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The LuMon™ System is a noninvasive, non-radiation device that provides information on regional impedance variation within a cross-section of a patient's thorax. Graphical and numerical information is presented to the user as an adjunctive tool to other clinical information to support the user to assess a patient's respiratory condition.

The LuMon™ System is indicated for neonatal and infant patients with chest circumferences between 16.5 - 50 cm and adolescent through adult patients with chest circumferences between 76 - 128 cm who are breathing spontaneously or require mechanical ventilation in professional healthcare facilities.

Impedance-based respiratory rate monitoring is indicated for adults 22 years and older whose chest circumference is above 76 cm only.

The LuMon™ System also displays selected physiological and respiratory parameters from supported bedside devices.

The LuMon™ System does not measure regional ventilation of the lungs.

The LuMon™ System is a compact and lightweight Electrical Impedance Tomography (EIT) system that provides noninvasive monitoring of variations of regional air content/volume within a cross-section of the patient's thorax and patient respiration. It displays the results as real-time EIT images, waveforms, and derived parameters.

The system consists of a controller display unit, signal acquisition connector cable, and patient-applied conductive textile electrode belts. The system can connect to external bedside devices such as ventilators and monitoring devices to display contextual information for interpretation of EIT measurements.

The provided FDA 510(k) clearance letter and summary for the LuMon™ System contains information regarding its acceptance criteria and the studies conducted to demonstrate its performance. However, some specific details commonly found in a comprehensive study report (e.g., exact sample size for each clinical study, number of experts for ground truth, adjudication methods beyond "clinician-scored") are not explicitly stated in this high-level summary.

Based on the provided text, here's a structured response addressing your request:

Acceptance Criteria and Device Performance for LuMon™ System

The LuMon™ System underwent extensive non-clinical (bench and pre-clinical) and clinical testing to demonstrate its safety and effectiveness. The acceptance criteria are implicitly defined by the performance characteristics presented in the comparison tables and the successful attainment of stated accuracies and correlations.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally established as equivalent to or better than the predicate/reference devices, or as meeting pre-defined tolerances for specific parameters.

• Data Provenance: Not explicitly stated regarding country of origin for clinical data. The studies are described as "pre-clinical" and "clinical," with no indication of being retrospective. "Clinical testing was performed to support safety and effectiveness" generally implies prospective data collection for regulatory purposes.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Not specified.
• Qualifications of Experts: For the Respiration Rate study, the reference standard was "Clinician-scored EtCO2 capnogram." This implies medical professionals were involved in establishing the ground truth, but their specific qualifications (e.g., types of physicians, years of experience) are not detailed.

4. Adjudication Method for the Test Set

• For Respiration Rate Ground Truth: "Clinician-scored EtCO2 capnogram" implies expert review. However, the exact adjudication method (e.g., 2+1, 3+1, majority vote, independent reads with reconciliation) is not specified.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• It is not explicitly stated that a specific MRMC study was conducted to compare human readers with and without AI assistance.
• The device is presented as an "adjunctive tool to other clinical information to support the user," meaning it assists clinicians rather than replacing them. Its effectiveness is shown through its ability to provide accurate EIT data and respiratory rate, which clinicians would then integrate into their assessment. The summary focuses on the device's accuracy relative to reference standards or predicate devices, not on direct human-AI performance comparison studies.

6. Standalone (Algorithm Only) Performance

• Yes, the performance characteristics listed in the tables (e.g., R-squared correlations for EIT-CT, accuracy for RRi against reference standards, SNR, voltage accuracy) represent the standalone performance of the algorithm and the device. The clinical studies compare the device's output itself to established medical standards or other modalities, distinct from how a human user might interpret or use that output.

7. Type of Ground Truth Used

• Pre-clinical (Regional Impedance Distribution): Differential CT changes in aeration (healthy and injured lungs, one- and two-sided intubation) and "established physiological changes" were used as ground truth.
• Clinical (Global Volume Changes): Body plethysmograph traces and Ventilator flow-sensed volumes were used as ground truth.
• Clinical (Regional Impedance Distribution): The Timpel Enlight 2100 predicate comparison was used for ground truth.
• Clinical (Respiration Rate): Clinician-scored EtCO2 capnogram was used as ground truth.

