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The 740 SafeSAT is indicated for use as a bedside, portable device for use by health care professionals, clinicians and medically qualified personnel for spot checking, continuous monitoring of adult and pediatric patients, excluding neonates. The Monitor features technology to facilitate the monitoring of non-invasive blood pressure, pulse rate and functional arterial oxygen saturation (SpO2) in a variety of clinical environments.

The 740 SafeSAT physiological patient monitor is a portable and rugged non-invasive multiparameter device used for spot checking, continuous monitoring, and recording of blood pressure, pulse rate, and functional arterial oxygen saturation (SpO2) in a variety of clinical environments. The 740 SafeSAT monitor employs SafeSAT SpO2 technology which includes components from OSI Optoelectronics. The monitor is compact and lightweight, with a color touch screen for user interface. It supports point-of-care and variable acuity monitoring, including saving spot vital signs and continuous monitoring with alarms. Features include a Standby Mode, Trends Display, screen keyboard for patient data entry, serial data output for EMR connectivity, an internal isolated relay switch for nurse call systems, and support for an optional external thermal strip chart recorder. It measures non-invasive blood pressure (NIBP) using the oscillometric technique and pulse oximetry (SpO2) by measuring the absorption of red and infrared light. Alarm conditions are displayed visually and audibly.

Here's a breakdown of the acceptance criteria and study information for the 740 SafeSAT device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary does not explicitly state the quantitative acceptance criteria for SpO2 accuracy. Instead, it refers to the performance requirements of a standard and global claim of "exceeds its performance claims." Based on the clinical testing section, the core acceptance criteria for SpO2 accuracy are derived from ISO 80601-2-61.

Note: The document states "The clinical data demonstrates that the device exceeds its performance claims for SpO2 measurement accuracy under motion and non-motion conditions," but it does not provide the specific numerical performance claims (e.g., Accuracy Root Mean Square (ARMS) values).

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

• Test Set Sample Size: "healthy male and female adults in the range of 20 to 40 years of age and with a range of skin tone." The exact number of participants is not specified in the provided text.
• Data Provenance: Not explicitly stated (e.g., country of origin). The studies appear to be prospective clinical studies conducted specifically for this device's submission.

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

This information is not provided in the text. For SpO2 accuracy studies, arterial blood gas measurements (which serve as the ground truth) are typically verified by trained medical personnel, but details on the number or specific qualifications of such personnel are not present.

4. Adjudication Method for the Test Set

This information is not explicitly stated. Given that the ground truth for SpO2 accuracy is typically established through arterial blood gas measurements, an adjudication method in the traditional sense (e.g., for image interpretation) would not be directly applicable. The accuracy of the blood gas measurements themselves would follow established laboratory protocols.

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

No. An MRMC comparative effectiveness study was not performed. This type of study is more common for diagnostic imaging AI, where human readers interpret medical images. The 740 SafeSAT is a physiological monitor, and its primary clinical validation focuses on the accuracy of its physiological measurements against a reference standard.

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

Yes. The clinical studies performed were standalone, meaning they evaluated the device's SpO2 measurement accuracy directly against blood testing (ground truth), not in conjunction with human interpretation or assistance. The device itself performs the measurement.

7. Type of Ground Truth Used

The ground truth used for the SpO2 accuracy studies was blood testing (specifically, arterial blood gas measurements are the de facto standard for this), as stated: "clinical studies were performed... to determine accuracy with respect to blood testing."

8. Sample Size for the Training Set

This information is not provided within the 510(k) summary. The summary focuses on the validation of the device, including its embedded SafeSAT SpO2 OEM technology. The training set would pertain to the development of the SafeSAT SpO2 OEM module's algorithms, which is manufactured by OSI Optoelectronics, not the final 740 SafeSAT device itself. Details on that development are outside the scope of this 510(k) submission.

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

This information is not provided. Similar to the training set sample size, the establishment of ground truth for training the SpO2 algorithms embedded within the SafeSAT OEM module would be part of the OEM's development process and is not detailed in this 510(k) summary for the integrating device.

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The Zoe Medical Nightingale Monitoring System is indicated for use in adult & pediatric patient populations.

