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Neuromuscular electronic stimulator indicated for use under medical supervision for adjunctive therapy in the treatment of medical diseases and conditions.

As powered muscle stimulator:

• Temporary Relaxation of muscle spasms
• Prevention or retardation of disuse atrophy
• Increasing local blood flow in the treatment area
• Muscle re-education
• Prevention of post-surgical phlebo-thrombosis through immediate stimulation of calf muscles
• Maintaining or increasing range of motion

As external functional neuromuscular stimulator:

• Helps to relearn voluntary motor functions of the extremities
  The device must be used by trained and qualified personnel.

The g.Estim FES is a constant-current powered muscle stimulator that can deliver rectangular electrical pulses with alternating polarities, lengths and amplitudes, or trains of such pulses. The device is battery supplied and can be connected via USB to a computer. It can be triggered via software or with a hand or foot switch.

The programmable parameters of the stimulator are: frequency, current, pulse width, ramp up and down and session length. The phase width and the stimulation current can be changed during stimulation; the other parameters can only be changed when the stimulator is stopped. Stimulation can be started and stopped using a configurable ramp for smooth on- and offsets. A LED shows the stimulus onset.

The system consists of the stimulator, a USB connector cable to connect the device to a host computer, patient cables for electrode connection and a software package including the driver and a graphical user interface. Optional trigger out cables and trigger in cables as well as a hand switch and foot switch to trigger the stimulator are available. The device stops stimulation if an over-load is detected or the electrodes are disconnected.

A foot switch or hand switch can be used to trigger the stimulator.

The device can perform an impedance measurement to check the electrodes impedance before the stimulation is done and can measure the actual stimulation current when a stimulation is done. The impedance measurement is done quickly so that the stimulation can rapidly be performed. If a high impedance is detected the stimulator does not stimulate.

g.Estim FES works in the same manner as the approved predicate devices.

The provided document is a 510(k) summary for the g.Estim FES device, a neuromuscular electronic stimulator. It details various technical characteristics of the device and compares them to predicate devices to demonstrate substantial equivalence, rather than providing an independent study report with acceptance criteria and performance against those.

Therefore, many of the specific questions about acceptance criteria for an AI/ML device study, such as sample size for test/training sets, expert ground truth establishment, MRMC studies, or standalone performance, are not directly applicable or answerable from this document, as it concerns a physical medical device (electrical stimulator) which relies on demonstrating technical similarity and compliance with safety standards rather than AI performance metrics.

However, I can extract the relevant information regarding acceptance criteria (in the context of demonstrating substantial equivalence to predicate devices) and the "study" or testing that proves the device meets these "acceptance criteria" as described in this 510(k) summary.

Device: g.Estim FES (Neuromuscular Electronic Stimulator)

Regulatory Submission: 510(k) Premarket Notification (K200088)

In the context of this 510(k) submission for a non-AI medical device, "acceptance criteria" refer to the technical specifications and safety standards a new device must meet or demonstrate substantial equivalence to, compared to legally marketed predicate devices. The "study" involves technical testing and comparison against these predicate devices.

Here's the information extracted and re-framed to address your request, acknowledging the nature of the device and its regulatory pathway:

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

The "acceptance criteria" for this conventional medical device are implicitly defined by the technical specifications of the predicate devices and relevant safety standards (IEC 60601 series). The "reported device performance" is the g.Estim FES's measured technical characteristics. The document presents a comparative table (starting on page 6 and continuing through page 14) that serves this purpose.

Below is a summarized version of key performance characteristics and their comparison, focusing on how the g.Estim FES meets the "acceptance criteria" by demonstrating equivalence or adherence to standards.

