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The iX series Patient Monitors including iX10, iX12, iX15 are intended to be used for monitoring, storing, and reviewing of, and to generate alarms for, multiple physiological parameters of adults and pediatics (including neonates). The monitors are intended for use by trained healthcare professionals in hospital environments.

The monitored physiological parameters include: ECG, respiration (RESP), temperature (TEMP), functional oxygen saturation of arterial hemoglobin (SpO2), pulse rate (PR), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), carbon dioxide (CO2), cardiac output (C.O.), and Anaesthesia gas (AG).

The arrhythmia detection and ST Segment analysis are intended for adult patients.

The NIBP monitoring supports iCUFS algorithm and iFAST algorithm is intended for adult, pediatric and neonatal patients. The iFAST algorithm is intended for adult and pediatic patients (≥3 years of age). Both measurement algorithms are also intended for use with pregnant women, including pre-eclamptic patients. NIBP MAP is not applicable to pregnant women.

The Spot Temp with T2A module can only measure temperature of adult and pediatric (> 1 year of age) patients. The monitors are not intended for MRI environments.

The cardiac output (C.O.) is only intended for adult patients.

The iX series Patient Monitors including iX10, iX12, iX15 can perform long-time continuous monitoring of multiple physiological parameters. Also, it is capable of storing, displaying, analyzing and controlling measurements, and it will indicate alarms in case of abnormalities so that doctors and nurses can respond to the patient's situation as appropriate.

This document describes the premarket notification (510(k)) for the Edan Instruments, Inc. Patient Monitor (iX10, iX12, iX15) and its equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the new device were generally established by compliance with various international standards for medical electrical equipment and specific performance characteristics. The reported device performance indicates that the device meets these standards and its specified accuracy.

For the Quick Temp Module (T2A), the provided text details specific clinical study results. Other parameters were tested for compliance with relevant standards through non-clinical testing.

2. Sample Size for Test Set and Data Provenance

For the Quick Temp Module (T2A) Predict Mode clinical accuracy study:

• Sample Size: 142 valid cases for sublingual and axillary temperature measurements.
• Data Provenance: Clinical investigation (prospective study). No country of origin is explicitly stated, but the company is based in China.

For other parameters, specific sample sizes for non-clinical (bench) testing are not provided, but the document states "Edan has conducted functional and system level testing to validate the performance of the results of the bench testing show that the subject device meets its accuracy specification and meet relevant consensus standards."

3. Number of Experts and their Qualifications for Ground Truth

The document does not specify the number or qualifications of experts used to establish ground truth for the clinical study of the Quick Temp Module (T2A). It only mentions that the study compared the new module against the "direct mode of F3000 Temp Module of M3A Vital signs monitor," implying the predicate device served as a reference for accuracy.

For other non-clinical tests, the ground truth is implicitly defined by the specifications and performance requirements outlined in the referenced international standards.

4. Adjudication Method for the Test Set

The document does not describe a specific adjudication method (e.g., 2+1, 3+1) for the clinical study or any other test sets.

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

No multi-reader multi-case (MRMC) comparative effectiveness study is mentioned in the provided text. The device is a patient monitor, and its performance evaluation typically focuses on the accuracy and reliability of its physiological parameter measurements, not on improving human reader performance with AI assistance.

6. Standalone (Algorithm Only) Performance Study

Yes, standalone performance was evaluated for the components of the device. The non-clinical data section describes extensive functional and system-level testing to validate the performance against relevant consensus standards. This includes specific tests for algorithms like cardiac rhythm and ST segment measurement. The clinical study for the Quick Temp Module (T2A) also assesses the standalone performance of that specific module.

7. Type of Ground Truth Used

• For the Quick Temp Module (T2A) clinical study: The ground truth was established by comparison to a reference device's direct temperature measurement mode ("direct mode of F3000 Temp Module of M3A Vital signs monitor"). This is a form of reference standard comparison (using a predicate device as the reference).
• For other parameters (e.g., ECG, NIBP, SpO2, CO2, AG): The ground truth for non-clinical testing is implicitly based on the specifications and performance requirements outlined in the referenced international consensus standards (e.g., IEC 60601 series, ISO 80601 series, AAMI standards).

8. Sample Size for the Training Set

The document does not provide information about a training set since this is a patient monitoring device and not a machine learning algorithm as typically understood in the context of large-scale image-based diagnostics. The "algorithms" mentioned (e.g., arrhythmia detection, NIBP algorithms) are likely engineered signal processing algorithms rather than deep learning models requiring large training datasets.

9. How Ground Truth for Training Set was Established

Not applicable, as no training set for a machine learning model is described in the provided text. The algorithms for the patient monitor's functions are developed and validated against established physiological principles and engineering standards.

