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The STM9000 is intended for stimulation of peripheral nerves for diagnostic purposes.

The STM 9000 are magnetic stimulators used for magnetic stimulation. Magnetic stimulation is a noninvasive technique for stimulating neural and cortical tissue. Application areas of magnetic stimulation are a subset of the application areas for current stimulation. The STM 9000 is connected to a magnetic coil which transfers the magnetic stimulation to the tissue. The STM 9000 consists of power electronics to generate the magnetic field in the magnetic coil. The STM 9000 is controlled via a simple user interface, enabling the operator to overview all functions, stimulus sequences, controls, status and measured data. The magnetic pulse is capable of biphasic and monophasic waveforms and the stimulate with a frequency up to 100 pulses per second (pps).

This document is a 510(k) Premarket Notification for the STM9000 device, which is an evoked response electrical stimulator. The purpose of a 510(k) submission is to demonstrate that a new device is "substantially equivalent" to a legally marketed predicate device. This type of submission relies heavily on showing that the new device has similar technological characteristics and performance to existing devices, rather than comprehensive clinical trial data for novel claims.

Therefore, the structure of the provided text does not contain the specific information typically found in a study proving a device meets acceptance criteria for an AI/Machine Learning (ML) enabled medical device. The STM9000 is a magnetic stimulator, and the performance data presented is focused on demonstrating its safety and basic functionality in comparison to a predicate device, as required for a traditional 510(k).

The document addresses:

• Biocompatibility Testing: To ensure the device materials are safe for contact with the human body.
• Electrical Safety and Electromagnetic Compatibility (EMC): To ensure the device operates safely in its electromagnetic environment and does not pose electrical hazards.
• Software Verification and Validation Testing: To ensure the software functions correctly and reliably, commensurate with its "Moderate" level of concern.

It does not contain the kind of performance data (e.g., sensitivity, specificity, AUC, accuracy) that would be derived from a study proving an AI/ML diagnostic or prognostic device meets acceptance criteria. There are no mentions of:

• A test set of patient data (e.g., images, physiological signals).
• Ground truth established by experts.
• Adjudication methods.
• Multi-reader multi-case (MRMC) studies or standalone algorithm performance.
• Training set details for an ML model.

Therefore, I cannot fulfill the request to provide a table of acceptance criteria and reported device performance, nor details about sample sizes, expert involvement, or MRMC studies, as this information is not present in the provided 510(k) document for the STM9000. The performance data provided is about the device's inherent safety and functional compliance, not its diagnostic or prognostic accuracy on a dataset.

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The GALILEO NT Line software is intended to record and display EEG, PSG, EMG and EP data acquired from the patient body through EBNeuro proprietary, FDA cleared, Acquisition Platform.(BE Plus LTM K121986, BE micro K093728, Nemus 2 system K133517.)

The device is intended to be used in the clinical and hospital environment (including the hospital room, emergency room, intensive care unit, neuro-intensive care unit) to aid the diagnosis and monitoring of potential disorders of the central and peripheral nervous system and muscles

Galileo NT Line is a software package running on a Personal Computer under Windows Operative System. This package is devoted to the complete management of various exams in the Neurodiagnostic field of application, as electroencephalography, electromyography, Evoked Potentials etc.

The product is essentially a suite of applications dedicated to the comprehensive management of neurological diagnostics in a Department of Neurophysiology, etc. ... starting from the patient's acceptance, the execution of specific tests, and finally to the production of the exam reports. The package is substantially made by a common "platform" and by various independent modules, each of which is devoted to a particular application (EEG, Video EEG, EMG, EP, ICU, etc.). All the parts of the package together with the related User Documentation are residing on the same distribution media (a DVD).

As illustrated by figure 1 below, GALILEO NT Line (simply Galileo NT in other documents of this submission) is a "software only device" that can control and acquire data from a series of (FDA cleared) Amplifier platforms developed by EBNeuro for the Neurodiagnostic field and specifically :

• 1. BE micro (K093728)
• 2. BE Plus LTM (K121986)
• 3. Nemus 2 (K133517)

For each of the above devices, Galileo NT provides the appropriate "software interface" module in order to allow the control of the Amplifier (and of all the accessories eventually provided with it, as, for example, the Evoked Potential stimulators embedded in the Nemus 1 and 2 hardware) and in order to collect the acquired data. The data, once acquired from the amplifier, are "passed" to the specialized module for successive handling as display, measure, printing, trending, archiving and so on.