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The system is intended to statistically evaluate brain activity reflected in a broad band of high-gamma frequencies in the human electroencephalogram (EEG). These measures should always be interpreted in conjunction with review of the original EEG waveform.

cortiQ PRO is intended for the evaluation of intracranial EEG recorded with the g.Hlamp.

cortiQ PRO is a system that uses g.Hlamp to map high-gamma broad band brain activity while running an experimental paradigm. The software helps to identify electrode positions coding differences in brain activity by means of experimental paradigm. cortiQ PRO performs the signal analysis in real-time and compares the highgamma broad band activity during specific tasks. Then it performs a statistical analysis and visualizes electrodes coding the information that are statistically significant. It is abstracted from technical details of data acquisition, channel order and signal processing assuring robust and efficient measurements.

cortiQ PRO reads in the digital data from the g.Hlamp amplification system (1200 Hz sampling frequency, up to 256 channels) via USB into the processing computer. The data is acquired without bandpass and notch filtering and without bipolar derivation. The software allows one to select the channels that should be acquired and stores the raw data together with header information for later off-line analysis.

Raw data is visualized on a raw data scope to inspect the data quality. The scope allows scaling of the data in amplitude and time. Furthermore the software allows scaling of all the channels to the same amplitude to make the interpretation easier. In the scope, it is possible to select a new ground and reference channel and to exclude a channel from the processing (if the data quality is bad). The raw data scope filters the data with a high-pass filter to remove DC-offsets for optimal visualization.

cortiQ PRO allows the operator to select an experimental paradigm that instructs the patient to perform certain tasks. The instructions are presented on a patient computer screen or are given via a speaker. The user can select, start and terminate the experimental paradigm. Additionally, the number of repetitions can be selected. A dedicated paradigm editor creates new paradigm files or modifies existing paradigms.

The rapid cortical mapping functions perform a common average reference (CAR) of all the active channels to remove common mode signals such as power line interference. Then the module calculates the high-gamma activity in certain frequency ranges for the different tasks and compares the high-gamma activity to those of another task according to the selected paradigm. Then a statistical analysis is performed and significant activation is plotted as bubble on the defined electrode position in order to identify important regions. When the mapping has ended, cortiQ PRO automatically generates a mapping report containing the montage definition, the paradigm definition, and the mapping results. This report is stored as pdf and can be printed. The mapping result is also stored for later analysis.

cortiQ PRO allows the operator to define montage definition files in the montage creator by loading predefined electrode grids from different manufacturers. Each grid has a certain number of channels. The montage creator allows the operator to assign a patient's name and date of birth, and a montage name to each file. Furthermore, it allows the operator to assign a grid name to each electrode grid. The grids can be placed on different background images to make the location interpretation easier. Electrodes from a grid can be disabled, used as reference or as ground electrodes. The grids can be resized or rotated. The montage creator assigns also the electrode grids automatically to the amplifier inputs channels and creates a report with the channel definition. The results can be stored to be modified later. The report is stored as pdf and can be printed.

cortiQ PRO comes with an installs the software under Windows. A hardlock is required to start the mapping software.

The mapping system comes with Instructions for use and a training program.

The provided 510(k) summary for the cortiQ PRO device does not contain a detailed study with specific acceptance criteria and reported device performance metrics in a tabular format as typically found in comprehensive clinical or performance studies. Instead, it offers a general statement about performance testing.

Here's an attempt to extract and present the information based on the available text:

Acceptance Criteria and Device Performance

The documentation states: "The testing showed that the difference in gamma activity can be correctly mapped to correct electrode channels." This is the primary functional performance claim related to the core function of the device in evaluating high-gamma brain activity. However, specific quantitative acceptance criteria (e.g., sensitivity, specificity, accuracy, precision, or minimum R2 values) are not explicitly provided in the given text, nor are specific reported device performance metrics in a tabular format.

Table 1: Acceptance Criteria and Reported Device Performance (as inferred)

Study Details

The provided text describes performance testing, but not a formal clinical study with detailed methodology typically associated with "acceptance criteria" and "device performance" in a quantitative sense.

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

   • Test Set: "several real electrocorticographic (ECoG) and artificial test signals." No specific number is given for "several."
   • Data Provenance: Not specified, but "real electrocorticographic (ECoG) data" would likely be from human subjects, potentially clinical. "Artificial test signals" are generated. Whether these ECoG data were prospective or retrospective is not stated. Country of origin is not specified.

