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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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