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The Grass "DE-48-Plus Disposable Electrodes" are intended for non-invasive use with recording and monitoring equipment, (active and reference), of Electromyography (EMG), Electroencephalograph (EEG) and Evoked Potentials.

The Grass Technologies DE48-Plus Disposable Electrodes (various lengths) are noninvasive, cutaneous devices, applied directly to the skin, and used in the acquisition of physiological signals for the purpose of montoring and recording Electroencephalograph (EEG), PSG and similar physiological parameters.

Non-invasive, disposable surface electrode discs (Cutaneous Electrodes), as included in this submission, are applied to the skin using a cream or gel for adhesion. Their purpose is to pick up and transfer microvoltage signals, as generated by the body, to recording equipment, for the purpose of monitoring and recording associated with electroencephalography and electromyography. The new Grass DE-48-Plus electrodes, as with the BNT predicate, are manufactured with a circular, raised cup body molded from ABS plastic and coated with silver chloride (Ag/AgCl). The disc is adhered to a lead wire which is covered with heat shrink tubing and terminates with a molded connector that conforms to DIN 42-802 for electrical safety. Grass DE-48-Plus Electrodes connect to, and work with, any EEG equipment, without special attachments.

The DE-48-Plus electrodes are made up of the following materials (same or equivalent to the Rhythmlink predicate).

Cup Disk: ABS Plastic with an Aq/AqCl coating which is nominally measured at 10mm (8.5 to 10mm).

The connecting wire which is manufactured from 28AWG stranded Tin Copper conductor with soft PVC insulation.

Wire crimped to Cup Electrode using Tin plated copper tubing.

Terminal connected with Alex crimp type, 24-30AWG Brass, Tin plated, Molded in Palprene.

This document describes a 510(k) summary for the DE-48-Plus Disposable Electrodes, a non-invasive cutaneous device for physiological signal acquisition. The submission focuses on demonstrating substantial equivalence to predicate devices rather than proving specific performance against defined acceptance criteria through a clinical study. Therefore, many of the requested criteria for a clinical study are not applicable or explicitly stated.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: Not explicitly stated. The document mentions "appropriate testing" but does not detail the number of electrodes or tests conducted for Resistance, Model Surface, Impedance, and Frequency Response.
• Data Provenance: Not explicitly stated, but it's implied that the testing was conducted by Grass Technologies as part of their submission process. Given the nature of a 510(k) for a medical device, this would typically involve laboratory testing, not human clinical trials. It's likely retrospective in the sense that it compares features and performance to existing, legally marketed predicate devices.

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

• Not Applicable. For this type of device (electrodes for acquiring physiological signals), ground truth isn't established by expert consensus on clinical findings. Instead, the "truth" is based on objective measurements of physical and electrical properties compared against established product specifications or the properties of predicate devices.

4. Adjudication method for the test set

• Not Applicable. As there's no clinical "ground truth" to adjudicate, this concept does not apply to the device's testing for substantial equivalence.

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 an electrode, not an AI diagnostic tool or system that assists human readers. Therefore, an MRMC study and AI-related effectiveness are irrelevant.

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

• Not Applicable. This is a hardware device (electrode), not an algorithm or software. "Standalone performance" in this context would refer to its physical and electrical characteristics, which were assessed as described in the "Performance Data" section.

7. The type of ground truth used

• The "ground truth" for demonstrating substantial equivalence was the established characteristics and performance of the identified predicate devices: the Rhythmlink Disc Electrodes (K061148) and Grass Technologies' Gold Electrodes (marketed prior to 1976).
• For the technical characteristics (Resistance, Model Surface, Impedance, Frequency Response), the ground truth would be the measured values from the predicate devices which the DE-48-Plus aimed to match or be "substantially equivalent" to.

8. The sample size for the training set

• Not Applicable. This is a physical medical device, not a machine learning model. Therefore, there is no "training set."

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

• Not Applicable. (See point 8).

Summary of the Study:

The "study" referenced in the document is not a traditional clinical trial but rather a series of bench tests and comparative analyses conducted by Grass Technologies to demonstrate that the DE-48-Plus Disposable Electrodes are "substantially equivalent" to legally marketed predicate devices.

The tests focused on physical and electrical performance characteristics such as Resistance, Model Surface, Impedance, and Frequency Response. The results of these tests, although not numerically detailed in the summary, reportedly showed that the DE-48-Plus electrodes were "found, through appropriate testing to be substantially equivalent" to the Rhythmlink Disc Electrodes and existing Grass Technologies' Gold Electrodes. Material composition and design were also compared directly to the predicates.