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The monitors are intended to be used for monitoring, storing, recording, and reviewing of, and to generate alarms for, multiple physiological parameters of adults and pediatrics. The monitors are intended for use by trained healthcare professionals in hospital environments. The monitored physiological parameters include: ECG, respiration (RESP), temperature (TEMP), oxygen saturation of arterial blood (SpO2), pulse rate (PR), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), carbon dioxide (CO2), cardiac output (C.O.), and Anaesthesia gas(AG). The arrhythmia detection and ST Segment analysis are intended for adult patients. The monitors are not intended for MRI environments.

The iM series Patient Monitor including iM50, iM60, iM70 and iM80 can perform long-time continuous monitoring of multiple physiological parameters. Also, it is capable of storing, displaying, analyzing and controlling measurements, and it will indicate alarms in case of abnormalities so that doctors and nurses can respond to the patient's situation as appropriate.

Based on the provided text, the device in question is a Patient Monitor (Model: iM50, iM60, iM70, iM80), which monitors various physiological parameters. The document focuses on demonstrating substantial equivalence to a predicate device, rather than providing detailed acceptance criteria and a standalone study for a novel AI device. Therefore, much of the requested information regarding AI-specific evaluation (e.g., sample size for AI test sets, expert adjudication, MRMC studies, AI effect size, ground truth establishment for training) is not applicable or not present in this 510(k) summary.

However, I can extract information related to the device's self-contained performance testing and regulatory acceptance criteria.

Acceptance Criteria and Device Performance for Patient Monitor (iM Series)

The document primarily relies on bench testing and software verification and validation to demonstrate that the iM series Patient Monitor meets its accuracy specifications and relevant consensus standards, thereby establishing substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present explicit "acceptance criteria" in a quantitative table for this specific device in the manner typically seen for novel AI models. Instead, it compares the technical specifications of the subject device to a predicate device and states that "the results of the bench testing show that the subject device meets its accuracy specification and meet relevant consensus standards."

The comparison table (pages 5 & 6) implicitly indicates that "acceptance" for the subject device's performance corresponds to ranges/specifications that are identical or comparable to the cleared predicate device.

Notes on the 'AG Module': The document explicitly states for the AG (Anesthesia Gas) module that its "indication is not present in the primary predicate, but is present in Edan Patient Monitor V series K160981." This implies that while it differs from the immediate primary predicate, it is substantially equivalent to a different, already cleared, predicate device from the same manufacturer.

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

• Sample Size: The document does not specify a distinct "test set" sample size in terms of patient data or number of tests. The performance data section refers to "functional and system level testing" and "bench testing." This implies testing against specifications and standards rather than a clinical dataset of a specific size.
• Data Provenance: Not specified. Given it's a bench test, it would typically be conducted in a laboratory setting. There's no mention of country of origin for test data, nor whether it's retrospective or prospective patient data, as clinical data was deemed "Not applicable."

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

Not applicable. This is a physiological monitor, not an AI diagnostic device requiring expert consensus for ground truth on images or signals. The "ground truth" for the device's performance would be derived from calibrated measurement references and established engineering principles in bench testing.

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

Not applicable. As above, this is not an AI diagnostic device relying on human expert review for ground truth.

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

Not applicable. This device is a physiological monitor, not an AI-assisted diagnostic tool that requires human readers for interpretation.

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

The device's performance in terms of its physiological measurements and alarm detection is inherently "standalone" in that it performs these functions without direct human intervention in the measurement process itself, generating outputs for healthcare professionals. The bench testing performed would be considered evaluating this standalone performance against technical specifications and standards.

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

For the non-clinical performance (bench testing), the "ground truth" is based on:

• Calibration standards: Using known, precise inputs (e.g., electrical signals simulating ECG, precise pressures for NIBP, known gas concentrations for CO2/AG) to verify the accuracy of the device's measurements.
• Consensus Standards: Adherence to recognized international standards for medical electrical equipment (e.g., IEC 60601 series, ISO 80601 series). These standards define acceptable performance limits and test methodologies.

8. The sample size for the training set

Not applicable. This document does not describe an AI/ML device that requires a "training set" in the conventional sense. The device's algorithms are likely based on established physiological signal processing, not deep learning models trained on large datasets.

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

Not applicable, as there is no "training set" for an AI/ML model described.

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The monitors are intended to be used for monitoring, storing, recording of, and to generate alarms for, multiple physiological parameters of adults, pediatrics and neonates. The monitors are intended for use by trained healthcare professionals in hospital environments.

The monitored physiological parameters include: ECG, respiration (RESP), temperature (TEMP), oxygen saturation of arterial blood (SpO2), pulse rate (PR), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), carbon dioxide (CO2), cardiac output (C.O.).

