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The Respiree Cardio-Respiratory Monitor is a respiratory monitor intended for hospitals and hospital-type facilities in non-ICU settings and home settings.

The Respiree Cardio-Respiratory Monitor is indicated for the non-invasive spot checking of respiration rate (RR) for adult patients.

The Respiree Cardio-Respiratory Monitor System comprised of the following devices:

• Respiree Cardio-Respiratory Monitor
• Respiree Gateway and accessories (Antenna, charging cable)
• Respiree Dashboard

The Respiree Cardio-Respiratory Monitor is a wearable respiratory monitor. For measurement of respiration rate (RR), the device is affixed to the chest using a disposable adhesive patch with a hook-and-loop fastener to attach to the monitor. The device uses a vertical-cavity surface-emitting diode to emit optical light directed toward the skin. An integrated photodetector in a nearby position senses the diffused collected light. An adaptive signal processing method is used to enhance the device respiratory rate measurements by splitting the signal processing optimizations across different respiratory rate bands.

The monitor is powered by a 3.7V rechargeable, lithium-ion battery and is charged using the gateway provided. The Respiree Cardio-Respiratory Monitor transmits respiration rate raw data to the gateway via AES 256 encrypted Bluetooth wireless technology, and the latter uploads the data to the fixed secured cloud server either via Wi-Fi or LTE.

The Respiree Dashboard is a web application user interface that enable healthcare professional to access recorded respiration rate information for spot patient monitoring. The data from the Respiree Cardio- respiratory Monitor are intended for use by healthcare professionals as an aid to diagnosis and treatment. The device is not intended for use on critical care patients.

The provided FDA 510(k) clearance letter and summary for the Respiree Cardio-Respiratory Monitor System (K250934) indicate that clinical studies were not required for this specific submission, as there was "no change in the respiration rate software algorithm cleared in the previous version of the device (K223681)." This implies that the performance data for the respiration rate measurement itself was established in a prior submission (K223681).

Therefore, I cannot extract specific details about new clinical studies for K250934 that would directly prove the device meets acceptance criteria for respiration rate measurement within this document. The document primarily focuses on demonstrating substantial equivalence based on the updated hardware, expanded use environment (home setting), and data presentation methods, leveraging the previous clearance for the core measurement accuracy.

However, I can infer information about the acceptance criteria for the respiration rate measurement and the reported device performance based on the comparison table with the predicate devices. The other requested information (sample size, experts, adjudication, MRMC, standalone, ground truth, training set details) is typically found in the clinical study report itself, which is not part of this 510(k) summary for K250934.

Inference from K250934 Document (based on predicate comparison):

1. Table of Acceptance Criteria and Reported Device Performance (Inferred from Predicate Comparison)

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The RTM Vital Signs RTMsense is indicated for use by healthcare professionals in healthcare facilities, such as post-operative care and general wards, to monitor breathing in adult (at least 22 years old) patients.

RTMsense is a non-invasive system that graphically displays respiratory function against time and reports respiratory rate.

RTMsense measurements are used as an adjunct to other clinical information sources.

The RTMsense Respiratory Monitoring System is a single use wearable device consisting of a wearable trachea sound sensor (TSS) and software that continuously measures a patient's respiratory rate by analyzing the sounds of air flow within the proximal trachea during inhalation and exhalation. The acoustic signal is transmitted wirelessly to a Lenovo Tablet, and the respiratory measurement values are displayed on the tablet after analysis of the acoustic data by a proprietary software algorithm.

The RTMsense software application has three parts: firmware on the TSS, a web-based application on the Lenovo tablet, and a cloud-based proprietary software algorithm. The TSS securely transmits acoustic data wirelessly to the local, Bluetooth low energy enabled Lenovo tablet. The tablet uses a web-based application to securely transmit the acoustic data to the cloud for analysis in RTM's proprietary cloud-based algorithm. The web application retrieves the processed data from the algorithm to display respiratory rate on the tablet.

The device will be used by healthcare professionals in healthcare facilities such as post-operative care or general wards. The RTMsense respiratory measurements are used as an adjunct to other clinical information sources.

The TSS is held in place by a flexible wearable carrier adhered to the patient's proximal trachea with commercially available medical grade adhesive. The TSS contains the audio sensor, onboard processing, wireless communications technology, and Lithium-ion coin cell rechargeable battery. A custom charger is provided to charge the battery.