8. Sample Size for the Training Set

• The information provided is a 510(k) summary, which typically focuses on validation. The sample size for the training set is not provided in this document. Training data details are usually proprietary and not disclosed in 510(k) summaries unless directly relevant to the regulatory pathway or substantial equivalence claim.

9. How Ground Truth for the Training Set Was Established

• The document does not specify how ground truth was established for the training set. Similar to the training set size, details about the training data and its ground truth establishment are generally considered proprietary and are not typically included in a public 510(k) summary. The summary focuses on the independent test data performance.

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AirTom is a non-invasive, non-radiation medical device that provides information of local impedance variations within a cross section of a patient's thorax. This information is presented to the clinician user as an adjunctive tool to other clinical information in order to support the user's assessment of variations in regional air content within a cross section of a patient's lungs.

It is intended for mechanically-ventilated patients in a professional healthcare facility, whose chest circumference is within the range of 32 ~ 130 cm.

AirTom does not measure regional ventilation of the lungs.

AirTom is a ventilatory electrical impedance tomograph that uses several electrodes (16+1) placed around the patient's thorax to assess regional impedance variations in a lung slice (tomography). It provides only relative measurements about variations in local impedance.

AirTom estimates local impedance variations, occurring in a cross section of the thorax during a breathing cycle, which are linearly related to variations in regional air content within the lungs.

The provided document, a 510(k) summary for BiLab's AirTom device, focuses primarily on establishing substantial equivalence to a predicate device (TIMPEL S.A.'s Enlight 2100) rather than presenting a detailed study proving the device meets specific acceptance criteria based on quantifiable performance metrics. The summary outlines non-clinical (bench) and clinical performance data, but these are presented as comparative results to support substantial equivalence, not as formal acceptance criteria with corresponding performance against those criteria.

Therefore, the following response will extract the relevant information regarding performance and present it in a structured way that attempts to align with the request, acknowledging where explicit "acceptance criteria" (defined as specific thresholds for success) are not provided in the document.

Acceptance Criteria and Device Performance Study for AirTom

The provided 510(k) summary for AirTom focuses on demonstrating substantial equivalence to a predicate device (ENLIGHT 2100) through a comparison of technological characteristics and performance data. While explicit "acceptance criteria" with quantitative thresholds for study success are not formally stated in the document in the format typically requested (e.g., "Accuracy > 90%"), the document does list several "Performance Characteristics - Bench Test" with corresponding reported ranges for both the subject device (AirTom) and the predicate. These can be interpreted as the performance measures that were assessed to demonstrate equivalence.

The "clinical performance data" presented are descriptive and illustrative of the device's capability to assess regional ventilation, rather than a formal validation against a set of statistical acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance

As explicit acceptance criteria are not provided for the clinical studies, the table below lists the Performance Characteristics - Bench Test for which quantitative data is presented to support substantial equivalence. The "Acceptance Criteria" column is inferred from the ranges reported for the predicate device, as the goal is to show comparable performance.

Note: For the clinical performance sections (A, B, C), the document describes observed physiological changes in regional ventilation/impedance under different clinical conditions that are consistent with expected physiological responses or comparisons to other imaging modalities (e.g., CT). It does not provide quantitative acceptance criteria or statistical hypothesis testing results for these observations beyond p-values for differences between states.

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

The document describes three clinical "assessments" that serve as a form of test set, demonstrating the device's performance in clinical settings:

• A. Comparison of regional ventilation distributions: EIT vs. X-ray CT image

  • Sample Size: 6 patients
  • Data Provenance: Retrospective ("AirTom was used on six patients during routine clinical practice in ICU. X-ray CT or chest X-ray images were acquired...")
  • Country of Origin: Not explicitly stated, but assumed to be where the clinical practice occurred, likely in South Korea given BiLab's location.