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

   • This information is not provided in the document. The ground truth for artificial signals is inherent in their design. For real ECoG data, how "task-related differences" were confirmed as ground truth is not detailed, nor is the involvement of experts in establishing this ground truth.

3. Adjudication method for the test set:

   • This information is not provided. Given the nature of the testing described (mapping gamma activity), it's unclear if an adjudication method between multiple readers/interpreters was necessary or employed.

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:

   • A multi-reader multi-case (MRMC) comparative effectiveness study is not mentioned in the document. The cortiQ PRO is described as a system for statistical evaluation and visualization of brain activity, intended to be interpreted in conjunction with review of the original EEG waveform and dependent upon the judgement of the clinician. This implies human-in-the-loop, but without a formal MRMC study evaluating improvement with AI assistance.

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

   • The description of the testing ("The testing showed that the difference in gamma activity can be correctly mapped...") suggests performance validation of the algorithm's ability to identify and map differences in gamma activity. This can be interpreted as a form of standalone performance evaluation for its core function. However, the device's indications for use emphasize that measures "should always be interpreted in conjunction with review of the original EEG waveform," implying it is not intended for fully standalone diagnostic interpretation.

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

   • For artificial test signals: The ground truth is the inherent design of the signals, where "lower amplitude in the task baseline interval" and "higher amplitude in the action interval" on specific channels define the expected difference.
   • For real electrocorticographic (ECoG) data: The ground truth relies on "task-related differences in the high-gamma frequency band." How these differences are definitively established as "ground truth" (e.g., through other modalities, expert consensus, surgical outcomes) is not explicitly stated.

7. The sample size for the training set:

   • This information is not provided. The document describes performance testing but does not detail the development or training of the algorithm that identifies "high-gamma broad band brain activity."

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

   • This information is not provided as details about a training set are absent.

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The g.Estim PRO is intended for functional brain mapping via electrical stimulation prior to cortical resections in the vicinity of essential cortex. The device must be used by trained and qualified personnel within a medical environment.

The g.Estim PRO is a neural, constant current, monophasic stimulator for electrical stimulation of the brain (cortical stimulator). The device is battery supplied and can be controlled via USB from a computer. It can be trigged via software or with external devices and can provide beside the stimulation pulse also trigger signals for other devices. The system consists of the stimulator, a USB connector cable to connect the device to a host computer, trigger out cables and trigger in cables, the driver and software package (including a graphical user interface and communication interface). Additionally the device can be triggered with a hand switch and/or foot switch. The stimulator can be programmed and is a constant-current stimulator that can deliver electrical pulses with alternating polarities, lengths, amplitudes or trains of such pulses. The device is connected via USB to a computer and on the computer stimulator settings can be performed. On the computer a graphical user interface allows to perform all settings required for the stimulator. The stimulator is battery powered and has an optical isolation from the computer for safety reasons. A LED shows the stimulus time point. The stimulator allows to send trigger pulses to external devices to synchronize the stimulus e.g. with EEG data acquisition devices. Such a trigger pulse can be programmed to occur prior to the stimulus so that e.g. a switching unit can switch before the stimulus occurs and can last longer than the electrical pulse to switch back after the pulse. Furthermore the triggers can be perfectly aligned with the stimulus so that an accurate trigger signal can be sent to the external device. The trigger lines are TTL compatible. Two trigger lines are supported. The stimulus can be triggered via the software running on the computer or via external inputs to the stimulator. Important is that the stimulus is triggered very accurately for perfect synchronization. A foot switch or hand switch can be used to trigger the stimulator. The trigger input is TTL compatible. One trigger line is supported. The device can perform an impedance measurement to check the electrodes impedance before the stimulation is done and can measure the actual stimulation current when a stimulation is done. The results are shown in the graphical user interface and can be passed also to other applications via an interface. The impedance measurement is done quickly so that the stimulation can rapidly be performed. If a high impedance is detected the stimulator does not stimulate. g. Estim PRO works in the same manner as the approved and predicate device.