The provided text is a 510(k) premarket notification for the EB Neuro Galileo NT Line software. This document primarily focuses on establishing substantial equivalence to predicate devices based on technological characteristics and intended use, rather than presenting a performance study with detailed acceptance criteria and results.

Therefore, the document does not contain the information requested regarding acceptance criteria and a study proving the device meets them in the format specified (a table of acceptance criteria and reported device performance, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or ground truth details for testing/training).

Specifically:

• 1. A table of acceptance criteria and the reported device performance: This information is not present. The document focuses on comparing the software's features and intended use to predicate devices, not on quantitative performance metrics with associated acceptance criteria.
• 2. Sample sized used for the test set and the data provenance: Not applicable, as a performance study of this nature is not described.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
• 4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
• 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 is a software package for recording and displaying physiological data, not an AI-powered diagnostic tool that assists human readers.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The device is a software suite for managing neurodiagnostic exams, not an algorithm with standalone diagnostic performance.
• 7. The type of ground truth used (expert concensus, pathology, outcomes data, etc.): Not applicable.
• 8. The sample size for the training set: Not applicable, as no algorithm training is described for diagnostic performance.
• 9. How the ground truth for the training set was established: Not applicable.

The document explicitly states under "Summary of Clinical Tests": "No clinical tests were performed." This further confirms that no performance study as described in your request was conducted for this 510(k) submission. The FDA clearance was based on substantial equivalence to existing devices and compliance with relevant industry standards (ISO 14971, IEC 62304, IEC 62366) for design and development, rather than a clinical performance study.

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The Nemus 2 System is intended to acquire the bioelectric signals produced by the patient's central and peripheral nervous system and muscles. The acquired signals are transmitted to a PC during recording of neurophysiology examinations. The Nemus 2 System consists of a physiological signal amplifier, an evoked response auditory stimulator, an evoked response electrical stimulator, and an evoked response photic stimulator. The user needs to assure compatibility of the Nemus 2 System to the other components of the user's own system.

The Nemus 2 System is made up of the Nemus 2 Amplifier/Stimulator, an AC/DC converter to power the amplifier, a "junction box" to connect the system to the Host PC, and (optionally) by a dedicate keyboard and a Flash LED stimulator.

The Nemus 2 System is intended to acquire bioelectric signals produced by the patient's central and peripheral nervous system and muscles. The acquired signals are transmitted to a PC during recording of neurophysiology examinations. The device may use electrical stimulus, sound stimulus, or visual stimulus for use in evoked response analysis.

The Nemus 2 System is an amplifier/stimulator device especially developed to amplify biological signals. The amplifier captures the biological signal from the human body through specialized sensors or electrodes, amplifies the very low electrical signal, and filters it to accomplish an antialiasing in order to make an optimal ANALOG to DIGITAL conversion. The data, once converted in numerical form, are "passed" to a host computer, which at this point is free to elaborate the data following the logic of the application software running on the host. The Nemus 2 System is not involved in the data management performed by the host.

Here's an analysis of the provided text regarding the Nemus 2 System's acceptance criteria and studies:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document (K133517) is a 510(k) summary for a medical device. In these summaries, acceptance criteria are typically presented as technical specifications that the new device must meet to demonstrate substantial equivalence to predicate devices. The study proving these criteria are met is usually a series of non-clinical bench tests.

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

• Sample Size: Not applicable in the context of this 510(k) summary for engineering verification. The "test set" here refers to the device itself and its components undergoing bench testing, not a dataset of patient cases.
• Data Provenance: Not applicable. The "study" described is verification testing against technical specifications, not a study involving patient data.

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

• Number of Experts: Not applicable. Ground truth as typically defined for medical AI (e.g., expert labels on images) is not relevant for this type of device and study. The "ground truth" for the verification testing is adherence to established engineering specifications and medical device safety standards.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The testing involves objective measurements against predefined technical specifications and safety standards, not a subjective interpretation requiring adjudication among experts.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of Human Readers Improving with AI vs. Without AI Assistance

• MRMC Study: No. This device is a physiological signal amplifier and stimulator, not an AI-powered diagnostic tool that would typically undergo MRMC studies to evaluate reader performance.
• Effect Size of Human Readers: Not applicable.

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

• Standalone Performance: Not applicable. This is a hardware device for acquiring and stimulating bioelectric signals, not an algorithm. Its performance is evaluated based on its ability to accurately amplify, filter, and stimulate according to its specifications.

