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Glide is to be used exclusively for exoprosthetic fittings of the upper limb.

Glide is a surface electromyography (EMG) electrode and control system intended to be used with an upper limb prosthesis. Glide detects surface EMG signals using IBT Electrodes V2 placed on the user's skin. These signals are processed by Glide and are used to drive the upper limb prosthesis.

Glide is compatible with industry standard domes. Glide does not have any direct skin contacting parts. Glide is compatible with most hands, wrists, and elbows that accept industry standard inputs. Glide accepts power from the prosthesis batteries and outputs control signals to hands, wrists, and other prosthetic components. The components of Glide are assembled into the prosthesis by a certified prosthetist or trained technician according to the individual needs of the amputee. Glide is a reusable single patient use device.

Glide does not replace or modify any functionality of connected prosthetic components.

Adjustments to the Glide components can be performed through Bluetooth data transfer using the IBT Control Application. The IBT Control Application runs on the iPad OS platform and allows the prosthetist to adjust the settings of the system, such as assignment of input filtered signal to prosthesis movements, adjustment of gains, etc.

Glide components:

• Core2 Controller (90010)
• Output Cable (90020-XX)
• IBT Remote Dome Electrodes (upto 8)
• Electrode Cables
• IBT Control Application
• Core2 Fabrication Kit (94001)
• Documentation
• Dome Fabrication Kit (optional)

This document describes the Glide device, an electromyography (EMG) electrode and control system for upper limb prostheses, and its comparison to a predicate device for FDA 510(k) clearance.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a quantitative manner for specific performance metrics (like sensitivity, specificity, accuracy, or specific thresholds for latency, signal-to-noise ratio). Instead, it relies on demonstrating compliance with recognized performance standards and successful completion of internal verification and validation testing, implying that passing these tests constitutes meeting the acceptance criteria for safety and effectiveness.

General Performance and Acceptance Status: The Glide device passed all internal testing regimens and relevant performance standards.

Note regarding predicate device comparison: For software V&V and Design V&V, the document states "As with any device, the predicate would also have been tested to determine if user and device requirements are met. There is no publicly available information on the same." This indicates the comparison is based on the expectation that the predicate met similar internal standards, rather than direct public data.

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

The document does not explicitly state the sample size for any specific performance tests (e.g., number of users, number of devices tested, or duration of tests). It generally refers to "Internal Testing Regimen" and "Validation testing on Glide."

The data provenance is internal, from Infinite Biomedical Technologies, LLC. No country of origin of the data is specified beyond the manufacturer's location (Baltimore, MD, USA). The studies appear to be prospective in nature, performing tests on the Glide device to gather data for submission.

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 ground truth for testing. The validation tests (e.g., "Patient Use of UI," "Practitioner Use of UI") imply user testing, but details on how success was evaluated or if independent experts were involved in defining successful outcomes are not provided.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1 consensus) for establishing ground truth or evaluating test results. The implication is that internal teams and standard testing procedures determined pass/fail outcomes.

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

The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study or any studies evaluating the effect size quantifying human reader improvement with or without AI assistance. The Glide device is an EMG control system for prostheses, not an AI diagnostic imaging tool that would typically involve human "readers."

6. Standalone Performance Study

The information provided focuses on the standalone performance of the Glide system (algorithm and hardware together) through various verification and validation tests and compliance with performance standards. The results listed in the "Performance Data" section (e.g., "Installation of Core2," "Battery Life," "Lifetime and Reliability Testing") are all indicative of standalone algorithmic and system performance. The "IBT Control Application" runs on an iPad OS platform, and its software verification and validation is part of the standalone performance assessment.

7. Type of Ground Truth Used

The ground truth used for the tests appears to be based on device functionality and compliance with engineering/performance standards. For example:

• Engineering specifications: (e.g., successful installation, battery life, lifetime and reliability)
• User interaction/usability: (e.g., UI use by patient and practitioner, patient use of prosthetic component)
• Regulatory standards: (e.g., IEC/EN 60601 series for safety, essential performance, EMC).
• Physical testing: (e.g., packaging drop test).

The ground truth is not related to expert consensus, pathology, or outcomes data in a clinical diagnostic sense, but rather to the successful and safe operation of the medical device as per its design and intended use.

8. Sample Size for the Training Set

The document does not mention a training set or its sample size. The Glide device functions as a real-time control system for prostheses, processing electromyography (EMG) signals. While such systems may involve machine learning or signal processing algorithms, the document focuses on the performance verification of the final device, rather than the training phase of any underlying algorithms. It states that "Glide processes inputs from two to eight electrodes to drive a prosthesis into multiple movements without the use of traditional triggers and/or calibration," and uses "vector summation control." This implies a deterministic or rule-based control scheme, or a pre-trained model where the training details are not elaborated.

