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QBioScan is indicated for the measurement of galvanic skin response to aid in the assessment of the sudomotor function. The device is intended for use on the general adult population in medical clinics, healthcare practices and out-patient departments of hospitals.

QBioScan™ is a galvanic skin response measurement device intended for the collection and display of galvanic skin response recorded by the device consists of the following components:

• . an off-the-shelf computer with proprietary device software pre-installed
• . a custom electronics box that houses the QBioScan circuitry
• a USB cable to connect the electronics box to the computer .
• reusable electrode lead cables .
• reusable hand and foot electrodes and optional disposable forehead electrodes .
• . an off-the-shelf printer (optional)
  The device allows for a evaluation of sweat gland function based on a measuring method where patients are in contact with surface electrodes (reusable stainless-steel plates and optional disposable electrodes) and are exposed to an incremental low voltage (under the 60601-1 standard safety limits). The device tests the electrochemical reaction between electrodes and the chloride ion released by the stimulated sweat glands. This active test method provides information and evidence of a sweat gland dysfunction that might otherwise not be detectable in a physiological examination. The Bioelectrical Conductance (BEC, in micro-Siemens, uS) representing galvanic skin response for the hands and feet are expressed as quantitative results along with an asymmetry value expressed as the percent difference between the BEC values of the right / left hands and the right / left feet. The device does not provide any direct diagnosis rather the device provides information to the physician for inclusion in their decision making process.

The QBioScan device does not appear to have acceptance criteria for clinical performance explicitly stated in this 510(k) summary. The document focuses on demonstrating substantial equivalence to a predicate device (Sudoscan) primarily through technological characteristics and non-clinical testing.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

As there are no specific performance acceptance criteria for clinical outcomes mentioned, a table cannot be fully provided. The non-clinical testing refers to compliance with safety and EMC standards and software V&V, which are typically pass/fail.

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

• No clinical test set was used for a performance study. The document explicitly states: "No Clinical testing was necessary to determine substantial equivalence."
• Data Provenance: Not applicable for clinical testing. For the non-clinical testing (electrical safety, EMC, software V&V), the data would have been generated internally by Medeia, Inc. or by a contract testing laboratory.

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

• Not applicable as no clinical test set with human subjects requiring ground truth establishment was used.

4. Adjudication Method for the Test Set

• Not applicable as no clinical test set was used.

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

• No. The document states, "No Clinical testing was necessary to determine substantial equivalence." This type of study would fall under clinical testing.

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

• Not explicitly described as a standalone performance study. The device is a "galvanic skin response measurement device" which directly measures a physiological signal. While it processes data and displays it, it's not an "algorithm only" device in the context of, for example, an AI diagnostic tool. The focus is on the device's ability to accurately measure the physiological parameter, which is addressed through the technological comparison to the predicate and non-clinical safety/EMC testing.

7. The Type of Ground Truth Used

• Not applicable for clinical validation, as no clinical studies were performed. For the technical aspects, the "ground truth" would be the established safety standards (IEC 60601-1, EN 60601-1-2) and the functional specifications of the device itself (for software V&V).

8. The Sample Size for the Training Set

• Not applicable. This device is a measurement device, not an AI/machine learning device that requires a training set in the conventional sense. Its "training" would be its design and engineering to accurately measure galvanic skin response.

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

• Not applicable, as there is no training set in the context of AI/ML.

Summary of Approach:

The manufacturer, Medeia, Inc., pursued a 510(k) pathway for substantial equivalence. Their strategy was to demonstrate that the QBioScan device shares the same intended use and similar technological characteristics with a legally marketed predicate device (Sudoscan), and that any differences do not raise new questions of safety or effectiveness. This allowed them to forgo clinical testing and rely on non-clinical (electrical safety, EMC, software verification, and validation) testing, alongside a detailed technological comparison.

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SudoC device is a medical device for the measurement of galvanic skin response related to the sweat glands.

The SudoC provides values. It is the physician's responsibility to make proper judgments based on these numbers. The device is indicated for use in general adult population.

Prescription Use: Federal law restricts this device to sale by or on the order of a physician.