The provided FDA 510(k) clearance letter and summary for the RTM Sense (A-0001) device details several aspects of its performance and validation. However, it does not explicitly provide a table of acceptance criteria for specific metrics, instead focusing on overall "passing" of predefined performance criteria. The information regarding ground truth establishment for the training set, number and qualifications of experts, and adjudication methods is also limited.

Based on the provided text, here's an attempt to reconstruct the information:

Overview of RTM Sense (A-0001) Performance Study

The RTM Sense (A-0001) is a non-invasive respiratory monitoring system that continuously measures a patient's respiratory rate by analyzing tracheal sounds. The device, intended for use by healthcare professionals in healthcare facilities, underwent non-clinical and clinical performance testing to demonstrate its safety and effectiveness and establish substantial equivalence to predicate devices.

1. Acceptance Criteria and Reported Device Performance

While explicit acceptance criteria are not presented in a table format within the document, the "Clinical Performance Testing" section describes primary endpoints that serve as de facto acceptance criteria. The results indicate that the device met these criteria.

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FH Vitals SDK-RR is a software-only respiratory rate measurement tool intended to be integrated into third-party software applications on compatible mobile devices, laptops, or computers. It is intended for spot checking of Respiration Rate (RR) in an automatic contactless manner by analyzing chest wall movement from video input when the subject is still and properly positioned in front of the camera in a well-lit environment.

FH Vitals SDK-RR is intended for use under the supervision of a healthcare professional, either in clinical or home environments, and is not intended for continuous monitoring, apnea detection, or as the sole method for evaluating physical health. It is intended to serve as a supplemental tool to assist in the overall assessment of the patient. The software is indicated for use on individuals aged 18 years and older who do not require critical care or continuous vital sign monitoring.

The FaceHeart Vitals Software Development Kit (FH Vitals SDK-RR) is a software product designed for integration into various software applications, such as those on mobile devices, laptops, or computers. This SDK is strictly a software-only product and is compatible with the following operating systems: Windows 10, Android 14, and iOS 17. It has been tested and is currently only compatible with the following cameras:

• Logitech C930 webcam
• Samsung S24+, S24+ smartphone front-facing cameras
• iPhone 15 Pro, and iPhone 15 Pro Max front-facing cameras

The SDK is non-contact and designed to measure the respiratory rate in breaths per minute based on facial video streams. When the SDK receives a video stream, it first identifies and tracks the face within the video, ensuring consistent positioning of the face. Based on the tracked facial region, the system identifies the chest as the region of interest (RoI) and locates reliable key points. The system then focuses on the movement of the chest within the RoI to further determine the number of respiratory cycles. By analyzing the frequency of chest elevation and depression, the SDK calculates the respiratory rate in breaths per minute.

FH Vitals SDK-RR is designed for non-invasive respiratory rate measurement with a validated measurement range of 5-36 bpm. The SDK is not intended for apnea monitoring or detecting the cessation of breathing. FH Vitals SDK-RR is a prescription-use software device that must be used under the clinical supervision or instruction of a licensed healthcare professional (HCP).

Here's a detailed breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) Clearance Letter and 510(k) Summary.

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: 420 participants
• Data Provenance:
  • Country of Origin: Taiwan (377 subjects) and United States (43 subjects)
  • Retrospective or Prospective: Not explicitly stated as retrospective or prospective, but the description of "evaluation in a clinical study involving 420 participants" generally implies a prospective collection for the purpose of the study.

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

The document does not provide information regarding the number of experts used or their qualifications for establishing the ground truth. It states that the ground truth was established by a "gold standard etCO2 device (manually counted/annotated respiratory rate from analysis of waveform output from the Philips MX100 with Microstream CO2 Extension)." This suggests that human expert annotation may have been involved in the manual counting/annotation, but the specifics are not detailed.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method (such as 2+1, 3+1, none) for the test set. The ground truth was derived from a direct comparison to a gold standard medical device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study's focus was on the standalone performance of the FH Vitals SDK-RR against a gold standard, not on the improvement of human readers with AI assistance.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, a standalone study was done. The entire clinical performance summary describes the FH Vitals SDK-RR (algorithm only) processing video input to measure respiratory rates and comparing these measurements directly against a gold standard device, without human intervention in the measurement process itself.