7. The Type of Ground Truth Used

The "ground truth" for this device's acceptance is based on:

• Conformity to international electrical and medical device safety standards (e.g., IEC 60601 series).
• Demonstration through verification testing that the device meets its own established technical specifications for parameters such as noise, CMRR, IMRR, input impedance, and channel characteristics.
• Substantial equivalence to predicate devices (Nemus 1 and BE Plus LTM) based on technological characteristics and intended use.

8. The Sample Size for the Training Set

• Sample Size: Not applicable. This is not an AI/machine learning device. There is no "training set."

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

• Ground Truth Establishment: Not applicable. There is no training set or associated ground truth in this context.

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The BE Plus LTM / GWi Amplifier is intended to be used by or under the direction of a physician for acquisition of EEG, polygraphy and polysomnography signals and transmission of these signals to a PC during recording of neurophysiology examinations.

The BE Plus LTM / GWi amplifiers system, which has 64 channels, is an amplifier system which collects the bioelectric signals from the surface of the human body trough appropriate electrodes or sensors, intensify the very low signal captured (typically the amplitude range is of the order of the uVolts), condition them (filtering), convert them in numeric form and pass these data to the "host" elaboration unit (Personal Computer or equivalent system).

For these reason this device is not intended for a "direct" use by the physician but rather by a "manufacturer" or "System Builder" (a company or a researcher) which wants to build a "complete" medical device using the "BE Plus LTM / GWi" amplifier device as the "acquiring part" of the whole system.

BE Plus LTM / GWi is therefore intended to be assembled into an electromedical system by a System Builder, who will define the specific intended use of the assembled medical device.

Here's a breakdown of the acceptance criteria and study information based on the provided 510(k) summary for the BE Plus LTM/GWi Amplifier:

1. Table of Acceptance Criteria and Reported Device Performance:

The provided 510(k) summary for the BE Plus LTM/GWi Amplifier does not present a formal table of specific acceptance criteria with quantifiable metrics. Instead, it states that:

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

• Sample Size for Test Set: The document does not specify a sample size for any "test set" in the traditional sense of a clinical trial or large-scale data evaluation. The verification and validation activities described are more aligned with engineering and software testing.
• Data Provenance: Not applicable, as there isn't a "test set" of patient data described. The testing performed was non-clinical.

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

Not applicable. This device is a physiological signal amplifier, and the testing described is primarily technical and engineering-focused (software, wireless, EMC). There is no mention of "ground truth" being established by medical experts for a clinical test set in this 510(k) summary.

4. Adjudication Method for the Test Set:

Not applicable, as no clinical test set requiring expert adjudication is mentioned.

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

• No, an MRMC comparative effectiveness study was not done.
• Effect Size of Human Readers: Not applicable, as no such study was conducted. The device aims to acquire and transmit signals, not to provide diagnostic interpretations that would involve human readers.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

While the term "standalone" isn't explicitly used as such, the non-clinical performance data section effectively describes standalone testing of the device's technical functions and software. The device itself is described as an "acquiring part" of a larger system, indicating its primary function is data capture and transmission, not interpretation requiring a human-in-the-loop for its basic operation. The focus was on verifying its technical performance and capabilities (e.g., signal acquisition, wireless connectivity, software functionality) against predefined requirements and standards, not on its diagnostic accuracy as a standalone diagnostic tool.

7. Type of Ground Truth Used:

• For the non-clinical performance data, the "ground truth" was established by engineering specifications, functional requirements, and relevant industry standards (e.g., for software, wireless, and electromagnetic compatibility). The device's performance was compared against these established technical benchmarks.

8. Sample Size for the Training Set:

Not applicable. This device is a hardware amplifier with associated software. It is not an AI/ML algorithm that requires a "training set" of data for learning or pattern recognition.

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

Not applicable. As stated above, this device does not utilize a training set in the AI/ML context.

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BE micro/Trea intended use is collecting and recording physiological data to be used in neurology (EEG), polysomnography (PSG) and sleep disorder studies. The BE micro is intended for pediatric to adult population, and can be used either home or hospital environments. The BE micro/Trea is only to be used under the direction or supervision of a physician, or other trained health care professional.