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

Since a training set is not explicitly mentioned, the method for establishing its ground truth is also not described.

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Sense System with IBT Electrodes is to be used exclusively for external prosthetic fittings of upper limbs.

The Sense System is a surface electromyography (EMG) electrode system designed to enhance control of upper limb prosthetic devices. The Sense System detects EMG signals using the IBT Electrodes (previously approved by the FDA under 510k, K173571). The electrode signals are then processed using a pattern recognition algorithm and translated to output signals that are standardized to be compatible with an array of connected prosthetic devices, such as hands, wrists or elbows. The Sense System does not replace or modify any functionality of connected prosthetic components.

The Sense System is compatible with most hands, wrists, and elbows that accept industry standard signals. It is typically sold with three-port kidney-style output connectors; however, alternative connectors may be used to ensure compatibility with other components. The Sense System accepts power from IBT's FlexCell Battery system and outputs control signals to hands, wrists, and other prosthetic components. The Sense System is installed in the prosthesis by a trained prosthetist and connected to prosthetic components selected to meet the needs of the individual user.

Sense System components:

• IBT Electrodes (up to 8)
• Signal Processing Box
• User Interface Software
• Fabrication dummies for electrodes and processing box

The provided text describes a 510(k) premarket notification for the "Sense System with IBT Electrodes." It focuses on demonstrating substantial equivalence to a predicate device ("COMPLETE CONTROL System") rather than providing detailed acceptance criteria and a study dedicated to proving the device meets those criteria in the way typically found for an AI/ML medical device's performance claims.

The document primarily addresses the technological characteristics, performance, and safety of the Sense System in comparison to a predicate device to establish substantial equivalence for regulatory clearance. It doesn't present a study aimed at validating distinct performance metrics against specific, predefined numerical acceptance criteria for an AI model's accuracy, sensitivity, or specificity.

However, based on the information provided, we can infer some "acceptance criteria" through the lens of safety and effectiveness equivalence, and summarize the supporting "study" as a series of verification and validation tests.

Here's an attempt to structure the answer based on your request, while acknowledging the limitations of the provided text for a typical AI/ML performance study description:

Device: Sense System with IBT Electrodes

Purpose of the "Study" (Verification & Validation Testing): To demonstrate the safety and effectiveness of the Sense System with IBT Electrodes and its substantial equivalence to the legally marketed predicate device, the COMPLETE CONTROL System (K162891).

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a 510(k) submission based on substantial equivalence, the "acceptance criteria" are implicitly tied to demonstrating the new device performs as safely and effectively as the predicate, and does not raise new or different questions of safety and effectiveness. The "reported device performance" is the outcome of various tests and comparisons confirming this equivalence. Specific quantitative performance metrics for a pattern recognition algorithm's accuracy (e.g., control accuracy rates) are not detailed in this document.

2. Sample Size and Data Provenance

The document does not specify a "sample size" in the context of a dataset for an AI model's performance evaluation (e.g., number of patient cases). Instead, it refers to various engineering and functional tests.

• Test Set Sample Size: Not applicable in the context of a test set for an AI model's performance on patient data. The tests described are functional, electrical safety, usability, and design verification tests.
• Data Provenance: Not explicitly stated as retrospective or prospective clinical data. The testing appears to be internal validation and verification, simulating use and testing components as per regulatory standards. No country of origin for specific "data" (apart from the manufacturer being in Baltimore, Maryland, USA) relating to patient cases is mentioned.

3. Number of Experts and Qualifications for Ground Truth

The document does not describe a process for establishing ground truth through expert review of patient data, as would be typical for an AI diagnostic device. The "ground truth" for this device's performance appears to be established by engineering specifications, safety standards, and functional requirements. For the "Practitioner Use of UI" and "Patient Use of UI" tests, it can be inferred that prosthetists and patients were involved, but the number and their specific qualifications for establishing ground truth are not detailed.

4. Adjudication Method for the Test Set

Not applicable. The tests described are engineering and functional validation, not clinical review of cases requiring adjudication.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done or at least not described in this document. The device is a control system for prosthetics, where the "human-in-the-loop" is the user of the prosthetic. The document does not evaluate how human readers (e.g., radiologists interpreting images) improve with AI assistance.

6. Standalone (Algorithm Only) Performance

The sense system is described as using a "pattern recognition algorithm" to process EMG signals (Page 4). However, the document does not report standalone performance metrics (e.g., accuracy, sensitivity, specificity) for this algorithm in isolation. The evaluation focuses on the entire "Sense System" as a functional unit to ensure safety and effectiveness for controlling prosthetic devices.

