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SCS:
This system is indicated as the sole mitigating agent, or as an adjunct to other modes of therapy used in a multidisciplinary approach for chronic, intractable pain of the trunk and/or limbs, including unilateral pain. The trial devices are solely used for trial stimulation (no longer than 30 days) to determine efficacy before recommendation for a permanent (long term) device.

PNS:
This system is indicated for pain management in adults who have severe intractable chronic pain of peripheral nerve origin, as the sole mitigating agent, or as an adjunct to other modes of therapy used in a multidisciplinary approach. The Nalu Neurostimulation System for PNS is not intended to treat pain in the craniofacial region. The trial devices are solely used for trial stimulation (no longer than 30 days) to determine efficacy before recommendation for a permanent (long term) device.

The Nalu Neurostimulation System (referred to as the "Nalu System") incorporates a miniature implantable pulse generator (IPG), powered by an externally worn Therapy Disc device. The Nalu System therapy utilizes pulsed electrical current to create an energy field that acts on peripheral nerves or central nerves to inhibit the transmission of pain signals to the brain. The Nalu System may be implanted following a successful trial period using the Nalu Neurostimulation trial system. This device is intended to be used in the spinal column as well as the peripheral nerves in arm, leg, pelvic and other areas, as is typical of other devices and treatments for the same intended use.

The Nalu System is intended for stimulation of the spinal cord or peripheral nerves for patients experiencing chronic, intractable pain. This system is indicated for pain management in adults who have severe intractable chronic pain, as the sole mitigating agent, or as an adjunct to other modes of therapy used in a multidisciplinary approach. The system is not intended to treat pain in the craniofacial region. The trial devices are solely used for trial stimulation (no longer than 30 days) to determine efficacy before recommendation for a permanent (long term) device.

The Nalu System is comprised of the following components:
• Implantables (there are no proposed changes to these components as previously provided in K221376):
o Implantable pulse generator (IPG; available either as an integrated lead unit or with separately connected lead(s)) – provides electrical stimulation pulses that are transmitted through the leads, to the desired location, either on the spinal cord or peripheral nerve site(s).
o Leads – implantable and designed to deliver electrical pulses to the nerves via an array of four (4) or eight (8) cylindrical electrodes at the distal end.
o Surgical and Trial Tools – includes anchors, spoonbill needs, stylets, tearaway introducers, pocket tunneler, torque wrench, IPG insertion tool, straw tunneler; tools to support implantation of lead and IPG.

• Externals, Non-Sterile:
  o Externally worn controllers (for use with the permanent implant) and accessories – includes the Therapy Disc, Adhesive Clip, Wearable Garment, Therapy Disc Charger; houses the battery and electronics for RF power and controls the IPG for therapy delivery via the remote programmer (subject of this submission).
  o Externally worn stimulator (for use with the trial lead) and accessories – includes the Trial Therapy Disc; sends signals to the percutaneous leads during the trial period by way of the Electrode Interface Cable (EIC).
  • Software (subject of this submission):
  o Clinician Programmer, Patient Remote Control – used to configure the system parameters; also manages patient records, Therapy Discs and remote controls for patients with the Nalu System; runs on Android and iOS platforms and can be optionally used to control and manage Therapy Discs over a secure Bluetooth® Low Energy connection.

The provided text is a 510(k) premarket notification for the Nalu Neurostimulation System. It details modifications made to an existing device, primarily to its external components and software, and argues for substantial equivalence to a previously cleared predicate device (K221376).

Crucially, this document does not describe a study to prove a device meets acceptance criteria related to efficacy or performance comparable to what would be found in a multi-reader, multi-case (MRMC) study or a standalone algorithm performance evaluation for an AI/ML medical device.

Instead, the "acceptance criteria" and "proof" provided are focused on engineering verification and validation to demonstrate that the modifications to the existing device do not raise new questions of safety or effectiveness, thus maintaining substantial equivalence to its predicate. The device itself is a neurostimulation system for pain relief, not an AI/ML diagnostic tool.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts for ground truth, MRMC study, effect size of human reader improvement, standalone performance, type of ground truth, training set sample size, ground truth for training set) are not applicable to this submission, as it is not for an AI/ML algorithm requiring such performance evaluations.

However, I can extract information relevant to the engineering acceptance criteria and the validation activities performed for the modified device components.

Here's a breakdown of the information that can be extracted from the provided text, and an explanation of why other requested information is not present:

Acceptance Criteria and Device Performance (Engineering/Safety Context)

The document frames its "acceptance criteria" as demonstrating that the modified device's technological characteristics are effectively the same or do not raise different questions of safety and effectiveness compared to the predicate device. The performance is then shown through various engineering and validation tests.

Study Details (Context of Engineering Validation, Not AI Performance)

1. Sample size used for the test set and the data provenance: Not applicable in the context of clinical results from a test set as would be used for an AI/ML diagnostic device. The "test set" here refers to physical units of the modified device and its software undergoing various engineering and software validation tests. Data provenance is not described in terms of patient data.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as typically defined for AI/ML performance (e.g., expert consensus on medical images) is not relevant for this engineering and software validation. The "ground truth" for these tests are largely defined by engineering specifications, regulatory standards, and functional requirements.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. Adjudication methods are used in studies involving human interpretation or performance, typically for diagnostic accuracy.