The purpose of this submission (510(k)) is to demonstrate that the new device is as safe and effective as a legally marketed device, not to prove novel performance through a clinical trial with human subjects.

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The intended use for TWin Neurotrac-III is: To record the electroencephalogram (EEG) and the computed EEG trends over extended periods of time in order for trained health care professionals to observe changes over time. TWin Neurotrac-III does not provide any diagnostic conclusion about the patient's condition. TWin-Neurotrac-III is intended for use only by medically trained and qualified personnel, within a hospital or medical environment.

TWin Neurotrac-III is used with Grass-Technologies TWin (#K012976) EEG Recording and Review systems for displaying and recording long term trends of EEG features during continuous EEG monitoring in the ICU, NICU, OR, EEGIPSG laboratories, and/or inpatient long-term seizure monitoring units. TWin Neurotrac-III can be used with EEG acquisition systems configured with any of Grass-Technologies' amplifiers, including AS40 (#K021807), AURA (#K033978), AURA-LTM64 (#K053606) and Beehive (#K884937) amplifiers. The number of EEG channels recorded is dependent on the amplifiers used, the number of electrodes applied to the patient. and the user selected EEG display montage. In addition to displaying and recording the EEG waveforms. TWin Neurotrac-III can also display and record trends of user selectable EEG features in the EEG over prolonged periods of time. The number and the EEG channels processed are selected by the user.

The provided text describes the TWin Neurotrac-III device and its 510(k) submission, K081551. However, it does not contain specific acceptance criteria, a detailed study protocol, or quantitative performance metrics as typically expected for a medical device. This device is an electroencephalograph (EEG) system accessory that displays and records EEG waveforms and trends. Its clearance is based on substantial equivalence to predicate devices, not on a new clinical efficacy study.

Therefore, many of the requested sections (e.g., acceptance criteria, detailed performance, sample sizes for test/training sets, ground truth establishment for AI, MRMC studies) cannot be directly addressed from the provided document. The document focuses on demonstrating functional equivalence through in-house and beta site testing.

Here's an attempt to answer based only on the information available in the provided text:

1. Table of acceptance criteria and the reported device performance

Since this is a 510(k) for substantial equivalence based on functional requirements rather than a novel diagnostic algorithm with quantitative performance metrics, there are no explicitly stated numerical acceptance criteria or performance metrics in terms of sensitivity, specificity, or similar. The "performance" is described in qualitative terms of meeting functional requirements and not adversely altering existing systems.

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

The document mentions "real EEG from previously recorded studies" for in-house testing and "Beta sites" for testing.

• Sample Size (Test Set): Not specified. The number of "previously recorded studies" or patients/cases at "Beta sites" is not provided.
• Data Provenance:
  • In-house testing: "simulated signals, as well as real EEG from previously recorded studies". The origin of these "previously recorded studies" (country, institution) is not specified. It can be inferred as retrospective, as they are "previously recorded."
  • Beta Site Testing: Performed "at Beta sites." The number or location of these sites, or the number of cases/patients involved, is not specified. The nature of this testing (retrospective/prospective) is also not specified, though "Beta site testing" often implies prospective usage by medical personnel in a real-world setting.

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

N/A. The device records and displays EEG data; it "does not provide any diagnostic conclusion." The testing focused on functional requirements and safety. There is no mention of establishing ground truth for diagnostic accuracy, as the device itself is not making a diagnosis. The Beta site testing was supervised by "qualified medical personnel," but their specific number or qualifications are not given, nor was their role to establish a diagnostic ground truth for device performance evaluation.

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

N/A. There was no diagnostic "ground truth" to adjudicate, as the device does not provide diagnostic conclusions. The testing was functional and safety-oriented.

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

N/A. No MRMC comparative effectiveness study was performed. The device is a tool for displaying and recording EEG, not an AI diagnostic aid designed to improve human reader performance for specific tasks. "No clinical testing was necessary to demonstrate substantial equivalence for this product."

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

N/A. The TWin Neurotrac-III is intended for use by "medically trained and qualified personnel." It is an accessory to an EEG recording and review system. It is not a standalone diagnostic algorithm that operates without human involvement.

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

N/A. As the device does not provide diagnostic conclusions, no diagnostic ground truth (like expert consensus, pathology, or outcomes) was used to evaluate its performance. The "ground truth" for the testing performed was likely the expected functional output of the device (correct display of waveforms and trends, no adverse effects).