The SudoC is a programmable electro medical system including:

• USB plug and play hardware device including an electronic box, 2 reusable cables to connect . the box to electrodes and 2 tactile electrodes placed on the sole of each foot.
• Software installed on a computer. ●

As a galvanic skin response measurement device, it measures the skin resistance (i.e., conductance).

The provided text is a 510(k) Premarket Notification for a device named SudoC. This document primarily focuses on demonstrating that the SudoC device is substantially equivalent to a previously cleared predicate device (SudoPath K131568) and does not contain detailed information about specific acceptance criteria, study designs, or reported device performance for the SudoC as an independent, de novo submission would.

Therefore, many of the requested details cannot be extracted directly from this document. However, I can provide the information that is present and explain why other information is not available.

Here's a breakdown based on the provided text:

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

This document does not provide a table of acceptance criteria with specific performance metrics (e.g., sensitivity, specificity, accuracy) or reported performance values for the SudoC. The core of this submission is to demonstrate substantial equivalence to a predicate device, meaning it asserts that the modifications to SudoC do not change its performance.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

This information is not provided. The document states that the modifications to the proposed device "do not change the performance of the device" as shown with:

• New risk management
• Software verification (SRS/SDS/STD/STR)
• Summary of Design Control Activities and Declaration of Design control conformity.
• Comparison of the conductance values using stainless steel electrodes versus conductive disposable cloth electrode.
• The removal of the hand electrodes does not affect the performance of the galvanic skin response measurement.

The crucial point is the "Comparison of the conductance values" which suggests some testing was done, but details like sample size, provenance, or whether it was a "test set" in the context of a clinical study are absent.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

This information is not provided. The SudoC is a galvanic skin response measurement device, which measures physiological responses. "Ground truth" in this context would likely refer to the accuracy of the measurements themselves or their correlation with a specific physiological state, which is not detailed in this type of submission for substantial equivalence.

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

This information is not provided.

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

This information is not provided. The device (SudoC) is described as a measurement device that provides values, and "It is the physician's responsibility to make proper judgments based on these numbers." This indicates it's a diagnostic aid, not an AI-assisted detection or interpretation system that would typically involve human reader performance studies.

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

The SudoC is a measurement device. It provides raw "values." The "algorithm" here would be the processing of the galvanic skin response to produce those values. The document asserts that the fundamental scientific technology and the range of conductance measurements (1 to 120 micro Siemens) are the same as the predicate. While software verification was done, a standalone performance study with specific metrics is not detailed as per the typical requirements for a new, complex algorithm or AI.

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

This information is not explicitly stated. For a galvanic skin response device, the ground truth would likely be the accurate measurement of skin conductance. The document states "Comparison of the conductance values using stainless steel electrodes versus conductive disposable cloth electrode," suggesting that the accuracy of the conductance measurement itself with the new electrodes was assessed against the prior electrode type.

8. The sample size for the training set

This information is not provided. Since this is a 510(k) for a measurement device and not an AI/ML algorithm requiring extensive training data, such details are typically not included unless the specific modifications involved significant new algorithmic development or a new intended use. The software changes primarily relate to "New design and change in time and sequence of measurement."

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

This information is not provided, for the same reasons as point 8.

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The SUDOSCAN System is a medical device for the measurement of galvanic skin response to aid in the assessment of sudomotor function. SUDOSCAN is indicated for use in the general adult population.

SUDOSCAN is based on two well-known principles, reverse iontophoresis and electrochemistry. SUDOSCAN collects physiological data by means of chronoamperometry and processes them with analysis software. SUDOSCAN devices use both technologies, coupled and complemented with exclusive software which analyzes cutaneous conductance data collected through the chronoamperometric measurements. The SUDOSCAN system is composed of: - analog acquisition electronic circuitry with low-noise front end - multiplexing control unit for selecting the appropriate acquisition channels - optically isolated USB interface controller - power converter - 4 electrodes placed on the feet and the hands - touch-screen computer running the proprietary SUDOSCAN software

The provided text is a 510(k) Summary for the SUDOSCAN device (K141872). It compares the proposed device to a predicate device (K100233), which is itself an earlier version of the SUDOSCAN.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in terms of specific performance metrics (e.g., sensitivity, specificity, accuracy) for a new clinical study. Instead, it argues for substantial equivalence based on technological characteristics and a change in indication statement and labeling compared to its own predicate device. The performance data section refers back to the testing provided in the K100233 submission.

