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Neuronaute is a system intended to acquire, display, store, archive, and periodically transmit EEG signals from the brain using a full montage array to enable review at a physician's office, hospital, or other remote locations. It allows remote access by users via the Neuronaute N-CLOUD which receives EEG signals from Neuronaute Head Module which sends transmissions to the cloud. Neuronaute and its associated software are intended to assist in the diagnosis of neurological disorders. Neuronaute and its components do not provide any diagnostics conclusions or automated alerts of an adverse clinical event about a patient's clinical condition.

The device is for use by trained medical professionals for patients under medical supervision. The device is intended for use on adults (ages 18 and above). Neuronaute is not intended to replace direct communication with healthcare providers. The system data should not be used alone, but should be used along with all other clinical data and exams to come to a diagnosis.

Neuronaute allows up to 24 channels EEG monitoring. It includes the following components: Neuronaute Head Module, Neuronaute High Capacity Battery Module, Neuronaute BioAdapter, Neuronaute Mobile App, Neuronaute N-CLOUD, Neuronaute N-DEO, Neuronaute N-WAY, Neuronaute IceCap.

The provided text describes the Neuronaute device, an electroencephalograph (EEG) system, and its substantial equivalence to a predicate device (AE-120A EEG Head Set, K183529) for FDA clearance. However, it does not contain a specific study demonstrating that the device meets numerically defined acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, accuracy for a particular condition). Instead, the submission focuses on demonstrating substantial equivalence through non-clinical performance testing against recognized standards.

Therefore, many of the requested items (e.g., sample size for test set, number of experts for ground truth, MRMC study, standalone performance) are not applicable or cannot be extracted from this document, as a clinical performance study with such metrics was not submitted.

Here's a breakdown of the information that can be extracted or inferred:

1. Table of Acceptance Criteria and Reported Device Performance

As a clinical performance study with specific diagnostic metrics (like sensitivity, specificity, or accuracy) was not submitted, there isn't a table of acceptance criteria for diagnostic performance against specific disease states. Instead, the acceptance is based on meeting technical and safety standards, and demonstrating signal quality, all of which are considered "performance" in this context.

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Esprit Nova is a software-only product intended to assist a physician in the diagnostic evaluation of sleep quality and sleep disordered breathing in adults only. Esprit Nova analyzes the physiological signals and automatically scores sleep events; including the stages of sleep, microarousals, snoring, periodic limb movements, desaturations and sleep disordered breathing events apneas, hypopneas, and respiratory event related arousals). This device is to be used under the supervision of a physician. The device does not provide any diagnostic conclusion about the patient's condition.

Esprit Nova is a software application that analyzes previously recorded physiological signals obtained during sleep. The software can analyze any EDF files acquired with Trackit SleepWalker (K010460) Compumedics Somté PSG System( K072201) and/or Sandman (K040113). Automated algorithms are applied to the raw signals to interpret the raw signal information. The software automates recognition of:

• Sleep stages Rapid Eye Movement (REM), nREM (N1, N2, N3) and wake
• Heart rate
• Snoring
• Sleep/wake
• Body position
• Arousals
• EEG, ECG, EOG, EMG waveforms
• Sa02
• Airflow
• Respiratory Effort
• Apneas and Hypopneas
• Oxygen desaturations.
• Limb movements .
  The software identifies and rejects periods with poor electroencephalography signal quality. The output of the device is a comprehensive sleep study report. Medical and history information can be entered from a questionnaire. The automated analysis of physiological data is integrated with the questionnaire data, medical and history information and included in the report. The Esprit Nova analysis module is hosted on a central server, while the administrative module is a stand-alone application for use on Microsoft Windows 7 (or higher) operating system platforms. The administrative module works as a local database to keep records of patients' and to transmit data back and forth to the central server.

Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criterion for Esprit Nova's performance was to demonstrate equivalence to the reported performance of the predicate device (Sleep Profiler K153412 for sleep staging, and Sandman Elite K153353 for PLM detector) and to "perform equivalently to the gold standard" (panel of 3 electrophysiologists). The table above shows the reported performance and how it compares to these benchmarks.