8. The sample size for the training set

N/A. This device is not described as employing machine learning or AI models that would require a distinct "training set." Its development and clearance relied on demonstrating functional performance and safety.

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

N/A. No training set, as per point 8.

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The AURA-PSG amplifier system is intended for recording routine Electroencephalography (EEG) and Polysomnography (PSG). This device is intended to be used only by physicians, technicians, or other medical professionals that are trained in EEG and/or PSG.

AURA-PSG is a compact multi-channel amplifier and data acquisition device Aort F OO is a compoephalography (EEG) and polysomnography (PSG) recording applications. It provides for patient safety isolation, signal conditioning, and data sampling. The AURA-PSG amplifier system consists of two major components: the Amplifier Unit and the Base Station. The Amplifier Unit provides connections for electrodes and sensors and is normally worn by the subject in a vest or pocket. The Amplifier and sonoord and to hernRay istation using either a signal cable (tether) or a wireless connection. Both transmit digitized waveform to the Base Station where it is converted to standard network protocols and made available to supporting computers. AURA-PSG can be used for off-line, ambulatory recording. When used in this fashion, power is supplied by a battery and data is stored in internal memory. When the study is complete, data can be sent to a computer for review. The Base Station provides Menu selections for configuring the unit, communicating with the host computer, and implementing an electrode impedance test. It contains an LCD that can display status and other information. Power is supplied to the AURA-PSG Base Station through a rear connector that attaches to a medical-grade requlated power supply (+12 volts DC). The AURA-PSG Amplifier Unit is 5.5 inches x 3.5 inches by 1.0 inches and the AURA-PSG Base Station is approximately 7" x 6" x 2" inches. The Base Station can be attached to a cart arm, mounted on a wall or flat on a tabletop.

The provided text is a 510(k) summary for the AURA-PSG EEG Amplifier System, seeking substantial equivalence to predicate devices. It describes the device's intended use and technological characteristics. However, it does not contain any information regarding acceptance criteria, device performance studies, sample sizes, ground truth establishment, expert qualifications, or comparative effectiveness studies.

Therefore, I cannot populate the table or answer the specific questions about performance criteria and study details based on the provided input. The document focuses on regulatory compliance through substantial equivalence to existing devices rather than presenting detailed performance efficacy data.

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The ADAM amplifier system is intended for recording routine EEG and EEG associated with long term monitoring for epilepsy. This device is intended to be used only by physicians, technicians, or other medical professionals that are trained in electroencephalography.

The ADAM amplifier system is an EEG Amplifier System.

The provided text is a 510(k) summary for the Grass-Telefactor ADAM EEG Amplifier System. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, the document does not contain any information regarding acceptance criteria or a study proving the device meets acceptance criteria.

Therefore, I cannot populate the table or answer the questions you've posed based on the given input text. The 510(k) summary is primarily concerned with establishing substantial equivalence, not with detailing performance studies with specific statistical metrics and ground truth methods.

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Grass Brainwave Software is intended for use by qualified research and clinical professionals with specialized training in the use of EEG/PSG recording instrumentation for the digital recording, playback, and analysis of physiological signals. Its specifications and features make it especially well suited to electroencephalography and polygraphic sleep recordings.

The Grass® Night Vision is a Microsoft Windows95™ application software package for monitoring, recording, and reviewing physiological signals. It includes features for assisting the user with making measurements, marking significant events, and tabulating the events for easier interpretation. The software consists of two major modules, the Recorder and the Reviewer, and several minor modules for setup, montage editing, file management, and report generation. Together with a personal computer and a set of physiological signal conditioners (like the Grass® Model 15 amplifier system), the plight Vision software enables the user to replace or upgrade traditional strip-chart recorders used in the sleep laboratory with modern, digital recording and review methods.

This document is a 510(k) summary for the Grass® NightVision Software, which is described as a Polysomnograph/Electroencephalograph Software. The information provided focuses on the device's intended use, functionality, and comparison to legally marketed predicate devices.

Crucially, this document does not contain a study proving the device meets specific acceptance criteria in the typical sense of a performance study with quantitative outcomes.

Instead, the document primarily makes a claim of "substantial equivalence" to existing devices based on similar design, function, and intended use. The "acceptance criteria" presented below are inferred from the device's description and its stated functionality, as no explicit performance metrics are provided in the document for statistical analysis.