The BE micro is manufactured by EBNeuro and intended for use in collecting and recording physiological data to be used in diagnosis in EEG (electroencephalography) and PSG (sleep disorder studies) clinical investigation. The BE micro is a portable multi-channel recording system that capture and digitally amplifies neurological (EEG) and/or Polysomnography (PSG) physiological activity and records the acquired data onto an internal NAND flash memory chip and/or sends those data directly to a PC via the USB port. The BE micro system is a small, lightweight recording system that is comfortable for the patient and simple for the clinician to set up. The Amplifier can be worn by the patient allowing in such way the patient to freely move or sleep while recordings are being made, allowing a more comfortable and efficient test.

The provided 510(k) summary for K093728 details the "BE micro/Trea" device, an electroencephalograph for collecting and recording physiological data in neurology and sleep studies. However, the document primarily focuses on establishing substantial equivalence to predicate devices through a comparison of technological characteristics and non-clinical performance data.

The document does NOT provide information regarding specific acceptance criteria for clinical performance, nor does it describe a study proving the device meets such acceptance criteria through clinical performance metrics (e.g., sensitivity, specificity, accuracy).

Instead, the "Summary of Non-Clinical Performance Data" section indicates:

• "Data to verify and validate the measurement algorithm and software functionality. RESULT: PASS"
• "Data to evaluate electrical safety and electromagnetic compatibility (per IEC 60601-1, IEC 60601-1-2, and other standards). RESULT: PASS"

This suggests that the performance requirements are related to the successful operation of the device's software and its compliance with electrical safety and EMC standards, rather than diagnostic accuracy or clinical effectiveness in identifying specific conditions.

Given the information provided, here's what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

As no explicit clinical performance acceptance criteria and corresponding reported performance are provided in the document, this table is based on the non-clinical performance data statements.

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

Not applicable from the provided document. The non-clinical performance data described relates to software functionality and electrical/EMC compliance, not a test set for clinical performance.

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

Not applicable from the provided document, as no clinical test set requiring expert ground truth is described.

4. Adjudication Method for the Test Set

Not applicable from the provided document.

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

No MRMC comparative effectiveness study is mentioned or summarized in the provided document.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No standalone performance study for an algorithm related to clinical diagnosis is described. The "measurement algorithm and software functionality" likely refers to the core processing of physiological signals rather than a diagnostic algorithm.

7. Type of Ground Truth Used

Not applicable from the provided document for clinical performance. For the described non-clinical tests:

• For software functionality, the "ground truth" would be the expected output or behavior according to design specifications.
• For electrical safety and EMC, the "ground truth" is compliance with the specific parameters and limits defined in the referenced IEC and other standards.

8. Sample Size for the Training Set

Not applicable from the provided document, as no machine learning algorithm development (with training/test sets) for diagnostic purposes is described.

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

Not applicable from the provided document.

Conclusion from document analysis:

The 510(k) summary for K093728 establishes substantial equivalence primarily through a comparison of technological characteristics with predicate devices and demonstration of compliance with engineering standards for software functionality, electrical safety, and electromagnetic compatibility. It does not contain information about clinical performance acceptance criteria or a clinical study proving that the device meets such criteria for diagnostic accuracy or effectiveness. This is typical for Class II devices like electroencephalographs, where substantial equivalence can often be demonstrated through technological and performance comparisons to existing legally marketed devices without requiring extensive de novo clinical performance studies for diagnostic accuracy.

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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).

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).

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.

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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Intended for use in collecting and recording physiological data to be used in polysomnography and sleep disorder studies. The Sandman Pocket is intended for pediatric through adult patient populations, and can be used in either home or hospital environments. The Sandman Pocket is not intended for use as life supporting equipment such, as a vital sign monitoring in an intensive care unit. The device does not produce alarms and is not intended as an automated apnea monitor. The Sandman Pocket is only to be used under the direction or supervision of a physician, technologist or clinician.

