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The Wave Electrode is to be used exclusively for external prosthetic fittings of the upper limbs.

Wave Electrode is an active analogue electrode for detecting any surface electromyographic signals, used for controlling prosthetic devices. It is compact and low-power, ensuring an accurate and fast reading of muscle electrical potentials generated voluntarily by the user. It also provides a real-time output signal proportional to the detected muscle activation. Through the Wave Electrode it is possible to non-invasively detect the electrical signal produced by the residual muscles on the patient's amputated limb (unilateral amputees, starting from a transradial amputation level) and send an electrical signal to the electronic board of the prosthetic hand with a proportional width to the detected contraction. Wave Electrode is only compatible with the Adam's Hand that, according to the Requlation Number 890.3420, are classified as class I medical device. Wave Electrode is available in two different models: Mod. AE02-50, with notch filter centred on the 50 Hz frequency; Mod. AE02-60, with notch filter centred on the 60 Hz frequency

This document is a 510(k) Premarket Notification from BionIT Labs Srl for their Wave Electrode (AE02-60; AE02-50) devices, seeking clearance from the FDA. The document focuses on demonstrating substantial equivalence to predicate devices, and therefore does not contain acceptance criteria or performance studies in the way you might expect for a novel device or AI/ML algorithm.

Here's an analysis based on the provided text, highlighting what is present and what is absent regarding your requested information:

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

The document does not explicitly present a table of acceptance criteria with corresponding performance statistics. Instead, it relies on demonstrating compliance with recognized electrical safety, EMC, and biocompatibility standards, and functional compatibility with a specific prosthetic hand. The performance is assessed by meeting these standards and ensuring the device operates as intended alongside the "Adam's Hand®" prosthetic hand.

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

This information is not provided in the document. The non-clinical performance data refers to "internal testing" and testing by "an accredited laboratory," but specifics on sample sizes, types of data (e.g., specific scenarios, duration), provenance, or study design are omitted.

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)

This information is not applicable/not provided as there is no mention of a ground truth established by experts in the context of diagnostic or interpretive performance for an AI/ML algorithm. The device is a cutaneous electrode for EMG signal detection, and its performance is evaluated against engineering and biological safety standards, not against an expert-derived ground truth for an interpretation task.

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

This information is not applicable/not provided. As explained above, there's no mention of a ground truth derived from expert adjudication for interpretive tasks.

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. This type of study is typically relevant for AI/ML-driven diagnostic or interpretive devices that assist human readers. The Wave Electrode is a hardware device for signal acquisition, not an AI/ML diagnostic tool.

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

No standalone algorithm-only performance study was done or mentioned. The device itself is hardware. The document states it is an "analog device and has no on-board programmable electronics (FW and or PEMS)."

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

Given the nature of the device (cutaneous electrode), the "ground truth" implicitly refers to:

• Engineering specifications and recognized standards: Performance is measured against criteria for electrical safety (IEC 60601-1, IEC 60601-1-11), electromagnetic compatibility (IEC 60601-1-2), and biocompatibility (ISO 10993 series).
• Intended function: The ability to "detect, process, and transmit physiological signals" and operate as intended "in conjunction with 'Adam's Hand®' prosthetic hand."

There is no mention of ground truth related to medical diagnoses, pathology, or outcomes data, as these are not relevant to the function of a cutaneous EMG electrode.

8. The sample size for the training set

This information is not applicable/not provided. The Wave Electrode is described as an analog device without programmable electronics or software. Therefore, there is no AI/ML algorithm that would require a "training set."

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

This information is not applicable/not provided for the same reasons as point 8.

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REL-k is a prosthetic knee, important element of a lower limb prosthesis, a medical device that is used to replace a missing or deformed limb in both static and dynamic deambulation functions

The Rel-k is an artificial limb prosthesis indicated for individuals that have undergone a trans-femoral amputation. The Rel-k is intended to replace a missing or deformed limb and functions in both normal/standing (static) and dynamic walking. The Rel-k consists of: Pyramidal Head, Angular Sensor, Force sensor, Servo assisted Hydraulic Damper (MPC damper), Removable Battery and electronics compartment, Carbon Fiber Shell (outer casing), Attachment for a standard 30mm diameter tube.

The provided 510(k) summary for the Rel-k Artificial Limb Prosthesis does not contain information about acceptance criteria or a study proving the device meets said criteria in the way typically associated with AI/software devices. This document is for a physical medical device (an artificial limb), not a software algorithm or AI model, hence the typical metrics for software performance (sensitivity, specificity, AUROC, etc.) are not applicable here.

The 510(k) process for devices like the Rel-k focuses on demonstrating "substantial equivalence" to a predicate device, primarily through engineering principles, physical testing (e.g., fatigue, static load), material compatibility, and sometimes clinical performance in human use for the specific physical device.

Therefore, many of the requested fields regarding AI/algorithm performance and ground truth establishment cannot be filled from this document.

However, I can interpret the request in the context of the provided document by focusing on the "demonstration of substantial equivalence" which is the core of this type of 510(k).