The "Performance Data" section states: "The modifications that are the subject of this 510(k) are to the indication statement, labeling and minor software and hardware upgrades. Therefore the performance testing provided in K100233 is applicable to this 510(k)."

This implies that the performance of the device, in terms of its ability to measure galvanic skin response, is considered unchanged from the predicate and thus already "meets acceptance criteria" from its previous clearance. The acceptance criteria would have been established during the K100233 submission.

The table below summarizes the technological characteristics of the proposed device as presented in the "Device Comparison Table" within the document, rather than specific performance metrics from a new study designed to meet pre-defined acceptance criteria for this 510(k).

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

The document for K141872 explicitly states that no new performance testing was conducted for this submission (K141872) related to the device's ability to measure galvanic skin response. It relies on the performance testing from the predicate device (K100233). Therefore, information on a "test set" and "data provenance" for this specific 510(k) application is not provided as new clinical performance data was not generated.

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

As no new clinical performance testing was conducted for K141872, this information is not available in the provided document. The original ground truth establishment would have occurred for the K100233 submission.

4. Adjudication method for the test set

Not applicable, as no new clinical test set and associated performance evaluation were conducted for K141872.

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. The SUDOSCAN device is a diagnostic measurement device for sudomotor function, not an AI-assisted interpretation tool for images or other complex data requiring human reader interaction in the way a MRMC study typically evaluates. No MRMC study is mentioned or relevant to this device's function.

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

The device itself is a standalone measurement system. The document does not describe "algorithm only" performance in the context of interpretation or diagnosis being done without human involvement. The device measures galvanic skin response, and a physician interprets the results. The statement "Used to provide feedback to physicians, not to diagnose" reinforces the human-in-the-loop aspect for diagnosis, but the measurement itself is standalone. The performance testing for K100233 would have established the accuracy of these standalone measurements.

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

Given that the device measures galvanic skin response, which is a physiological parameter, the ground truth for the original K100233 submission would likely have involved:

• Reference standards for conductivity measurements: Calibration against known electrical standards.
• Correlation with clinical conditions: For its intended use in assessing sudomotor function, the ground truth would have been established by comparing SUDOSCAN measurements with other validated methods for assessing sudomotor function or with clinical diagnoses of conditions affecting sudomotor function, possibly including expert clinical assessment or other established diagnostic tests.
• The provided document for K141872 does not specify the ground truth methodology for K100233.

8. The sample size for the training set

Not applicable. The document describes a 510(k) submission for an existing device with minor changes and expanded indications, relying on the previous clearance. It does not discuss a "training set" in the context of machine learning model development.

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

Not applicable, as this submission does not involve a machine learning model requiring a training set with established ground truth.

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SudoPath is a Galvanic skin response measurement device. The SudoPath provides values. It is the physician's responsibility to make proper judgments based on these numbers. The device is indicated for use in general adult population Prescription Use: Federal law restricts this device to sale by or on the order of a physician.

SudoPath is a programmable electro medical system including: USB plug and play hardware device including an electronic box, 2 reusable cables to connect the box to electrodes and 4 tactile electrodes placed on the sole of the feet and on the palm of the hands. Software installed on a computer. As a galvanic skin response measurement device, it measures the skin resistance (i.e., conductance).

The provided document is a 510(k) Premarket Notification for the SudoPath device, a Galvanic Skin Response (GSR) measurement device. It details the device's characteristics and compares it to a previously cleared predicate device (EIS-GS).

However, the document does not contain the information requested regarding acceptance criteria and the study proving the device meets those criteria in the context of AI/ML or comparative diagnostic performance.