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

• Sample Size: 60 PSG studies.
• Data Provenance: The studies were from "adult patients that were seen at a Sleep Clinic." The specific country of origin is not explicitly stated, but the submitter's address is in Dundas, Ontario, Canada, which could suggest Canadian data. The studies comprised a mix of diagnoses:
  • 40 studies with varying degrees of Obstructive Sleep Apnea (12 severe, 14 moderate, 14 mild)
  • 1 study for Restless Legs Syndrome
  • 3 studies for Restless Legs Syndrome + OSA
  • 7 Titration studies
  • 9 normal studies
• Retrospective/Prospective: Not explicitly stated, but the description "studies from adult patients that were seen at a Sleep Clinic" typically implies retrospective data collection from existing patient records.

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

• Number of Experts: 3
• Qualifications of Experts: "3 EEG board certified medical professionals" (referred to as "electrophysiologists" in another section).

4. Adjudication method for the test set

• The text describes the ground truth as "a panel of 3 EEG board certified medical professionals scoring studies as done in their daily practice (i.e gold standard)". This implies that the consensus or individual scores of these three experts served as the ground truth. However, the specific adjudication method (e.g., 2+1, 3+1, majority vote, or if each expert's scoring was considered individually against the algorithm's output without inter-expert adjudication for the final ground truth) is not explicitly stated. It just says their scoring was the "gold standard."

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 in the context of human readers with AI assistance versus without AI assistance. The study focused on the standalone performance of the algorithm against expert scores. The "gold standard" was the panel of experts, not human readers assisted by AI.

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

• Yes, a standalone performance study was done. The entire clinical validation section describes the "Algorithm Performance Comparison" of Esprit Nova against the "expert scoring," which establishes its standalone performance.

7. The type of ground truth used

• Expert Consensus/Opinion: The ground truth for the sleep staging and PLM detection was established by a "panel of 3 EEG board certified medical professionals" scoring the studies. This is explicitly stated as the "gold standard."

8. The sample size for the training set

• The document does not explicitly state the sample size used for the training set. It only describes the test set.

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

• The document does not provide information on how the ground truth for the training set was established. It only details the ground truth establishment for the clinical validation (test) set.

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The Lifelines iEEG is an EEG system that allows acquisition, display, archive, storage and analysis of physiological signals. The intended user of this product is a qualified medical practitioner trained in electroencephalography who will exercise professional judgment in using the information. The Lifelines iEEG system also includes the display of a quantitative EEG plots, power spectrum, which is intended to help the user to monitor and analyze the EEG. This device does not provide any diagnostic conclusion about the patient's condition to the user.

Lifelines iEEG is medical device used to acquire, display, archive, store and analyze EEG examinations. The EEG is presented in a conventional way and conventional signal processing is applied such as re-montaging and band pass filtering. The system is also capable of acquiring and presenting digital video synchronized to the EEG if this is available. Some advanced analysis methods are provided as an aid: FFT analysis and Artifact Removal. The system software is designed using service oriented architecture enabling the possibility of reviewing data over WAN without the use of additional remote desktop software solutions.

The components of Lifelines iEEG are:

• Lifelines iEEG software:
  • . iEEG Centrum
  • . iEEG Review
  • iEEG Acquisition .
• Lifelines Trackit, Lifelines Ltd, 510(k)#K010460
• Lifelines Photic Stimulator, Lifelines Ltd, 510(k)# K101691 ●
• Off the shelf PC and medical grade power supply ●
• Off the shelf IP Video Camera ●

This 510(k) submission for the Lifelines iEEG 2.0 device primarily focuses on demonstrating substantial equivalence to a predicate device (Natus Medical, Inc., DG Nervus/NicoletOne, K964280) rather than presenting a standalone study with acceptance criteria for clinical performance. The documentation emphasizes software verification and validation, along with conformance to various IEC standards for safety and essential performance.

