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The ADVIA 2120 and ADVIA 2120i with autoslide are quantitative, automated hematology analyzers that provide the following information for in vitro diagnostic use in clinical laboratories:

• A complete blood count (CBC) consisting of WBC, RBC, Hgb, CN-Free Hgb, Calculated Hgb, MCV, Hct, MCH, MCHC, CHCM, RDW, HDW, CH, Plt, MPV.
• A leukocyte differential count consisting of Neut (%/#), Lymph (%/#), Mono (%/#), Eos (%/#) Baso (%/#), LUC (%/#).
• A reticulocyte analysis consisting of Retic (%/#), MCVg, MCVr, CHCMg, CHCMr, CHg, CHr.
• A nucleated red blood cell count consisting of NRBC(%/#).
• Enumeration of the total nucleated cell (TNC) count and RBC count for pleural, peritoneal, and peritoneal dialysis (PD) specimens.
  Note: Above measurands are determined (in whole blood, pleural, peritoneal, or peritoneal dialysis specimens with K2 and/or K3 EDTA anti-coagulants).
• Quantitative determination of blood cells in Cerebrospinal Fluid (CSF) consisting of WBC, RBC, Neut (%/#), Lymph (%/#), Mono (%/#), MN (%/#),PMN (%/#).
  In addition, the system provides the added capability to automatically prepare and stain high quality blood smears on a microscope slide.

The ADVIA 2120/210i Hematology systems with Auto slide are an integrated option of a Hematology analyzers with complete blood cell count, leukocyte differential cell count, reticulocyte analysis capability, nucleated red blood cell count, quantitative determination of blood cells in Cerebrospinal Fluid (CSF), enumeration of the total nucleated cell (TNC) count and RBC count for pleural, peritoneal, and peritoneal dialysis (PD) specimens and a slide stainer designed to provide reflexive slide making/staining without user intervention based upon pre-selected, user-definable criteria.
The ADVIA 2120/210i Hematology systems with Auto slide consists of the following: an analytical module that aspirates, dilutes, and analyzes whole blood samples; an auto sampler that automatically mixes, identifies, and presents the samples for processing; a computer workstation that controls the instrument, provides primary user interface with the instrument and manages the data produced by the instrument; a printer that optionally generates reports based on the instrument results and an auto slide module that prepares a wedge smear from a drop of blood, places it on a microscope slide and stains the slide in accordance with Wright, Wright-Giemsa and May-Grnwald Giemsa Staining techniques.

The provided text is a 510(k) Summary for the ADVIA® 2120/2120i Hematology auto-analyzers. This document focuses on demonstrating substantial equivalence to a predicate device, which means the new device is as safe and effective as a legally marketed device. It does not describe a study that proves the device meets specific acceptance criteria in the way you might expect for a novel AI device with a defined set of performance metrics.

Instead, the submission shows the new device with an ARM9 CPU board performs similarly or identically to the predicate device (the ADVIA 2120/2120i with the current CPU board) across various specifications. The "acceptance criteria" here are essentially the established performance characteristics of the predicate device, and the "study" is the comparison data presented to support substantial equivalence.

Here's an attempt to answer your questions based on the provided text, acknowledging that some information you requested (like AI-specific details, ground truth establishment for a training set, and expert adjudication for a test set) are not relevant or present in this type of FDA submission for a hardware/firmware upgrade to an existing analyzer.

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

The acceptance criteria are implied to be the performance characteristics of the predicate device. The "reported device performance" is the expectation that the new device (AVIA 2120/2120i with ARM9 CPU) will exhibit identical performance.