Here's why and what information is missing:

• Type of Device: The SudoPath is described as a hardware device (with an electronic box, cables, and electrodes) and accompanying software for measuring galvanic skin response. This is a measurement device, not a diagnostic AI/ML system that would typically have acceptance criteria related to accuracy, sensitivity, specificity, or reader improvement.
• Focus of the 510(k) Summary: The summary focuses on demonstrating substantial equivalence to a predicate device. This is primarily achieved by showing that the SudoPath has the same intended use, similar hardware, and the same fundamental scientific technology as the predicate device. The "modifications" listed (change of trade name, removal of two frontal electrodes, and changes in software for number and sequence of measurements) are presented as minor and not affecting safety or effectiveness.
• "Performances and Effectiveness" Section: This section only lists:
  1. New risk management (generic for medical devices).
  2. Software verification (SRS/SDS/STD/STR - standard software development lifecycle documentation).
  3. Summary of Design Control Activities and Declaration of Design control conformity (again, standard quality system requirements).
     None of these refer to clinical performance studies, AI/ML model performance metrics, or human reader studies.
• Substantial Equivalence Justification: The conclusion explicitly states: "The SudoPath device is equivalent in performances, technology, safety and efficacy to the legally marketed (unmodified) predicate device." This equivalence is established through the technical comparisons provided, not through a comparative clinical study.

Therefore, I cannot populate the requested table or answer the specific questions about acceptance criteria, study data, ground truth, expert involvement, or MRMC studies because this information is not present in the provided 510(k) summary.

Specifically, the document DOES NOT provide:

1. A table of acceptance criteria and reported device performance (in terms of diagnostic accuracy, sensitivity, specificity, etc.) relevant to AI/ML or a diagnostic claim. The "performance" mentioned refers to the device's functionality and equivalence, not its diagnostic output accuracy.
2. Sample size used for the test set or data provenance because no clinical performance test set, in the sense of a diagnostic evaluation study, is described.
3. Number of experts used to establish ground truth or their qualifications.
4. Adjudication method.
5. Information on any Multi Reader Multi Case (MRMC) comparative effectiveness study or effect size of human readers improving with AI assistance. This device is a measurement device, not an AI assistance tool for image interpretation.
6. Information on standalone algorithm performance.
7. Type of ground truth used (expert consensus, pathology, outcomes data, etc.).
8. Sample size for the training set.
9. How ground truth for the training set was established.

The document primarily focuses on demonstrating that the changes made to the predicate device (EIS-GS) to create SudoPath are minor enough that new clinical performance data is not required, as it is fundamentally the same type of measurement device.

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The measurement of Galvanic Skin Response; Prescription Use

The ZYTO Hand Cradle is a Galvanic Skin Response Measurement Device. The device is designed, owned, manufactured, and distributed by ZYTO Technologies, Inc. The device consists of electrical circuit boards encased in a plastic/metal case. The device is non-invasive and comes in contact with the patient via conductive contacts (the equivalent of a stylus and hand-mass) incorporated into one piece, using the same functionality as the predicate device. The device connects to a computer to supply data to an operator.

The provided 510(k) summary for the ZYTO Hand Cradle describes performance testing conducted for substantial equivalence, but it does not provide specific acceptance criteria or a study demonstrating the device meets those criteria in the way typically expected for clinical performance evaluation (e.g., accuracy, sensitivity, specificity against a clinical gold standard).

Instead, the documentation focuses on bench testing for equivalency to a predicate device and electrical safety/EMC standards compliance.

Here's an analysis based on the provided text:

1. Table of acceptance criteria and reported device performance

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

• Bench Test: No specific number of "samples" (in terms of resistor values or repetitions) is stated, nor is the data provenance (e.g., country, retrospective/prospective) relevant for this type of test.
• Electrical Safety/EMC: Typically, one or a few units of the device are tested in a controlled laboratory environment. Data provenance is not applicable.

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

Not applicable. The "ground truth" for the bench test was the known values of the resistors and the performance of the predicate device. For electrical safety, the ground truth is defined by the technical standards. No human expert consensus was involved in establishing ground truth for these tests.

4. Adjudication method for the test set

Not applicable. There was no human judgment or adjudication process described for these engineering/bench tests.

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 MRMC study was performed. The device is a measurement tool, not an AI-assisted diagnostic output for human readers.

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

The device itself is a standalone measurement instrument. The "Non-clinical Testing" section describes its standalone performance against a predicate and against electrical safety standards. There is no "algorithm" in the sense of a complex AI for diagnostic interpretation. It is a direct physiological measurement device.