The Zoe Medical Nightingale Monitoring System facilitates the monitoring of:

• ECG -
• Impedance respiration -
• Non-Invasive blood pressure -
• Invasive blood pressure -
• Body temperature "
• Functional arterial oxygen saturation (SpO2) -
• -End-tidal & inspired CO2

The Zoe Medical Nightingale Monitoring System is a prescription device intended to be used by healthcare professionals in all areas of a healthcare facility.

The Zoe Medical Nightingale Monitoring System (NMS) facilitates the monitoring of patient physiological parameters both at the bedside on the Nightingale PPM3 monitor and remotely on the Nightingale MPC central station. The physiological parameters monitored by the NMS include: ECG. impedance respiration, non-invasive blood pressure, invasive blood pressure, body temperature, functional arterial oxygen saturation (SpO2), and end-tidal & inspired CO2 (capnography). The Nightingale Monitoring System as described in this submission is a new device, and will be marketed as the next generation product superseding the original and previously cleared Zoe Medical NMS (K001775).

The part numbers for the four Nightingale PPM3 variants and their associated configurations are given below.

179-0003 NIGHTINGALE PPM3 (with NIBP, SPO2, ECG, and Temp)

179-1000 NIGHTINGALE PPM3 WITH IBP (with NIBP, SPO2, ECG, Temp, & IBP)

179-1001 NIGHTINGALE PPM3 WITH ETCO2 (with NIBP, SPO2, ECG, Temp, & Microstream ETCO2)

179-1002 NIGHTINGALE PPM3 (with NIBP, SPO2, ECG, Temp, IBP, & Microstream ETCO2)

The Nightingale MPC central station (171-0001) will be sold as an option available to all customers based on their needs.

The provided document describes the Zoe Medical Nightingale Monitoring System, a patient physiological monitor. Here's an analysis of its acceptance criteria and the studies performed:

1. Table of Acceptance Criteria and Reported Device Performance

The submission focuses on establishing substantial equivalence to a predicate device (Spacelabs Healthcare Vital Signs Monitoring System, K090556) rather than detailing specific numerical acceptance criteria for each physiological parameter. The acceptance criteria are broadly defined by compliance with applicable standards and demonstration that the device's performance meets its predetermined specifications.

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

The document does not specify a separate "test set" in the context of device performance data beyond the compliance testing. The performance and safety validations were primarily based on engineering and laboratory testing against established standards and internal requirements. Therefore:

• Sample Size: Not applicable in terms of a clinical dataset for a test set. The samples would be the physical devices and components undergoing the various safety and performance tests.
• Data Provenance: The data comes from internal testing conducted by Zoe Medical, Inc., as part of their design and development processes. It is retrospective in the sense that the testing was completed before submission for clearance. The country of origin of this internal testing data is likely the USA (Topsfield, MA, where the company is located).

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

This information is not applicable. The device's performance is assessed against recognized industry standards and internal specifications, not against a "ground truth" established by experts in the typical sense of a clinical diagnostic study. The "ground truth" for electrical safety would be the requirements of the IEC 60601 series, and for EMC, the IEC 60601-1-2 standard. Internal engineering experts and certified testing laboratories would be involved in verifying compliance.

4. Adjudication Method for the Test Set

This is not applicable as there is no mention of a "test set" in the context of human interpretation or clinical data requiring adjudication. Compliance with standards is typically a pass/fail outcome based on measurements and observations.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. The submission relies on demonstrating substantial equivalence to a predicate device and compliance with relevant safety and performance standards for a physiological monitor, not on assessing the improvement of human readers with this AI-assisted technology. This device is a monitor, not an AI diagnostic tool.

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

This is not applicable. The Zoe Medical Nightingale Monitoring System is a physiological patient monitor, a hardware device with embedded software. Its performance is inherent to the device itself and its sensors, not a standalone algorithm in the AI sense. Its intended use involves healthcare professionals continuously monitoring the patient via the device.

