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510(k) Data Aggregation

    K Number
    K073415
    Manufacturer
    Date Cleared
    2008-05-23

    (171 days)

    Product Code
    Regulation Number
    890.1375
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    NEMUS SYSTEM; NEMUS PC PERIPHERAL

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    NEMUS systems are diagnostic medical systems able to detect the electric signals produced by the peripheral nerve system and by skeletal muscles.

    The NEMUS system is intended to monitor, record and display the bioelectric signal produced by the muscles, to stimulate peripheral nerves, and to monitor, record and display the electrical activity produced by nerves to aid the clinician in the diagnosis and prognosis of neuromuscular diseases (EMG). The device may use electrical stimulus or sound stimulus for use in evoked response measurements (EP).

    Device Description

    There are two configurations of NeMus: NeMus System and NeMus PC Peripheral.

    The "Nemus system" is a complete system provided with a cart (expressly designed for this device and equipped with isolation transformer, the base unit support mobile arm, places for computer, keyboard, footswitch, printer, and dedicated keyboard and so on. The complete system provided of all the part ordered by the customer is completely wired, assembled and tested in factory before to ship to the final user. Like the hardware parts, all the needed software is installed and configured in factory.

    The "Nemus PC Peripheral" is a base kit (constituted by the NeMus 1 Amplifier the AC/DC adapter, cables and GALILEO NT management software) which, by adding a Personal Computer, becomes a digital electromiograph system. This configuration is developed and verified in order to allow a Distributor or the User to "build" an acquisition/processing EMG signal system by using the NeMus 1 acquisition module, the GALILEO NT/MYTOWIN management software and their own Personal Computer (and peripherals). However the PC must be compliant with EBNeuro specified minimum requirements. Of course the "system builder" must follow all the indications detailed in the related User Manual provided with the system. In this kind of system configuration, the "base kit" provided by EBNeuro is a sort of "peripheral" of a PC system. This configuration allows the Distributor or the User to use its own PC, cart or other "system" arrangement of its choice.

    NeMus systems are diagnostic medical systems able to detect the electric signals produced by the peripheral nerve system and by skeletal muscles.

    The Nemus system is intended to monitor, record and display the bioelectric signal produced by the muscles, to stimulate peripheral nerves, and to monitor, record and display the electrical activity produced by nerves to aid the clinician in the diagnosis of neuromuscular diseases (EMG). The device may use electrical stimulus or sound stimulus for use in evoked response measurements (EP).

    AI/ML Overview

    The provided text is a 510(k) summary for the Nemus System and Nemus PC Peripheral, which are electromyographs. This summary primarily focuses on establishing substantial equivalence to predicate devices and describes the device's technical characteristics and intended use.

    Crucially, this document does NOT contain information about specific acceptance criteria or a study designed to prove the device meets those criteria, as typically found in clinical validation studies. The information provided is for regulatory clearance based on substantial equivalence to existing devices, not a de novo clinical performance study against pre-defined performance metrics.

    Therefore, many of the requested points cannot be answered from the provided text. I will indicate where the information is not available.


    Acceptance Criteria and Device Performance (Not applicable directly from the provided text):

    The document does not specify quantitative acceptance criteria for device performance (e.g., sensitivity, specificity, accuracy, or specific thresholds for physiological signal capture). Instead, it relies on demonstrating that the device has similar technological characteristics to its predicate devices, implying comparable performance.

    The table below summarizes some key performance characteristics from the provided comparison table, but these are typically specifications, not acceptance criteria against which a clinical study would be measured in this context.

    Product Characteristic (Performance-Related)Acceptance Criteria (Not Explicitly Stated as such in the document)Reported Device Performance (Nemus System)
    Acquisition
    CMRR (Common Mode Rejection Ratio)Comparable to predicate (>100 dB for PHASIS, >110 dB for Sinergy LT)>100 dB
    NoiseComparable to predicate (100 MOhm for PHASIS, >1000 MOhm for Sinergy LT)> 1000 MOhm / 8 pF
    A/D conversionComparable to predicate (16 bit for both predicates)24 bit Sigma-Delta
    Sampling rateComparable to predicate (0.5 µs max for PHASIS, 50 kHz for Sinergy LT)4.194 MHz
    Ohmmeter rangeComparable to predicate (0-100 kOhm for PHASIS, 0-32 kOhm for Sinergy LT)0-100 kOhm (auto full scale)
    Stimulators
    Max output (Somatosensory Elec. Stimulator)Comparable to predicate (100 mA for both predicates)100 mA
    Pulse width (Somatosensory Elec. Stimulator)Comparable to predicate (0.01-1 ms for PHASIS, 0.05-1 ms for Sinergy LT)0.05 - 1 ms
    Sound pressure (Audio Stimulator)Comparable to predicate (20-132 dB SPL for PHASIS, 0-122 dB SPL for Sinergy LT)0-132 dB SPL

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

    As mentioned above, the 510(k) summary does not define specific "acceptance criteria" in the way one might expect for a clinical performance study. Instead, the "performance" is presented as technical specifications and compared to predicate devices for the purpose of demonstrating substantial equivalence. The table above provides the most relevant performance characteristics available.


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

    Not Applicable. The provided document is a 510(k) summary for regulatory clearance based on substantial equivalence. It does not describe a clinical performance study with a test set of patient data. The "testing" involved appears to be related to engineering specifications and safety standards (e.g., IEC 60601-1).


    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. No ground truth establishment is described, as there is no mention of a clinical test set or human interpretation being evaluated.


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

    Not Applicable. No adjudication method is described, as there is no mention of a clinical test set or human interpretation being evaluated.


    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. This document pre-dates widespread AI integration in medical devices (2008) and does not describe any MRMC studies or AI assistance features. It is purely an electromyograph device.


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

    Not Applicable. This device is an electromyograph, which assists clinicians in diagnosis, but it is not an AI algorithm performing diagnostic tasks in a standalone capacity. Its performance is measured by its ability to accurately acquire and display bioelectric signals.


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

    Not Applicable. No ground truth is described, as the document focuses on the device's technical specifications and substantial equivalence, not a clinical validation study against a pre-defined diagnostic gold standard.


    8. The sample size for the training set:

    Not Applicable. There is no mention of a training set, as the device is not based on machine learning or AI that would require such data.


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

    Not Applicable. No training set is mentioned in the document.

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