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The Spacelabs Healthcare Qube Compact Monitor (91390), functioning as either bedside or central monitors; passively displays data generated by Spacelabs Heatthcare parameter modules, Flexports interfaces, and other SDLC based products in the form of waveform and numeric displays, trends and alarms. Key monitored parameters available on the Model 91390 when employing the Spacelabs Command Module, consist of ECG, respiration, invasive and noninvasive blood pressure, SpO2, temperature and cardiac output. Additional parameters and interfaces to other systems are also available depending on the parameter modules employed.

The Qube is intended to alert the user to alarm conditions that are reported by Spacelabs Healthcare parameter modules and/or other physiologic monitors via Flexport interfaces. These devices determine a) when an alarm condition is violated; b) the alarm priority (i.e. high, medium or low); c) alarm limits; and d) when to initiate and terminate alarm notifications. The patient monitors are also capable of displaying alarm conditions on other monitors that are on the network through the Alarm Watch feature.

The Qube may also function as a generic display or computer terminal. As a generic display or terminal, the patient monitors allow networkbased applications to open windows and display information on other networked monitors.

The Qube is also designed to communicate with a variety of external devices such as displays, network devices, serial devices, user input devices, audio systems, and local/remote recorders.

The Qube is intended for use under the direct supervision of a licensed healthcare practitioner, or by personnel trained in proper use of the equipment in a hospital environment.

The Spacelabs Spacelabs Healthcare Qube Compact Monitor (91390) (Qube) is a component of the Spacelabs Medical Patient Monitoring System. The monitor accepts and displays parameter information, waveform and numeric data, and alarm conditions including arrhythmia information received from the same family of modules as its predicate, the Spacelabs Medical Model 91370 Patient Monitor.

The Spacelabs Healthcare Qube Compact Monitor (91390), functioning as either bedside or central monitors; passively displays data generated by Spacelabs Heatthcare parameter modules, Flexports interfaces, and other SDLC based products in the form of waveform and numeric displays, trends and alarms. Key monitored parameters available on the Model 91390 when employing the Spacelabs Command Module, consist of ECG, respiration, invasive and noninvasive blood pressure, SpO2, temperature and cardiac output. Additional parameters and interfaces to other systems are also available depending on the parameter modules employed.

The Qube is intended to alert the user to alarm conditions that are reported by Spacelabs Healthcare parameter modules and/or other physiologic monitors via Flexport interfaces. These devices determine a) when an alarm condition is violated; b) the alarm priority (i.e. high, medium or low); c) alarm limits; and d) when to initiate and terminate alarm notifications. The patient monitors are also capable of displaying alarm conditions on other monitors that are on the network through the Alarm Watch feature.

The Qube may also function as a generic display or computer terminal. As a generic display or terminal, the patient monitors allow networkbased applications to open windows and display information on other networked monitors.

The Qube is also designed to communicate with a variety of external devices such as displays, network devices, serial devices, user input devices, audio systems, and local/remote recorders.

The Qube is intended for use under the direct supervision of a licensed healthcare practitioner, or by personnel trained in proper use of the equipment in a hospital environment.

The provided text describes the Spacelabs Healthcare Qube Compact Monitor (91390) and its 510(k) premarket notification. However, it does not describe acceptance criteria or a study proving the device meets those criteria in the context of an Artificial Intelligence (AI) or machine learning algorithm. The document pertains to a medical device (patient monitor) and its regulatory clearance based on substantial equivalence to a predicate device. The performance testing outlined focuses on electrical safety, electromagnetic compatibility, software validation, usability, and alarm systems, which are standard for such medical devices, not for AI algorithm performance.

Therefore, for aspects related to AI/ML specific criteria (like ground truth, expert consensus, MRMC studies, sample sizes for training/test sets for an algorithm, and improvement with AI assistance), the information is not present in the provided document.

Here's an analysis based on the information available in the provided text:

Acceptance Criteria and Device Performance (Based on available information)

• IEC 60601-1-6: 2010 (Usability)
• IEC 60601-1-8: 2006 (Alarm systems)
• IEC 62366: 2007 (Application of usability engineering)
• ISTA Procedure 1A (Packaged-products under 150 lb (68 kg) non-simulation integrity performance test procedure) | "Test results indicated that the Qube complies with its predetermined specification and with the applicable Standards." |
  | Conclusion/Overall | Safe and effective when used in accordance with intended use and labeling, and substantially equivalent to predicate device. | "Verification and validation activities were conducted to establish the performance and safety characteristics of the device modifications made to the Qube. The results of these activities demonstrate that the Qube is safe and effective when used in accordance with its intended use and labeling. Therefore, the Qube is considered substantially equivalent to the predicate device." |

Study Details (Based on available information for a medical device, not an AI algorithm)

The document describes performance testing for a medical device (patient monitor), not a study for an AI/ML algorithm. Therefore, many of the requested AI/ML-specific details are not applicable or not present.

1. A table of acceptance criteria and the reported device performance: (Provided above)

2. Sample sizes used for the test set and the data provenance:

   • The document does not specify sample sizes for any of the performance tests (e.g., number of units tested, duration of tests, or amount of data used for software validation).
   • Data provenance is not mentioned. These are typical engineering and regulatory compliance tests performed on the device itself.

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

   • This concept of "ground truth" and "experts" as in AI/ML is not applicable to the type of device testing described. The tests are against established engineering standards and internal specifications, not a clinical "ground truth" adjudicated by medical experts.

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

   • Not applicable as this is not a study assessing human or AI interpretation against a clinical 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:

   • No MRMC study was conducted or mentioned, as this device is a patient monitor, not an AI-assisted diagnostic tool.

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

   • Not applicable. The device itself is the system; there is no separate "algorithm only" performance reported in the context of an AI.

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

   • Not applicable in the AI/ML sense. The "ground truth" for the device's performance is adherence to established engineering and medical device safety standards (e.g., IEC standards, internal specifications).

8. The sample size for the training set:

   • Not applicable. This document is for a medical monitor, not an AI/ML algorithm that requires a training set.

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

   • Not applicable.

In summary, the provided K120616 document is a 510(k) summary for a patient monitoring device, demonstrating its substantial equivalence to a predicate device through adherence to recognized performance, safety, and electromagnetic compatibility standards. It does not involve artificial intelligence or machine learning algorithms and therefore does not contain information on "acceptance criteria" or "study" as one would expect for an AI/ML-based medical device.

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