7. The Type of Ground Truth Used

The "ground truth" for the performance and safety testing is based on:

• Pre-determined specifications: Internal requirements established by Zoe Medical.
• International and National Standards: Compliance with recognized standards such as AAMI ES 60601-1, IEC 60601-1-2, IEC 60601-2-XX series, ISO 80601-2-XX series, IEC 62366, and IEC 62304. These standards define acceptable levels of safety and performance for physiological monitors.

8. The Sample Size for the Training Set

This information is not applicable. The device is a physiological monitor, not an AI/ML algorithm that requires a "training set" in the machine learning context. Its functionality is based on established engineering principles and signal processing, not on learning from a large dataset.

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

This information is not applicable, as there is no "training set."

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The Ultraview DM3 Monitor is indicated for use by health care professionals for monitoring patient vital signs.

The Ultraview DM3 Monitor is intended for monitoring, recording, and alarming basic vital signs on adult and pediatric patients. Monitored parameters include SpO2, pulse rate, NIBP, and temperature.

The Ultraview DM3 Monitor is a portable patient monitor intended to be used by clinicians and medical qualified personnel for spot check and continuous monitoring of non-invasive blood pressure (NIBP), pulse oximetry (SpO2), and temperature.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Ultraview DM3 Monitor, structured to address your specific points.

Acceptance Criteria and Device Performance for Ultraview DM3 Monitor

1. Table of Acceptance Criteria and Reported Device Performance

The provided document, a 510(k) summary, focuses on demonstrating substantial equivalence to predicate devices rather than detailing specific numerical acceptance criteria for performance metrics (like accuracy or precision). It lists general categories of testing and concludes that the device "complies with its predetermined specification."

Since explicit numerical acceptance criteria and corresponding reported performance values are not provided in this document, the table below reflects what can be inferred.

Important Note: The document consistently states "complies with its predetermined specification" or "complies with its predetermined requirements" which indicates acceptance was met for these general categories. However, the exact numerical specifications themselves (e.g., NIBP accuracy range, SpO2 bias and precision) are not disclosed in this summary.

2. Sample Size for the Test Set and Data Provenance

• Sample Size for the Test Set: Not explicitly stated for NIBP or Temperature. For Pulse Oximetry (SpO2), the document mentions "Clinical performance testing was performed according to ISO 9919:2005." ISO 9919:2005 (Medical electrical equipment – Particular requirements for the basic safety and essential performance of pulse oximeter equipment) typically requires a minimum of 10 healthy adult volunteers whose arterial blood hemoglobin oxygen saturation can be reduced and stabilized over a specific range to perform accuracy testing. While the exact number isn't in this document, this is the standard typically applied.
• Data Provenance: Not specified in the provided text. It does not mention the country of origin of the data or whether the study was retrospective or prospective, except for the clinical performance testing for oximetry, which by its nature (involving human subjects in a controlled setting) would be prospective.

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

• Number of Experts: Not explicitly stated. The provided document details a 510(k) submission for a physiological monitor, not a device requiring expert interpretation of diagnostic images or signals. The "ground truth" for a monitor like this typically comes from reference devices or direct physiological measurements, not expert consensus in the diagnostic sense.
• Qualifications of Experts: Not applicable or not specified, as "experts" for ground truth are not mentioned in the context of interpretation, but rather skilled personnel performing measurements.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable or not specified. Adjudication methods (like 2+1 or 3+1) are typically used when multiple human readers interpret ambiguous cases in diagnostic studies (e.g., radiology for AI algorithms). For a vital signs monitor, the comparison is usually against a reference standard, not a consensus of human interpretations.

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

• MRMC Comparative Effectiveness Study: No, this type of study was not performed and is not relevant for the Ultraview DM3 Monitor. This device is a physiological monitor that measures vital signs, not an AI-assisted diagnostic tool that helps human readers interpret data. The comparison is between the device's measurements and a reference standard, not between human performance with and without AI.

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

• Standalone Performance Study: Yes, the described "Performance Testing - Bench" and "Clinical performance testing... to demonstrate safety and effectiveness of the oximetry feature" can be considered standalone performance assessments. These tests evaluate the device's ability to accurately measure physiological parameters independently, without necessarily involving human intervention in the data processing itself, beyond setting up the device and potentially interpreting its output clinically. The document states that the software was "verified and validated" confirming its standalone function.