7. The Type of Ground Truth Used

The ground truth used was a gold standard etCO2 device, specifically the "manually counted/annotated respiratory rate from analysis of waveform output from the Philips MX100 with Microstream CO2 Extension." This is a form of physiological measurement data, potentially with human expert review/annotation of that waveform.

8. The Sample Size for the Training Set

The document does not provide any information about the sample size used for the training set. The descriptions are exclusively for the clinical performance study (test set).

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

The document does not provide any information on how the ground truth for the training set was established, as the training set details are not included.

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VitalSigns Camera Medical Library is a software library that can be integrated into a customer application for use during virtual consults or health screening. It is intended for spot checking of Respiration Rate (RR) in an automatic contactless manner as a data point in the overall assessment of the patient. It is used under the supervision of a health care professional, either in the home or in a clinical environment when the subject is still and positioned properly in front of the camera (Samsung Galaxy A20e), which is placed on a stable surface in an adequately lit environment.
It is intended to be used on patients aged 22 years and older that classify as ASA I (American Society of Anesthesiologists), which is defined as a normal healthy patient, non-smoking and no or minimal alcohol use.
It is not intended for continuous patient monitoring system or as the sole method of checking the physical health of the patient, nor as an apnea monitor, but as a part of a framework which mandates periodic checks by a health care professional to ensure appropriate clinical diagnosis and treatment can be reached.

The Philips VitalSigns Camera Medical Library (hereafter known as Philips VSC-MEDlib) is a software library that shall be used in conjunction with a camera which can be part of another platform or as part of a medical device. The Philips VSC-MEDlib incorporates an algorithm which allow for automatic, contactless measuring of Respiration Rate (RR). Philips VSC-MEDlib utilizes the video stream of an unobstructed view of the subject's torso captured from a camera to calculate the RR from torso motion. The video stream can be captured during a video consult or health screening which should always be conducted in the presence of a physician or other Health Care Professional (HCP). The patient must be properly positioned in front of the camera, sitting still and in an adequately lit environment. From a video stream that typically lasts 60 seconds or less, a spot measurement is taken.

Here's a breakdown of the acceptance criteria and the study proving the device meets those criteria, based on the provided FDA 510(k) clearance letter:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

Note: While the predicate device had an accuracy of ±2 bpm, the Philips VSC-MEDlib's stated primary endpoint (acceptance criterion) for RMSE was ≤ 3 BPM, which it met. This suggests a slightly less stringent accuracy requirement for the new device, but the FDA still deemed it substantially equivalent based on the overall package of evidence.

2. Sample Size and Data Provenance

• Test Set Sample Size: 92 subjects were enrolled in the prospective clinical investigation. VSC-MEDlib provided a RR output for 83 subjects (93.3%).
• Data Provenance: Single center, prospective clinical investigation conducted in the Netherlands. The study explicitly states the subject population was representative of the intended U.S. population and evaluated performance under suboptimal conditions.

3. Number of Experts and Qualifications for Ground Truth

• The document states that the gold standard reference device was manually annotated capnography. It does not specify the number of experts or their qualifications for this manual annotation.

4. Adjudication Method for the Test Set

• The document does not specify an adjudication method for establishing the ground truth. It simply states "manually annotated capnography" was used as the gold standard.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not reported. The study focused on the standalone performance of the device against a gold standard, not on how human readers' performance might improve with AI assistance.

6. Standalone Performance

• Yes, a standalone (algorithm only, without human-in-the-loop performance) study was performed. The clinical investigation directly evaluated the Philips VSC-MEDlib's accuracy in measuring RR against a gold standard reference.

7. Type of Ground Truth Used

• The ground truth used was manually annotated capnography. This is considered a gold standard for respiration rate measurement.

8. Sample Size for the Training Set

• The document does not provide the sample size used for the training set. It only details the clinical investigation used for performance evaluation (test set).

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

• The document does not provide information on how the ground truth was established for the training set. This is a common omission in 510(k) summaries, which tend to focus on the validation/test set performance.

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The Makani Science™ Respiration Monitoring System is indicated for continuous, non-invasive, and real-time monitoring of a patient's breathing. It graphically displays respiration versus time and reports the respiratory rate value.

