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The SVM-7200 series Vital Signs Monitor is intended for monitoring of physiologic parameters, including non-invasive blood pressure (systolic, and mean arterial pressure), pulse rate, non-invasive functional oxygen saturation of arteriolar hemoglobin (SpO2), and temperature, and neonatal patients in hospital environments when used by clinical physicians or appropriate medical staff under the direction of physicians.

The SVM-7200 series Vital Signs Monitor is intended to be used by clinicians, doctors, nurses, and medically qualified personnel for measuring noninvasive blood pressure (NIBP), noninvasive functional oxygen saturation of arteriolar hemoglobin (SpO2), body temperature (TEMP) of one patient at a time. The monitors can be used in the specialized health care environment such as hospitals, clinics, special medical facilities, independent surgery centers, multitherapy facilities and wards. Adults, children and neonates can be monitored using this device. The SVM-7200 series monitors have an eight-inch TFT color display and two modes: spot check and continuous mode. The monitor can operate with either a wired or wireless LAN connection.

The NIHON KOHDEN SVM-7200 series Vital Signs Monitor obtained FDA clearance (K190468) based on its substantial equivalence to predicate devices, leveraging previously validated clinical accuracy data for its sub-systems.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly present a table of quantitative acceptance criteria for device performance (e.g., specific accuracy ranges for SpO2, NIBP, Temperature). Instead, the acceptance criteria are implicitly met by demonstrating compliance with various recognized standards and by leveraging clinical accuracy data from previously cleared sub-systems.

The reported device performance for the SVM-7200 series (referring to accuracy) is based on the validation of its constituent clinical sub-systems, not on new, standalone performance studies for the integrated SVM-7200 itself.

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

The document states: "New clinical accuracy validation testing was not necessary as these subsystems along with their accessories have been previously validated and cleared. This 510(k) leverages the previous clinical accuracy data from the predicates..."

Therefore, there is no new sample size for a test set conducted specifically for the SVM-7200 series for clinical accuracy. The "test set" in this context refers to the data used in the original validation studies of the individual sub-systems (Masimo SpO2, Nellcor SpO2, Nihon Kohden SpO2, Covidien TEMP, Exergen TEMP, Nihon Kohden NIBP). The document does not provide details on the sample sizes or data provenance (e.g., country of origin, retrospective/prospective) of these historical studies.

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

Since no new clinical accuracy studies were conducted specifically for the SVM-7200 series, this information is not provided in the document. The ground truth for the leveraged clinical accuracy data from the sub-systems would have been established during their original validation studies, but details on experts and their qualifications are not included here.

4. Adjudication Method for the Test Set:

This information is not provided as no new clinical accuracy studies were performed for the SVM-7200 series in this submission.

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:

This device is a vital signs monitor, not an AI-assisted diagnostic tool that would involve "human readers" interpreting images or data. Therefore, an MRMC comparative effectiveness study is not applicable and was not performed.

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

The device performance, particularly for its various measurement sub-systems (NIBP, SpO2, Temp), is essentially "standalone" in the sense that the algorithms embedded within these components calculate the physiological parameters. The document confirms that "New clinical accuracy validation testing was not necessary as these subsystems along with their accessories have been previously validated and cleared." This implies that the algorithms for calculating these vital signs had their standalone performance validated in previous 510(k) submissions. The SVM-7200 (the subject device) integrates these already validated standalone sub-systems.

7. The Type of Ground Truth Used:

The ground truth for the clinical accuracy of the individual sub-systems (NIBP, SpO2, Temperature) would have been established using reference methods or clinically accepted gold standards during their original validation studies. For example:

• SpO2: Co-oximetry for arterial blood gas analysis would typically be the ground truth.
• NIBP: Invasive arterial blood pressure measurement or auscultatory methods would be common ground truths.
• Temperature: Rectal temperature, or other highly accurate core body temperature measurements, are typically used.

The document does not detail the specific ground truth methods for the (already cleared) sub-systems, but it implicitly relies on their validation against such standards.

8. The Sample Size for the Training Set:

The SVM-7200 is not described as utilizing machine learning or AI models that require "training sets" in the conventional sense. Its sub-systems (NIBP, SpO2, Temp) are based on established algorithms and hardware. Therefore, information regarding a "training set sample size" is not applicable/provided.

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

As no training set is discussed or implied for this device in the context of machine learning, this information is not applicable/provided.

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The OLG-3800A CO2 monitor is intended to monitor respiratory rate, CO2 partial pressure and EtCO2. The device is also intended to monitor pulse rate and SpO2.

The device may generate an audible and/or visible alarm when a measured physiological rate falls outside preset limits, or when a technical error is detected.

The devices are intended to be used by qualified medical facility, such as hospital or clinic, on all patient populations including adult, neonate, infant, child, and adolescent subgroups.

The Nihon Kohden OLG-3800A is a compact CO2 monitor with a 7-inch display and is designed so the operator can directly touch the screen from the operator position. The CO2 monitor displays the patient's vital signs (CO2, RR, SpO2, PR) on the screen and generates an alarm according to the setting. Alarms are indicated with a screen message, sound, blinking or lighting of the alarm indicator. The device is used with commercially available sensors for intubated and non-intubated patients. The CO2 monitor is intended to be used in an ER, OR, ICU, CCU or general ward on all patient populations, depending on the accessories used with the device. The OLG-3800A is AC and/or battery operated.

