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The Zio monitor is a prescription-only, single-use, ECG monitor that continuously records data for up to 14 days. It is indicated for use on patients, 18 years and older, who may be asymptomatic or who may suffer from transient symptoms such as palpitations, shortness of breath, dizziness, lightheadedness, pre-syncope, syncope, fatigue, or anxiety.

The Zio monitor is a non-sterile, single-use, continuously recording, long-term ambulatory ECG monitor that is adhered to a patient's left pectoral region in a modified Lead II orientation. The goal of the Zio monitor is to help physicians initiate long-term, patient-compliant ECG monitoring utilizing proprietary technology. The Zio monitor is applied and activated by the patient at home or at a clinic. Once activated, the device provides continuous, uninterrupted ECG recording into memory with minimal patient interaction. There is a button on the surface of the Zio monitor, which serves to activate the device and may be pressed by the patient during wear to indicate when he or she is experiencing a symptom. Additionally, there is a surface LED light that blinks green to confirm proper activation or that the device is working, and orange to indicate loss of connection with the skin or the presence of error conditions.

The Zio monitor utilizes firmware that captures single-channel ECG data into memory, there is no wireless transmission of data during the wear period of the device. After the prescribed monitoring period is complete, the Zio monitor is returned to iRhythm where the ECG data is then analyzed and annotated by the ZEUS System (K222389). ECG data is then presented to the Qualified Cardiac Technicians (QCT) at the Independent Diagnostic Testing Facility (IDTF) for review and subsequent creation and posting of the end-of-wear report with preliminary findings. Zio monitor device is not intended for real-time patient monitoring.

The provided text is an FDA 510(k) clearance letter and summary for the Zio® monitor. It details the device, its indications for use, comparison to a predicate device, and nonclinical testing performed to establish substantial equivalence. However, it explicitly states:

"No clinical testing was performed in support of this premarket notification."

Therefore, I cannot provide a table of acceptance criteria and reported device performance based on a clinical study, nor specific details about sample size, data provenance, ground truth establishment, expert qualifications, or MRMC studies, as these aspects relate to clinical testing which was not conducted for this submission.

Here's what I can extract and state based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance:

Based on the provided document, the acceptance criteria and device performance are established through nonclinical testing, demonstrating conformance to recognized standards and performance specifications, rather than through a clinical study with specific performance metrics like sensitivity or specificity for detecting arrhythmias.

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

• Sample Size for Test Set: Not applicable as no clinical testing was performed. The nonclinical testing would have used various test samples, components, or simulated data as appropriate for each specific engineering and performance test (e.g., system testing, electrical testing).
• Data Provenance: Not applicable for clinical data. For nonclinical testing, the data is generated in-house or by accredited testing laboratories as part of the device's design verification and validation.

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

• Not applicable as no clinical testing with human-established ground truth was reported. Ground truth in nonclinical testing refers to established engineering specifications or reference standards.

4. Adjudication method for the test set:

• Not applicable as no clinical testing requiring expert adjudication was performed.

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 comparative effectiveness study was done as no clinical testing was performed. The device, Zio monitor, is described as recording ECG data which is then "analyzed and annotated by the ZEUS System (K222389)" and "presented to the Qualified Cardiac Technicians (QCT) at the Independent Diagnostic Testing Facility (IDTF) for review." This implies an existing workflow with a human-in-the-loop, but this submission specifically states no clinical testing was performed to evaluate its effectiveness in combination with human readers.

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

• The document implies that the "ZEUS System (K222389)" performs initial analysis and annotation of the ECG data, but this specific 510(k) is for the Zio® monitor hardware device. Performance data for the ZEUS System itself would be found in its own 510(k) clearance (K222389). This submission does not provide standalone algorithm performance metrics.

7. The type of ground truth used:

• For the nonclinical testing, the ground truth would be based on:
  • Engineering Specifications: Device design requirements and intended performance.
  • Recognized Consensus Standards: Compliance with international standards (e.g., IEC 60601 series, ISO 10993 series).
  • Internal Product Specifications: How the device is designed to function and its measurable outputs.

8. The sample size for the training set:

• Not applicable. This submission is for a hardware device and relies on nonclinical testing for substantial equivalence, not a machine learning model's training set. While the ZEUS System (K222389) likely uses a training set, details for that system are outside the scope of this document.

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

• Not applicable as no training set for an algorithm is discussed in this submission for the Zio® monitor hardware.

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The VSH101 is designed to record, transmit, and store single channel electrocardiogram (ECG) data via Bluetooth communication to compatible Bluetooth enabled devices. The device is intended for use by healthcare professionals, individuals with known or suspected cardiac conditions, and health-conscious users. The ECG data serves as a supplementary source of patient information and is not intended for automated analysis.

