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For Prescription and Home Use by prescription from a medical professional:
The TrainFES advanced is a neuromuscular electrical stimulator indicated for use under medical supervision for adjunctive therapy in the treatment of medical diseases and conditions.

As a powered muscle stimulator, TrainFES advanced is indicated for the following conditions:

• Relaxation of muscle spasms
• Prevention or retardation of disuse atrophy
• increasing local blood circulation
• immediate post-surgical stimulation of calf muscles to prevent venous thrombosis
• Maintaining or increasing range of motion
• Muscle re-education

As an external functional neuromuscular stimulator (FES), TrainFES Advanced is indicated for the following conditions:

• Helps to relearn voluntary motor functions of the extremities.

TrainFES' Advanced intended population is anybody aged 22 or over.

Environments of use: TrainFES Advanced devices can be used by both therapists and patients, in the clinic, hospitals or at home.

Platform: TrainFES is a battery-powered, wireless device, accessible through software.

TrainFES Advanced is a portable functional electrostimulator with 6 channels designed for use in the clinics and hospitals by the medical professionals as well as in the home environment by the patient. This device generates electrical impulses to stimulate the musculature of paralyzed seqments and facilitate both the relearning of movement and neuromodulation of tone.

TrainFES Advanced is a battery-powered, wireless device, configurable from the TRAINFES App, available for Smartphone and Tablets, which allows you to adjust different parameters and follow a training plan from your smartphone. Session settings can be retrieved from the PC or Cloud.

The provided document describes the FDA 510(k) premarket notification for the "TrainFES Advanced" device, a neuromuscular electrical stimulator. The purpose of this submission is to demonstrate substantial equivalence to a predicate device (Stella BIO, K210002).

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

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state "acceptance criteria" for the device's performance in a quantitative manner (e.g., target accuracy, sensitivity, specificity). Instead, the substantial equivalence justification relies on demonstrating that the TrainFES Advanced device performs similarly to or meets the safety and effectiveness standards of the predicate device, K210002.

The table below summarizes the comparison of key technical characteristics between the TrainFES Advanced and its predicate, Stella BIO, highlighting where "performance" is discussed in terms of meeting relevant standards or being considered equivalent. The reported "performance" for TrainFES Advanced is intrinsically linked to its compliance with these standards and the assertion that differences do not raise new safety or effectiveness concerns.

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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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The NeuroMetrix SENSUS is intended for use as a transcutaneous electric nerve stimulation device for the symptomatic relief and management of chronic intractable pain.

The device may be used during sleep. The device is labeled for use only with the NeuroMetrix SENSUS Electrode.

The SENSUS device, is a transcutaneous electrical nerve stimulator with a single output mode. The device utilizes a microprocessor running embedded software to control a high-voltage circuit that generates stimulating pulses with specific technical characteristics including pulse shape, amplitude (current), duration, pattern, and frequency. The device is powered by a permanent rechargeable Lithium-Ion battery that is charged through a USB cable connected to an AC adapter.

The device delivers electrical stimulation to the patient through disposable, single-patient use electrodes placed on the patient's body. The device is labeled for use only with the SENSUS Electrode (K121816), to which it connects through insulated female medical snap connectors embedded within its housing.

The device has a push-button that initiates stimulation, and controls the intensity. The device has a single two color LED for indication of stimulation status, battery charging, and error conditions.

Here's an analysis of the acceptance criteria and study for the NeuroMetrix SENSUS device, based on the provided text:

Acceptance Criteria and Device Performance

The primary focus of the study described is the validation of the device's electrode peeling detection feature, which allows the device to be safely used during sleep.

Study Details for Electrode Peeling Detection Validation

1. Sample Size Used and Data Provenance:

   • Test Set Sample Size: 66 subjects and 132 SENSUS electrodes were used. There were two protocol runs, each with 66 tests, totaling 132 tests. The prospective validation sample size was set to 60 tests to meet the 0% failure rate statistical criterion.
   • Data Provenance: The study was described as "prospective validation," indicating it was specifically designed and conducted for this purpose. The country of origin is not explicitly stated, but NeuroMetrix is based in Waltham, MA, USA, suggesting the study was likely conducted in the USA.

2. Number of Experts and Qualifications for Ground Truth:

   • The document does not explicitly mention the use of external experts to establish ground truth for the electrode peeling detection test. The "ground truth" for this test was the physical measurement of the electrode area remaining on the skin at the instant stimulation halted, as determined by the study methodology.

3. Adjudication Method:

   • Not applicable/Not mentioned. The study involved objective measurements of physical parameters (electrode contact area).

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No. This was a technical validation study for a safety feature, not a comparative effectiveness study involving human readers.

5. Standalone (Algorithm Only) Performance:

   • Yes. The study focused on the automatic performance of the device's embedded algorithm in detecting electrode peeling and halting stimulation. There was no human-in-the-loop component for this safety feature.

6. Type of Ground Truth Used:

   • Objective Measurement/Engineered Truth: The ground truth was established by direct measurement of the electrode-to-skin contact area at the point where the device halted stimulation. The "failure" condition was defined objectively as the remaining contact area being less than 3.5 cm².

7. Sample Size for Training Set:

   • Not applicable/Not mentioned. The document describes a validation study for a specific safety mechanism (electrode peeling detection). It does not provide details of any machine learning model training or a "training set" in the context of AI. The device uses "embedded software to control a high-voltage circuit," implying rule-based or control system logic rather than a conventional machine learning model with a distinct training phase.

8. How Ground Truth for Training Set was Established:

   • Not applicable, as no training set for a machine learning model is described. The device's operational parameters and safety thresholds (like the 3.5 cm² peeling threshold) would have been established through engineering design, risk analysis, and relevant standards, rather than a data-driven training process with a ground truth similar to clinical AI models.

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