Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K102166
    Date Cleared
    2010-12-10

    (130 days)

    Product Code
    Regulation Number
    882.1540
    Reference & Predicate Devices
    N/A
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    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.

    Device Description

    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.

    AI/ML Overview

    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

    Acceptance Criteria (Stated or Implied)Reported Device Performance/Evidence
    Functional Performance (Implied by equivalence)- Measures galvanic skin response.- 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: < 0.01 UA/mm2.
    Accuracy (Calibration)- Calibration tests (simulator) were performed. (Specific acceptance criteria for these tests and their numerical results are not provided).
    Software Functionality- Software verification (SRS/SDS/STD/STR) was performed. (Specific acceptance criteria and results are not provided).
    Electrical Safety- Passed IEC 60601-1-1 Ed: 2 (General requirements for safety - Collateral standard: Safety requirements for medical electrical systems).- Achieved Class II classification.- Degree of protection against electric shocks: BF.- Galvanic isolation between analog and digital parts (optocouplers, AC/AC converter).
    Electromagnetic Compatibility (EMC)- Passed IEC 60601-1-2 Ed: 2 (Medical Electrical Equipment Part 1-2: General Requirements for Safety – Collateral Standard: Electromagnetic Compatibility - Req. and Tests - Including Section 6 manual review).
    Substantial Equivalence to SUDOSCAN (K100223)- Same intended use and same technology as SUDOSCAN.- Comparison table provided showing similar specifications for power supply, data acquisition, power density, electrical classification, protection, sequence of measurement, anatomical site, cleaning, and standards met. Minor differences noted (e.g., skin conductance range, electrical output voltage, specific electrode sizes, display OS, output options).- Conclusion: EIS-GS is equivalent in performance, technology, safety, and efficacy to the predicate device.
    Intended Use Compliance- Will be used for measurement of galvanic skin response.- Not for diagnosis.- For healthy adult subjects.- In practitioner's office and clinical setting.- Prescription Use only.
    Risk Mitigation (Contraindications, Undesirable Side Effects)- Document lists contraindications (dermatological lesions, defibrillators/pacemakers, inability to sit, metal implants, pregnancy, absence of limbs, synthetic floor, low humidity, MRI/CT presence) and undesirable side effects (skin irritation/hypersensitivity). These are accepted as part of safe use by the FDA's clearance.

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

    • Not Available. The document primarily relies on technical verification and validation against standards and a comparison to a predicate device. It does not describe a clinical study with a "test set" of patient data for performance evaluation in terms of diagnostic accuracy or clinical outcomes. The "calibration tests (simulator)" are mentioned, but no sample size for a test set is 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/Available. Since no clinical test set with human subjects and a corresponding ground truth is described for performance evaluation, this information is not present. The device is for "measurement of galvanic skin response" and "not intended for use in any diagnosis," which suggests its performance isn't being assessed against a diagnostic ground truth established by experts.

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

    • Not Applicable/Available. No clinical test set requiring adjudication is 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

    • No. This device is a galvanic skin response measurement tool, not an AI-assisted diagnostic imaging device. Therefore, an MRMC study is not relevant and was not performed or described.

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

    • Not Applicable. The device itself is a standalone measurement tool (algorithms are integrated into its software to record and process the raw electrical conductivity data). The context of "standalone performance" often refers to algorithms designed to interpret data (e.g., detect disease) without human input, which is not the stated intended use of the EIS-GS (it measures, but does not diagnose). The performance mentioned relates to calibration and software verification, not clinical accuracy in a diagnostic sense.

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

    • Not Applicable. The document describes "calibration tests (simulator)" which would imply a known, controlled electrical input as a ground truth for verifying measurement accuracy. However, no specific details about this ground truth (e.g., standard reference resistors, known voltage/current outputs) are provided. For clinical claims or diagnostic accuracy, no such ground truth is mentioned because the device is explicitly not for diagnosis.

    8. The sample size for the training set

    • Not Applicable/Available. The document does not describe the use of machine learning or AI models that would require a "training set" in the context of typical AI device submissions. The device appears to be based on established physiological measurement principles and programmed algorithms rather than learned models.

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

    • Not Applicable/Available. As no training set for a machine learning model is described, this information is not relevant or provided.
    Ask a Question

    Ask a specific question about this device

    Page 1 of 1