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The Digital NeuroPort Biopotential Signal Processing System supports recording, processing, and display of biopotential signals from user-supplied electrodes. Biopotential signals include: Electrocorticography (ECoG), electroencephalography (EEG), electromyography (EMG), electrocardiography (ECG), electroculography (EOG), and Evoked Potential (EP).

The Digital NeuroPort Biopotential Signal Processing System is used to acquire, process, visualize, archive/record signals as acquired from user-supplied electrodes for biopotential monitoring. Signals are acquired using a headstage relay that attaches to the pedestal interface and digitizes the signal through the hub. The Digital NeuroPort System uses preamplifiers, analog to digital converters, a signal processing unit, and software running on a personal computer to visualize and record biopotentials from electrodes in contact with the body.

The document describes the Digital NeuroPort Biopotential Signal Processing System, which is a physiological signal amplifier. The device's substantial equivalence to a predicate device (K090957, NeuroPort Biopotential Signal Processing System) is affirmed based on various performance data.

Here's an analysis of the acceptance criteria and the supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance:

   Test / Characteristic	Acceptance Criteria	Reported Device Performance
   NeuroPlex E Functional Testing
   Mating	Screws down on pedestal and LED turns green	Pass
   Crosstalk	Isolation resistance of 1kΩ at 500 V DC	Pass
   Label Durability	IEC 60601-1:2005/A1:2012, Edition 3.1 7.1.3	Pass
   Digital Accuracy	Appropriate voltages for different filters (0.02-10 kHz Wide, 0.3-7.5 kHz Standard); Peak-to-peak of 500mV ±10%	Pass
   Input Impedance	≥10MΩ	Pass
   Impedance Measurement	820 ± 15% kOhms and 170 ± 15% kOhms	Pass
   Current Rating

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The Blackrock NeuroPort Biopotential Signal Processing System supports recording, processing and display of biopotential signals from user supplied electrodes. Biopotential signals include: Electrocorticography (ECoG), electroencephalography (EEG), electromyography (EMG), electrocardiography (ECG), electrooculography (EOG) and Evoked Potential (EP).

The Blackrock NeuroPort Biopotential Signal Processing System (System), when connected to customer supplier bio-potential electrodes or the NeuroPort Electrode Array (K042384), supports recording and display of bio-potential signals. Bio-potential signals that can be recorded by the System include:

1. Electrooculography (EOG),
2. Electrocorticography (ECoG),
3. electroencephalography (EEG),
4. electromyography (EMG),
5. electroencephalography (ECG) and
6. evoked potential (EP).
   The System is not a monitoring system. No physiologic alarms are provided. The acquisition and display of bio-potential signals is for the interpretation and use of the clinician.

The provided 510(k) summary for the Blackrock NeuroPort Biopotential Signal Processing System does not contain the detailed information typically found in a clinical study report that proves a device meets specific acceptance criteria using a test set. This document is a premarket notification for a medical device to demonstrate substantial equivalence to existing predicate devices.

Instead, it focuses on comparing the new device's technical specifications and intended use with previously cleared (predicate) devices to argue that it raises "no new questions of safety or effectiveness."

Therefore, much of the requested information regarding acceptance criteria, study details, sample sizes, ground truth establishment, expert involvement, and comparative effectiveness studies is not available in this document.

Here's an attempt to extract and infer information based on the provided text, while making explicitly clear what is not present:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in the sense of predefined performance targets for a clinical study. Instead, it compares the device's technical specifications to those of predicate devices. The implicit acceptance criterion is that the device's performance characteristics are equivalent to or better than the predicate devices, and that it adheres to relevant safety standards.

Note on "Reported Device Performance": The reported performance is essentially a restatement of the technical specifications, demonstrating they match or exceed the predicate devices. There is no independent "study" performance data presented in this 510(k) summary that would provide statistical measures like sensitivity, specificity, accuracy, or other metrics typically seen in diagnostic device studies.

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

• Not Provided. This document does not describe a "test set" in the context of a clinical study with human or animal subjects, nor does it mention data provenance (country of origin, retrospective/prospective). The assessment appears to be based on direct technical specification comparison and perhaps internal engineering testing (referred to as "system testing" and "software documentation" in Section 4.0).