The Makani Science™ Respiration Monitoring System is intended to be used by healthcare professionals in healthcare facilities and dental offices on adult patients aged 22 or older. It is not intended to be used as an apnea monitor.

The Makani Science™ Respiration Monitoring System (Makani Science RMS) is a respiration rate (RR) monitoring system that consists of a pair of identical, battery-powered, wireless, Makani Science Ahe™ Respiration Sensors (Ahe Sensors - piezo-resistive strain sensors) and the Makani Science Ahe™ App (Ahe App), which is deployed and runs on an Apple® iPad®. The two (2) small and lightweight Ahe Sensors are paired to the Ahe App using Bluetooth Low Energy (BLE) 5.0 technology. The Makani Science RMS is intended to be used by trained healthcare providers (HCPs) in the management of their patients. The Ahe Sensors are single-patient use sensors and can be used up to 24 hours of continuous use. The sensors are applied to the patient's intact skin using an adhesive tape built into the sensors and are made to be retained on the skin in nonambulatory use situations, such as supine on a procedure room table or semi-recumbent in a dental chair. One sensor is applied to the patient's thoracic region and the other sensor is applied to the abdomen region. Correct placement of these sensors is important to the effectiveness of the device, and specific guidance is provided to the user in the labeling on where to place the sensors. The Ahe App is a software application, which guides the user through system setup and monitoring using display screens. During use, the iPad is forced into guided access, or "kiosk" mode, which prevents the user from using any other applications during the monitoring session. Once setup is complete and monitoring initiated, the Ahe App displays a graphical rendition and numerical value of the patient's RR. Low and high RR alarm thresholds provide a visual and audible notification if the patient's RR violates the user-determined alarm thresholds. Monitoring continues until the user terminates the monitoring session, at which time the Ahe App can save a report of the monitoring session to an external memory card, if desired by the user. No patient health information (PHI) is retained by the Ahe App after completion of the monitoring session. The Makani Science RMS does not interact with any third-party medical or non-medical devices other than a memory card that is used to store a report of the patient's monitoring session.

The Makani Science™ Respiration Monitoring System is designed for continuous, non-invasive, and real-time monitoring of a patient's breathing, graphically displaying respiration versus time and reporting the respiratory rate value. It is intended for use by healthcare professionals in healthcare facilities and dental offices on adult patients aged 22 or older.

Acceptance Criteria and Reported Device Performance

Although specific numerical acceptance criteria are not explicitly listed in the provided text, the document states that the device was evaluated against performance requirements, applicable standards, and guidance documents. The key performance metric mentioned is Respiratory Rate (RR) Accuracy.

This reported accuracy is directly compared to the predicate device's accuracy (PMD Solutions / RespiraSense, K220111), which also has an RR Accuracy of ± 3 BPM, indicating that the Makani Science™ RMS meets the established performance benchmark for respiration rate accuracy.

Study Proving Device Meets Acceptance Criteria

A clinical performance study was conducted to validate the respiration rate accuracy of the Makani Science™ Respiration Monitoring System.

1. Sample Size and Data Provenance:

   • Test Set Sample Size: 29 human subjects.
   • Data Provenance: The document does not explicitly state the country of origin, but it is clear the data is from human subjects from the "intended use population," implying a clinical setting. The study appears to be prospective, as it involved actively testing subjects with the device.

2. Experts for Ground Truth Establishment:

   • The document does not detail the number or qualifications of experts used to establish the ground truth beyond stating "manually counted end-tidal CO2." It is implied that healthcare professionals or trained personnel performed the manual counting.

3. Adjudication Method:

   • No adjudication method is described. The ground truth was established by "manually counted end-tidal CO2 using an FDA-cleared capnogram," suggesting a direct, objective measurement rather than subjective interpretation requiring adjudication.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No MRMC comparative effectiveness study was mentioned or performed. The study focused on the device's accuracy against a "gold standard" rather than comparing human reader performance with and without AI assistance.

5. Standalone Performance:

   • Yes, standalone (algorithm only) performance was assessed. The accuracy of the Makani Science™ RMS was validated against a gold standard method, specifically "manually counted end-tidal CO2 using an FDA-cleared capnogram." This evaluates the device's ability to accurately measure respiratory rate independently.