• B. Assessment of regional ventilation distributions: Anterior and posterior regions

  • Sample Size: 53 patients
  • Data Provenance: Retrospective analysis. Patients were undergoing general anesthesia during surgery.
  • Country of Origin: Not explicitly stated.

• C. Assessment of regional ventilation distributions: With and without pneumoperitoneum

  • Sample Size: 28 patients
  • Data Provenance: Retrospective analysis. Patients were undergoing general anesthesia during laparoscopic surgery with pneumoperitoneum.
  • Country of Origin: Not explicitly stated.

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

The document does not specify the number or qualifications of experts used to establish ground truth for the clinical observations.

• For section A (EIT vs. CT), it mentions X-ray CT or chest X-ray images were acquired to identify likely regions with different tidal ventilation. This implies a clinician (likely a radiologist or intensivist) interpreted these images, but no details are provided about their number or specific qualifications.
• For sections B and C, the "ground truth" implicitly relies on established physiological understanding of lung mechanics and the expected changes under conditions like atelectasis or pneumoperitoneum, rather than a separate expert-labeled ground truth for each case for direct comparison.

4. Adjudication Method for the Test Set

The document does not describe any formal adjudication method (e.g., 2+1, 3+1) for establishing ground truth or for reviewing the outputs of the AirTom device in the context of the clinical assessments. The findings are presented as observations consistent with clinical expectations or comparisons to CT.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with AI assistance versus without AI assistance was not conducted or described in this document. The AirTom device is described as providing "information of local impedance variations" to the "clinician user as an adjunctive tool to other clinical information." It is not presented as an AI-powered diagnostic tool that directly assists human readers in interpreting images in a comparative setting.

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

The document does not describe a standalone performance study of the AirTom algorithm in isolation. The device's output (tidal images, regional distribution percentages, total impedance changes) is the direct measurement from the device, which is then interpreted by clinicians. The clinical performance data sections (A, B, C) illustrate the device's ability to capture physiological phenomena, essentially demonstrating its "standalone" measurement capabilities in a clinical context against expected physiological changes or other imaging modalities like CT.

7. The Type of Ground Truth Used

• For the bench tests (Section 9, under "Performance Characteristics - Bench Test"), the ground truth is based on engineering specifications, physical phantoms, and controlled electrical measurements.
• For the clinical performance data (Section 8):
  • Section A (EIT vs. X-ray CT): The ground truth was established by comparing AirTom's visual representations of regional ventilation to X-ray CT or chest X-ray images, which are standard clinical imaging modalities for assessing lung conditions like atelectasis and pneumothorax. This represents a type of imaging ground truth.
  • Sections B & C (Regional ventilation changes with PEEP, and with/without pneumoperitoneum): The ground truth is effectively physiological ground truth/clinical understanding. The studies observed the device's ability to reflect expected physiological changes in lung ventilation/impedance under known clinical interventions (e.g., induction of anesthesia and PEEP changes influencing atelectasis, or CO2 insufflation during surgery). The statistical significance of observed changes (p-values) supports that the device is reflecting these known physiological responses.

8. The Sample Size for the Training Set

The document does not specify any training set sample sizes. This device, as described, appears to be an Electrical Impedance Tomography (EIT) device that directly measures and reconstructs impedance images based on physical principles, rather than a deep learning/AI model that requires a specific training dataset (unless inherent to the image reconstruction algorithm which is not described as a deep learning model). The "clinical performance data" presented are likely used for validation/demonstration of the final product, not for training.

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

As no training set is described (see point 8), the method for establishing ground truth for a training set is not applicable or detailed in this document.

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ENLIGHT 2100 is a non-invasive, radiation free medical device that provides information from impedance variation from a cross-section of a patient's thorax. This information is presented to the clinician user as an adjunctive tool to other clinical information in order to support the user's assessment of variations in regional air content within a cross section of a patient's thorax.