Therefore, many of the requested sections related to clinical study design, sample sizes for test/training sets, expert adjudication, MRMC studies, and ground truth establishment are not explicitly addressed in this document. The device is an EEG system for acquisition, display, archive, storage, and analysis of physiological signals, and the submission argues that it is substantially equivalent to existing, legally marketed devices.

Here's a breakdown of the available information:

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

No explicit acceptance criteria or reported device performance metrics in terms of clinical accuracy (e.g., sensitivity, specificity for diagnostic tasks) are provided in this document. The submission focuses on demonstrating substantial equivalence based on intended use, technological characteristics, and conformance to safety and performance standards.

The document highlights the following characteristics of the Subject Device (Lifelines iEEG):

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The device is intended to measure, amplify, and record physiological signals acquired from a patient for archival in a sleep study. The physiological signals and conditioned for analysis and display. The data may be analyzed in real-time or offline on dedicated polysomnography software running on a personal computer by a qualified sleep clinician to aid in the diagnosis of Sleep Disorders.

The device is intended for use by healthcare professionals within a hospital, laboratory, clinic, or nursing home; or outside of a medical facility under direct supervision of a medical professional.

The device is intended for use on both adults and children only under the direction of a physician or qualified sleep technician.

The device or any accessory, does not include alarms, and is not intended to be used as a critical component of an alarm system.

The device or any accessory, is not to be used alone as an apnea monitor or as a component in an apnea monitoring system.

The device or any accessory, is not to be used alone as a life support device or as a critical component of a life support system.

The Polysmith Sleep System, Model NTI6600 is intended to amplify and record physiologic potentials used for Polysomnography (PSG) or Sleep Studies. The device consists of a compatible amplifier, head box, PC, patient sensors, and may include optional external devices, USB DC Box, and audio/video input devices.

Compatible amplifiers may use commercially available sensors and electrodes, an internal SpO2 module, and internal pressure transducers to collect, digitize, and send physiological signals to the host PC.

The Polysmith software may record from video, speaker and microphone equipment. The Polysmith software may also record auxiliary signals from compatible amplifiers or USB DC Box which allow for data inputs from compatible sources.

Polysmith records and displays the data for online or offline review. Qualified practitioners use the information to score Polysomnograms and diagnose Sleep Disorders.

Here's a breakdown of the acceptance criteria and study details for the Polysmith Sleep System, Model NTI6600, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" as separate performance thresholds the device must meet. Instead, it presents the "Automated Analysis Agreement" as the device's performance, which is then compared against "Average Human Scoring Agreement." Assuming the implied acceptance is substantial equivalence to human performance for these metrics, the table is structured as follows:

In the "Additional Sleep Staging Analysis," which seems to be a more detailed analysis, the total agreement for automated scoring against consensus human scoring is:

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

• Sample Size (Automated Analysis): 8,053 recorded epochs, of which 7,606 were scored.
• Sample Size (Additional Sleep Staging Analysis): 20 sleep studies.
• Data Provenance: The studies were chosen at random from existing sleep studies of acceptable signal quality from accredited labs. For the automated analysis, studies were chosen at random from a sleep lab independent of Neurotronics. The document does not specify the country of origin, but given the FDA submission, it's likely US-based or compliant with US standards. The data is retrospective.

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

• Automated Analysis: Two expert scorers from different organizations. Each is a registered sleep clinician with at least 5 years' experience scoring sleep records.
• Additional Sleep Staging Analysis: Three independent scorers. Each is a registered sleep specialist with at least five years' experience in the field. Each had some prior experience using Polysmith to manually score studies.