Here's an attempt to address the prompt based on the available information, noting where information is not present:

Acceptance Criteria and Study for Rel-k Artificial Limb Prosthesis

The provided 510(k) summary for the Rel-k Artificial Limb Prosthesis focuses on establishing substantial equivalence to a legally marketed predicate device (Otto Bock C-Leg, K991590), rather than defining and meeting specific, quantifiable acceptance criteria for an AI or software model. The "study" in this context refers to the comparison and analysis performed to demonstrate this equivalence.

This device is a physical knee joint for a prosthetic limb, and the regulatory pathway does not involve the type of performance metrics, training sets, or expert adjudication typically associated with AI/ML diagnostic or prognostic devices.

1. Table of Acceptance Criteria and Reported Device Performance

Given this is a physical device submission focused on substantial equivalence, the "acceptance criteria" are implied by the features and performance of the predicate device, and the "reported device performance" is the demonstration that the Rel-k is comparable.

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

• Sample Size for Test Set: Not applicable in the context of an AI/ML algorithm's test set. For a physical device submission, this would typically involve mechanical testing (e.g., fatigue, static load tests) on a specific number of manufactured units, or potentially a limited human factors or clinical study if new questions of safety/effectiveness arose. This document does not detail specific physical testing numbers.
• Data Provenance: Not applicable for AI/ML data provenance. Any testing data would have been generated in a lab setting, or potentially from a limited clinical trial (though none is explicitly mentioned as part of the equivalence demonstration for this Class I device).

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

• Number of Experts: Not applicable. Ground truth for an AI/ML model.
• Qualifications of Experts: Not applicable.

4. Adjudication method for the test set

• Adjudication Method: Not applicable.

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, this is not applicable as the device is a physical prosthetic component, not an AI-based diagnostic/assistant tool.

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

• Standalone Performance: No, this is not applicable. The Rel-k is a physical device that functions in conjunction with a human wearer.

7. The type of ground truth used

• Type of Ground Truth: Not applicable for AI/ML ground truth. For a physical device, "ground truth" relates to engineered specifications, material properties, and the established performance profile of the predicate device against which the new device is compared. This would be established through engineering standards, mechanical tests, and potentially clinical evaluations of the predicate itself.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This concept pertains to AI/ML models.

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

• How Ground Truth for Training Set was Established: Not applicable.

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SILVERSEAL® Orthotic Components with X-Static® are used as components on various orthotic devices intended for medical purposes that can be worn as a cervical collar or brace. The component comprises a knitted stockinette which is made of 90% cotton or polyester, and 10% X-Static®, which is 1.5% silver oxide. The component provides the skin with an antimicrobial barrier.

SILVERSEAL® Orthotic Components with X-Static® are made of flexible, non-adherent fabric consisting of a knitted or made or in fabric which is 90% cotton or polyester, and 10% of a continuous nylon fiber substrate with a metallic silver surface containing approximately 1.5% silver oxide.

The Noble Fiber Technologies, Inc. 510(k) submission for the SILVERSEAL® Orthotic Components with X-Static® does not include acceptance criteria or a study that evaluates device performance against specific efficacy endpoints in the same way a diagnostic or therapeutic device might. Instead, this submission focuses on biocompatibility and substantial equivalence to a predicate device.

Here's an breakdown of the relevant information provided:

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

This document does not present quantitative acceptance criteria or a performance table for efficacy. The "performance" assessment is based on biocompatibility and antimicrobial properties, which are discussed qualitatively.

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 states that the device was "subjected to standard in vivo biocompatibility" tests, including sensitization, irritation, and acute in vivo blood incompatibility. However, it does not specify the sample size for these tests. It also does not explicitly state the country of origin of the data or whether the tests were prospective or retrospective, although biocompatibility testing is typically prospective. The testing was performed by "North American Science Associates, Inc. (NAMSA)."

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):

This information is not provided. Biocompatibility testing typically involves laboratory professionals and toxicologists, but no details on "experts" or their qualifications for establishing ground truth are given in this K051256 summary.

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

This information is not provided. Adjudication methods are not typically relevant for standard biocompatibility testing. The assessment of biocompatibility usually relies on established laboratory protocols and interpretation of results against predetermined biological endpoints.

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:

This is not applicable. This device is a component of an orthotic, and its performance evaluation is based on biocompatibility and antimicrobial properties, not on diagnostic or therapeutic effectiveness requiring human reader-dependent interpretation or AI assistance.

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

This is not applicable. This device is not an algorithm or AI system. Its performance relates to material properties and biological interaction.

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

The ground truth for biocompatibility testing is based on established biological endpoints and toxicological principles, as defined by international standards (ISO 10995, likely a typo for ISO 10993 which is for Biological Evaluation of Medical Devices). This involves evaluating for adverse biological reactions such as irritation, sensitization, and specific toxic effects, usually observed in animal models (in vivo) or in vitro cell cultures.

8. The sample size for the training set:

This is not applicable. This device is not an AI/ML algorithm that requires a "training set."

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

This is not applicable. As mentioned above, there is no training set for this type of device.

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The MyoSystem with Customizing is intended for adult(s) who require an external electric upper extremity system.