ENLIGHT 2100 also provides respiratory parameters based on spirometric monitoring.

It is intended for mechanically ventilated adult and pediatric patients in a hospital setting, whose thorax perimeter is within the range of 37.5 - 134 cm.

ENLIGHT 2100 does not measure regional ventilation of the lungs

ENLIGHT 2100 is a Ventilatory electrical impedance tomograph that uses several electrodes (usually between 16 and 32) placed around the patient's thorax to assess regional impedance variation in a lung slice (tomography). It provides a relative measurement, so it only provides information on variations in local impedance. ENLIGHT 2100 estimates Local Impedance Variation, occurring in a cross section of the thorax during a respiratory cycle, and which are linearly related to Variations in Regional Air Content within the lung.

The ENLIGHT 2100 is a ventilatory electrical impedance tomograph that also provides respiratory parameters based on spirometric monitoring. It is intended for mechanically ventilated adult and pediatric patients in a hospital setting. The device provides information on impedance variation from a cross-section of a patient's thorax as an adjunctive tool to support the user's assessment of variations in regional air content. It does not measure regional ventilation of the lungs. The device relies on a primary predicate (ENLIGHT 2100 - K211135) for its Electrical Impedance Tomography (EIT) data and a secondary predicate (Philips NM3 Respiratory Profile Monitor with VentAssist – K103578) for its spirometric monitoring capabilities. The data provided focuses on non-clinical/bench testing to demonstrate substantial equivalence to these predicates.

1. Acceptance Criteria and Reported Device Performance

The acceptance criteria for the ENLIGHT 2100 are based on its performance characteristics in comparison to its predicate devices for both EIT parameters and spirometric parameters. The study conducted was non-clinical bench testing.

Table 1: Acceptance Criteria and Reported Device Performance

The "Explanation of Differences" column in the provided tables typically serves as the primary source for the reported device performance and the proof that it meets the acceptance criteria (i.e., demonstrating substantial equivalence to the predicates based on the non-clinical testing). For the EIT parameters, the performance is reported as "Same" as the predicate, with the rationale that the hardware and EIT algorithm are identical. For the spirometric parameters, specific accuracy metrics are provided for the subject device and its accuracy relative to the secondary predicate (NM3).

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

The document explicitly states that "Bench Testing - We have performance tests to check the automatic calculation of the parameters shown at the Trend Screen." and lists "Non-clinical testing" and "Bench Test" as the method. Therefore, the data provenance is bench test data. No information is provided regarding the specific sample size (e.g., number of test points, simulated cases, or repetitions) used for this bench testing. The data does not specify the country of origin, but given the sponsor's location (Brazil) and the nature of bench testing, it would likely be laboratory/engineering data. It is inherently prospective as it involves controlled testing to confirm performance.

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

The study described is non-clinical bench testing. It involves evaluating the device's numerical calculations and performance against specified ranges and accuracy criteria, likely using simulated physiological signals or validated reference equipment. Therefore, no human experts were used to establish ground truth in the way they would be for image interpretation or diagnosis. The ground truth for this type of testing is established by the specifications of the signals generated or the reference standards of the testing equipment.

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

Given that this was a non-clinical bench study focused on numerical calculation accuracy and signal acquisition performance, no human adjudication method was employed. The "ground truth" was inherently defined by the test setup and reference measurements, not by human interpretation or consensus.

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. The device (ENLIGHT 2100) functions as a sensor and data display unit for physiological parameters, not an AI-assisted diagnostic tool that would directly assist human readers in interpreting complex medical images or data where a reader study would be applicable. The document describes it as an "adjunctive tool to other clinical information," implying it provides data for clinicians to interpret, but not in a way that necessitates an AI-assistance reader study.

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

Yes, a standalone (algorithm only) performance evaluation was implicitly done through the bench testing. The document states, "We have performance tests to check the automatic calculation of the parameters shown at the Trend Screen." This testing evaluates the device's ability to accurately measure and calculate the specified EIT and spirometric parameters within defined ranges and accuracies, independent of human interaction or interpretation beyond setting up the test and recording results.