4. Adjudication Method for the Test Set

• Automated Analysis: The document states "The human scoring was completed by two expert scorers." It then calculates "Average Human Scoring Agreement," implying an average of their individual scores or comparison. It doesn't explicitly describe an adjudication process for disagreements between the two human scorers to establish a single ground truth for direct comparison with the automated analysis. Instead, it compares the automated system's performance against this average human agreement, and also compares the two human scorers' agreement with each other.
• Additional Sleep Staging Analysis: This section explicitly used a majority method (2/3 majority-rule) to establish the "true sleep staging (consensus)." Epochs where there was no agreement among the human scorers were discarded (non-consensus).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, a direct MRMC comparative effectiveness study "with AI vs without AI assistance" was not explicitly described in the context of improving human reader performance. The study focused on the standalone performance of the automated analysis system compared to human scoring. While humans scored the data, the goal was to assess the device's accuracy relative to human experts, not to measure the improvement in human performance aided by the device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, a standalone performance analysis was conducted. The "Automated Analysis Agreement" and the "Results" section for "Additional Sleep Staging Analysis" directly report the performance of the algorithm itself against human expert assessments (either average or consensus). The scorers for the "Additional Sleep Staging Analysis" were explicitly provided with a version of Polysmith that "did not have any automated analysis capability," emphasizing that the human scoring served purely as ground truth.

7. The Type of Ground Truth Used

• Expert Consensus / Expert Scoring: For both analyses, the ground truth was established by human expert scorers. In the "Automated Analysis," it's based on two expert scorings. In the "Additional Sleep Staging Analysis," it's based on a 2/3 majority rule consensus of three expert scorers.

8. The Sample Size for the Training Set

• Not provided. The document states, "The studies used for this testing were not used to train the algorithm," but it does not specify the size or characteristics of the training set used for the algorithm's development.

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

• Not provided. The document focuses solely on the ground truth for the test sets and explicitly states the test sets were not used for training. Information on how the training data's ground truth was established is absent.

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The iEEG device is intended to acquire and store electrical activity of the brain and patient data for review by a medical professional using a digital EEG system to monitor the brain. The device is intended for use in a healthcare facility, clinical research environment, or in the home under the supervision of a qualified healthcare professional. The device is intended for use on all patient populations including pediatric.

The Intelligent Electroencephalogram (iEEG) device acquires and stores electrical activity of the brain and patient data. The iEEG can be used with other FDA cleared devices such as the BraiNet Kit (K043009) and Ives EEG electrode (K062880). The BraiNet Kit consists of the BraiNet Template (electrode cap), and Sub-dermal EEG Needle Electrodes and Cutaneous EEG Electrodes.

The iEEG consists of an iEEG transmitter module, a medical grade AC charging adapter/charging cable and an iEEG viewer/recorder software.

The wireless iEEG transmitter module provides an EEG electrode connection, electrode impedance (connection) status indicator(s), a single-user multi-function push button switch that provides power on/off, electrode impedance check. The wireless module is powered by an internal rechargeable energy source.

The AC charger module provides a convenient means to recharge the wireless module's internal energy source when not in use. The device is not intended to be charged when attached to the patient.

The iEEG viewer/recorder software provides, with the aid of host computer hardware and operating system, the ability to collect EEG electrode data from the wireless iEEG transmitter module, view EEG data, and record data to digital file. The iEEG viewer/recorder provides eight signal graphic display of selectable EEG montages (lead/electrode combinations). It also enables subject data entry (Name, DOB, ID number etc.) and control of EEG data recording to digital file.

The Intelligent Electroencephalogram (iEEG) is designed to be capable of usage and storage in hospital, clinic, and emergency room environments. The iEEG transmitter modules communicate with the computer by using Bluetooth wireless technology.

The provided 510(k) summary for the iEEG (Intelligent Electroencephalograph) device does not contain a dedicated section detailing acceptance criteria or the specifics of a study conducted to prove the device meets such criteria. Instead, it focuses on demonstrating substantial equivalence to predicate devices. This type of submission relies on showing that the new device is as safe and effective as a legally marketed device, rather than proving performance against specific pre-defined acceptance criteria through a clinical study.