Based on the provided text for the g.Estim PRO, here's a description of the acceptance criteria and the study proving the device meets them:

Disclaimer: This device, "g.Estim PRO," is a cortical stimulator, not an AI-powered diagnostic device. Therefore, many of the typical acceptance criteria and study aspects related to AI (e.g., ground truth establishment for AI, MRMC studies, training/test sets for AI, effect size of human reader improvement with AI) are not applicable to this submission. The provided text describes a traditional medical device submission focused on demonstrating substantial equivalence to a predicate device primarily through technical specifications, safety, and functionality.

Acceptance Criteria and Device Performance for g.Estim PRO

This submission demonstrates substantial equivalence to a predicate device (Chatten Associates S12X, K082629). The "acceptance criteria" for this type of submission are implicitly tied to demonstrating that the new device is as safe and effective as the predicate, despite minor differences. The performance is assessed by comparing technical specifications and functionalities.

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) Summary includes a comparative table (Section 807.92(a)(6)) that serves as the basis for demonstrating substantial equivalence. The "acceptance criteria" are the features and performance parameters of the predicate device, and the "reported device performance" are the corresponding features and parameters of the g.Estim PRO.

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

For this traditional medical device submission, there isn't an "AI test set" in the sense of a dataset of patient images or physiological signals. The "test set" consists of the physical device and its components, which were subjected to various engineering tests to verify their functionality and safety according to defined specifications and standards.

• Sample Size: The sample size for testing would typically be a specific number of manufactured units of the g.Estim PRO device. The text does not specify the exact number of units tested, but it is implied that a sufficient number were tested to demonstrate reliable performance.
• Data Provenance: The tests are performed in a laboratory/engineering environment. The "data" provenance refers to the results of these technical and safety tests. The device manufacturer, g.tec medical engineering GmbH, is based in Austria (Europe). The tests would have been conducted by the manufacturer or accredited testing facilities. The data is prospective, generated specifically for this submission.

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

This is not applicable as the submission is for a medical device (cortical stimulator), not an AI diagnostic tool requiring ground truth established by medical experts on patient data. The "ground truth" for this type of device is its adherence to engineering specifications, safety standards, and functional requirements, which are verified through technical measurements and testing. This is typically done by qualified engineers and technicians.

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

Not applicable for a non-AI medical device testing, as there are no interpretations of medical images/data that require adjudication. Functional and safety tests have pass/fail criteria.

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 not an AI-powered device, and it does not involve human readers interpreting medical cases.

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

Not applicable. This is a medical device, not an algorithm. Its performance is inherent to its physical and software functionality. The text states:

• "The stimulator was tested with a data acquisition device and provides rectangular stimulation pulses with the necessary frequency and amplitude range."
• "Furthermore digital outputs were tested to provide trigger signals and digital inputs were tested to trigger the stimulation."
• "The impedance measurement was tested with test impedances."

These describe standalone functional tests of the device's hardware and integrated software.

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

The "ground truth" for this device is primarily the predefined engineering specifications, functional requirements, and relevant safety standards (e.g., IEC 60601-1, IEC 60601-1-2, IEC 60601-2-40, ISO 14971, IEC 62304, IEC 62366). The device's performance is verified against these objective, measurable criteria.

8. The sample size for the training set

Not applicable. This is not an AI device trained on a dataset.

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

Not applicable. There is no AI training set for this device.

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The g.Nautilus PRO is intended to be used to acquire the electroencephalogram (EEG) and transmit it wirelessly to a computer.