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

The ground truth used for this non-clinical bench testing was established through engineered inputs/simulations and/or comparisons to a validated reference standard. For example, for spirometric parameters like Tidal Volume or Respiratory Rate, the system would be fed precisely controlled and measured airflow/pressure signals, and the device's output would be compared to the known input values of these signals. For EIT parameters, the ground truth would similarly come from controlled electrical impedance variations generated under laboratory conditions.

8. The sample size for the training set

The document describes non-clinical bench testing for the purpose of demonstrating substantial equivalence. It does not mention any machine learning or AI components that would require a separate training set. Therefore, information regarding a training set sample size is not applicable or provided in this context. The device's algorithms are likely based on established physiological and electrical impedance principles, not trained on a large dataset of patient measurements requiring specific "training set" ground truth establishment.

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

As there is no mention of a training set or machine learning/AI model training, the question of how its ground truth was established is not applicable based on the provided information.

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ENLIGHT 2100 is a non-invasive, non-radiation medical device that provides information of local impedance variation within a cross-section of a patient's thorax. This information is presented to the clinician user as an adjunctive tool to other clinical information in order to support the user's assessment of variations in regional air content within a cross section of a patient's lungs.

It is intended for mechanically ventilated adult and pediatric patients in a hospital setting, whose thorax perimeter is within the range of 37.5 - 134cm.

ENLIGHT 2100 does not measure regional ventilation of the lungs.

ENLIGHT 2100 is a Ventilatory electrical impedance tomograph that uses several electrodes (usually between 16 and 32) placed around the patient's thorax to assess regional impedance variation in a lung slice (tomography). It provides a relative measurement, so it only provides information on variations in local impedance.

ENLIGHT 2100 estimates Local Impedance Variation, occurring in a cross section of the thorax during a respiratory cycles, and which are linearly related to Variations in Regional Air Content within the lung.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) clearance letter for the Timpel S.A. Enlight 2100 device:

Important Note: The provided document is a 510(k) clearance letter from the FDA. 510(k) clearance is based on demonstrating substantial equivalence to a previously legally marketed device (predicate device), not necessarily on rigorous clinical effectiveness studies or extensive AI model validation metrics typically seen for novel AI/ML devices. Therefore, the details around specific acceptance criteria, test sets, ground truth establishment, and MRMC studies for AI performance, as might be expected for an AI/ML software as a medical device (SaMD), are not explicitly detailed in this type of regulatory document. The focus here is on demonstrating that the new device (Enlight 2100) is sufficiently similar to the predicate (Enlight 1810) in terms of safety and performance.

Analysis of Acceptance Criteria and Device Performance

The provided document describes bench testing to demonstrate substantial equivalence, rather than clinical studies with human readers or AI-specific performance metrics like sensitivity/specificity for a diagnostic task. The acceptance criteria are implicit in the comparison table (Table 5.1) between the subject device (Enlight 2100) and the predicate device (Enlight 1810). The "Explanation of Differences" column directly indicates whether the performance attributes are similar or if one is slightly better, implying the new device meets or exceeds the predicate's performance.

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria (Implied: Performance comparable or better than Predicate Device)

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

• Sample Size: The document does not specify a "test set" in terms of patient data or a specific number of unique tests for each performance characteristic. Instead, it refers to "bench testing" which implies testing on a controlled system or phantom, not human subjects, for these specific performance metrics. The comparison table focuses on instrument performance rather than AI model performance on a clinical dataset.
• Data Provenance: Not specified, as these are bench test results of the device itself rather than clinical data from a specific region or patient cohort. It is implicitly "prospective" bench testing of the new device.

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

• Not applicable for this type of submission. The "ground truth" for the performance characteristics listed in the table comes from verifiable engineering measurements on the device, often using calibrated equipment or phantoms, not human expert consensus. This is a technical performance evaluation, not a clinical diagnostic assessment.