• RBC (10⁶/μL): 0.0 to 7.0 (Max Deviation: 0.1)
• HGB (g/dL): 0 to 22.5 (Max Deviation: 0.2 or 2.0%)
• PLT (10³/μL): 5.0 to 3500 (Max Deviation: 5.0 or 5.0%)
• %RETIC: 0.2 to 24.5 (Max Deviation: 5.0%)
• CN-free HGB (g/dL): 1 to 22.5 (Max Deviation: 0.3 or 3.0%)
• CSF WBC (cells/µL): 0 to 50 (Max Deviation: 5)
• CSF RBC (cells/µL): 50 to 5000 (Max Deviation: 10%)
• BF TNC (10³/µL): 0 to 50 (Max Deviation: 5)
• BF RBC (10⁶/µL): 50 to 1500 (Max Deviation: 10%) | Same |
  | Within-Run Precision| (See detailed table in original text; e.g., WBC: Nominal 7.5, SD 0.2, CV 2.66%) | Same |
  | Carryover | Less than or equal to 1% | Same |
  | Physical/Electrical | (Various detailed specifications for Temperature, Humidity, Noise, Weight, Dimensions, Vacuum/Pressure, Reaction Chamber Temp, Power Pack Temp, Light Intensities, Power Supply Voltages, Sample Mode Volumes, Throughput, Sample Capacity, Tube Sizes/Types, Barcode Reader functionality) | Same |
  | Data Management | TDC version 9 or higher, Database storage, Review/edit, User-defined reports/ranges, Bi-directional communication, QC features, ILQC programs, User assistance | Same |
  | Consumables/Reagents| CBC TIMEPAC Baso HGB RBC/PLT Defoamer CN-Free CBC TIMEPAC; DIFF TIMEPAC, Perox 1, 2, 3, Perox Sheath, autoRetic, EZ KLEEN, Sheath/Rinse, CSF | Same |
  | Calibrators | ADVIA OPTIpoint, ADVIA SETpoint | Same |
  | Controls | ADVIA TESTpoint Low/Normal/High, Retic Low/High, 3-in-1 Abnormal1/Normal/Abnormal2 | Same |

2. Sample sizes used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The document lists performance specifications (linearity, precision) but does not specify the sample sizes or data provenance (country, retrospective/prospective) used to establish these predicate device performance characteristics. The context is that the new device's performance is expected to be identical to the established predicate performance, implying that these performance metrics have been previously validated and are being maintained.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

This is not applicable to this submission. The "ground truth" for hematology analyzers is typically established through reference methods, calibrated controls, and comparison to established, validated manual methods, not through expert consensus in the way an imaging AI algorithm's ground truth might be. The document focuses on the technical specifications and equivalence of a hardware component change.

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

Not applicable. This type of submission does not involve adjudication of diagnostic decisions as would be relevant for an AI algorithm.

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 is for a hematology auto-analyzer, 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

The device itself is a standalone automated hematology analyzer. The submission is not for a new algorithm, but for a hardware (CPU board) and associated software upgrade to an existing analyzer. The performance characteristics presented are those of the entire automated system.

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

Not explicitly stated for the predicate device's original validation. However, for hematology analyzers, "ground truth" for parameters like cell counts, hemoglobin, etc., is typically established using:

• Reference methods: Highly accurate and precise laboratory methods.
• Calibrated materials: Use of control materials with known values traceable to international standards.
• Manual microscopy or other established techniques: For differential counts or specific cell morphology, comparison to manual review by highly trained laboratorians.

8. The sample size for the training set

Not applicable. This device does not use a "training set" in the context of machine learning. It's a change to a pre-programmed analytical instrument.

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

Not applicable, as there is no "training set" in the AI sense.

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The Bio-logic Sleepscan product family is indicated for use in the recording and analysis of human physiological data necessary for the diagnosis of Sleep-related disorders. It is intended to record and present this data in a form that can improve the speed of diagnosis and assist in potential treatment decisions. Sleepscan Analysis performs calculations and presents recorded data in various ways on the computer screen and in reports. The Analysis features in the Sleepscan product are intended to be performed without patient hookup being necessary, and may even be performed on a different computer system from that which was used for the patient recording.

It can be used for patients of all ages, from children to adults, including geriatric patients. The use of the Sleepscan family of products is to be performed under the prescription of a physician or other trained health care professional.

The primary feature modification represented in this Special 510(k) is for the Microsoft Windows operating system and its associated user interface functionality.

The Bio-logic Sleepscan family of products is intended to be used for the recording and analysis of human physiological data for the purpose of diagnosis and treatment of Sleep-related disorders. The predicate vice referenced above was the first such system marketed by Bio-logic. Other related devices comprising the Sleepscan family include:

• 1 . 510(k) #K930790 - Addition of Oximeter to Sleepscan Product.
• 510(k) #K964132 Modification to Bio-logic Sleepscan product with Built-in Oximeter, 2.
• 3. 510(k) #K971501 - Sleepscan Airflow Pressure Transducer.

The predicate device performs both Sleep recording and analysis functions, providing up to 40 channels of simultaneous data recording from a variety of sensors and transducers, and a number of specialized analysis functions including event highlighting and Sleep stage identification. Related Device #1 above is a recording hardware modification to Bio-logic's standard 32-channel EEG recording system, incorporating a built-in Oximeter module and DC channels specifically designed for Sleep recordings. Related Device #2 above is another recording hardware modification, this one based on the Bio-logic "Ceegraph Traveler" (510(k) #K954954) device. Also incorporating a built-in oximeter, this is a smaller battery-operated device offering fewer recording channels at a lower price. Related Device #3 above is a very sensitive transducer for the recording of airflow associated with breathing, based on the measurement of air pressure variations instead of the more indirect method using temperature measurements.