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

• Not Applicable/Not Provided. Since there is no "test set" or clinical study described for ground truth establishment, this information is not present.

4. Adjudication method for the test set

• Not Applicable/Not Provided. No adjudication method is mentioned as there's no described test set or expert evaluation process.

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 Provided. This device is a signal processing system for acquiring and displaying biopotential signals. It is not an AI-assisted diagnostic tool for human readers, and therefore, an MRMC study comparing human reader performance with and without AI assistance is not relevant to this device description and was not performed.

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

• Not Applicable/Not Provided. The device itself is a hardware and software system for signal acquisition and display. It does not perform automated interpretations or diagnoses requiring a standalone "algorithm only" performance evaluation in the typical sense of AI/ML devices. Its performance is defined by its ability to accurately acquire and condition the biopotential signals. The "software testing" mentioned in Section 6.0 likely refers to verification and validation of the software's functionality within the system.

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

• Not Applicable/Not Provided. Given the nature of a signal processing system, "ground truth" would typically relate to the accuracy of the signal acquisition and conditioning itself, which is assessed through engineering tests against known input signals, not clinical ground truth like pathology or outcomes data. The document does not specify how the performance metrics (e.g., CMRR, impedance, sampling rate) were verified, but it would logically involve calibrated electronic test equipment.

8. The sample size for the training set

• Not Applicable/Not Provided. This device is not an AI/ML device that requires a "training set" in the context described.

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

• Not Applicable/Not Provided. As there's no training set, this is not applicable.

Summary of the "Study" (as described in the 510(k) Summary):

The "study" described in this 510(k) summary is not a clinical trial or performance study against predefined clinical acceptance criteria involving human subjects or expert readers. Instead, it is a technical comparison and verification process.

• Purpose: To demonstrate "substantial equivalence" of the Blackrock NeuroPort Biopotential Signal Processing System to legally marketed predicate devices (K042626, K060803, K040113).
• Methodology:
  • Comparison of Intended Use/Indications for Use: Showing the new device's intended use is equivalent to or falls within the scope of predicate devices.
  • Comparison of Technological Characteristics: A detailed feature-by-feature comparison of specifications (e.g., number of channels, input impedance, A/D conversion, sampling rate, CMRR) between the new device and predicate devices.
  • Hardware Modifications Verification: Mention of verifying new interface cables and a passive splitter box through "continuity of the single pathway" and "continuity of the signal pathways."
  • Software Testing: Indication that "software testing" was performed for new functionalities like syncing with external EEG instruments and cascading two systems.
  • Standards Compliance: Affirmation of compliance with relevant safety standards (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-26).
• Conclusion: The modifications to the predicate NeuroPort System "raise no new questions of safety or effectiveness," indicating that the device is considered safe and effective based on its equivalence to existing cleared devices.

In essence, this document is a regulatory submission demonstrating technical equivalence rather than a report of a scientific study with clinical performance endpoints.

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The Actical is a compact, lightweight, waist-, wrist-, or ankle-worn activity monitor that may be used to assess human gross motor activity, caloric expenditure, and estimates of energy expenditure based on motor activity in any instance where quantifiable analysis of physical motion is desirable.

The subject device can be classified as physiological signal conditioner as described in 21 CFR 882.1845. Actical is a physiological data recorder consisting of a data recorder which can be worn on the waist (hip), wrist, or ankle of the subject and that detects, measures, and records physical Activity data. A Reader is used to transfer the recorded rata to a Personal Computer (PC) running the Actical Host software. The host software is used to configure the data recorder for data collection, to retrieve logged data from the recorder, to display data and trend graphs, and to provide a means to store the logged data in a PC for later use.

The provided text is a 510(k) summary for the Actical Physiological Signal Recorder. This document focuses on demonstrating substantial equivalence to predicate devices and does not contain detailed information about specific acceptance criteria, performance studies, or the methodologies used to establish ground truth.