4. 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, an MRMC comparative effectiveness study was NOT done. The document explicitly states: "No clinical testing was performed."
   • This device is a neurostimulation system, not a diagnostic imaging AI/ML device that assists human readers.

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

   • Not applicable in the context of an AI/ML algorithm. The "software testing" mentioned evaluates the software's functional correctness against its specifications, not its standalone diagnostic or interpretive performance.

6. The type of ground truth used (expert concensus, pathology, outcomes data, etc.): Not applicable for an AI/ML context. For the engineering and software validation, the "ground truth" is adherence to established engineering specifications, industry standards (e.g., ISO, IEC), and regulatory guidance.

7. The sample size for the training set: Not applicable. This submission is for hardware and software modifications to a neurostimulation device, not for an AI/ML model that requires a training set.

8. How the ground truth for the training set was established: Not applicable, as there is no AI/ML training set in this context.

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This system is indicated for pain management in adults who have severe intractable chronic pain of peripheral nerve origin, as the sole mitigating agent, or as an adjunct to other modes of therapy used in a multidisciplinary approach. The system is not intended to treat pain in the craniofacial region.

The trial devices are solely used for trial stimulation (no longer than 30 days) to determine efficacy before recommendation for a permanent (long term) device.

The Nalu Neurostimulation System for Peripheral Nerve Stimulation (also referred to as the "Nalu System") is used for peripheral nerve stimulation to provide therapeutic relief for chronic, intractable pain of peripheral nerve origin. The Nalu System incorporates a miniature implantable pulse generator, powered by an externally worn Therapy Disc device. The Nalu Neurostimulation therapy utilizes pulsed electrical current to create an energy field that acts on the peripheral nerves to inhibit the transmission of pain signals to the brain. The Nalu System may be implanted following a successful trial period using the Nalu Neurostimulation trial system. The Nalu System is comprised of 5 elements: Nalu Implantable Pulse Generator, Leads, Surgical and Trial Tools, Externally worn Therapy Disc, and Clinician Programmer and Remote Control.

This document describes a 510(k) premarket notification for the Nalu Neurostimulation System for Peripheral Nerve Stimulation. The submission aims to establish substantial equivalence to a previously cleared predicate device (K183579), primarily focusing on an update to the device's Magnetic Resonance (MR) Conditional Labeling to include full body scans.

Based on the provided text, there is no acceptance criteria table or specific study performance data for a device meeting acceptance criteria in the traditional sense of an AI/ML model for diagnostic or predictive purposes. This document is a regulatory submission for a physical medical device (implantable neurostimulator) and its associated external components and software, not an AI/ML diagnostic software. The "performance" discussed here relates to the safety and functionality of the device itself, particularly its compatibility with MRI, rather than the accuracy of a diagnostic algorithm.

Therefore, many of the requested elements (e.g., sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set details) are not applicable to this type of medical device submission.

However, I can extract the relevant information regarding the device's "performance" as presented in the context of this 510(k) submission, specifically concerning the MRI compatibility, as this is the primary change necessitating the resubmission.

Summary of Acceptance Criteria and Device (MRI) Performance:

Since this is not an AI/ML diagnostic device, the "acceptance criteria" are not framed in terms of metrics like accuracy, sensitivity, or specificity. Instead, they are related to established safety standards for medical devices, particularly regarding MRI compatibility. The "device performance" refers to the results of testing performed to ensure these safety standards are met.

1. Table of Acceptance Criteria and Reported Device Performance (Focusing on MRI Compatibility):

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

• Sample Size: The document does not specify the sample sizes used for the engineering tests (e.g., number of devices tested for MRI compatibility, displacement, torque, or artifacts). These are typically bench tests on physical units, not clinical data sets.
• Data Provenance: Not applicable in the context of clinical data. The tests are laboratory-based, non-clinical performance and bench testing.

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

• Not Applicable. This is not a study assessing the performance of a diagnostic algorithm where expert ground truth is established for medical images. The "ground truth" for this device's performance relies on engineering measurements and adherence to international and national standards (e.g., ISO, ASTM) for device safety and functionality.

4. Adjudication Method for the Test Set:

• Not Applicable. As there are no human readers or diagnostic interpretations involved in the "test set" (which consists of physical device tests), no adjudication method is necessary.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No. This type of study is typically done for diagnostic imaging devices or AI tools that assist human readers. This submission is for an implantable neurostimulation system, not a diagnostic imaging or AI assistance tool.

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

• Not Applicable. There is no "algorithm only" performance being evaluated in this submission in the context of diagnostic AI. The device's functionality (e.g., electrical stimulation parameters) and safety (e.g., MRI compatibility) are evaluated.

7. The Type of Ground Truth Used:

• The "ground truth" for the device's safety and performance is established through adherence to recognized international and national consensus standards (e.g., ISO/TS 10974, ISO 14708, ASTM F2052-15, ASTM F2213-17, ASTM F2119-2013) and engineering verification and validation testing. It is not based on expert consensus on medical image interpretations or clinical outcomes data in the context of diagnostic accuracy.

8. The Sample Size for the Training Set:

• Not Applicable. This is not an AI/ML device that requires a training set of data.

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

• Not Applicable. (See point 8).

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