The MyoSystem with Customizing is an adult external electric upper extremity system which allows the CPO to adjust all relevant parameters of the control of an external powered upper extremity prosthesis by a Personal Computer (PC). The system allows the connection of the control of a prosthesis with a PC by serial communication. A PC Software program allows the monitoring of how the patient performs with the prosthesis and enables the practitioner to change the control parameters according to the patient's needs. In addition, the practitioner can do the same program changes between control programs of a component as he/she can do by changing a colored coding plug. As it is a much faster process to change a program by the click of a button rather than to dismantle the prosthesis to gain access to the coding plug of a component, there is less disruption in the fitting process. This makes it less tiring for the patient and practitioner. As this system allows only additional adjustments to the existing adjustment possibilities by dials, there is no program change in the components, The same components which are used by the current conventional adjustment process are used with the adjustment process by CUSTOMIZING.

The provided text is a 510(k) summary for the Otto Bock MyoSystem with Customizing. It describes the device, its intended use, and its substantial equivalence to a predicate device. However, it does not contain any information regarding acceptance criteria or a study that proves the device meets specific performance criteria.

The document is a regulatory submission for premarket notification, focusing on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting specific performance study results against defined acceptance criteria.

Therefore, I cannot provide the requested information from the given text.

Here's why each point cannot be addressed:

1. A table of acceptance criteria and the reported device performance: This information is not present. The document focuses on describing the device and asserting substantial equivalence.
2. Sample sized used for the test set and the data provenance: No test set or study data are mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable as no test set or ground truth establishment is described.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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 external limb prosthetic system, not an AI diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

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Fitting of lower limb prosthesis .
Highly mobile individuals and/or individuals who need stance stability .

C-LEG (3C100) is a microprocessor-controlled knee joint system with hydraulic stance and swing phase control. The C-LEG immediately adapts to different walking speeds and provides knee stability.
The C-LEG (3C100) is recommended for lower limb amputees weighing up to 110 kg (220 pounds) who have a moderate (level 2 or 3) functional level. It is a monocentric knee joint composed of:

• Carbon Fiber Frame ●
• Hydraulics with Servo Motor ●
• Electronics .
• Distal Tube Clamp ●
• . Upper Joint
• Shin Tube Adapter
  Components of the C-LEG (3C100) are the following:
• Electronic Knee Joint 3C87 ●
• 2R90 Tube Adapter or .
• Tube Adapter with Torsion Adapter 2R91 .
• Rotation Adapter 4R57 .
  Accessories are the following:
  • 757L17 Charging Device
• Power Unit ● 757L16
• Prosthetic Foot 1D10, 1D25, 1A30 .
• Foam Cover ● 3826
• . 4X70 Slider Software
• Extension Cable . 4X72
• 4X71 PC Interface .
• 4R302 Transportation Case ●

The provided text does not contain detailed information about specific acceptance criteria or a study that proves the device meets those criteria in the format requested.

The document is a 510(k) summary for the Otto Bock C-LEG (3C100), which declares its substantial equivalence to a legally marketed predicate device (Otto Bock's 3C1). In the context of 510(k) submissions, the primary "acceptance criterion" is often demonstrating substantial equivalence to a predicate device, rather than meeting specific performance thresholds through a new, independent clinical study as might be required for a PMA or de novo submission.

Here's a breakdown of why many of your requested items cannot be fulfilled based on the provided text:

• No detailed performance study with acceptance criteria: The document focuses on demonstrating substantial equivalence, not on presenting a standalone performance study with specific metrics and acceptance thresholds.
• No information on sample sizes, ground truth, experts, or adjudication methods for a performance study: Since a detailed performance study proving specific acceptance criteria isn't described, these details are absent.
• No MRMC study information: This type of study would be part of a comprehensive performance evaluation, which is not detailed here.

However, I can extract information related to the device and its intended use, which indirectly relates to its "acceptance" for market clearance:

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

Based on the 510(k) summary, the primary "acceptance criterion" for market clearance is substantial equivalence to a predicate device.

The study that proves the device meets the acceptance criteria:

The document states: "The C-LEG (3C100) is substantially equivalent to Otto Bock's 3C1, a Class I Exempt Device according to 21 CFR Part 890.3420. Differences that exist between these devices, relating to technical specifications, physical appearance and design, do not affect the relative safety and effectiveness of the C-LEG (3C100)."

This suggests that the "study" was primarily a comparative analysis demonstrating that the C-LEG (3C100) is sufficiently similar to the predicate device, and any differences do not raise new questions of safety or effectiveness. This is typical for a 510(k) submission. No specific patient study with acceptance criteria, sample sizes, or ground truth establishment is described in this summary.

Details that cannot be extracted from the provided text:

2. Sample size used for the test set and the data provenance: Not applicable/not provided for a comparative equivalence submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable/not provided.
4. Adjudication method: Not applicable/not provided.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. The device is a prosthetic knee joint, not an AI diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. The device is a prosthetic knee joint, not an algorithm.
7. The type of ground truth used: Not applicable/not provided.
8. The sample size for the training set: Not applicable (not an AI/ML device, and no training set for a performance study is mentioned).
9. How the ground truth for the training set was established: Not applicable.

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