Therefore, I cannot extract the requested information as it is not present in the provided text. The document primarily covers:

• Contact person and date
• Trade name, common name, classification, and product code
• Legally marketed substantially equivalent predicate devices
• Description of the device
• Intended Use
• Comparison of technical characteristics, stating that "Results of performance tests, risk analysis, and verification and validation testing demonstrate that the devices are substantially equivalent." However, it does not detail these tests, criteria, or results.
• FDA's letter of clearance, confirming substantial equivalence.

Without a detailed study report, specific acceptance criteria, sample sizes, expert qualifications, and ground truth methodologies cannot be described.

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The VitalSense XHR can be used in any setting where physiological body core temperature, skin temperature, or heart rate are used to further the understanding of body function or where quantifiable analysis of temperature or heart rate data is desirable.

The subject device can be classified as physiological signal conditioner as described in 21 CFR 882.1845. VitalSense XHR is a physiological data recorder that is worn on the body. Up to ten sensor inputs may be used with a single VitalSense XHR recorder. The device senses and records physiological data and displays the data on its LCD screen. Recorded data may be transferred later to a PC for display and conversion for export to other programs.

Here's an analysis of the provided text regarding the acceptance criteria and study for the device:

Summary of Device Performance Study

The provided documentation for the Respironics VitalSense XHR (K061870) describes a submission for a modified device based on a predicate device (VitalSense K033534). The core of the study is a demonstration of substantial equivalence to this predicate device by showing that modifications (primarily to software for heart rate display) have no impact on safety and effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not explicitly list quantitative acceptance criteria for specific physiological parameters (e.g., accuracy ranges for temperature or heart rate) alongside reported device performance. Instead, it states:

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

• Test Set Sample Size: Not specified. The document refers to "performance tests, risk analysis, and verification and validation testing" but does not give a sample size for human subjects or data points used in these tests.
• Data Provenance: Not specified. The document does not indicate the country of origin of any data or whether the data was retrospective or prospective.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not conducted or described. This device is a physiological data recorder, 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

• Standalone Performance: The documentation implies that "performance tests, risk analysis, and verification and validation testing" were done on the device itself. Given that it's a physiological recorder, its performance fundamentally relates to its ability to accurately sense and record data in a standalone manner. However, specific details of these "performance tests" are not provided. The focus is on the substantial equivalence of the modified software within the existing hardware.

7. The Type of Ground Truth Used

• Type of Ground Truth: Not explicitly stated. The document implies that the device's measurements (body core temperature, skin temperature, heart rate) are considered the "truth" for the purpose of demonstrating substantial equivalence to the predicate device. It's likely that established measurement standards or comparison to other validated devices would serve as the ground truth during performance testing, though this is not detailed.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is a physiological recorder, not an AI/ML device that requires a training set in the typical sense. The software modification described (allowing heart rate display) would not involve a machine learning training set.

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

• Ground Truth for Training Set: Not applicable, as no training set for AI/ML is described.

In summary:

The submission for the VitalSense XHR focuses on demonstrating substantial equivalence to an existing predicate device after a software modification. The provided text outlines a regulatory submission process rather than a detailed scientific study with quantitative performance metrics, test set descriptions, or expert involvement in establishing ground truth for a diagnostic algorithm. The "acceptance criteria" are broad statements about meeting regulatory requirements and ensuring the modifications have no impact on safety and effectiveness, rather than specific numerical targets for physiological measurement accuracy.

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The Actiheart is an ambulatory Heart Rate and Activity Recorder. Actiheart may be used to quantifiably measure Heart Rate, Activity, and estimates of Caloric Expenditure. This device is not intended for use as an ECG monitor.

Actiheart is a compact, ambulatory, physiological Heart Rate and Activity data recorder. Actiheart may be attached to the chest surface through the use of standard ECG electrodes. Recorded data may be transferred later to a PC for display and conversion for export to other programs.

The document provides details of the Actiheart device, an ambulatory Heart Rate and Activity Recorder. It includes information on its substantial equivalence to a predicate device, indications for use, device description, and performance testing results against acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the sample size of unique patients or recordings for the test sets. Instead, it refers to "libraries of ECG waveforms" such as the MIT-BIH Normal Sinus Rhythm waveform library, European ST-T waveform library, and AAMI Normal Sinus Rhythm waveform library. These are standardized, publicly available databases of ECG recordings, often used for testing algorithms and devices. The provenance of these publicly available libraries is generally known, but not detailed in this document. The testing described is a "bench test comparison report" and relies on "library recordings of known Heart Rate." This suggests a retrospective analysis using pre-recorded data.