7. The type of ground truth used

• Bench Test: The ground truth was the known resistance values of the resistors used for testing and the measured output of a legally marketed predicate device (K943101 - GLOBAL ENT. GALVANIC SKIN RESPONSE DEVICE).
• Electrical Safety/EMC: The ground truth was the requirements and limits defined by international standards EN60601-1-2 and EN55011 CLASS B PCC Part 15B.

8. The sample size for the training set

Not applicable. This device is a measurement device and does not describe any machine learning or AI components that would require a "training set."

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

Not applicable, as no training set was used.

Summary of the "Study" and Evidence Provided:

The "study" demonstrating the device meets acceptance criteria consists of:

1. Bench Testing for Performance Equivalence: Conducted by ZYTO Technologies, Inc. This involved comparing the ZYTO Hand Cradle's readings of various resistors against those obtained from a predicate device. The conclusion was that the responses were "substantially the same."
2. Independent Third-Party Electrical Safety and EMC Testing: Performed by SDP Engineering in December 2010. This validated the device's compliance with EN60601-1-2 (Medical electrical equipment – Part 1-2: General requirements for basic safety and essential performance – Collateral standard: Electromagnetic disturbances – Requirements and tests) and EN55011 CLASS B PCC Part 15B (Limits and methods of measurement of radio disturbance characteristics of industrial, scientific and medical (ISM) radio-frequency equipment / FCC Part 15B, which governs electromagnetic compatibility). The device "met all testing requirements."

Conclusion:

The ZYTO Hand Cradle's 510(k) submission primarily relies on demonstrating substantial equivalence through engineering bench tests measuring its performance against a predicate device and adherence to electrical safety and electromagnetic compatibility standards. It explicitly focuses on the device's ability to measure Galvanic Skin Response, which is its stated intended use. The provided documentation does not detail a clinical study with patients, expert adjudication, or AI performance metrics, as these are not relevant for the type of device and the pathway used for its clearance.

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EIS-GS (Electro Interstitial Scan-GS) is a medical device for the measurement of galvanic skin response. The device is not intended to be used for any diagnosis. The data are stored in the PC in the backup system of the EIS-GS software. The device is intended for use only in healthy adult subjects. The device is intended for use only in practitioner's office and clinical setting. Prescription Use Caution: Federal law restricts this device to sale by or on the order of a physician.

The EIS-GS system is a programmable electro medical system including: USB plug and play hardware device including an electronic box, 6 disposable electrodes, reusable electrodes and reusable cables. Software installed on a computer. Protocol communication: USB port. Through the 6 tactile electrodes, a weak current with a very low frequency is sending alternatively between 2 electrodes with a sequence and the EIS-GS system is recording the electrical conductivity of 22 pathways of the human body. In accordance with the 21 CFR 882.1540, the EIS-GS system is a galvanic Skin response device that provides skin conductance measurements on the PC screen.

The provided document is a 510(k) Premarket Notification for the EIS-GS (Electro Interstitial Scan-Galvanic Skin) device. It describes the device, its intended use, and claims substantial equivalence to a predicate device (SUDOSCAN).

However, the document does not contain typical acceptance criteria for device performance in terms of clinical accuracy (e.g., sensitivity, specificity, accuracy against a gold standard) or the results of a primary clinical study designed to prove such performance.

Instead, the submission focuses on technical specifications, verification, validation, and safety standards to demonstrate substantial equivalence to an existing legally marketed device.

Here's a breakdown of the requested information based on the provided text, with clear indications where the information is not available:

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

• Record intensity changes of 22 body parts/pathways following weak current/tension (1.28V, very low frequency).
• Skin conductance measurement range: 1 to 120 micro Siemens (Predicate: 10 to 100 micro Siemens).
• Data acquisition duration: 120s.
• Electrical output to the skin: 1.28 V (Predicate: 4 V maximum).
• Electrical output unit duration: 1s.
• Power density at electrode:

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The SudoScan system is a medical device for the measurement of galvanic skin responses.

SUDOSCAN device is based on two well-known principles, reverse iontophoresis and electrochemistry. SUDOSCAN device collects physiological data by means of chronoamperometry and processes them with analysis software. SUDOSCAN device uses both technologies, coupled and complemented with exclusive software which analyzes cutaneous conductance data collected through the chronoamperometric measurements.

