer-Reviewed Publications): These are external studies. The document only lists the publications without detailing their sample sizes or methodology beyond their titles. To get this info, one would need to refer to the publications themselves.

3. Number of Experts Used to Establish Ground Truth and Qualifications of Those Experts

This information is not provided in the document. The "ground truth" for the device's performance appears to be established through:

• Known signals (bench testing).
• Internal electrodes (animal study).
• Established clinical methods like manometry and Smart Pill (clinical studies).

There is no mention of human expert consensus or adjudication being used as a "ground truth" reference for this device's output. The device provides "measurements" to be used at the "discretion of the Physician or Clinical User," suggesting the physician interprets the device's data rather than the device providing a definitive "diagnosis."

4. Adjudication Method for the Test Set

This information is not applicable/provided. No "test set" in the context of expert review with adjudication is described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, What was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance?

This information is not provided and such a study design is not described for this device. The G-Tech WPS provides "measurements" for physicians to use in their diagnosis; it is not described as an AI-powered diagnostic aid that re-interprets medical images or provides a direct diagnostic output that a human then uses. Therefore, a study on human reader improvement with/without AI assistance isn't relevant to the information presented for this device.

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

The document states: "Data analysis algorithms process the uploaded data to measure and report myoelectrical activity for the stomach and intestines." The "Bench Performance Study" and "Animal Study" would represent aspects of standalone algorithm performance, as they assess how well the system, through its algorithms, extracts and measures signals compared to known inputs or internal direct measurements.

• Bench Performance Study: Confirmed algorithms are "efficient engines for extracting rhythmic motor activity signals."
• Animal Study: Confirmed surface signals "have fidelity to the internally measured signals in frequency and spectral shape."

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

The types of "ground truth" or reference standards used are:

• For Bench Testing: Known, synthetic electrical signals with realistic background, artifact, and noise characteristics.
• For Animal Study (Fidelity): Simultaneous measurements using "multi-element electrodes sutured to serosal surfaces of stomach, small intestine, and colon." (i.e., direct internal physiological measurements).
• For Clinical Studies (Concordance):
  • High-resolution manometry data (for antroduodenal and colonic myoelectrical activity).
  • Smart Pill measurements (for gastrointestinal transit and related activity).
• For Clinical Utility/Correlation (Supplemental Evidence): Clinical markers of postoperative recovery.

8. The Sample Size for the Training Set

This information is not provided. The document describes the device as a measurement system, not a machine learning model developed with explicit training and test sets in the typical AI/ML sense (though data analysis algorithms are present). If the algorithms involved machine learning, the training set details would be critical, but they are not mentioned here.

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

This information is not provided, as details regarding a specific "training set" are absent.

Summary of Missing Information critical for a typical AI/ML Diagnostic Study:

• Quantitative acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, AUC).
• Sample sizes for human clinical "test sets."
• Details on expert involvement, qualifications, and adjudication methods for any human interpretation studies.
• MRMC study results for human-AI collaboration.
• Explicit training set details, including size and ground truth establishment, for the data analysis algorithms (if they are AI/ML-based algorithms requiring such, which is not explicitly stated).

The provided text focuses on the device's technical performance (signal acquisition, processing, safety) and its correlation/concordance with existing physiological measurement techniques, supporting its claim of substantial equivalence as an electrogastrography system.

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The PolygrafID with POLYGRAM NET™ ElectroGastroGraphy Application is intended to record, store, process and view gastric myoelectrical activity as an aid in the diagnosis of gastrointestinal motility disorders.

The system is a stationary electrogastrography system for use in the evaluation of gastrointestinal motility disorders. The system measures the myoelectrical activity of the gastrum using sensors situated on the skin. The parameters measured are presented on a computer screen during the capture and are also stored for later display, review, analysis and reporting.

Here's an analysis of the provided text regarding the EGG system's acceptance criteria and study data:

This 510(k) submission primarily focuses on demonstrating substantial equivalence to a predicate device for a new Electrogastrography (EGG) system. It does not contain detailed information about specific acceptance criteria, a dedicated study proving performance against those criteria, or the typical AI/ML study components you've requested.

The document is a US FDA 510(k) Notification, which aims to show that a new device is "substantially equivalent" to a legally marketed predicate device. This process often relies on comparisons of technical specifications, intended use, and safety/performance characteristics rather than new clinical trials with defined acceptance criteria and statistical endpoints, especially for low-risk devices.

Therefore, many of your requested points cannot be directly answered from the provided text.

Here's a breakdown of what can be extracted and where information is missing:

Electrogastrography (EGG) System - Acceptance Criteria and Study Information

Note: This 510(k) submission primarily establishes substantial equivalence to a predicate device. It does not describe a standalone clinical performance study with predefined acceptance criteria as would be typical for a novel AI/ML device or a device requiring new clinical validation. The "acceptance criteria" here implicitly refer to the device performing comparably to the predicate and meeting general safety and electrical standards.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of this 510(k), explicit acceptance criteria are not stated in a quantitative performance table. Instead, the "performance" is implicitly deemed acceptable if the device is substantially equivalent to the predicate and adheres to relevant standards.

Key Implication: The "acceptance criteria" are generally met by demonstrating that the device functions correctly, adheres to electrical safety standards (EN 60601-1, etc.), and provides equivalent or improved data capture and processing capabilities compared to the predicate device for its intended use.

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

• Sample Size: Not specified. The document states, "Clinical trials are not performed." It implies that performance was assessed through engineering verifications and comparisons to the predicate device's specifications and functionality rather than a clinical "test set" with patient data.
• Data Provenance: Not applicable, as formal clinical test data, in the sense of patient studies, were not conducted for this 510(k).

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

• Number of Experts: Not applicable. No clinical test set requiring expert ground truth establishment is described.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. No clinical test set requiring adjudication is described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance

• MRMC Study: No. This device is an EGG system, not an AI-based interpretation tool for human readers.
• Effect Size of AI: Not applicable.

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

• Standalone Performance: Not applicable in the context of an AI algorithm. The device measures and processes physiological signals. Its performance is related to the accuracy and reliability of these measurements and processing, which are verified through engineering tests and comparison to the predicate, not in an "algorithm-only" performance study.

7. The type of ground truth used

• Type of Ground Truth: For the device itself, the "ground truth" for verification would primarily be:
  • Engineering Specifications: Ensuring hardware and software perform according to design (e.g., gain settings, frequency filtering, digital resolution).
  • Predicate Device Performance: The predicate device (3CPM EGG Machine) serves as the benchmark for "truth" in terms of clinical utility and output characteristics.
  • Regulatory Standards: Compliance with electrical safety and EMC standards (EN 60601-1, etc.) acts as a form of "ground truth" for safety.
  • "Verifications results show that the enhanced system performs as its predicate system." This statement implies the predicate's established performance is the de facto ground truth.

8. The sample size for the training set

• Sample Size: Not applicable. This is not an AI/ML device that requires a training set of data.

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

• Ground Truth Establishment: Not applicable. This is not an AI/ML device.

In summary: The provided 510(k) document is for an Electrogastrography (EGG) system seeking substantial equivalence to a predicate. It relies on non-clinical performance data (engineering verifications, adherence to standards, and feature comparison to the predicate) to demonstrate equivalence rather than a clinical trial with predefined acceptance criteria against new patient data. Therefore, most of the questions related to AI/ML device validation are not applicable.

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