7. Type of Ground Truth Used

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

• Engineering specifications and design requirements.
• International standards for medical electrical equipment (IEC/EN 60601 series) and battery safety (IEC 62133, UN38.3).
• Functional performance (e.g., proper signal output, compatibility with prosthetic components).
• Usability testing, which would involve observing user interaction with the system.

It is not based on expert consensus on patient cases, pathology, or outcomes data in the typical sense of a diagnostic AI device.

8. Sample Size for the Training Set

Not applicable. The document does not describe the specifics of the pattern recognition algorithm's training, including its training data size. The focus is on the integrated system's safety and effectiveness.

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

Not applicable. The document does not provide details on the training process or ground truth establishment for the internal pattern recognition algorithm.

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The Element system is intended to be used exclusively for myoelectric exoprosthetic fittings of the upper limb.

The Element system is a surface electromyography (EMG) electrode system that is to be used with upper limb prosthetic devices. Element outputs standard envelop EMG signals detected from EMG electrodes (IBT Electrodes) placed on the user's skin. These signals are used as inputs by connected prosthetic devices, such as hands, wrists or elbows. The Element system is an alternative to standard suction socket myoelectrodes, with the advantages of a lower profile, digital signal processing, and wireless gain adjustment. Element does not replace or modify any functionality of connected prosthetic components.

Element is compatible with most hands, wrists, and elbows that accept standard analog EMG electrode inputs. The Element system is typically sold with three-port kidney-style output connectors, however alternative connectors may be used to ensure compatibility with other terminal devices. The Element system accepts power from IBT's FlexCell Battery system and outputs control EMG signals to hands, wrists, or other prosthetic components. The Element system is installed in the prosthesis by a trained prosthetist and connected to prosthetic components selected to meet the needs of the individual user.

System components:

• IBT Electrodes (up to 2)
• Signal Processing Box
• Element Desktop Software

The provided document is a 510(k) summary for the Infinite Biomedical Technologies (IBT) Element System with IBT Electrodes. It outlines the device's characteristics, comparison to a predicate device, and the testing conducted to demonstrate substantial equivalence.

Here's an analysis of the acceptance criteria and study information, addressing your specific questions:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly present a table of acceptance criteria with corresponding pass/fail results for each criterion to demonstrate "device performance" in terms of clinical outcomes or specific quantitative metrics for the Element System's functionality as a myoelectric signal processor. Instead, it focuses on demonstrating safety and effectiveness through adherence to recognized standards and successful completion of various verification and validation tests.

However, we can infer acceptance criteria from the "Performance Data" section. The acceptance criterion for each test is generally "Pass," indicating that the device met the requirements of the specified standard or test protocol.

Here's a table based on the provided "Performance Data":

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

The document does not specify the sample sizes used for the various verification and validation tests listed. It also does not provide details on data provenance (e.g., country of origin of the data, retrospective or prospective) for these tests. The tests mentioned are primarily laboratory-based simulations and regulatory standard adherence, not clinical trials with patient data.

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. The tests described are engineering and regulatory compliance validations rather than diagnostic or interpretative studies requiring expert ground truth establishment. For example, "Signal Performance during Simulated Use" would likely involve objective measurements against predefined specifications, not expert consensus on an interpretation.

4. Adjudication Method for the Test Set

This information is not provided and is generally not applicable to the types of engineering and regulatory compliance tests described. Adjudication methods (like 2+1, 3+1) are common in clinical studies where multiple human readers interpret data, and an agreed-upon truth is needed.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done and is not applicable to this device. The Element System is a myoelectric signal processing unit for prosthetic control, not an AI-assisted diagnostic or interpretive tool that human readers would use. The document describes the system as an alternative to standard suction socket myoelectrodes, with advantages like a lower profile, digital signal processing, and wireless gain adjustment, but it doesn't involve "AI assistance" in the sense of improving human reader performance.

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

The Element System itself is a standalone algorithm/device for processing myoelectric signals. The performance tests ("Signal Performance during Simulated Use", "Simulated battery life with Element", "Simulated use with Region Specific Noise") would effectively be standalone performance evaluations of the device's electrical and signal processing capabilities, without human user interaction as part of the performance measurement. However, its intended use is with a human user providing the EMG signals and benefiting from its processing for prosthetic control.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

For the specific tests mentioned, the "ground truth" would be established by:

• Regulatory Standards: For tests like IEC 60601-1, ISO 10993, and UN38.3, the ground truth is adherence to the requirements and specifications defined by these international standards.
• Engineering Specifications: For tests like "Compatibility with IBT Electrodes," "Signal Performance during Simulated Use," and "Simulated Seal," the ground truth would be predefined engineering specifications, performance tolerances, or established benchmarks for electrical signals and mechanical functions.
• Simulated Conditions: For tests involving "simulated use" or "simulated battery life," the ground truth is the controlled and measurable conditions established within the simulation.