7. The Type of Ground Truth Used

• Type of Ground Truth:
  • For SpO2 (Pulse Oximetry): Likely arterial blood gas analysis (co-oximetry) as a reference standard, which is the gold standard for SpO2 accuracy testing as per ISO 9919:2005.
  • For NIBP (Non-Invasive Blood Pressure): Likely a reference NIBP device that has been validated against an invasive arterial manometer or a double-auscultation method using qualified observers, following recognized standards (e.g., ANSI/AAMI/ISO 81060-2).
  • For Temperature: Likely reference thermometers that are calibrated to a known standard.
  • For Software, Electrical Safety, EMC, Bench Performance: Ground truth is established by the specifications of applicable standards (e.g., ISO, AAMI, IEC standards) and the manufacturer's own predetermined internal requirements.

8. The Sample Size for the Training Set

• Sample Size for the Training Set: Not applicable or not specified. This document pertains to a traditional physiological monitor, not a device developed using machine learning or AI that would typically have distinct "training sets." The device's algorithms for NIBP, SpO2, and temperature processing are based on established physiological principles and signal processing, not a data-driven training process in the AI sense.

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

• How Ground Truth for the Training Set Was Established: Not applicable. As explained above, this device does not utilize a training set in the context of machine learning. The "ground truth" for the development of its algorithms would stem from established medical and engineering principles, physiological models, and empirical testing during the design phase, rather than a formally labeled "training set" with ground truth generated by experts.

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The Well@Home System is indicated for use for patients who need home-based health care from professional clinicians. The system provides benefits for patients who need periodic remote monitoring of their vital signs (such as noninvasive blood pressure, oxygen saturation, pulse rate, temperature, respiration rate, weight, blood glucose level, heart rate, or ECG) or self-reported symptoms, who need reminders to take prescribed medications, or who need training about how to manage their illness.

The Well@Home System consists of the home-based "Well@Home Monitor" and the office-based "Well@Home Clinician Application". Using the Well@Home System, clinicians can monitor theised at home or in another remote health care facility. The use model is "daily checkups", rather them continuous monitoring.

The Well@Home Monitor collects vital signs and symptom information on a periodic basis via a patientfriendly user interface. The user interface guides the patient through a schedule of activities using voice promots, instructional diagrams and large, easy-to-read buttons. The scheduled of doutinities can'nclude reminders to take medications or to take vital signs measurements. The schedule for these activities can be customized by the clinician according to the patient's medical condition. The user interface also provides opportunities for the patient to report symbons at any time, and to review training ontent related to managing the patient's illness.

The Well@Home monitor measures noninvasive blood pressure, oxygen saturation, pulse rate, temperation | President rate, heart rate, and ECG. The Well@Home Monitor is designed to interface to Other Medical Devices (OMD's) for the purpose of gathering physiological data from those devices. The interface is through the monitor's three OMD serial ports. These serial ports are electrically isoated from each other and from the monitor's own physiological front-end. The list of supported OMD's is as follows:

• . Fairbanks Digital Scale (private labeled and device listed as a Zoe Medical accessory)
• Lifescan One Touch Ultra Blood Glucose Meter (or compatible BGM from Lifescan) .

The OMD interface mechanism is designed to be expandable. Future OMD's may include a Spirometer or a PT/INR measurement device.

The Well@Home Monitor transmits the gathered information to a clinician over the patient's existing telephone line. This information is received and stored by the Well(@Home Clinican Application.

The Well@Home Clinician Application is essentially a patient data management and record keeping program that includes an interface to the Well@Home Monitor. The Well@Home Clinician Application stores information that is gathered from multiple Well@Home Monitors and allows a clinician to review a given patient's information. It also allows the clinician to make adjustments to a patient's schedule of activities as needed. These adjustments are sent back to the patient's Well@Home Monitor over the same telephone link.

The Well@Home Clinician Application software was developed by Patient Care Technologies (PtCT) of Atlanta, Georgia, and is designed to run on standard Windows-based PC's. These PC's are typically installed at the office of a home care agency, and are referred to in this 510(k) as "Agency Servers". The Agency Servers may run other information management software developed by PtCT that is not part of the Well@Home System. The Well@Home System is product-branded to tie into PtCT's information management software product line.