g.Nautilus PRO is g.tec's bio-potential amplifier with wireless data transmission technology. The device allows the acquisition of up to 32 EEG (Electroencephalogram) channels with 24 bit resolution. The sampling frequency can be set up to 250 or 500 Hz. g.Nautilus PRO is available with 8-32 channels. The wireless amplifier is transmitting data to a PC or notebook with 2.4 GHz technology. On the computer a receiver unit is connected with USB. Up to 32 analog to digital converters perform the simultaneous sampling. The sampling frequency can be set to 250 Hz or 500 Hz. Each analog to digital converter is operating with 1.024 MHz and performs a 2048 times oversampling for 500 Hz. A sampling frequency of 250 Hz vields to an over-sampling rate of 4096 with a very high signal to noise ratio. Furthermore, the device has an internal impedance check unit. g.Nautilus PRO works with either active gel or active dry electrodes and comes with an EEG cap with chinstrap. The device is controlled via its driver and application programming interface (API), which is part of the g.tec device service g.NEEDaccess. The device is battery supplied. The g.Nautilus PRO is intended to be used to acquire the electroencephalogram (EEG) and transmit it wirelessly to a computer. It captures the data, converts it into digital form and passes it on to a host computer running appropriate software. The device can be used for adults, children and infants. The host computer must use Microsoft Windows. g.Nautilus PRO comes with a C Application Programming Interface (C API) which allows to control the device. The system consists of the charging device, the g.Nautilus PRO Headset (the amplification and digitization unit with EEG electrodes, cap and chin-strap), the receiver unit (with USB connector cable to connect the device to a host computer), the driver and the C API software. g.Nautilus PRO works in the same manner as the approved and predicate device.

The provided document, K171669, is a 510(k) premarket notification for the g.Nautilus PRO device. This type of submission is for demonstrating substantial equivalence to a predicate device, not for proving a device meets specific acceptance criteria through a clinical study as might be done for a novel or higher-risk device. Therefore, much of the requested information regarding "acceptance criteria and the study that proves the device meets the acceptance criteria" in terms of clinical performance, ground truth, expert consensus, MRMC studies, or training/test sets is not typically found or required in a 510(k) summary for a physiological signal amplifier unless clinical performance is a new claim or a significant change in the intended use.

The document focuses on demonstrating technical equivalence and safety and effectiveness compared to predicate devices through technical specifications and adherence to standards.

However, I can extract the following information relevant to the device's technical performance and how it meets its intended use, framed within the context of a 510(k) submission:

Device: g.Nautilus PRO (Physiological Signal Amplifier for EEG)

Intended Use (from the document): The g.Nautilus PRO is intended to be used to acquire the electroencephalogram (EEG) and transmit it wirelessly to a computer.

1. Acceptance Criteria and Reported Device Performance

The "acceptance criteria" in a 510(k) context for this type of device are primarily compliance with technical specifications comparable to predicate devices and adherence to relevant safety standards. The document doesn't present these as explicit "acceptance criteria" in a table with performance targets for a clinical study, but rather as comparative technical specifications to demonstrate substantial equivalence.

Here's a table comparing the g.Nautilus PRO (This Submission) against its primary predicate device, g.HIamp K123255, based on the "Technological Characteristics" table provided. The "Substantial Equivalence Comments" indicate how the new device's performance is deemed acceptable (i.e., "equivalent in safety and effectiveness") despite differences.

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

The document describes bench testing rather than a clinical study with a "test set" in the sense of patient data.

• Test Sample: The amplifier itself was tested. The "sample size" is effectively n=1 (the g.Nautilus PRO device).
• Data Provenance: Not applicable as it's not patient data. The testing was performed by applying "sinusoidal signals with different frequencies and amplitudes to the inputs of the amplifier" using an "external signal generator." This suggests laboratory-based, controlled input signals.

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

Not applicable. This was a 510(k) focused on technical equivalence and safety standards, not an AI or diagnostic device requiring expert review of output. The "ground truth" for the performance tests was the known characteristics of the input signals from the external signal generator.

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

Not applicable. No human adjudication was involved as the test was based on comparing measured electrical signals against known input signals and technical specifications.

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 device is a physiological signal amplifier, not an AI-assisted diagnostic tool for interpretation of medical images or signals by human readers.

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

The "standalone" performance here refers to the device's ability to accurately acquire and transmit EEG signals. The document states:

• "The amplifier was tested with an external signal generator which applies sinusoidal signals with different frequencies and amplitudes to the inputs of the amplifier."
• "The correct signal transmission and amplification was determined with Bode plots for each channel."
• "The impedance measurement was tested with test impedances."
• "Noise was tested by short-cutting the input channels."
• "The tests show that the signal quality is appropriate for EEG measurements and that impedance measurements are accurate."