Based on the provided information, here's a breakdown:

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a 510(k) submission primarily establishing equivalence and describing functionality for a software product in 1997, explicit "acceptance criteria" with quantifiable performance metrics (like sensitivity, specificity, accuracy) and a "reported device performance" section with statistical results from a study are not present in this document.

The "acceptance criteria" can be broadly interpreted as the software's ability to successfully perform its described functions as a digital polysomnograph/electroencephalograph software. The "reported device performance" in this context refers to the described features and capabilities of the software.

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

• Sample Size for Test Set: Not applicable / Not mentioned. The document does not describe a clinical performance study using a "test set" of patient data in the context of evaluating diagnostic accuracy or a specific performance metric. The submission focuses on device functionality and equivalence.
• Data Provenance: Not applicable. Without a defined test set, there is no mention of data provenance (e.g., country of origin, retrospective/prospective).

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

• Number of Experts: Not applicable / Not mentioned. As no test set for performance evaluation is described, there's no mention of experts establishing a ground truth for such a set.
• Qualifications of Experts: Not applicable. The document does mention that the software is for "qualified research and clinical professionals with specialized training in the use of EEG/PSG recording instrumentation," and refers to the American Sleep Disorders Association guidelines for manual review by experts. However, these are general statements about the intended user and standard practice, not specific to a performance study's ground truth establishment.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable / Not mentioned. No test set or performance study requiring an adjudication method is described.

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

• MRMC Study Done?: No. There is no mention of an MRMC comparative effectiveness study in this document. The software explicitly states it does not use automated algorithms for staging sleep or scoring respiratory events; it merely assists human users. Therefore, a study comparing human readers with AI assistance versus without AI assistance would not be relevant for this particular device's described function.
• Effect Size of Human Readers Improve with AI vs. without AI assistance: Not applicable.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study Done?: No. The document explicitly states: "Night Vision uses the power of the computer whenever possible to aid and speed the scoring and review of the data files by keeping track of relevant signal information... Unlike some competitive products on the market, it makes no determination of clinically significant events automatically using algorithms (like apneas or sleep stages)." Therefore, a standalone performance study of an algorithm's diagnostic capabilities would not be relevant, as the device doesn't perform such automated diagnostics. Its role is as a tool for manual review and data presentation.

7. Type of Ground Truth Used

• Type of Ground Truth: Not applicable / Not mentioned for performance evaluation. Given the device's role as an assistant for manual human scoring and review, the "ground truth" ultimately relies on the interpretation of the "qualified research and clinical professionals." The software itself does not generate a diagnostic output or classification that would require an independent ground truth for validation in the context of a performance study. For the training set, see point 9.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable / Not mentioned. As the software "makes no determination of clinically significant events automatically using algorithms," it does not employ machine learning algorithms in a way that would necessitate a "training set" of annotated data for an AI model. The software's functionality is based on traditional software programming logic to display, record, and organize data according to user inputs and specifications.

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

• How Ground Truth for Training Set was Established: Not applicable. Since there is no indication of machine learning or an AI algorithm that requires a "training set" with ground truth, this question is not relevant to the described device. The software's "ground truth" during its development would be its adherence to established specifications for data acquisition, display, storage, and reporting, and its ability to accurately reflect user-entered information and perform calculations as programmed (e.g., cursor measurements, report generation based on entered scores).

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The Model 15 combines up to 32 of the P511 amplifier circuits (in banks of 4) in a single enclosure and replaces the P511 manual switches with solid-state switches that are controlled via a standard RS-232 serial port. The Model 15 relies on the essential safely features of the P511 amplifier capacity-coupled patient circuit and safety-extra-low-voltage operation (12VDC) and improves on the safety of the P511 by isolating the patient applied circuits from the enclosure (earth).

This K96 3669 document is a 510(k) summary for the Grass® Model 15 Neurodata Amplifier System. It focuses on demonstrating substantial equivalence to pre-existing devices rather than presenting a study proving the device meets specific performance acceptance criteria.

Therefore, the requested information regarding acceptance criteria, study design, sample sizes, ground truth, and expert adjudication cannot be extracted from the provided text. The document primarily describes the device, its classification, and its equivalence to older Grass models (P511) and the Melville Diagnostics MMC Series, highlighting design and safety similarities.

There is no mention of a clinical or performance study with defined acceptance criteria, test sets, training sets, or expert evaluations. The closest relevant information is the assertion that the Model 15 shares essential design, performance, and safety characteristics with the older, FDA-listed Grass P511 amplifier.

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