Throughout the history of the Sleepscan product, from the introduction of the present, all Sleepscan software has been developed and based on the Microsoft MS-DOS Operating System. This new Special 510(k) is for the Device Modification of Sleepscan software, the primary new feature being the use of the Microsoft Windows Operating System. As such, although most of the standard Sleepscan functions are very similar to those used in the DOS version, much of the User Interface and presentation of graphical data is now performed using Windows-standard Graphical User Interface (GUI) methods. This 510(k) does not cover the recording functions of the Sleepscan family, which are defined in the predicate device and Related Devices #1 and #2 above. Data recording may be performed using any of the Bio-logic approved-for-market Sleepscan and Ceegraph recording devices with the associated recording software. Any recordings made for the diagnosis and treatment of Sleep disorders can be analyzed with either the existing DOS-based software or the new Windows-based software. This latter software package is the subject of this 510(k).

Most of the finctional features of the Bio-logic Sleepscan for Windows software package are similar to those of the predicate device. These include:

• Graphical presentation of the "raw data" as recorded by one of the recording devices. .
• Epoch-based data scaling to simulate paper recordings. ﻬ
• Variable time scaling of data (simulating a variety of "paper speeds") and variable epoch sizes for detailed or summary viewing.
• Rapid report generation based on operator review and interaction with the data presented by the Analysis software.
• Several summary graphs allow for the display of the complete night's Sleep recording on one screen, allowing the user to quickly identify periods of the study requiring closer scrutiny.
• Graphical Overlay with Zoom-In allows the user to quickly look at "interesting" periods of a night's Sleep recording at the raw data level.
• User-defined montages and comments.
• Screen presentations can be customized to display several different kinds of data in separate windows at the same time.
• Data analysis is performed on specific channels of raw data for the identification of possible respiratory or neurological events.
• • Color-coded events highlight areas of the data for further review by the technologist or physician.
• Computer-assisted highlighting of data events can be easily modified or deleted by the user, and new events not highlighted by the program can be added at the user's discretion.

New features in the Windows-based software include:

• ◆ Standard Windows GUI functionality.
• · Extensive On-line Help.
• · More extensive and user-configurable reporting features.
• · Patient database information features.
• · Enhanced sleep stage scoring features.

The provided text describes a 510(k) summary for a software modification to the Bio-logic Sleepscan product, moving it from a DOS-based operating system to a Windows-based one. The focus of the document is on establishing substantial equivalence to a predicate device for this software modification.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present formal acceptance criteria or quantitative performance metrics in the way one might expect for a new algorithmic device claiming improved diagnostic accuracy. Instead, it aims to demonstrate equivalence to a predicate device. The "Performance" parameter in the comparison table explicitly states "No differences."

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

The document does not mention any specific test set, sample size, or data provenance (e.g., country of origin, retrospective or prospective) for validating the software modification. The approach taken is comparative to a predicate device, focusing on functional equivalence rather than new performance claims requiring a test set.

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

Since no specific test set or clinical study to establish new performance claims is described, there is no mention of experts or ground truth establishment in this context. The assessment relies on a comparison of technological characteristics and functionalities.

4. Adjudication Method

There is no mention of an adjudication method as no test set requiring multi-expert review or consensus is described.

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

No MRMC comparative effectiveness study was mentioned. The document describes a software modification primarily focused on the operating system and user interface, aiming to maintain core functionality rather than demonstrate improved human reader performance with AI assistance. The device's analysis functions are described as computer-assisted highlighting, subject to user review and modification, emphasizing that the program does not make final diagnoses.

6. Standalone Performance Study

No standalone performance study was explicitly described. The document focuses on the functional similarity to the predicate device's analytical features, which include event identification and data highlighting, but these are presented as tools for a human expert, not as a standalone diagnostic algorithm. The emphasis is on the software supporting human diagnosis rather than replacing it.

7. Type of Ground Truth Used

Given the nature of the software modification (OS migration and GUI enhancement) and the absence of new performance claims, no specific type of ground truth (e.g., expert consensus, pathology, outcome data) was used or discussed in relation to validating this modification. Validation appears to be based on functional verification and equivalence to the predicate.