SUDOSCAN device is composed of:

• -> The analog acquisition electronic circuitry with low-noise front end
• → The multiplexing control unit for selecting the appropriate acquisition channels
• -> The signal formatting and processing capabilities

• The optically isolated USB interface controller

• -> The power converter,

• The connection circuitry to 6 electrodes placed on the feet, the hands and the forehead of the patient. is integrated into a customized touch-screen Windows XP-based Industrialgrade personal computer running the proprietary SUDOSCAN acquisition control and analysis software also responsible for archiving measurements taken on all patients.

The provided 510(k) summary for the Impeto Medical SUDOSCAN device focuses on demonstrating substantial equivalence to a predicate device (EDX Epi-Scan) for the measurement of galvanic skin response. It does not contain information about clinical studies with specific acceptance criteria that demonstrate device performance against a defined ground truth in a clinical context.

Therefore, many of the requested details regarding acceptance criteria, study design, expert involvement, and ground truth establishment are not available in this document.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state acceptance criteria in terms of clinical performance metrics (e.g., sensitivity, specificity, accuracy) or the results of a study designed to meet such criteria. It focuses on comparing the technical specifications of the SUDOSCAN to its predicate.

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

• Sample Size for Test Set: Not mentioned. The document refers to "verification of specifications and validation, including software validation," but does not detail a clinical test set or its sample size.
• Data Provenance: Not mentioned.

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

• Not mentioned, as a clinical test set with ground truth established by experts is not described.

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

• Not mentioned, as a clinical test set with ground truth is not described.

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 performed or mentioned. The SUDOSCAN device measures galvanic skin response and does not involve human readers interpreting images or data where AI assistance would be applicable in the context of an MRMC study. It is an objective measurement device.

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

• The device performs a standalone measurement of galvanic skin response. The "study" mentioned is "verification of specifications and validation," which implies technical performance rather than clinical performance against a diagnostic endpoint. No clinical standalone performance metrics (e.g., sensitivity, specificity) are reported.

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

• Not mentioned. For a device measuring galvanic skin response, ground truth would typically refer to the accuracy of the measurement itself against a known standard or a biological correlate. The document states "SUDOSCAN device is able to obtain measurements from a larger area at one time whereas EDX Epi-Scan obtains the measurements by taking several measurements over a period of time and then averaging the data," implying the "truth" is the physiological measurement.

8. The sample size for the training set:

• Not mentioned. This device does not appear to use a training set in the sense of machine learning/AI for diagnostic classification. It is a measurement device.

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

• Not applicable/Not mentioned, as no training set or its ground truth establishment is described.

Summary of what is available from the document:

The provided 510(k) summary focuses on demonstrating the technical equivalence of the SUDOSCAN device to its predicate, EDX Epi-Scan, for the purpose of measuring galvanic skin response. It highlights similarities in their intended use, measurement principles, and compliance with electrical safety and EMC standards. The "study" referenced is primarily non-clinical testing, including "verification of specifications and validation, including software validation," rather than a clinical study evaluating diagnostic performance against established acceptance criteria using a ground truth.

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The MSAS -- Vantage intended use is for the measurement of Galvanic Skin Response.

Not Found

This document is a 510(k) clearance letter from the FDA for a device called "MSAS - Vantage." It states that the device is substantially equivalent to legally marketed predicate devices.

However, this letter does not contain the information required to answer your specific questions about acceptance criteria and study details.

Here's why and what you would typically look for in such a document or related submissions:

• Acceptance Criteria and Reported Device Performance: This letter only confirms that the device is "substantially equivalent" but does not detail the specific performance metrics used for that determination or the achieved results against acceptance criteria. A 510(k) submission would typically include a comparative analysis of the new device to a predicate device, often using metrics relevant to the device's function. For a galvanic skin response measurement device, this might include measures of accuracy, precision, or repeatability compared to a standard.
• Study Details (Sample Size, Data Provenance, Ground Truth, Experts, Adjudication, MRMC, Standalone, Training Set): None of this information is available in the provided FDA clearance letter. These details would be found in the actual 510(k) submission, specifically in the sections detailing the studies performed to demonstrate substantial equivalence.

In summary, based only on the provided text, I cannot complete the table or answer the specific questions. The document is a regulatory approval, not a technical report on the device's performance study.