The Sandman Pocket is a physiological data recorder that is part of a polysomnography system. It consists of two units: the Recorder Unit, which stores the data and sends it to a USB port, and Headbox Unit, which is the connection point for all patient sensors with the exception of the Nellcor Puritan Bennett oximetry probe. The role of the Sandman Pocket is only to capture the data and pass it to the host with the necessary accuracy and reliability according to the product and communication control specifications. A fundamental characteristic of the Sandman Pocket is the ability to be an ambulatory/portable physiological data recorder. Because of its small size and light weight (about 210 grams including the battery), the system is compact and durable. The Headbox Unit is used for connecting patient electrodes and sensors. It includes Bipolar channels, pressure sensors, power supply for a dedicated body position sensor, an abdomen sensor, a chest sensor, a snore sensor and a thermistor. The patient inputs are isolated with a CF type isolation level. The Sandman Pocket device is provided without standard sensors. The system builder should integrate the device with FDA cleared Nellcor Puritan Bennett sensors only and specified for the usage with NELL-1 module. The Headbox Unit captures the biological signals from the human body surface through specialized sensors and electrodes, while the Recorder Unit amplifies the very low electrical signal and filters the signals to make an optimal ANALOG to DIGITAL conversion. The data, once converted in numerical form, are sent to a host computer for review and analysis. The host can "program" the amplifier behavior by setting the sampling frequency and the dynamic range allowed and so on. The host computer reads the acquired data through a dedicated interchange protocol, and allows a clinician to analyze the data using sleep review analysis software, provided by the end user or system builder. The clinician must use an electrically isolated computer (with a medical grade isolation transformer or medical grade power supply) or batterysupplied laptop when the Sandman Pocket device is connected to the host PC and the patient is connected to the Sandman Pocket Headbox. The Sandman Pocket system is not in any way involved in the data management performed by the host. The host computer must operate using one of the following Operating System: Microsoft Windows 98 / ME / NT / 2K / XP. The device has a built-in impedance meter. This function allows the clinician to check the electrode contact impedance and display the results of the check on the display. The display is located in the Recorder Unit, while the circuitry controlling the impedance meter is located in the Headbox Unit. The Sandman Pocket can be powered through 3 Alkaline 1.5V standard non rechargeable batteries or via the USB cable. The user is recommended to use a medical grade type PC. The Sandman Pocket system consists of two interconnected units: the Headbox Unit and the Recorder Unit.

The Sandman Pocket is a physiological data recorder intended for use in collecting and recording physiological data for polysomnography and sleep disorder studies in pediatric through adult patients, in both home and hospital environments. It is not intended for life support, vital sign monitoring in an ICU, or as an automated apnea monitor. It must be used under the direction or supervision of a physician, technologist, or clinician.

Here's an analysis of the provided information regarding acceptance criteria and the study:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document, a 510(k) summary, primarily focuses on demonstrating substantial equivalence to predicate devices rather than directly presenting a table of acceptance criteria and performance against those criteria in a typical evaluation study format.

However, the "Technological Characteristics Substantial Equivalence Comparison Table" implicitly serves to show that the performance characteristics of the Sandman Pocket are comparable to the legally marketed predicate devices, thereby meeting the unstated "acceptance criteria" of being as safe and effective as the predicates.

I will construct a table showing key performance characteristics of the Sandman Pocket alongside its predicate devices, as this is the closest equivalent to stated "acceptance criteria" through comparison. The "reported device performance" is implicitly shown to be acceptable by its similarity to the predicates.

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

The provided 510(k) summary does not contain information about a specific clinical study with a test set of patient data to evaluate the performance of the Sandman Pocket.

Instead, the submission relies on demonstrating substantial equivalence to predicate devices (Nellcor Puritan Bennett Inc. SUZANNE K990565 and Respironics, IN Alice S K040595) through direct comparison of technological characteristics, intended use, and conformance to recognized consensus standards (e.g., electrical safety, EMC).

Therefore:

• Sample size for the test set: Not applicable/Not provided, as a clinical performance study on patient data is not described.
• Data provenance: Not applicable/Not provided.

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

Since no clinical study with a test set requiring ground truth establishment is described in the provided document:

• Number of experts: Not applicable/Not provided.
• Qualifications of experts: Not applicable/Not provided.

4. Adjudication Method for the Test Set

As there is no described clinical study with a test set, there is no adjudication method mentioned.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study is not mentioned or described in the provided 510(k) summary. The submission focuses on substantial equivalence based on technical specifications and intended use comparison.

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

This device is a physiological data recorder, not a diagnostic algorithm. Its primary function is to capture and store physiological signals for subsequent review and analysis by a clinician using sleep review analysis software. It does not perform automated diagnoses or interpretations; therefore, a "standalone algorithm only" performance study, as typically understood for AI/CADe devices, is not relevant or described for this type of device.

The study presented focuses on the device's technical specifications - how accurately and reliably it records data, and its compliance with relevant safety and performance standards.

7. The Type of Ground Truth Used

As no clinical performance study involving diagnostic interpretation is described, the concept of "ground truth" (e.g., pathology, outcomes data, expert consensus) is not directly applicable in the traditional sense for evaluating the device's output. The device itself is recording raw physiological data, not producing interpretations that require a ground truth for validation. Its "truth" lies in its ability to faithfully capture the actual electrical signals.