The submission primarily lists technological characteristics and benchmarks them against predicate devices. The "Performance Data" section briefly mentions:

"The device was tested to IEC 60601-1-1 for safety and IEC 60601-2 Electromagnetic Compatibility. The device was also evaluated to standard IEC 60601-2-26 for essential EEG performance specifications. The device with a suitable battery charger was evaluated to IEC 60601-1/A2:1995, IEC 60601-2-26 and applicable national requirements. All applicable tests according to the specified standards were completed and passed. Bench testing was performed and confirms that the device meets design requirements and specifications."

This indicates that various engineering and safety standards were met through bench testing, but these are not the "acceptance criteria" for a clinical performance study in the way implied by the request. There is no clinical study described with a test set, ground truth, or expert review for diagnostic performance.

Therefore, for the points requested by the user, most of the information is not available in the provided text.

Here's a breakdown of what can be inferred or explicitly stated based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

• "The device was also evaluated to standard IEC 60601-2-26 for essential EEG performance specifications."
• "The device with a suitable battery charger was evaluated to IEC 60601-1/A2:1995, IEC 60601-2-26 and applicable national requirements."
• "All applicable tests according to the specified standards were completed and passed."
• "Bench testing was performed and confirms that the device meets design requirements and specifications." |
  | Technological Equivalence (Relative to Predicate Devices) | - Channels: 8 (Equivalent to Zoom-100, within range of Trackit)
• ADC Resolution: 16 bit (Same as Zoom-100 and Trackit)
• ADC CMRR: >115dB (Slightly better than predicates (>100dB), deemed "comparable performance")
• Input Impedance: 10MOhm (Same as Zoom-100, better than Trackit)
• Electrode Impedance Check: Yes (Same as predicates)
• Wireless Output: Bluetooth 2.4 GHz (Same as predicates)
• Data Format: edf (Equivalent to Trackit)
• Electrode Material: Standard off-shelf electrodes (Same as predicates)
• Battery: Rechargeable Lithium-Polymer (Equivalent to Lithium-Ion in predicates)
• Charger: Yes (Same as predicates)
• Hi Filter Settings: Ranges listed (Deemed "Same or clinically insignificant differences" to predicates)
• Low Filter Settings: Ranges listed (Deemed "Same" to predicates)
• 60 Hz Filter: Yes (Same as predicates)
• Gain Settings: Ranges listed (Deemed "Same or clinically insignificant differences" to predicates)
• Time Base Settings: Ranges listed (Deemed "Same or clinically insignificant differences" to predicates)
• Display Montage: User selectable (Deemed "Same or clinically insignificant differences" to predicates) |

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

• Not Available. The document describes bench testing against engineering standards and comparison of technical specifications against predicate devices. It does not mention any clinical test set or patient data used to evaluate diagnostic performance.

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

• Not Applicable / Not Available. No clinical test set or ground truth establishment based on expert consensus for diagnostic performance is described. The evaluation was based on conformance to engineering standards and comparison of technical specifications.

4. Adjudication method for the test set

• Not Applicable / Not Available. No clinical test set or adjudication method is described.

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. An MRMC comparative effectiveness study was not conducted or reported. The iEEG device is described as an "electroencephalograph" intended to acquire and store electrical activity for review by a medical professional, implying it is a data acquisition and display tool, not an AI-assisted diagnostic tool designed to improve human reader performance or automate diagnosis.

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

• No. The device is not an algorithm for standalone diagnostic performance. It is a hardware/software system for acquiring and displaying EEG data for human review.

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

• Not Applicable / Not Available. For its "performance data," the device primarily refers to meeting engineering and safety standards (IEC 60601 series). For demonstrating substantial equivalence, its technical specifications were compared to those of already cleared predicate devices. There is no mention of a clinical ground truth (like expert consensus, pathology, or outcomes data) being established for evaluating diagnostic accuracy.

8. The sample size for the training set

• Not Applicable / Not Available. This device is an EEG acquisition and display system, not an AI/ML algorithm that requires a "training set" in the context of diagnostic performance. Any internal development or validation would be against technical specifications, not a clinical training set for an algorithm.

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

• Not Applicable / Not Available. As noted above, there is no mention of a "training set" or corresponding ground truth.

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