This constitutes a form of "standalone" functional and performance testing of the hardware.

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

For the technical performance tests, the ground truth was the known, precisely controlled electrical signals generated by an external signal generator and the expected device outputs based on its design specifications.

8. The sample size for the training set

Not applicable. This is a hardware device (physiological signal amplifier) and does not involve machine learning or a "training set" in the context of AI.

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

Not applicable (as above).

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The g.Hlamp amplifier is intended to be used to acquire biopotentials and transmit them to a computer via the USB port connection. These biopotentials include for example electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG), and electrocardiogram (ECG).

The g.Hlamp is a fully programmable system which provides a total of 256 analog input channels each of which can be configured, amplified and converted to digital form (analog to digital conversion). The applied part is digitally isolated. The amplifier receives its power from a dedicated AC/DC adapter, meeting the IEC 601-1 requirements, which feeds in +5V DC. Internally, the +5V DC is further isolated by a dedicated DC/DC type converter.

The g.Hlamp amplifier is intended to be used to acquire biopotentials and transmit them to a computer via the USB port connection. These biopotentials include for example electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG), and electrocardiogram (ECG). It captures the data, converts it into digital form and passes it on to a host computer running appropriate software. The device can be used for adults, children, infants and animals. The host computer must use Microsoft Windows 7. g.Hlamp comes a driver and with a C Application Programming Interface (C API) which allows to control the device.

The system consists of the AC/DC adapter (power supply unit), g.HIamp (the amplification and digitization unit), electrode connector boxes with cables to the g.HIamp (to connect EEG electrodes), a USB connector cable to connect the device to a host computer and the driver and C API software.

The g.Hlamp device is a physiological signal amplifier. The provided text describes its 510(k) premarket notification. Here’s an analysis of the acceptance criteria and the study conducted:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to a predicate device (g.USBamp K060803) rather than defining specific numerical acceptance criteria for clinical performance. The "acceptance criteria" are implied by comparing the g.Hlamp's technical specifications and intended use against those of the predicate device, as well as by adherence to relevant safety standards.

Study Details:

Since the g.Hlamp is a hardware device for acquiring raw biopotential signals (amplifier), and not an AI or diagnostic algorithm, many of the typical study criteria for AI/ML or diagnostic devices do not apply.

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

  • Test Set: No patient or clinical data test set was used. The device was tested using an "external signal generator" applying "sinusoidal signals with different frequencies and amplitudes."
  • Data Provenance: Not applicable, as testing was done with simulated/generated signals.

• 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 would be the known parameters of the signals generated by the external signal generator. No human experts were involved in establishing this "ground truth."

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

  • Not applicable. No human interpretation or adjudication was involved. The performance was assessed by comparing the device's output to the known input signals.

• 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 an amplifier, not an AI or diagnostic system.

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

  • Yes, in essence, the testing performed was a "standalone" evaluation of the hardware's ability to accurately amplify and transmit signals. The device's performance was measured directly against known input signals from a signal generator.

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

  • The ground truth was established by the known, precisely controlled input signals from an external signal generator. This is a technical ground truth, not a clinical or expert-derived ground truth.

• 8. The sample size for the training set:

  • Not applicable. This is a hardware device, not a machine learning algorithm that requires a training set.

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

  • Not applicable.

Summary of the "Study" (Verification and Validation):

The "study" described for the g.Hlamp amplifier is a technical verification and validation process focused on hardware performance and adherence to safety standards, rather than a clinical trial or a study of diagnostic accuracy.

• Methodology:

  • Signal Transmission & Amplification: An external signal generator applied sinusoidal signals of varying frequencies and amplitudes to the amplifier inputs. The correctness of signal transmission and amplification was determined using BODE diagrams for each channel.
  • Impedance Measurement: Tested using "test impedances."
  • Noise: Tested by "short-cutting the input channels."
  • Safety: Medical safety was confirmed by evaluating the isolation using digital isolators, DC/DC converters, and a medical power supply unit. The current for impedance measurement was also verified to be limited for safety.