The "ground truth" for the device's functioning is implicitly its adherence to:

• Its own product and communication control specifications for data capture accuracy and reliability.
• International standards for electrical safety (IEC 60601-1, UL 2601, CSA C22.2 No 601-1-M90), and electromagnetic compatibility (IEC 60601-1-2, etc.).

8. The Sample Size for the Training Set

The provided 510(k) summary does not describe any training sets as part of a machine learning or algorithmic development process. The Sandman Pocket is a hardware data acquisition device, and its design and verification are based on engineering principles and regulatory standards, not on model training with large datasets.

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

Since no training set is described, the method for establishing its "ground truth" is not applicable.

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The BE Plus / AURA-LTM64 Amplifier is intended to be used by or under the direction of a physician for acquisition of EEG, polygraphy and polysomnography signals and transmission of these signals to a PC during recording of neurophysiology examinations.

The BE Plus / AURA-LTM64 Amplifier is a fully programmable system which provides a total of 64 analog input channels each of which can be configured, amplified and converted to digital form (analog to digital conversion). The amplifier receives its power from a dedicated AC/DC adapter, meeting the IEC 60601-1 requirements, which feeds a +15VDC. Internally, the +15VDC is further isolated by a dedicated DC/DC CF type converter. The BE Plus / AURA-LTM64 Amplifier is intended to be used to amplify and filter bioelectric signals captured via a lead or transducer on the surface of the human body. It captures the data, converts it into a digital form and passes it on to a host computer running appropriate amplification software. Typical fields of application will be: Electroencephalograph (EEG), Evoked Potentials (EP), Polysomnography (Sleep Analysis) and General Polygraphy. The BE Plus / AURA-LTM64 Amplifier does not contains a Pulse Oximeter module. The host computer must use one of the following Operating Systems: Microsoft Windows 98, Microsoft Windows NT or Microsoft Windows XP. The BE Plus / AURA-LTM64 Amplifier system consists of three interconnected units: the amplifier box, the PC interface (PCMCIA interface or BE Net) and the AC/DC adapter; optionally the system may be completed by a led visual stimulator.

The provided text is a 510(k) Summary for a medical device (BE Plus / AURA-LTM64 Amplifier) seeking FDA clearance. It focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics and intended use. This type of submission document does not typically include detailed information about specific acceptance criteria or a dedicated study proving performance against those criteria in the way a clinical trial or performance study report would.

Therefore, I cannot extract the full scope of requested information from the provided text. However, I can provide what is explicitly mentioned or can be reasonably inferred from the document regarding "acceptance criteria" through a comparison to predicate devices.

Here's an analysis based on the available text:

The "acceptance criteria" for this 510(k) submission are fundamentally based on demonstrating substantial equivalence to legally marketed predicate devices, specifically the EB Neuro MIZAR Amplifier (K003154) and the EB Neuro Nic36 Amplifier (K041198). The study that "proves" the device meets these criteria is the comparison of technological characteristics presented in the 510(k) summary itself. The FDA's acceptance (issuance of a substantial equivalence determination) is the "proof" that these criteria have been met for market clearance.

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

The acceptance criteria are not explicitly stated as quantitative thresholds like in a performance study. Instead, they are implicitly defined by the characteristics of the predicate devices. The "reported device performance" is the description of the new device's characteristics.

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 in the 510(k) summary. 510(k) submissions demonstrating substantial equivalence, especially for devices like physiological signal amplifiers, typically rely on engineering testing to confirm specifications, not patient data in the sense of a clinical trial. The "test set" here refers to the device itself being tested against its specifications and then compared to the predicate.

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 and is not applicable to a 510(k) submission for a physiological signal amplifier based on substantial equivalence. There is no "ground truth" in the clinical sense established by experts as would be for an AI diagnostic device. The performance specifications are engineering parameters.

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

This information is not provided and is not applicable for this type of 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 comparative effectiveness study was not done. This device is a physiological signal amplifier, 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

No, a standalone algorithm performance study was not done. This device is hardware and associated firmware/software for signal acquisition, not a standalone algorithm.

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

The "ground truth" for this device's performance, in the context of a 510(k) submission for substantial equivalence, is essentially the engineering specifications and demonstrated performance of the predicate devices. The new device's performance characteristics (e.g., CMRR, noise, sampling rate) are measured and then compared to those of the predicates to show it is as safe and effective. It does not involve clinical "ground truth" from patient data.

