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The Cionic Neural Sleeve NS-100 is intended to provide ankle dorsiflexion in adult individuals with foot drop and/or to assist knee flexion or extension in adult individuals with muscle weakness related to upper motor neuron disease /injury (e.g. stroke, damage to pathways to the spinal cord). The Cionic Neural Sleeve NS-100 electrically stimulates muscles in the affected leg to provide ankle dorsiflexion of the foot and/or knee flexion or extension; thus, it also may improve the individual's gait.

The Cionic Neural Sleeve NS-100 may also:

• Facilitate muscle re-education
• Prevent/retard disuse atrophy
• Maintain or increase joint range of motion
• Increase local blood flow

The Cionic Neural Sleeve NS-100 is a platform for the measurement and augmentation of lower limb mobility composed of a body-worn legging, a battery-powered electronic controller and a mobile application. The Cionic Neural Sleeve NS-100 has embedded sensors to measure limb movement and muscle activity. These data are used by the control unit to generate stimulation intended to activate muscles for exercise or functional assistance.

The Cionic Neural Sleeve NS-100 system sales carton consists of the following components:

• 1. SL-100 a fabric sleeve covering the upper and lower leg containing embedded motion sensors and skin-contacting electrodes. Left and right leg sleeves are available in two sizes: small, and medium.
• 2. DC-100 a portable battery-powered Control and Stimulation Unit that connects to, and is worn within the SL-100. The DC-100 communicates over Bluetooth™Low Energy protocol to the Cionic mobile application ("Cionic app").
• 3. Power supply and cable to recharge the DC-100 and connect the DC-100 to a user's computer when required.
• 4. Adhesive, electrically conductive and replaceable electrode pads.
• 5. Electrode cover sheets.
• 6. Instructions for Use documents.

Components are available as accessories to the Cionic Neural Sleeve NS-100 system:

• o Replacement electrode pads.
  The Cionic Neural Sleeve NS-100 requires a password-protected Cionic mobile application that is exclusively available to Cionic Neural Sleeve NS-100 iOS and Android users.

The Cionic Neural Sleeve NS-100 system consists of a software and hardware architecture that enables users to access a library exercise and augmentation programs. Programs can be added and removed from the user's mobile app. All exercise and assistance programs utilize a standard calibration and stimulation user interface that is extendible to future exercise and augmentation programs.

This 510(k) submission (K221823) from Cionic, Inc. is a Special 510(k) submission to add compatibility of the Cionic Neural Sleeve to support the Android operating system and minor software updates to improve overall stability and performance. As such, the submission primarily focuses on software verification and validation, along with wireless coexistence testing. The claim of substantial equivalence is made with respect to the predicate device, also the Cionic Neural Sleeve NS-100 (K213622).

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The provided 510(k) summary does not detail specific sample sizes for the test sets. For software validation and wireless coexistence, these typically involve testing on the device itself and against relevant communication standards. No patient data or clinical study details are provided in this summary. Therefore, there's no information on the country of origin of data or whether it was retrospective or prospective.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

Not applicable. This submission is for a software/OS compatibility update and does not involve clinical performance assessment requiring expert opinion for ground truth establishment.

4. Adjudication Method for the Test Set:

Not applicable. The tests performed are primarily engineering and software validation tests (wireless coexistence, software validation) and do not involve subjective interpretation requiring adjudication.

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

No, an MRMC comparative effectiveness study was not done. This submission is for a software and OS compatibility update, not for establishing clinical effectiveness or comparing human reader performance with and without AI assistance.

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

Not explicitly stated in terms of "standalone performance" in the context of an algorithm assessing medical images or data without human input. However, the software validation and wireless coexistence tests verify the system's technical functionality, which is an evaluation of the system's independent operation (without direct human user intervention during the specific test runs, although the device is designed for human interaction). There's no separate mention of an algorithm's standalone performance in a diagnostic or clinical decision-making capacity.

7. The Type of Ground Truth Used:

For the software and wireless coexistence tests, the ground truth would be defined by the technical specifications and standards (e.g., IEC 62304 for software, FDA guidance for wireless coexistence, Bluetooth Low Energy specifications for communication). The purpose of the tests is to verify that the device's software and communication capabilities adhere to these established technical requirements.

8. The Sample Size for the Training Set:

Not applicable. This is not an AI/ML device submission in the sense of a new algorithm being trained. The submission refers to "minor software updates" and "stability and performance" improvements. Therefore, there's no mention of a training set or machine learning model training in this context.

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

Not applicable, as there is no training set for an AI/ML algorithm mentioned in this submission.

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The Cionic Neural Sleeve NS-100 is intended to provide ankle dorsiflexion in adult individuals with foot drop and/or to assist knee flexion or extension in adult individuals with muscle weakness related to upper motor neuron disease /injury (e.g. stroke, damage to the spinal cord). The Cionic Neural Sleeve NS-100 electrically stimulates muscles in the affected leg to provide ankle dorsiflexion of the foot and/or knee flexion or extension; thus, it also may improve the individual's gait.

The Cionic Neural Sleeve NS-100 may also:

• Facilitate muscle re-education
• Prevent/retard disuse atrophy
• Maintain or increase joint range of motion
• Increase local blood flow

The Cionic Neural Sleeve NS-100 is a platform for the measurement and augmentation of lower limb mobility composed of a body-worn legging, a battery-powered electronic controller and a mobile application. The Cionic Neural Sleeve NS-100 has embedded sensors to measure limb movement and muscle activity. These data are used by the control unit to generate stimulation intended to activate muscles for exercise or functional assistance.