VitalSigns 1-Lead Holter is an ambulatory and Bluetooth-based wireless communication ECG measurement solution designed to allow users to record, store, transmit, and display single-channel ECG data.

VitalSigns 1-Lead Holter consists of the following three components:

1. VS Electrode Patch "VSP101"
2. ECG Recorder Host "VSH101"
3. iOS APP "VSHealth"

When the ECG Recorder Host "VSH101" is fully charged and connected wirelessly via Bluetooth to the iOS app "VSHealth", it can instantly obtain the user's ECG data. VSHealth assists in transmitting, displaying, recording, and storing ECG data.

After the "VSH101" is fully charged, the device, through the VSHealth app, allows users to continuously use and record ECG data for 24 hours in their daily routines, whether at home or in a work environment.

The provided FDA 510(k) clearance letter and summary for the VitalSigns 1-Lead Holter (VSH101) primarily focus on demonstrating substantial equivalence to a predicate device through comparison of features and adherence to various safety and performance standards. However, it does not include explicit acceptance criteria tables or detailed study results for specific device performance metrics that would be typically found in a clinical or performance validation report.

The document states that "software validation, performance test and usability test have been completed to demonstrate that the differences between these parameters would not impact the safety and effectiveness of the subject device. The subject device has also undergone all safety and performance tests, and the results complied with the test requirements." It also mentions "Performance testing - IEC 60601-2-47 test" and "Disposable ECG electrode test."

Given the information provided in the 510(k) summary, I will infer the acceptance criteria based on the mentioned compliance standards and the general nature of an ECG Holter device, and then describe what is stated about the testing.

Inferred Acceptance Criteria and Reported Device Performance

The 510(k) summary for the VitalSigns 1-Lead Holter (VSH101) does not provide a specific table of acceptance criteria with corresponding performance metrics. Instead, it relies on demonstrating compliance with relevant international standards and equivalence to a predicate device. Based on the mentioned standards (e.g., IEC 60601-2-47 for ambulatory ECG recorders, ANSI/AAMI EC12 for disposable ECG electrodes), the general acceptance criteria for such a device would relate to the accuracy, signal quality, and reliability of ECG signal acquisition.

Here's a table based on the inferred acceptance criteria from the context of ECG device standards and the information stated in the document:

Study Proving Device Meets Acceptance Criteria

The provided 510(k) summary describes that comprehensive testing was conducted, primarily focusing on compliance with recognized consensus standards and demonstrating substantial equivalence to a predicate device, rather than a single large-scale clinical/performance study with detailed outcome metrics.

Here's an analysis based on the information provided:

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

   • As detailed above, a direct table is not provided in the 510(k) summary. The acceptance criteria are inferred from the listed compliance standards (e.g., IEC 60601-2-47, ANSI/AAMI EC12). The reported performance is generally stated as "complied with the test requirements," "met its pre-defined criteria," or "confirmed compliance."

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

   • Sample Size: Not explicitly stated for performance testing. For compliance with standards like IEC 60601-2-47 or ANSI/AAMI EC12, testing typically involves a sufficient number of device units or electrodes to statistically demonstrate compliance with the standard's requirements (e.g., a batch of electrodes, multiple device samples). The document does not specify if patient data was used for performance testing beyond what is implied by the "24 hours" recording capability.
   • Data Provenance (Country of Origin, Retrospective/Prospective): Not specified. Standard compliance testing is typically done in a lab setting rather than involving patient data in a "retrospective" or "prospective" clinical study design for 510(k) submissions unless a specific clinical performance claim needs to be proven. The focus here is on engineering verification and validation against standards.

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

   • This information is not provided in the 510(k) summary. The nature of the testing described (compliance with standards like IEC 60601-2-47 for signal quality, ANSI/AAMI EC12 for electrodes, and general electrical safety) suggests controlled laboratory testing and engineering validation, which typically does not involve human expert adjudication of ECG readings as a "ground truth" for device performance in this context. The device's indication for use explicitly states, "The ECG data serves as a supplementary source of patient information and is not intended for automated analysis," implying that human interpretation remains key. Therefore, ground truth establishment by experts for automated analysis is not applicable.

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

   • None is explicitly described. Based on the content, there was no clinical study described that would require a ground truth panel or adjudication method for ECG event interpretation. The testing focuses on technical performance compliance.

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 done or described. The device is a "1-Lead Holter" that records ECG data; it does not perform "automated analysis" or include AI assistance. Its purpose is to provide raw ECG data for supplementation of patient information, not for diagnostic interpretation by an algorithm. Therefore, an MRMC study assessing AI assistance is not relevant to this device's claims or function.