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

The document does not specify the number or qualifications of experts used to establish the ground truth for the test set. Ground truth for these waveform libraries is typically established through a combination of expert cardiological review and often includes reference annotations that have been meticulously validated.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method for the test set. Given that it relies on established ECG waveform libraries, the ground truth (e.g., true heart rate, QRS complex locations) from these libraries would serve as the reference, precluding the need for real-time expert adjudication of the device's output.

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

No multi-reader multi-case (MRMC) comparative effectiveness study is mentioned. The study focuses purely on the standalone performance of the Actiheart device against established benchmarks and in comparison to a predicate device in a bench test setting. It does not evaluate human readers' improvement with or without AI assistance.

6. Standalone Performance

Yes, a standalone performance study was conducted. The "Actiheart to Mini Logger Series 2000 bench test comparison report" directly assesses "the Heart Rate detection performance characteristics of both devices side-by-side against a set of library recordings of known Heart Rate." This is further supported by "Additional testing with the use of simulated recordings per ASTM EC13:2002," and the detailed "Assessment of non-clinical performance data" which lists various tests applied to the "submitted Recorder" (Actiheart) against specific performance requirements. These tests evaluate the device's ability to detect and measure heart rate independently.

7. Type of Ground Truth Used

The ground truth used for the performance testing cited in Table 10D is based on "known Heart Rate" from "libraries of ECG waveforms" such as MIT-BIH, European ST-T, and AAMI Normal Sinus Rhythm waveform libraries. These libraries contain reference annotations (e.g., R-peak locations, true heart rates) typically established through expert consensus and automated validation. The document also mentions testing with "simulated recordings per ASTM EC13:2002," implying a ground truth derived from controlled, simulated ECG signals.

8. Sample Size for the Training Set

The document does not provide information on the sample size used for the training set for any algorithms within the Actiheart device. It mentions "proprietary code transforms digitized signal and detects location of features in ECG complex" and "proprietary algorithms to detect motion" and "proprietary algorithm" for caloric expenditure, but does not detail the development or training of these algorithms.

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

The document does not provide information on how the ground truth for the training set (if any was used for the proprietary algorithms) was established.

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The Amplaid MK12 is a multi-channel system for electrodiagnosis capable of performing multisensory evoked potential tests including:

• Electronystagmography
• Visual evoked potentials,
• Auditory evoked potentials, and
• Electrical (somatosensory) evoked potentials.

The Amplaid MK12 Multi-channel system for electrodiagnosis consists of a two or four channel signal acquisition system coupled to a microcomputer which can perform signal averaging, storage and display, along with microcomputer controlled multiple mode evoked potential stimulators: auditory, visual, and electrical. A thermal printer is built in, and laser printer connection is supported.

The provided text describes the Amplaid MK12, an evoked potential electrodiagnostic system, and its substantial equivalence to a predicate device, the Amplaid MK15. However, the document does not contain details about specific acceptance criteria, a dedicated study proving device performance against those criteria, or the methodology typically used for such studies in the context of AI/ML or a new, novel medical device.

The submission is a 510(k) for a device that is stated to be "similar in design and function" to a previously cleared device (K861014). The primary focus of the 510(k) summary is to demonstrate substantial equivalence, rather than to present a de novo performance study against explicit acceptance criteria.

Therefore, many sections of your request cannot be fulfilled by the provided text.

Here is an attempt to address your request based on the available information:

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

The document does not explicitly state quantitative acceptance criteria for performance metrics (e.g., sensitivity, specificity, accuracy). Instead, it relies on demonstrating that the new device is "as safe and effective as the predicate device" through a comparison of characteristics.

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

The document mentions "bench and user testing" but does not provide details on:

• The specific sample size (number of cases, subjects, or data points) used for this testing.
• The data provenance (e.g., country of origin, retrospective or prospective nature).