There is no mention of expert consensus, pathology, or outcomes data being used as ground truth in this submission, as it's not a diagnostic or treatment outcome-focused device.

8. The Sample Size for the Training Set

The document does not mention any training set size. As the Element System with IBT Electrodes is a device that processes myoelectric signals based on predefined algorithms and hardware, it is unlikely to involve "training" in the machine learning sense that would require a distinct training set. The "digital signal processing" and "signal smoothing" functionalities are described as inherent design features or adjustable parameters, rather than learned models.

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

Since no training set is mentioned or implied, the question of how its ground truth was established is not applicable.

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The Vigilant EEG Monitor (Vigilant 2.0) is an electroencephalograph that works in conjunction with Vigilant bedside monitoring and remote review software. It is intended for measuring and recording the electrical activity of a patient's brain by applying 8 electrodes on the head.

The Vigilant EEG Monitor (Vigilant 2.0) requires competent user input, and its output must be reviewed and interpreted by trained medical professionals who will exercise professional judgment in using this information.

The Vigilant EEG Monitor (Model Vigilant 2.0) is a multi-channel EEG monitor. It is intended for monitoring the state of the brain by applying electrodes to a patient's head. It also includes software to enable remote monitoring by a neurologist or other trained personnel. Both acquisition and review of patient data can be performed at the bedside.

The Vigilant EEG Monitor does not include a computer monitor or video camera, but these are required for system use.

The Vigilant EEG Monitor consists of an EEG acquisition console with junction box and a software CD (bedside EEG monitoring software, server software for remote telecommunications and software for remote monitoring of EEG data). The principal component of the Vigilant EEG monitor is a Porti amplifier and power supply provided by TMS International (Oldenzaal, The Netherlands). The software is designed to be loaded onto an off the shelf computer monitor that may be supplied by the user. It is also designed to interface with a video camera for real-time video monitoring concurrently with EEG monitoring. Neither the computer nor the camera is considered part of the medical device.

The EEG signal display can be configured in a reduced mode (up to 4 EEG channels plus quantitative EEG metrics for each channel) or a full mode (up to 8 EEG channels). The display modes and channel display are configurable by the user.

In the reduced mode display, the user may select to display either the spectral edge frequency (SEF 95) as a line graph, or the power spectrum (POWER) displayed as four colored line graphs, each representing the standard EEG frequency bands (delta: 0-4Hz, RED: theta: 4-8Hz, YELLOW; alpha: 8-13Hz, GREEN; beta: 13-30Hz, BLUE).

Real-time video of the patient from the system camera is displayed in a separate window from the EEG signals. This window may be hidden or resized by the user. The video is recorded in synchronization with the EEG even when it is not displayed and may be replayed during review mode.

The provided 510(k) summary for the Vigilant 2.0 EEG Monitor indicates that the device's performance was evaluated through laboratory testing, demonstrating it met its design and functional requirements. However, it does not include a detailed study with specific acceptance criteria and reported device performance as requested. The document primarily focuses on establishing substantial equivalence to predicate devices based on intended use, technological characteristics, and principles of operation, rather than providing a performance study with quantitative metrics.

Therefore, many of the requested details cannot be extracted from the provided text.

Here's a breakdown of what can and cannot be answered based on the input:

1. Table of acceptance criteria and the reported device performance

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

• Sample Size: Not specified.
• Data Provenance: Not specified, but the testing was described as "Laboratory testing," suggesting it was conducted internally by the manufacturer or a contracted lab. The country of origin of the data is not mentioned.
• Retrospective/Prospective: Not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable as no "ground truth" was established in the context of a clinical performance study. The evaluation focused on meeting design and functional specifications. The device's output "must be reviewed and interpreted by trained medical professionals who will exercise professional judgment."

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

• Not applicable as no adjudication method for a test set is described.

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 MRMC comparative effectiveness study was done or mentioned. The device is an electroencephalograph, intended for measuring and recording, with output reviewed by trained medical professionals. It is not an AI-assisted diagnostic tool in the sense of providing automated interpretations that would be compared to human readers.

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

• The document describes "Laboratory testing" where the device's functions and features were evaluated against specifications. This can be interpreted as a form of standalone performance evaluation for the hardware and software components, but it's not a clinical standalone performance study comparing its diagnostic accuracy to a ground truth. The device is explicitly stated to "require competent user input" and its output "must be reviewed and interpreted by trained medical professionals."

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

• Not applicable in the context of a clinical performance study measuring accuracy against a "ground truth." The evaluation focused on the device's ability to "meet its design and functional requirements" and specifications for safety and electromagnetic compatibility.

8. The sample size for the training set

• Not applicable. This device is an EEG monitor, not a machine learning or AI-driven diagnostic algorithm that would typically have a "training set."

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

• Not applicable (see point 8).

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