8. The sample size for the training set

This information is not provided and is not applicable. This device is not an AI/ML model that requires a training set of data.

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

This information is not provided and is not applicable.

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The Nic36 Amplifier is intended to be used by or under the direction of a physician for acquisition of EEG, polygraphy and polysomnography signals and transmission of these signals to a PC during recording of neurophysiology examinations.

The Nic36 Amplifer is a fully programmable system which provides a total of 36 analog input channels each of which can be configured as monopolar or bipolar. The bioelectric signals are amplified and converted to digital form (analog to digital conversion). The amplifier receives its power from a dedicated AC/DC adapter which feeds a +15VDC. Internally, the +15VDC is further isolated by a dedicated DC/DC CF type converter.

The Nic36 Amplifier is intended to be used to amplify and filter bioelectric signals captured via a lead or transdaor on the surface of the human body. It captures the data, converts it into a digital format and transmits it on to a host computer running appropriate software. Typical fields of application will be: Electroencephalograph (EEG), Evoked Potentials (EP), Electromyography (EMG), Polysomnography (Sleep Analysis) and General Polygraphy.

The Nic36 Amplifier does not contain a Pulse Oximeter module.

The host computer must use one of the following Operating Systems: Microsoft Windows 98, Microsoft Windows NT or Microsoft Windows XP.

The Nic36 Amplifier system consists of three interconnected units: the amplifier box, the PCMCIA or BE Net interface and the AC/DC adapter; optionally the system may be completed by a led visual stimulator.

Here's an analysis of the provided text regarding the acceptance criteria and study information for the EB Neuro Nic36 Amplifier:

This 510(k) summary primarily focuses on establishing substantial equivalence to a predicate device (EB Neuro Mizar Amplifier K003154) rather than presenting a detailed independent study with specific acceptance criteria as you might find for a novel AI/software device. The information provided is characteristic of a Class II medical device where performance is compared against an already cleared predicate.

Therefore, many of your requested sections related to traditional study design, ground truth, and reader studies are not explicitly present or applicable in the provided text. I will fill in what can be inferred or explicitly stated.

Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly based on establishing substantial equivalence to the predicate device, the EB Neuro Mizar Amplifier (K003154). The Nic36 Amplifier's performance is considered acceptable if its technological characteristics and intended use are similar enough to the predicate such that it raises no new questions of safety and effectiveness.

Study Details:

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

   • Not Applicable. This submission is a 510(k) for a physiological signal amplifier, comparing its technical specifications to a predicate device. It does not involve a "test set" of patient data in the way an AI/software device would. The evaluation is based on engineering specifications and adherence to safety standards.

2. 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 in the context of expert medical interpretation for patient data is established or required for this type of device submission. The device's performance is measured against technical specifications and regulatory standards.

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

   • Not Applicable. See above.

4. 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 not an AI/software device designed to assist human readers, so an MRMC study is not relevant or included.

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

   • Not Applicable. The Nic36 Amplifier is a hardware device for signal acquisition and amplification; it is not an algorithm, and thus standalone performance for an algorithm is not relevant.

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

   • Not Applicable. For this submission, the "ground truth" or standard for comparison is the technical specifications and regulatory compliance of the predicate device (Mizar Amplifier K003154) and relevant international safety standards (IEC 601-1, IEC 601-1-2, IEC 601-2-26, IEC 601-1-4). The device's own performance is measured against these technical benchmarks, not clinical outcomes or expert consensus on patient data.

7. The sample size for the training set:

   • Not Applicable. This is a hardware device, not a machine learning algorithm, so there is no training set.

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

   • Not Applicable. This is a hardware device, not a machine learning algorithm, so there is no training set or ground truth for one.

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The SD20 Amplifier is intended to be used by or under the direction of a physician for acquisition of EEG, polygraphy and polysomnography signals and transmission of these signals to a PC during recording of neurophysiology examinations.

The Sandman SD20 Amplifer is a fully programmable system which provides a total of 22 analog input channels cach of which can be configured, amplified and converted to digital form (analog to digital conversion). The amplifier receives its power from a dedicated AC/DC adapter, meeting the IEC 601-1 requirements, which feeds a +15VDC. Internally, the +15VDC is further isolated by a dedicated DC/DC CF type converter.