8. Sample Size for the Training Set

The document does not mention a training set or its sample size. This is understandable as the modification is to an existing analysis system, and the focus is on re-platforming the software functionality, not on training a new machine learning algorithm.

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

As there is no mention of a training set, there is also no information on how ground truth for a training set was established. The software's "computer-assisted highlighting" suggests rule-based or historically developed algorithms rather than modern machine learning requiring extensive labeled training data.

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The Bio-logic Sleepscan Product is intended for use when it is necessary for a trained health care professional (for example, a Respiratory or EEG Technologist) to perform a Sleep diagnostic study on a patient with a possible Sleep disorder. This test consists of monitoring and recording various electrical signals from the patient, such as EEG siqnals from the brain, EOG, respiratory signals from transducers which measure air flow, effort, etc., arm and leg movement, body position while sleeping, pulse rate, and level of oxygen in the blood. Analysis features of the Sleepscan product allow for manipulation and presentation of this data in ways which enhance the physician's ability to reach informed diagnostic decisions quickly and efficiently. Although the addition of an internal oximeter does not, in itself, add to the features or capabilities of the Sleepscan product, it provides a simplification in hardware design which results in faster patient setup with fewer potential errors in setup. This latest modification to the Sleepscan product with Built-In Oximeter does not introduce any changes to the intended use of the product.

This Modification to the Bio-logic Sleepscan product with Internal Oximeter (Sleepscan Recorder) consists of a newly-designed hardware device for data recording. It is intended to complement the predicate device hardware in the Bio-logic Sleepscan product line offering new features which enhance ease-of-use and transportability. The design of this new device is nearly identical to that of the Biologic CEEGRAPH TRAVELER (tm) Ambulatory EEG Recorder (K954954), in that it provides for the data collection and storage of up to 24 channels of patient data in a digital form. The only significant difference in the design of these two devices is that the Sleepscan device includes the addition of an internal oximeter made by NONIN, The oximeter provides heartrate and blood oxygen level data to Inc. the Bio-logic data recording electronics, and this data is recorded along with the other patient data (EEG, body position, etc.). After the recording is completed, it can be analyzed using the existing Sleepscan (tm) analysis system, since the data file format is compatible with that employed in current Bio-logic Sleepscan equipment. It provides an improvement in data recording capacity through the use of the Bio-logic proprietary lossless data compression technique (SMART-PACK). This allows for the storage of up to 12 hours of typical Sleep patient data (EEG, oximetry, etc.) onto a single high-capacity PCMCIA hard disk. Power for the device is supplied by batteries inside the unit. Patient setup is accomplished by connecting the Sleepscan Recorder through an isolated serial link to a computer system running the patient setup program. After the electrodes are attached to the patient and other setup functions are completed (ie, impedance and calibration), the computer is disconnected, the Recorder is closed up, and it is placed close to the patient bedside for the duration of the Sleep recording. All setup functions, including periodic replacement of hard disk and batteries, must be performed by a qualified health care professional trained in the use of this product.

The Sleepscan Recorder is housed in a 2-part enclosure made of highstrength ULTEM 1000 plastic. This material was selected due to its high impact strength over a wide temperature range, resistance to alcohol, acetone and other chemicals, and non-flammability. The size of the enclosure is approximately 4.9" W x 6.4" L x 2.35" H (115 mm x 150 mm x 55 mm). The total weight with hard disk and batteries installed is approximately 2.1 lb (955 g). When closed, the Recorder is water-resistant, conforming to the IEC 529 IPX4 Splash-Proof specification.

The initial patient setup of the Sleepscan Recorder is accomplished through the connection of a computer system running the Sleepscan patient setup program. This connection is made between the serial port on the Recorder and a serial port on the computer system. When the computer used is a battery operated laptop, the connection is made via a standard "null modem" cable. If an AC-powered desktop computer is used, the connection to the Recorder must be made through the serial cable isolation device which provides for proper patient isolation.

There is a 62-pin cable connector on the Recorder which is used to connect to the patient electrodes and sensors. A variety of these cable-electrode assemblies are available, depending on the specific collection montage being used. The Recorder automatically senses which montage cable is in use, and records this in the data file being recorded. The ending time is also specified, or the recording will stop when the montage (electrode) cable is unplugged from the unit.