• Conclusion:

  • The tests demonstrated "appropriate signal quality for EEG measurements" and "accurate impedance measurements."
  • The device "amplify sinusoidal signals with varying frequencies and amplitudes in the same way" as the predicate device and is "working substantial equivalent and as effective as the marketed device."
  • It uses "the same key components for medical safety" as the predicate and is therefore considered safe.

In summary, the device met its implied acceptance criteria by showing substantial technical equivalence to its predicate device through rigorous engineering and safety testing, rather than through clinical or AI-specific performance metrics.

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Measuring, recording and analysis of electrical activity of the brain and/or through the attachment of multiple electrodes at various locations to aid in monitoring and diagnosis as routinely found in clinical settings for EEG.

The g.USBamp is a fully programmable system which provides a total of 16 analog input channels each of which can be configured, amplified and converted to digital form (analog to digital conversion). The applied part is optically isolated. The amplifier receives its power from a dedicated AC/DC adapter, meeting the IEC 601-1 requirements, which feeds in +5V DC. Internally, the +5V DC is further isolated by a dedicated DC/DC type converter.

The g.USBamp is intended to be used for measuring, recording and analysing of electrical activity of the brain and/or through the attachment of multiple electrodes at various locations to aid in monitoring and diagnosis as routinely found in clinical settings for EEG. It captures the data, converts it into digital form and passes it on to a host computer running appropriate software. The device can be used for adults, children, infants and animals. The host computer must use Microsoft XP. g.USBamp comes with a C Application Programming Interface (C API) which allows to control the device.

The system consists of the AC/DC adapter (power supply unit), g.USBamp (the amplification and digitization unit), a USB connector cable to connect the device to a host computer and the C API.

g.USBamp works in the same manner as the approved and predicate device.

The provided 510(k) summary for the g.USBamp focuses on establishing substantial equivalence to a predicate device (Neuroscan Nuamps K023536) rather than presenting a study to prove the device meets specific acceptance criteria. This type of submission typically relies on comparing performance specifications to the predicate device and demonstrating that the new device is as safe and effective.

Therefore, many of the requested sections about study design, sample sizes, and ground truth are not applicable or cannot be extracted from this document as a formal clinical or standalone performance study in the way one might expect for a diagnostic AI device.

Here's a breakdown of the information that can be extracted or inferred:

1. Table of Acceptance Criteria and Reported Device Performance

Instead of formal acceptance criteria for a study, this document performs a technological comparison between the proposed device and the predicate. The "acceptance criteria" here are effectively the performance characteristics of the predicate device that the new device must meet or exceed to demonstrate substantial equivalence.

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

• Sample Size: Not applicable. The "test set" in this context was a series of engineering and performance bench tests using signal generators, not patient data.
• Data Provenance: Not applicable. The testing described involves applying sinusoidal signals with different frequencies and amplitudes to the amplifier inputs. This is a technical performance verification rather than a test with biological data.

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

• Not applicable. Ground truth, in the sense of expert annotation for clinical data, was not established as the testing involved signal generators and impedance measurements.

4. Adjudication method for the test set

• Not applicable. There was no clinical ground truth requiring expert 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

• Not applicable. This device is a physiological signal amplifier, not an AI-powered diagnostic tool requiring a MRMC study for human reader performance.

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

• Yes, a standalone performance evaluation was done through bench testing. The amplifier was tested with an external signal generator, and its ability to correctly transmit and amplify signals was determined using BODE diagrams. Impedance measurements were also tested with test impedances. This demonstrates the algorithm's (or hardware's) standalone functionality.

7. The type of ground truth used

• The "ground truth" for the technical performance testing was the known, precisely generated sinusoidal electrical signals from an external signal generator. For impedance measurements, known test impedances were used.

8. The sample size for the training set

• Not applicable. This device, a physiological signal amplifier, does not involve a "training set" in the context of machine learning. Its functionality is based on established electronics and signal processing principles.

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

• Not applicable for the reason stated above.

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