The arrhythmia detection and ST Segment analysis are intended for adult patients. The monitors are not intended for MRI environments.

The X8 X10 X12 Patient Monitor (hereinafter called X series) can perform long-time continuous monitoring of multiple physiological parameters. Also, it is capable of storing, displaying, analyzing and controlling measurements, and it will indicate alarms in case of abnormity so that doctors and nurses can deal with them in time.

The provided text is a 510(k) Premarket Notification summary for the Edan Instruments, Inc. Patient Monitor (Models X8, X10, X12). This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device meets specific acceptance criteria through a clinical study of an AI algorithm's performance.

Therefore, the information required to answer the prompt (acceptance criteria, study details for an AI algorithm, expert ground truth, MRMC study, standalone performance, training set details) is not present in the provided document. The document describes a traditional medical device (patient monitor) and its compliance with general safety and performance standards.

Here's a breakdown of why the requested information cannot be extracted from the given text:

1. Table of acceptance criteria and reported device performance: The document lists various physiological parameters (ECG, RESP, NIBP, SpO2, Temp, IBP, CO2, C.O.) and their measurement ranges and accuracies, comparing them to a predicate device. These are performance specifications, not "acceptance criteria" in the context of an AI algorithm's performance study. There's no specific numerical performance target for an AI algorithm provided.

2. Sample size used for the test set and the data provenance: Not applicable. The document refers to "bench testing" and "software verification and validation testing," which are not described as using specific test sets of patient data for AI algorithm evaluation.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth establishment by experts is relevant for AI algorithm studies, which are not detailed here.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. This pertains to expert review in AI studies, which is not 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: Not applicable. No MRMC study is mentioned. This device is a patient monitor, not an AI-assisted diagnostic tool for human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. No standalone algorithm performance is described. The device's "arrhythmia detection and ST Segment analysis" are features of the patient monitor, not explicitly a separate AI algorithm being evaluated for standalone performance.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. The "ground truth" for the device's measurements (e.g., blood pressure accuracy) would be derived from calibrated reference instruments, not expert consensus or pathology in the context of an AI algorithm.

8. The sample size for the training set: Not applicable. There is no mention of a training set for an AI algorithm.

9. How the ground truth for the training set was established: Not applicable. There is no mention of a training set for an AI algorithm.

In summary, the provided FDA 510(k) summary for the Edan Instruments, Inc. Patient Monitor focuses on establishing substantial equivalence to existing predicate devices based on design features, performance specifications (e.g., accuracy of physiological measurements), and compliance with electrical safety and EMC standards. It does not describe a study involving an AI algorithm that would require the detailed information requested in the prompt.

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Passport 12m and 17m Patient Monitors:

The Passport 17m and Passport 12m patient monitors are intended for monitoring, displaying, reviewing, and transferring of multiple physiological parameters including ECG (3-lead or 12-lead selectable, arrhythmia detection, ST segment analysis, OT analysis, and heart rate (HR)), respiration rate (Resp), temperature (Temp), pulse oxygen saturation (SpO2), pulse rate (PR), non-invasive blood pressure (NIBP), invasive blood pressure(IBP), pulmonary artery wedge pressure (PAWP), cardiac output (C.O.), continuous cardiac output (CCO), mixed/central venous oxygen saturation (SvO2/ScvO2), carbon dioxide (CO2), Oxygen (O2), anesthetic gas (AC), impedance cardiograph (CCG), bispectral index (BIS), respiration mechanics (RM), and neuromuscular transmission monitoring (NMT). The equipment also provides an interpretation of resting 12-lead ECG.

All the parameters can be monitored on single adult, pediatric, and neonatal patients with the exception of the following:
• The arrhythmia detection, ST Segment analysis of Mortara algorithm, BIS, RM, CCO, SvO2/ScvO2, PAWP monitoring and NMT monitoring are intended for adult and pediatric patients only;

· ST Segment analysis of Mindray algorithm is intended for adult patients only;

· C.O. monitoring is restricted to adult patients only;

• ICG monitoring is only for use on adult patients who meet the following requirements: height: 122 to 229cm, weight: 30 to 155kg.

The monitor is to be used in healthcare facilities by clinical professionals or under their guidance. It should only be used by persons who have received adequate training in its use. It is not intended for helicopter transport, hospital ambulance, or home use.

T1 Patient Monitor:

The T1 Patient Monitor is intended for monitoring, displaying, reviewing, and transferring of multiple physiological parameters including ECG (3-lead, or 12-lead selectable, arrhythmia detection, ST Segment analysis, QT analysis, and heart rate (HR)), respiration (Resp), temperature (Temp), pulse oxygen saturation (SpO2), pulse rate (PR), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), pulmonary artery wedge pressure (PAWP), and carbon dioxide (CO2). The equipment also provides an interpretation of resting 12-lead ECG.