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For the measurement of galvanic skin response.

The development of the Epi-Scan P100 has been based on the combined principles of instrumentation and the electrophysiological effects of innervation of the sweat glands. This provides a noninvasive, painless instrument system fore the quantitative measurement of Selective Tissue Conductance, which has been operationally defined as "…the relative ability of biological tissue to conduct a weak (DC) electrical signal, which is applied for a selected period of time to a selected, limited and restricted surface area of that tissue ... " and which shares those same neuroanatomic reflex pathways as other tests of sympathetic skin activity or regional perspiration levels.

The provided text is a 510(k) premarket notification for the EDX Epi-Scan P100 device, which is a Galvanic Skin Response Measurement Device. This document primarily focuses on establishing substantial equivalence to a predicate device (K874850, Epi-Scan Selective Tissue Conductance Meter) and does not contain detailed information about acceptance criteria or a specific study proving the device meets particular performance metrics.

Therefore, many of the requested details about acceptance criteria, study design, sample sizes, expert qualifications, and ground truth establishment are not present in the provided text. The document is a regulatory submission for market clearance based on equivalence, not a direct report of a performance study with detailed statistical outcomes.

Here's what can be extracted based on the input, with clear indications where information is not available:

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

Explanation: The document does not provide specific quantitative acceptance criteria (e.g., minimum accuracy, specificity, sensitivity values) or numerical performance metrics. Instead, "acceptance" is framed within the context of substantial equivalence to a legally marketed predicate device. The claim is that the technological characteristics of the new device are similar to the predicate, implying that if the predicate performed adequately, the new device will as well.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample size for test set: Not provided. The document does not describe a clinical performance study with a test set of subjects or data.
• Data provenance: Not provided.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable. The document does not describe a study involving expert-established ground truth for a test set. Equivalence is claimed based on engineering and design characteristics compared to a predicate device.

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

• Not applicable. There is no described test set or adjudication process relating to clinical performance.

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 MRMC study was described. The device is a Galvanic Skin Response Measurement Device, not an AI-assisted diagnostic tool for human readers.

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

• The document implies standalone performance comparison of the device's characteristics against the predicate device's characteristics; however, this is not a detailed "standalone performance study" in the typical sense of algorithm-only evaluation for diagnostic accuracy. It's a review of technological features.

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

• Not directly applicable in the conventional sense of a clinical performance study. The "ground truth" for the substantial equivalence claim is the performance and characteristics of the legally marketed predicate device (K874850). The new device's characteristics (indications, skin conductance range, display, components, standards, software) are evaluated against those of the predicate device.

8. The sample size for the training set

• Not provided. The document does not describe a machine learning algorithm that would require a training set.

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

• Not applicable. No machine learning algorithm or training set is described.

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Output: The Anyra's intended use is for the measurement of Galvanic Skin Response

Galvanic Skin Response Device

The provided text is a 510(k) summary for the Asyra Galvanic Skin Response Device. This document focuses on establishing substantial equivalence to a predicate device and outlines safety features. It does not contain information about acceptance criteria or a study that proves the device meets specific performance criteria.

Therefore, most of the requested information cannot be extracted from the provided text.

Here's what can be stated based on the text:

1. Table of acceptance criteria and the reported device performance:

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• Not applicable. The document does not describe a performance study with a test set. It is a 510(k) submission based on substantial equivalence and safety features, not a clinical or performance study.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• Not applicable. There is no mention of a test set or ground truth establishment by experts in this document.

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

• Not applicable. There is no mention of a test set or adjudication.

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. This is a Galvanic Skin Response device, not an AI-assisted diagnostic tool. No MRMC study was conducted or is relevant here.

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

• Not applicable. This device is for measuring Galvanic Skin Response, which inherently involves human interaction (patient connected to electrodes). It does not appear to be an algorithm-only device in the context of advanced diagnostic interpretation.

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

• Not applicable. The document does not describe a study involving ground truth. The submission is based on substantial equivalence and safety rather than a performance study that requires ground truth.

8. The sample size for the training set:

• Not applicable. The document does not describe a machine learning or algorithm-based device that would require a training set.

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

• Not applicable. The document does not describe a machine learning or algorithm-based device that would require ground truth for a training set.

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