When the operation mode is set to Network mode, the CO2 monitor can connect to a Nihon Kohden monitoring system network and communicate with the central monitor and bedside monitor on the network.

A new optional accessory, single-use adult cap-ONE Biteblock YG-227T can be used together with OLG-3800. YG-227T is inserted between the patient's teeth to prevent closure of the patient's jaws. It connects to a specified Nihon Kohden CO2 sensor kit to measure the partial pressure of the expired CO2 of a patient. Also, it allows oxygen (including an oxygen-air mixture) to be provided to the patient during endoscopy.

This document describes the Nihon Kohden CO2 Monitor, Model OLG-3800A, and its substantial equivalence to predicate devices. However, it does not contain a typical study design with the elements requested (acceptance criteria, device performance, sample size, ground truth, expert involvement, etc.) for an AI/ML-based medical device. Instead, it details the device's technical specifications, indications for use, and compliance with various international standards for medical electrical equipment and a brief section on performance testing.

Therefore, many of the requested fields cannot be directly extracted from the provided text because they are not applicable to the type of regulatory submission (a 510(k) for a hardware medical device with standard electrical and performance testing against a predicate device, not an AI/ML algorithm requiring a clinical validation study with human readers or standalone performance metrics).

However, I can extract information related to the device's stated performance and compliance with relevant standards, which serve as its "acceptance criteria" in this context.

Here's the information that can be extracted or inferred based on the provided document:

1. A table of acceptance criteria (from standards) and the reported device performance:

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The Nihon Kohden Vital Sign Telemeters GZ-120P and GZ-130P are intended to monitor and transmit physiological data from a patient to a Nihon Kohden monitor via radiofrequency in the 802.11 band for continuous monitoring. Both GZ-120P and GZ-130P transmit electrocardiogram (ECG) and respiration data, and GZ-130P transmits blood oxygen saturation (SpO₂) in addition. The device may generate an audible and/or visible alarm when an arrhythmia exists, when a measured physiological rate falls outside preset limits, or when a technical error is detected. Furthermore, the devices can be configured for use as a temporary simple monitor to display the patient's vital signs on the device screens and generate alarms without transmitting the data to other Nihon Kohden monitor.

The devices are intended to be used by qualified medical personnel within a medical facility, such as hospital or clinic, on all patient populations including adult, neonate, infant, child, and adolescent subgroups.

The Nihon Kohden Vital Sign Telemeter GZ-120P/GZ-130P is mainly used as a telemetry system within a medical facility. The device transmits patient's vital signs (ECG, SpO2*, respiration, pulse waveform) and alarm information via wireless LAN connection to the central monitoring station. The device can be configured to display the patient's vital signs on the screen and generate alarms for use as a temporary simple monitor. *SpO2 is for GZ-130P only.

The provided text describes the Nihon Kohden Vital Sign Telemeter GZ-120P/GZ-130P and details its substantial equivalence to predicate devices, rather than a study proving the device meets specific acceptance criteria for a novel algorithm's performance. The document focuses on regulatory approval based on safety, essential performance, and equivalence to existing devices.

Therefore, many of the requested categories regarding algorithm-specific performance, ground truth, expert adjudication, and comparative effectiveness studies are not applicable or cannot be extracted from this document, as it describes a hardware device with monitoring capabilities, not an AI/algorithm-driven diagnostic/decision-support tool.

However, I can extract information related to the device's general performance and the types of tests conducted for its regulatory approval.

Here's the information based on your request, with an emphasis on what is available in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a tabular format with corresponding "reported device performance" in the context of an algorithm's diagnostic accuracy. Instead, it refers to compliance with safety and performance standards.

Implicit "Acceptance Criteria" (Compliance with Standards) and "Reported Performance" (Validation of Compliance):

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

The document does not specify a "sample size" in terms of number of patients or physiological recordings for evaluating performance of an algorithm. The testing described is primarily related to engineering and regulatory compliance of the device itself (hardware, software, communication protocols). Therefore, data provenance is not discussed in terms of country of origin or retrospective/prospective collection as there isn't patient data being evaluated for a diagnostic algorithm.

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

Not applicable. This document describes the regulatory clearance for a vital sign telemeter, which transmits physiological data (ECG, respiration, SpO2) and generates alarms. It does not involve a diagnostic algorithm that requires expert-established ground truth for performance evaluation in the context of diagnostic accuracy.

4. Adjudication Method for the Test Set

Not applicable for the reasons stated above.

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. The device is a monitor and telemeter, not an AI-assisted diagnostic tool that would involve human readers and their improvement with AI assistance.

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

The document does not describe a standalone algorithm performance study. The device itself performs functions like arrhythmia detection and alarm generation, but these are inherent to the monitor's functionality, not a separate "algorithm" requiring a standalone performance study. Its performance for these functions is indicated as being "equivalent to the predicate device."

7. The Type of Ground Truth Used

Not applicable in the context of an algorithm's diagnostic accuracy. The "ground truth" here would relate to the accuracy of the physiological measurements themselves against calibrated standards, and the proper functioning of alarms as per specifications and standards. This is implied by the "Test Summary" and "Standards compliance testing" sections.

8. The Sample Size for the Training Set

Not applicable. This device is not described as having an AI algorithm that requires a training set of data.

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

Not applicable for the reasons stated above.

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