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

   • Based on the indication for use, "The ECG data serves as a supplementary source of patient information and is not intended for automated analysis," there is no algorithm for diagnostic interpretation. Therefore, no standalone algorithm performance study was done or described.

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

   • As noted above, for the type of device and the presented summary, complex ground truth derived from expert consensus, pathology, or outcomes data is not applicable for the performance testing described. The "ground truth" for compliance testing is largely defined by the technical specifications and requirements within the IEC/AAMI standards themselves (e.g., known input signals for signal quality, chemical assays for biocompatibility).

8. The sample size for the training set:

   • Not applicable / Not provided. The device records raw ECG data and does not perform automated analysis using a trained algorithm. Therefore, no "training set" for AI/ML model development is mentioned or required for this type of device based on its intended use.

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

   • Not applicable. As there is no AI/ML model for automated analysis that requires a training set, the establishment of ground truth for such a set is not discussed.

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The Frontier X Plus device is an ambulatory monitoring device intended to record, store, and transfer single-channel (ECG) rhythms for monitoring and evaluation. The Frontier X Plus system also displays ECG waveforms and ECG rhythm analysis; detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, tachycardia, inconclusive and unreadable rhythm. The Frontier X Plus is intended for use by healthcare professionals, patients with known or suspected heart conditions and health-conscious individuals. It is indicated for use on adult patients who may be asymptomatic or who may suffer from transient symptoms requiring cardiac monitoring. The device has not been tested for pediatric use. The Frontier X Plus is a prescription-only device, and the reported information is provided for review by a physician who will render a diagnosis based on clinical judgment and experience.

The Frontier X Plus is an ECG (electrocardiogram) event recorder that records, stores and transfers single-channel electrocardiogram rhythms. The device utilizes a proprietary algorithm, to analyze single-channel ECG. The Frontier X Plus hardware transmits the ECG signal from a dry electrode array embedded in the Frontier X Plus chest strap to the embedded Frontier X Plus firmware, integrated with the HeartKey ECG algorithm to be analyzed and presented to the user. All ECGs are synced with the user's account.

The provided document describes the FDA 510(k) premarket notification for the Frontier X Plus device. It does not contain a specific table of acceptance criteria with reported device performance results, nor does it detail a multi-reader, multi-case (MRMC) comparative effectiveness study or provide effect sizes for human readers with AI assistance.

However, based on the Clinical Testing Summary section on pages 10-11, we can infer information about the study design that proves the device meets certain performance criteria.

Here's an attempt to structure the available information per your request:

Acceptance Criteria and Device Performance Study

The document doesn't explicitly state "acceptance criteria" in a quantitative table format. Instead, it describes a clinical investigation designed to demonstrate "substantial equivalence" to a predicate device, focusing on the ability of the device's algorithm to accurately detect and classify ECG rhythms.

Inferred Acceptance Criteria & Reported Device Performance (Qualitative)

Study Details:

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

   • Test Set Sample Size: A total of 832 users were included in the Study population for the clinical investigation.
   • Data Provenance: The document does not specify the country of origin for the data. It seems to be a prospective study as it describes the conduct of a clinical investigation where ECGs "were collected and analyzed at various time points."

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

   • The document implies that the ground truth for the rhythm analysis (Atrial Fibrillation, Normal Sinus Rhythm, Tachycardia, Inconclusive, noisy/unreadable signals) was established by comparison to a "standard 12-lead ECG device."
   • It also states that the "reported information is provided for review by a physician who will render a diagnosis based on clinical judgment and experience." This suggests that physicians (likely cardiologists or electrophysiologists) were the experts, but the number of experts and their specific qualifications (e.g., years of experience) are not explicitly stated for ground truth establishment within the study.

3. Adjudication Method for the Test Set:

   • The document does not describe a specific adjudication method (e.g., 2+1, 3+1) for the test set. It suggests that the 12-lead ECG served as the reference standard.

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:

   • No, a MRMC comparative effectiveness study was not explicitly described or summarized in this document. The study focused on the device's (algorithm's) performance against a reference standard, not on how human readers' performance might improve with the device's assistance.

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

   • Yes, a standalone performance evaluation of the algorithm appears to have been a primary component of the clinical investigation. The study "evaluated the reliability of the Frontier X Plus ECG rhythm analysis software algorithm by assessing its ability to detect and classify Atrial fibrillation, Normal Sinus Rhythm, Tachycardia, Inconclusive and noisy/unreadable signals, from all the ECG recordings obtained on the subject device, when compared to simultaneously acquired signals from a standard 12-lead ECG device." This describes the algorithm's performance independent of human readers.