6. Type of Ground Truth Used:

   • "Gold standard, manually counted end-tidal CO2 using an FDA-cleared capnogram." This represents a direct, objective physiological measurement.

7. Training Set Sample Size:

   • The document does not specify the sample size for the training set. The clinical study mentioned is for performance validation, not for training the algorithm.

8. Ground Truth Establishment for Training Set:

   • The document does not explicitly describe how the ground truth for the training set was established. However, given the nature of the device (respiration monitoring), it can be inferred that training data would likely involve various respiration patterns with corresponding accurate respiratory rate measurements, potentially derived from similar gold standard methods as used for the test set.

Additional Performance Testing Details:

The clinical testing also included:

• RR validation in all four available postures (supine, right side, left side, and reclined).
• Sub-group analysis to demonstrate maintained RR accuracy regardless of patient demographics (sex, BMI (healthy, overweight, and obese), Fitzpatrick skin type).
• Accuracy maintained in the presence of comorbidities.
• Accuracy maintained in the presence of artifacts (e.g., coughing).
• Accuracy maintained following positional change (e.g., supine → reclined position).
• Successful demonstration that RR accuracy was maintained over 24 hours of continuous use in bench testing.

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Airmod, when used in conjunction with Accursound Electronic Stethoscope AS-101, is a software as medical device intended to be used for the continuous, non-invasive monitoring of respiratory rate (RR) in adult patients who are subjected to procedural sedation and/or anesthesia.

Airmod is intended for use by healthcare professionals in hospitals and healthcare facilities who are legally credentialed to perform procedural sedation and/or anesthesia.

Airmod is intended for Android-based devices only.

Airmod 114 is an Android-based software application designed to aid healthcare professionals by monitoring a sedated and/or anesthetized patient's breathing in real time. The device has an AIbased algorithm that can detect inhalation acoustics and provides respiratory rates based on the analysis of the acoustic signals of breathing sounds collected by AccurSound Electronic Stethoscope AS-101. Airmodid for the continuous monitoring of respiratory rate (RR) in adults who are subjected to procedural sedation. Airmod™ is designed for use in hospitals and healthcare facilities performing procedural sedation/anesthesia. The device is not intended for patients who are not anesthetized/sedated.

Here's a breakdown of the acceptance criteria and study details for the Airmod device, based on the provided FDA 510(k) summary:

Acceptance Criteria and Device Performance

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Linshom Continuous Predictive Respiratory Monitor System (CPRMS) is indicated for use by healthcare professionals in healthcare facilities, such as procedural areas and recovery rooms, to monitor breathing in adult, (at least 22 years of age) patients.

The CPRMS is a non-invasive system that graphically displays temperature changes against time and reports values of respiratory rate and seconds since last breath, along with a trend of tidal volume.

CPRMS measurements are used as an adjunct to other clinical information sources.

The Linshom CPRMS (Continuous Predictive Respiratory Monitoring System) is portable, reliable and an inexpensive system for precise detection of spontaneous respiration. It is non-invasive and is not corrupted by motion artifacts. The system autonomously adapts to the local thermal environment to deliver a usable signal without complicated hardware and firmware processing.

The provided text details the FDA 510(k) clearance for the Linshom Continuous Predictive Respiratory Monitoring System (CPRMS), demonstrating its substantial equivalence to a predicate device. However, the document does not contain specific acceptance criteria, reported device performance metrics in a table, or details regarding the study designs (sample sizes, data provenance, expert qualifications, ground truth establishment, or clinical study effect sizes) that directly prove the device meets pre-defined quantitative acceptance criteria.

The document primarily focuses on:

• Regulatory Clearance: The FDA's determination of substantial equivalence for the CPRMS to its predicate device (Linshom Respiratory Monitoring Device - LRMD).
• Technological Comparison: A table comparing the characteristics of the subject device (CPRMS) and the predicate device (LRMD), highlighting their similarities.
• Non-Clinical Testing Summary: A general statement about the types of non-clinical tests performed (e.g., Lifetime Test, Movement Test, Respiration Rate Test, Tidal Volume Trend Test) and conformance to various medical device standards. It mentions "Statistical analysis, including correlation methods, showed strong alignment with reference data, indicating that the device functions accurately and reliably within its intended use parameters," but does not provide the specific numerical results of these analyses or the acceptance thresholds.