After the Sleep Recording period has been completed (typically 8 hours), the PCMCIA hard disk containing the patient data is analyzed using the standard Bio-logic Sleepscan Analysis programs. The data is first decompressed and transferred to a file format identical to that used by the predicate Sleepscan with Oximeter device. All analysis functions currently used in existing Bio-logic Sleepscan systems are available to use in the analysis of the data from the Sleepscan Recorder.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Modified Bio-logic Sleepscan product with Built-In Oximeter:

1. Table of Acceptance Criteria and Reported Device Performance

• Radiated Emissions: CISPR 11 / EN55011 (Satisfactory)
• Electrostatic Discharge Immunity: IEC 801-2 (Satisfactory)
• Radiated RF Immunity: IEC 801-3 (Satisfactory)
• Magnetic Fields Emissions: RE101 (Satisfactory)
• Magnetic Field Immunity: RS101 (Satisfactory)
• Quasi-Static Electric Fields: Tested per Reviewer's Guide (Satisfactory) |
  | Software Safety & Effectiveness | Criteria: Prevent "runaway software" condition and perform according to specifications.
  Performance: "a 'watchdog timer' circuit is included in the hardware design... effectively prevents a 'runaway software' condition of unknown consequences."
  "The system... was verified and validated; it was found to perform in accordance with specifications."
  "To establish the safety and effectiveness of the software... the system was validated in accordance with the IEEE Standards for Software Engineering, as well as Bio-logic internal software development policies and procedures modeled after the IEEE Standards."
  "The program in the Sleepscan Recorder, the patient setup program... and the data decompression/transfer program, were all developed and tested as specified in these procedures." |
  | Material Durability (Housing) | Criteria: High impact strength, resistance to chemicals, non-flammability, water-resistant.
  Performance: "housed in a 2-part enclosure made of high-strength ULTEM 1000 plastic. This material was selected due to its high impact strength over a wide temperature range, resistance to alcohol, acetone and other chemicals, and non-flammability."
  "When closed, the Recorder is water-resistant, conforming to the IEC 529 IPX4 Splash-Proof specification." |
  | Data Recording Capacity | Criteria: Store typical sleep patient data.
  Performance: "Provides an improvement in data recording capacity through the use of the Bio-logic proprietary lossless data compression technique (SMART-PACK). This allows for the storage of up to 12 hours of typical Sleep patient data (EEG, oximetry, etc.) onto a single high-capacity PCMCIA hard disk." |
  | Data File Format Compatibility | Criteria: Compatible with existing Sleepscan analysis system.
  Performance: "data file format is compatible with that employed in current Bio-logic Sleepscan equipment."
  After recording, "The data is first decompressed and transferred to a file format identical to that used by the predicate Sleepscan with Oximeter device. All analysis functions currently used in existing Bio-logic Sleepscan systems are available to use in the analysis of the data from the Sleepscan Recorder." |
  | Power Supply | Criteria: Provide power to the device.
  Performance: "Power for the device is supplied by batteries inside the unit." (Standalone operation) and "power source is only from the internal batteries" during normal operation. |

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The provided text does not specify a sample size for a test set related to patient data or clinical performance. The testing mentioned (EMI, ESD, Software validation) refers to engineering and software verification, not clinical evaluation with a patient data set. There is also no information about the country of origin of any data or whether it was retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This section is not applicable as the document describes a 510(k) summary for a hardware modification, focusing on engineering validation and demonstrating substantial equivalence to a predicate device, rather than a study involving expert-established ground truth for patient data or diagnostic accuracy. The device's purpose is data collection and recording, with analysis performed by existing Sleepscan systems and interpreted by a "trained health care professional."

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

This is not applicable. The document does not describe a test set requiring adjudication by multiple experts, as it is not a diagnostic device with an AI component being evaluated for accuracy against specific ground truth labels.

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

There is no mention of an MRMC comparative effectiveness study, nor any evaluation of human readers with or without AI assistance. The device is a data recorder, not an AI diagnostic tool.

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

The device itself is a data recorder and relies on human interpretation for diagnosis. It does not describe an "algorithm only" standalone performance in a diagnostic context. The software validation mentioned covers the device's internal software functions (data recording, compression, transfer, setup), confirming it performs "in accordance with specifications."

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

For the engineering and software validation, the "ground truth" was essentially the pre-defined engineering specifications and relevant international standards (e.g., CISPR 11, EN55011, IEC 801-2, IEEE Standards for Software Engineering). There is no patient-specific ground truth (like pathology or outcomes data) mentioned in this documentation for evaluating the device's performance.

8. The sample size for the training set

The document does not mention a training set as it is not describing a machine learning or AI algorithm in the context of diagnostic performance. The software development and testing mentioned relate to traditional software engineering validation.

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

This is not applicable as there is no mention of a training set or AI model development.

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