3. 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. Given that the testing mainly aimed to establish substantial equivalence based on safety and effectiveness comparable to a predicate, it's unlikely a formal "ground truth" establishment by multiple experts, as understood in an AI/ML context, was performed or detailed.

4. Adjudication method for the test set

This information is not provided in the document.

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

An MRMC study is not mentioned. The device is an evoked potential electrodiagnostic system and does not appear to be an AI-assisted diagnostic tool for human readers in the way an AI-powered image analysis system would be.

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

This concept is not applicable to the device described. The Amplaid MK12 is a multi-channel system for electrodiagnosis, implying human operation and interpretation of the evoked potentials. It's not a standalone algorithm in the sense of AI/ML.

7. The type of ground truth used

The document does not specify the type of ground truth used. For an evoked potential system, "ground truth" would generally relate to the accuracy, reliability, and precision of the physiological signal acquisition and processing compared to established medical benchmarks or the performance of the predicate device.

8. The sample size for the training set

The concept of a "training set" in the context of machine learning is not applicable here, as the device is not described as using AI/ML algorithms that require training data.

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

Not applicable for the same reason as point 8.

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The Amplaid MK22 is a multi-channel system for electrodiagnosis capable of performing multisensory evoked potential tests including:
Electronystagmography
Visual evoked potentials,
Auditory evoked potentials, and
Electrical (somatosensory) evoked potentials.

The Amplaid MK22 Multi-channel system for electrodiagnosis consists of a two channel signal acquisition system coupled to a microcomputer which can perform signal averaging, storage and display, along with microcomputer controlled multiple mode evoked potential stimulators: auditory, visual, and electrical. A thermal printer is built in, and laser printer connection is supported.

The Amplaid MK22 is an evoked potential electrodiagnostic system. The submission establishes substantial equivalence to the Amplaid MK15 (K861014).

1. Table of Acceptance Criteria and Reported Device Performance

For this 510(k) submission, the acceptance criteria are based on substantial equivalence to the predicate device, Amplaid MK15. This means the new device must be as safe and effective as the predicate device and have the same intended uses, with no new indications for use. Performance is implicitly assessed by demonstrating that the key characteristics of the new device are either identical or comparable to the predicate device and that any differences do not raise new questions of safety or effectiveness.

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

The document does not explicitly mention a "test set" in the context of a clinical performance study with human subjects or a defined set of data for algorithm evaluation. The assessment for this 510(k) is based on bench and user testing and a comparative analysis of specifications against the predicate device.

• Sample Size: Not applicable in the context of a traditional performance study. The evaluation focuses on the device hardware and software specifications, and its equivalence to a previously cleared device.
• Data Provenance: Not specified as there isn't a clinical data set being referenced for performance evaluation. The "bench and user testing" information is general and does not refer to specific patient data.

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

Not applicable. This 510(k) submission is for an electrodiagnostic system, and its clearance is based on substantial equivalence to a predicate device, not on diagnostic accuracy against a ground truth established by experts.

4. Adjudication Method for the Test Set

Not applicable. There is no specific "test set" and corresponding adjudication process described for evaluating device performance in this submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

No. An MRMC comparative effectiveness study was not performed or referenced in this 510(k) submission. The device is an electrodiagnostic system and the clearance pathway relies on demonstrating equivalent technical specifications and intended uses to a predicate device, not on improving human reader performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not applicable. The Amplaid MK22 is a medical device (an electrodiagnostic system) that acquires and processes physiological signals for medical diagnosis by a clinician. It is not an AI algorithm that produces a diagnostic output on its own. While it involves signal averaging, storage, and display, this is part of standard electrodiagnostic equipment functionality, not an AI algorithm performing diagnostic interpretation without human input.

7. The Type of Ground Truth Used

Not applicable. The submission does not refer to a ground truth for diagnostic accuracy, as it focuses on demonstrating the device's technical specifications and intended uses are substantially equivalent to a predicate.

8. The Sample Size for the Training Set

Not applicable. The Amplaid MK22 is a hardware and software system for electrodiagnosis; it is not an AI algorithm that undergoes a "training" phase with a dataset.

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

Not applicable, as there is no "training set" for this device.

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