Therefore, based solely on the provided text, I cannot complete many of the requested sections.

Here's a breakdown of what can be inferred from the text and what cannot:

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

The document mentions specific accuracy for respiration rate and tidal volume trend for both the subject and predicate devices:

Note: These are presented as specifications that are "Same" for both devices, implying the CPRMS met these already established performance levels of the predicate device. The text does not explicitly state them as "acceptance criteria" for a new study, but rather as inherent accuracy specifications of the device's mechanism.

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

• Sample Size for Test Set: Not specified. The document states "The subject device [K240271] underwent testing across the full range of physiological parameters, including respiratory rates from 0-60 breaths per minute (BPM)." This implies a test set was used, but its size or specific characteristics (e.g., number of subjects, number of data points) are not provided.
• Data Provenance: Not specified. It's unclear if the testing was retrospective or prospective, or the country of origin of the data. The testing mentioned appears to be laboratory/non-clinical.

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

• Not specified. The document outlines non-clinical testing focused on device performance against reference data, not human expert interpretation of clinical data for ground truth.

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

• Not applicable/Not specified for this type of non-clinical device performance testing. Adjudication methods are typically used in studies involving human interpretation (e.g., image reading).

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 or human-in-the-loop study is mentioned. The device provides measurements (respiratory rate, seconds since last breath, tidal volume trend) as an adjunct to other clinical information sources, but the text does not describe a study where human readers/clinicians used the device and their performance was evaluated comparatively.

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

• Yes, implicitly. The "Non-Clinical and/or Clinical Tests Summary" describes tests where the device's measurements (respiration rate, tidal volume trend) were compared against "reference data," indicating a standalone evaluation of the algorithm's performance against a known standard.

7. The type of ground truth used

• Reference Data: The document states "Statistical analysis, including correlation methods, showed strong alignment with reference data." This implies that the ground truth was derived from established, accurate measurement methods or simulated physiological parameters (e.g., a ventilator for tidal volume, a controlled breathing simulator for respiration rate). It's not explicitly stated as expert consensus, pathology, or outcomes data.

8. The sample size for the training set

• Not specified. The document mentions "Proprietary Algorithm" for both subject and predicate devices but provides no details on how these algorithms were developed or trained, nor the size of any training datasets.

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

• Not specified. As no training set details are provided, the method for establishing its ground truth is also absent.

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The Respiree Cardio-Respiratory Monitor is a respiratory monitor intended for hospital-type facilities in non-ICU settings. The Respiree Cardio-Respiratory Monitor is indicated for the non-invasive spot checking of respiration rate (RR) for adult patients.

The Respiree Cardio-Respiratory Monitor, Model RS001, is a small respiratory monitor. For measurement of respiration rate (RR), the device is affixed to the chest using a disposable adhesive patch with a hook-and-loop fastener to attach to the monitor. The device uses a vertical-cavity surface-emitting diode to emit optical radiation directed toward the skin. An integrated photodetector in a nearby position senses the diffused collected light. An adaptive signal processing method is used to enhance the device respiratory rate measurements by splitting the signal processing optimizations across different respiratory rate bands.

The monitor is powered by a 3.7V rechargeable, lithium-ion battery and a USB charging cable is provided. The Respiree Cardio-Respiratory Monitor also includes optional Bluetooth wireless technology for the wireless transfer of patient data to mobile devices.

Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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The Hillrom Heart and Respiration Rate Monitoring System powered by EarlySense is used with compatible bed system models and is intended for continuous measurement of respiration rate (RR) in an automatic, contactless manner. The system is indicated for use in children, adolescents, and adults in hospitals or clinical settings. It is intended to be used for the same patient populations and the same settings, within these ranges, as the bed with which it is used. The system has been validated to withstand up to 700 lb (318 kg).