Because of the remote-monitoring and spot check nature of the Well@Home System, there are no realtime "alarms" as in a hospital-style monitor. Rather, the clinician defines "alerts" that are to be generated (e.g., when a vital sign parameter exceeds set limits or when a particular symptom is reported). These alerts are part of the information package that is sent from the Well@Home Monitor to the Well@Home Clinician Application. The alerts are then visually highlighted when the clinician reviews the patient's information.

The provided text describes the Zoe Medical Well@Home System, which is a noninvasive blood pressure measurement system for remote patient monitoring. However, it does not include detailed acceptance criteria or a specific study proving the device meets those criteria in the way a modern medical device submission typically would.

Instead, the document focuses on demonstrating substantial equivalence to existing predicate devices through:

1. Technological Characteristics Comparison: Showing that the Well@Home System's design, functions, and principles of operation are similar to previously cleared devices.
2. Performance Testing: Stating that internal engineering tests were conducted to verify performance against functional requirements and to show substantial equivalence.

Given this, I will extract the information available and note where specific details (like numerical acceptance criteria, sample sizes for test sets, expert qualifications, etc.) are absent.

Acceptance Criteria and Device Performance (as inferred from the document)

Detailed Study Information (Based on Available Text):

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

   • Sample Size: Not specified. The document states "internal engineering tests" and "bench tests using simulators" were conducted, but no numerical sample sizes for these tests are provided for either human subjects or simulated data points.
   • Data Provenance: Not specified. The tests were "internal engineering tests," implying they were conducted by the manufacturer, Zoe Medical, but details on location or whether they involved human subjects are absent.
   • Retrospective or Prospective: Not specified. The nature of "internal engineering tests" and "bench tests using simulators" suggests they were likely prospective tests conducted on the device hardware and software.

2. 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):

   • Not applicable/Not specified. The "ground truth" for the vital signs measurements appears to be established by the predicate devices themselves (Nightingale PPM and One Touch Ultra) and, for overall system functionality, by functional requirements. There is no mention of independent experts establishing ground truth for a test set in the context of clinical accuracy or interpretation that would require such expertise. "Bench tests using simulators" imply comparison against known simulator outputs.

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

   • Not applicable/Not specified. The document does not describe a clinical study design that would involve expert adjudication of results. The testing described is primarily technical and functional equivalence vs. predicate devices or simulators.

4. 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 not an AI-assisted diagnostic tool for human readers. It is a remote monitoring system that collects and transmits vital signs and symptom data. Therefore, an MRMC study or AI-assistance effect size is not relevant to this submission.

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

   • Yes, implicitly. The "internal engineering tests" and "bench tests using simulators" for vital signs measurement evaluate the device's capability to measure data and display it correctly. For the blood glucose meter, the BGM's performance is explicitly stated as "no different when it is connected to the Well@Home Monitor as when it functions as a standalone device," indicating a standalone performance assessment of the BGM component. The Well@Home System functions as an "information transfer technology" for the BGM.

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

   • For vital signs measurement (Nightingale PPM comparison): The ground truth was presumably the known accurate outputs from physiological simulators or the validated measurements from the predicate Nightingale PPM itself.
   • For blood glucose measurement (One Touch Ultra comparison): The ground truth was the measurements provided by the standalone, predicate Lifescan One Touch Ultra Blood Glucose Meter.
   • For overall system functionality (HANC Network comparison): The ground truth was likely defined by functional requirements derived from the predicate HANC Network's capabilities.

7. The sample size for the training set:

   • Not applicable/Not specified. This document is for a medical device submission focused on substantial equivalence through hardware and software design, and functional testing. It does not describe a machine learning or AI model that would require a "training set" in the conventional sense. The software algorithms for vital signs measurement are stated to be "the same software algorithms" as the predicate Nightingale PPM, implying they were developed and validated previously, not newly trained for this specific application.

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

   • Not applicable. As there is no described training set for an AI/ML model, this question is not relevant to the provided information.

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