The Cionic Neural Sleeve NS-100 is intended to provide ankle dorsiflexion and/or plantarflexion in adult individuals with foot drop and/or to assist knee flexion or extension in adult individuals with muscle weakness related to upper motor neuron disease/injury (e.g. stroke, damage to pathways to the spinal cord). The Cionic Neural Sleeve NS-100 electrically stimulates muscles in the affected leg to provide ankle dorsiflexion and/or plantarflexion of the foot and/or knee flexion or extension; thus, it also may improve the individual's gait.

The Cionic Neural Sleeve NS-100 system sales carton consists of the following components:

• 1. SL-100 a fabric sleeve covering the upper and lower leg containing embedded motion sensors and skin-contacting electrodes. Left and right leg sleeves are available in two sizes: small, and medium.
• 2. DC-100 a portable battery-powered Control and Stimulation Unit that connects to, and is worn within the SL-100. The DC-100 communicates over Bluetooth™Low Energy protocol to the Cionic mobile application ("Cionic app").
• 3. Power supply and cable to recharge the DC-100 and connect the DC-100 to a user's computer when required.
• 4. Adhesive, electrically conductive and replaceable electrode pads.
• 5. Electrode cover sheets.
• 6. Instructions for Use documents.

Components are available as accessories to the Cionic Neural Sleeve NS-100 system:

• Replacement electrode pads.
  The Cionic Neural Sleeve NS-100 requires a password-protected Cionic mobile application that is exclusively available to Cionic Neural Sleeve NS-100 users.

The Cionic Neural Sleeve NS-100 system consists of a software and hardware architecture that enables users to access a library exercise and augmentation programs. Programs can be added and removed from the user's mobile app. All exercise and assistance programs utilize a standard calibration and stimulation user interface that is extendible to future exercise and augmentation programs.

The provided FDA 510(k) summary for the Cionic Neural Sleeve NS-100 (K213622) does not include a detailed study proving the device meets specific acceptance criteria based on performance metrics such as sensitivity, specificity, accuracy, or effect size for human readers with AI assistance.

The document focuses on demonstrating substantial equivalence to a predicate device (Bioness L300 Go System, K190285) rather than providing a standalone performance study with quantified acceptance criteria for diagnostic or assistive accuracy. The performance data presented is limited to non-clinical testing for safety and technical specifications, not clinical effectiveness in terms of how well it improves patient outcomes or how it performs against a measurable clinical metric.

Therefore, many of the requested items cannot be extracted directly from this document. However, I can provide what is available and clarify what is missing.

Acceptance Criteria and Device Performance (Based on Technical and Safety Testing)

While the document doesn't list quantitative clinical performance criteria, it outlines the non-clinical tests conducted to demonstrate the device performs as "intended" and is "substantially equivalent." The "reported device performance" in this context refers to its adherence to these technical and safety standards.

Detailed Information Regarding Study (Based on Document Analysis):

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not applicable/not provided in this summary. The document describes non-clinical bench testing and verification/validation processes, not a clinical study on a patient test set with performance metrics.
   • Data Provenance: Not applicable, as it's not a clinical data set. It refers to non-clinical testing performed by the manufacturer, Cionic, Inc.

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 clinical or diagnostic performance studies is not established in this document, as it outlines technical and safety testing.

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

   • Not applicable. There is no mention of a human-reviewed test set or adjudication process for clinical performance.

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. This is not an MRMC comparative effectiveness study involving human readers or AI assistance in a diagnostic context. The device is a functional neuromuscular stimulator, not an AI-assisted diagnostic tool.

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

   • The document implies extensive standalone engineering verification and validation of the device's electrical, mechanical, software, and biocompatibility aspects. However, this is not a clinical "standalone performance" in the sense of an algorithm making a clinical decision without human intervention. The device's function is to directly stimulate muscles based on detected limb movement.
   • The software was validated according to IEC 62304, and the overall system was "verified and validated successfully for its intended use through a combination of original bench testing and verification and validation of all software and firmware."

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

   • For the non-clinical testing, the "ground truth" was compliance with established engineering standards (e.g., IEC standards for electrical safety, biocompatibility, usability, software validation) and the device's design specifications. There is no clinical outcomes data or pathology-based ground truth presented in this summary for the purpose of demonstrating substantial equivalence.

7. The sample size for the training set:

   • Not applicable. This document does not describe an AI/machine learning model that would require a "training set" in the traditional sense for diagnostic or predictive performance. The device uses embedded sensors and a control unit to generate stimulation for functional assistance, implying a rule-based or control-loop system rather than a trained AI classification model.

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

   • Not applicable, as there is no mention of a training set for an AI/machine learning model.

Summary of Conclusions from the Document:

The Cionic Neural Sleeve NS-100 underwent comprehensive non-clinical testing, including electrical safety, biocompatibility, usability, and software validation. Based on the results, Cionic Inc. concluded that the device is substantially equivalent to the predicate Bioness L300 Go System. The differences noted, such as the ability to provide plantarflexion and variations in technological characteristics (e.g., number of output modes, power sources, stimulation channels, clinician/user control interfaces, and trigger sources), were deemed "minor with no impact to safety and effectiveness" because they either represented a subset of the predicate's capabilities, adhered to recognized safety standards, or achieved similar functional outcomes through different but validated technological means.

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