The Sandman SD20 Amplifier is intended to be used to amplify and filter bioelectric signals captured via a lead or transducer on the surface of the human body. It captures the data, converts it into a digital form and passes it on to a host computer running appropriate amplification software. Typical fields of application will be: Electroencephalograph (EEG), Evoked Potentials (EP), Electromyography (EMG), Polysomnography (Sleep Analysis) and General Polygraphy.

The Sandman SD20 Amplifier contains a Pulse Oximeter module. The data measured from this module is passed to the host computer together with the other channels' data. The MP100 Pulse Oximeter module, developed by Nellcor Puritan Bennett, is substantially equivalent to Nellcor Puritan Bennett's MP400 Pulse Oximeter module cleared with EB Neuro's Mizar Amplifier via K003154.

The host computer must use one of the following Operating Systems: Microsoft Windows 98, Microsoft Windows NT or Microsoft Windows XP.

The Sandman SD20 Amplifier system consists of four interconnected units: the headbox, the amplifier box, the PC interface (BE Net/Sandman eLink) and the AC/DC adapter.

The provided text is a 510(k) premarket notification for the Sandman SD20 Amplifier. This document focuses on demonstrating substantial equivalence to a predicate device (EB Neuro Mizar Amplifier K003154) rather than presenting a standalone study with acceptance criteria and performance data in the traditional sense of a clinical trial or performance study for a diagnostic algorithm.

Therefore, the information requested regarding acceptance criteria, study design, sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, and training set details is largely not present in this type of regulatory submission.

The acceptance criteria in this context are implicitly that the new device (Sandman SD20 Amplifier) performs at least as well as, or is substantially equivalent to, the predicate device (EB Neuro Mizar Amplifier K003154) based on technological characteristics and intended use.

Here's an attempt to answer your questions based only on the provided text, highlighting where information is absent:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The provided document does not explicitly state "acceptance criteria" as performance metrics with thresholds like sensitivity, specificity, accuracy, or a specific signal quality benchmark. Instead, it presents a comparison of technological characteristics between the proposed device and its predicate, implying that performance is acceptable if these characteristics are substantially equivalent and meet established industry standards for physiological signal amplifiers.

Note on "Acceptance Criteria" interpretation: For a 510(k) of a device like a physiological signal amplifier, "acceptance criteria" are generally met by demonstrating that the device meets recognized standards (e.g., IEC 601-1) for electrical safety and EMC, and that its technical specifications (like noise, CMMR, sampling rate) are equivalent or better than a legally marketed predicate device for the same intended use. The table above reflects this comparison of technical specifications, as no specific performance outcomes (e.g., diagnostic accuracy for a specific condition) are being measured or reported in this document. The "Accepatance Criteria" column is essentially reflecting the specifications of the predicate device, which the new device aims to be substantially equivalent to or better than.

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

• Sample Size: Not applicable/Not mentioned. This document is for a physiological signal amplifier, not a diagnostic algorithm that processes patient data to generate a finding. The "test set" would refer to the device itself being tested for its technical specifications and compliance with standards.
• Data Provenance: Not applicable/Not mentioned. The document describes the device hardware and its intended use for capturing bioelectric signals, not the analysis of pre-existing patient data.

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

• Not applicable/Not mentioned. Ground truth in this context would be related to the accurate measurement of electrical signals, typically assessed through engineering tests and calibration against known standards, not by expert interpretation of patient data.

4. Adjudication method for the test set

• Not applicable/Not mentioned. Adjudication methods are typically associated with resolving discrepancies in expert interpretations of diagnostic images or clinical data, which is not the subject of this 510(k).

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/Not mentioned. This is a medical device (signal amplifier) and not an AI-powered diagnostic system or an aid for human readers. Therefore, an MRMC study is not relevant to this submission.

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

• Not applicable/Not mentioned. The device is a hardware amplifier; it does not contain a standalone algorithm for diagnostic interpretation in the sense of AI. Its function is to acquire and transmit signals to a host computer for further software processing by a physician.

7. The type of ground truth used

• Ground Truth: For a physiological signal amplifier, "ground truth" would be the known electrical properties and performance standards against which the device's technical specifications (e.g., noise, Common Mode Rejection Ratio (CMMR), sampling rate accuracy) are measured and verified during engineering and compliance testing. This document does not detail these specific tests but rather presents the device's measured characteristics.

8. The sample size for the training set

• Not applicable/Not mentioned. This device does not use machine learning or AI that requires a "training set" of data.

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

• Not applicable/Not mentioned. As there is no training set for an AI/ML algorithm, this question is not relevant.

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