4. Adjudication Method for the Test Set

• Not applicable. As noted above, the "test set" refers to technical performance characteristics measured through bench testing, not a dataset requiring human adjudication of clinical findings.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No, an MRMC comparative effectiveness study was not done as described for AI assistance. This submission is for an Electrical Impedance Tomograph (EIT) device, which provides "information of local impedance variation" as an "adjunctive tool." It does not involve AI for interpretation or diagnosis, nor does it directly assist human readers in image interpretation in the way an AI-powered diagnostic tool would. It provides raw data/images for clinicians to interpret.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Yes, in spirit, the bench testing results represent a "standalone" evaluation of the device's technical performance. The reported performance characteristics (SNR, Voltage Accuracy, Drift, etc.) are inherent properties of the device and its internal algorithms, independent of human interaction or interpretation beyond setting up the test. However, this is not an "algorithm-only" study in the typical sense of a diagnostic AI algorithm that produces a specific output (e.g., classifying a disease). The device itself is the "algorithm" and hardware working together to produce data.

7. Type of Ground Truth Used

• The ground truth for the "Performance Characteristics" in Table 5.1 is based on engineering measurements and calibrations using established methods for evaluating electronic medical devices. It is not expert consensus, pathology, or outcomes data. For example, SNR is measured against a known signal input, and position error might be measured using phantoms with known, precisely located impedance changes.

8. Sample Size for the Training Set

• Not applicable. The Enlight 2100 is an EIT device that provides direct physical measurements and derived images based on those measurements, not a machine learning model that requires a "training set" of data in the typical sense. Its "algorithm" is based on the physics of electrical impedance tomography.

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

• Not applicable, as there is no "training set" for an AI model. The device's operation is based on established physical principles and engineering design.

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ENLIGHT 1810 is a non-invasive, non-radiation medical device that provides information of local impedance variation within a cross-section of a patient's thorax. This information is presented to the clinician user as an adjunctive tool to other clinical information in order to support the user's assessment of variations in regional air content within a cross section of a patient's lungs.

It is intended for mechanically ventilated adult patients in a hospital setting, whose thorax perimeter is within the range of 78-122 cm.

ENLIGHT 1810 is a non-invasive, radiation free medical device intended to provide information on the regional distribution of ventilation in a cross-sectional slice of the thorax.

As the total variation in impedance for the thorax corresponds to the total tidal volume, ENLIGHT 1810 can estimate the percentage of tidal volume in regions of interest (ROI) breath by breath, measuring the contribution of the impedance variation of that ROI to the total impedance of the lung.

Electrical impedance tomography (EIT) is a technique in which the electrical properties of tissues are estimated from surface electrode voltage measurements and used to provide information on Local Impedance Variation (LIV) within a cross section of a patient's thorax. Considerable electrical impedance variations are imposed on lung tissue by variations in the lung's air content. There is a linear relationship between the variations in air content and the percentage change in lung tissue impedance. This linear relationship is explored in Electrical Impedance Tomography, supporting its use as a tool to support the user's assessment of the variations in regional air content within a cross section of a patient's lungs.

The device may be used on adult patients undergoing either fully controlled or assisted mechanical ventilation in the ICU environment.

Acceptance Criteria and Study for ENLIGHT 1810

The ENLIGHT 1810 is a ventilatory electrical impedance tomograph intended to be an adjunctive tool to other clinical information to support the user's assessment of variations in regional air content within a cross-section of a patient's lungs. As such, the device's acceptance criteria primarily focus on its ability to qualitatively measure regional ventilation distribution and its safety and performance under various conditions.

1. Table of Acceptance Criteria and Reported Device Performance

The direct "acceptance criteria" for clinical performance are not explicitly stated in quantitative metrics (e.g., specific accuracy thresholds) for the human studies. Instead, the studies aim to demonstrate agreement and the qualitative utility of the device in assessing regional ventilation distribution compared to gold standards (CT). The bench tests, however, do have specific quantitative performance parameters.

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