The Hillrom Heart and Respiration Rate Monitoring System powered by EarlySense is designed for continuous and contact-free measurement of heart and respiratory rate (also referred to as Bed Sensing Unit). This device is used with a hospital bed system which is exempt from 510(k) premarket submission requirements. The Bed Sensing Unit (sensor) plugs into the bed frame to both receive power and to transmit data. Data from the System is available on the bed's graphical caregiver interface (GCI)/display unit and can be transmitted through wired and wireless communication channels to Hillrom Connectivity Solution (also known as (aka)- Hillrom Digital Health Gateway) for display, use, and storage. Additionally, the System can transmit alerts via Bloetooth to an existing hardwired Nurse Call system, speakers, and/or on/off alert lights within a bed system. The healthcare professional can adjust monitoring parameters by interacting with the bed's GCI. These parameters include hospital-defined alert thresholds, display settings, and alert configurations. The system provides alerts when patient heart rate and/or respiratory rate are recorded that are above or below the predefined thresholds.

The Hillrom Heart and Respiration Rate Monitoring System powered by EarlySense consists of:

• . The Bed Sensing Unit, placed on a bed frame under the mattress
  • This is functionally identical to the sensor cleared in K202018 -
• Software for data analysis, display, and input ●
  • The software for data analysis is identical to that cleared in K202018 -
  • The software for display and input is identical to the software cleared in -K202018
• The device hardware, specifically the connection between the sensor and • appropriate bed system
  • The hardware for the device is identical to that cleared in K202018 -
  • The Heart and Respiration Rate Monitoring System also uses certain hardware, such as the graphical caregiver interface and wireless communication module, of an appropriate bed system
• Hillrom Connectivity Solution (aka Hillrom Digital Health Gateway) .
  • The Hillrom Digital Health Gateway consists of gateways that make information about the bed and patient available to 3rd party applications. This is functionally identical to that cleared in K202018.

The provided text focuses on the substantial equivalence of the Hillrom Heart and Respiration Rate Monitoring System powered by EarlySense to a predicate device, K202018. It does not contain a dedicated study section detailing acceptance criteria for the device itself or a study proving those criteria are met.

However, the "Comparison of Subject to Predicate: Technology and Specifications" table (Table 2) lists certain performance characteristics identified as "Accuracy" for Heart Rate and Respiratory Rate, which can be interpreted as acceptance criteria based on the predicate device's established performance.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Based on the comparison table (Table 2), the "Accuracy" values for the subject device are stated to be the same as the predicate device. Therefore, we can infer the acceptance criteria for these specific metrics by looking at the predicate's reported performance.

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

The document does not provide specific details on the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective) for the accuracy testing of the subject device. It states, "Extensive testing has been conducted on the finished Hillrom Heart and Respiration Rate Monitoring System powered by EarlySense and demonstrates that the System is as safe and as effective as the predicate device." However, no specifics about these "extensive tests" are provided beyond non-clinical tests like EMC, Software V&V, Cybersecurity, and Coexistence testing.

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

The document does not provide information on the number or qualifications of experts used to establish ground truth for the performance metrics listed. It does not describe how the ground truth for the accuracy measurements (Heart Rate and Respiratory Rate) was established.

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

The document does not describe any adjudication method used for establishing ground truth or evaluating the test set performance.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. This device is a monitoring system and does not typically involve human "readers" or an AI component that assists in interpreting medical images or complex data in a way that would be assessed by MRMC.

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

The entire description of the device focuses on its standalone performance in continuously measuring heart and respiration rates. The accuracy values provided are for the system itself. Therefore, it can be inferred that standalone performance testing was done for the algorithm. However, no specific study details are provided, only that the reported accuracy performance (same as predicate) was met.

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

The document does not explicitly state the type of ground truth used for measuring the Heart Rate and Respiratory Rate accuracy. Given the nature of vital sign monitoring, the ground truth would typically be established by simultaneously recorded, highly accurate reference devices (e.g., ECG for heart rate, capnography or direct spirometry for respiration rate) in a controlled environment, rather than expert consensus, pathology, or outcomes data in the usual sense.

8. The sample size for the training set

The document describes the device as being "powered by EarlySense" and states that "The software for data analysis is identical to that cleared in K202018." This suggests the core algorithms and models were developed and potentially trained earlier as part of the predicate device's development. However, the document does not provide information on the sample size used for the training set.

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

Similar to point 8, the document states the software and analysis algorithms developed by EarlySense are identical to the predicate device. There is no information provided within this document about how the ground truth for any potential training set for these algorithms was established.

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