All the parameters can be monitored on single adult, pediatric, and neonatal patients with the exception of the following:
• The arthythmia detection, ST Segment analysis of Mortara algorithm, and PAWP monitoring are intended for adult and pediatric patients;

· ST Segment analysis of Mindray ECG algorithm is intended for adult patients only.

The monitor is to be used in healthcare facilities by clinical professionals or under their guidance. It should only be used by persons who have received adequate training in its use. It is not intended for helicopter transport, hospital ambulance, or home use.

The subject Passport Series Patient Monitors includes three monitors:

• o Passport 12m Patient Monitor
• Passport 17m Patient Monitor ●
• o T1 Patient Monitor

All of the devices in the family are multiparameter monitors indicated for monitoring, displaying, reviewing, alarming, and transferring multiple physiological parameters. The Passport 12m and 17m Patient monitors provide patient monitoring capabilities based on the user selected modules that are plugged into the main monitor.

The T1 patient monitor is one of the available modules that can be plugged into the Passport 17m or 12m monitor. The T1 can also be used as a standalone monitor and when used as a standalone monitor, it provides a subset of the functions that are provided by Passport 17m and 12m.

This document is a 510(k) summary for the Mindray Passport Series Patient Monitors (Passport 12m, Passport 17m, and T1). It focuses on establishing substantial equivalence to previously cleared predicate devices and does not contain a full study report with detailed acceptance criteria and performance data for a new AI/ML device.

Therefore, the following information, relevant to AI/ML device studies, cannot be extracted from the provided text:

• A table of acceptance criteria and the reported device performance: The document states that "functional and system level testing" was conducted and that the devices "continue to meet specifications and the performance of the device is equivalent to the predicate." However, it does not provide specific acceptance criteria values or detailed performance metrics.
• Sample sized used for the test set and the data provenance: Not mentioned.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned.
• Adjudication method for the test set: Not mentioned.
• 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: Not relevant as this is not a new AI/ML device being submitted for comparative effectiveness.
• If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not relevant as this is not a new AI/ML device.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not mentioned.
• The sample size for the training set: Not mentioned.
• How the ground truth for the training set was established: Not mentioned.

Summary of available relevant information from the document:

This 510(k) submission is for modifications to existing patient monitors, not for a new AI/ML device. The changes include:

• Wireless Module: Addition of a Laird (2.4GHz/5GHz) wireless module.
• MPM Module: Addition of an MPM 3.0 module with similar functionality to the MPM 2.0 module.
• Masimo SpO2 accessories: Support for new Masimo SpO2 accessories.
• ECG accessories: Support for new ECG accessories (12-lead, defibrillation-proof).
• CO2 accessories: Support for new DRYLINE PRIME and DRYLINE PRIME+ gas sampling lines and water traps.
• Signal Cord Resistance: Improvements to SpO2/CO2/BIS signal cord resistance to damage.
• NIBP Issue Correction: Correction of an issue where NIBP misreported "NIBP Excessive Motion" after 49 days.
• Anesthetic Agent (AA) Numerics: Support for End tidal (Et) and Fraction of Inspired (Fi) numerics for anesthetic agent (AA).
• Physiological Alarms: Support for specific physiological alarm behaviors (triggered only when parameter value is higher/lower than limits, re-alarming after reset, non-overlapping relationships of alarm limit setting).
• Alarm Setup Menu: Support for password protection for accessing the Alarm Setup menu.
• User Authorization: Support for user authorization via LDAP.
• Patient Monitor Information: Support for Facility information, Room No. information, and Visit Number in patient demographics.
• Printing: Support for printing arrhythmia settings in reports, changing factory default printer paper size, and QT report printing.
• MAC Address Display: Support to display the MAC address of the patient monitor.
• ST Values Display: Support for displaying ST values in the parameter tile.
• Patient Private Information: Support for encryption of patient private information sent to the network.
• ST Point Adjustment: Support for adjustment of the ST point on multiple displayed leads.
• NIBP Measurement on Clock: Support for NIBP measurement on the clock.
• Network Application Transmission Priority Setting: Support for network application transmission priority setting.
• ECG Beat Annotation: Support for ECG beat annotation.
• DNS for ADT and LDAP server address: Support for DNS for ADT and LDAP server address.
• Bed No. Issue Correction: Correction of an issue where the Bed No. of the Passport 12m/17m is changed after T1 is pulled out of the monitors.

Performance Data:
Mindray conducted functional and system level testing to evaluate the performance of these modifications. The testing demonstrated that the devices "continue to meet specifications and the performance of the device is equivalent to the predicate." The devices also meet relevant consensus standards (listed in the document).

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