6. The Type of Ground Truth Used:

   • The primary ground truth used was simultaneously acquired signals from a standard 12-lead ECG device. This can be considered a form of clinical standard/reference data. The document also mentions that a "physician who will render a diagnosis based on clinical judgment and experience" reviews the reported information, implying physician interpretation as a ground truth for final diagnosis.

7. The Sample Size for the Training Set:

   • The document does not provide information on the sample size used for the training set of the algorithm. It only discusses the clinical investigation/test set.

8. How the Ground Truth for the Training Set Was Established:

   • The document does not provide information on how the ground truth for the training set was established, as it focuses on the validation study and not the algorithm development process.

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The Zio AT device is intended to capture and transmit symptomatic and asymptomatic cardiac events and record continuous electrocardiogram (ECG) data for long-term monitoring. It is indicated for use on patients 18 years or older who may be asymptomatic or who may suffer from transient symptoms such as palpitations, shortness of breath, dizziness, light-headedness, pre-syncope, syncope, fatigue, or anxiety. It is not intended for use on critical care patients.

The Zio AT® Electrocardiogram (ECG) Monitoring System is intended for continuous, long-term monitoring of a patient's ECG data with the ability to provide symptomatic and asymptomatic transmissions of potential arrhythmias during wear time. The Zio AT ECG Monitoring System enables ambulatory Mobile Cardiac Telemetry (MCT) services for non-critical care patients by providing the following devices for use. The Zio AT device consists of the Zio AT patch and Zio AT wireless gateway. The Zio AT patch is a single-use ECG monitor applied to the patient's chest, in-clinic or at home, and worn for up to 14 days without any required patient interaction for maintenance, such as replacing or charging a battery. The patch continuously records ECG data and transmits symptomatic and asymptomatic cardiac events through the Zio AT wireless gateway during the wear period. After the wear period concludes, the patient removes and returns the patch to the monitoring center, an Independent Diagnostic Testing Facility (IDTF), for analysis and end-of-wear reporting. The Zio AT wireless gateway securely receives ECG data from the Zio AT patch using Bluetooth technology. The gateway securely transmits ECG data through cellular technology for subsequent processing. The Zio AT device is designed to be used with the interoperable Zio ECG Utilization Service (ZEUS) SaMD which provides an arrhythmia detection algorithm for analysis and reporting.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Zio AT device, organized as requested:

Device: Zio AT® device (A100A1001)

This premarket notification (K240177) is for an updated version of an already cleared device (Zio® AT ECG Monitoring Device [K240029]). Therefore, the submission primarily focuses on demonstrating substantial equivalence to the predicate device through non-clinical testing rather than presenting new clinical study data with detailed acceptance criteria and performance metrics for the device's diagnostic capabilities. The document explicitly states: "No clinical testing was performed in support of this premarket notification."

As such, many of the requested details related to clinical performance, such as detailed acceptance criteria tables, sample sizes for test sets, expert qualifications, and MRMC studies, are not available in this 510(k) summary. The acceptance criteria described here pertain to safety and engineering standards, not clinical accuracy for arrhythmia detection.

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

Since this is a 510(k) for substantial equivalence based on non-clinical testing for an updated device, the "acceptance criteria" are predominantly for engineering and safety standards, and the "reported performance" is that the device conforms to these standards.

Regarding the study that proves the device meets the acceptance criteria:

The study referenced is a comprehensive set of nonclinical performance testing. The document states: "All necessary performance testing was conducted on the Zio AT device to ensure performance as intended per specifications and to support a determination of substantial equivalence to the predicate device."

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

• Sample Size for Test Set: Not applicable/not provided for clinical performance. The nonclinical testing involves evaluating the physical device and its software against engineering standards. The sample size would refer to the number of devices or components tested to ensure compliance with specific technical standards (e.g., a certain number of units for electrical safety testing, material samples for biocompatibility), but specific quantities are not detailed in this summary.
• Data Provenance: Not applicable, as this is nonclinical (engineering/safety) testing.

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

Not applicable, as this document focuses on nonclinical testing and substantial equivalence, not clinical diagnostic performance requiring expert interpretation as ground truth.

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

Not applicable, as this document focuses on nonclinical testing, not clinical performance where adjudication of "ground truth" labels would be necessary.

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 comparative effectiveness study was done or reported in this 510(k) summary. This submission explicitly states "No clinical testing was performed in support of this premarket notification." The Zio AT device uses an arrhythmia detection algorithm (provided by the interoperable ZEUS SaMD), but the evaluation here is for the physical device's safety and engineering, not the diagnostic performance of the AI component.

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

This document does not provide details on standalone algorithm performance. The "Zio AT device is designed to be used with the interoperable Zio ECG Utilization Service (ZEUS) SaMD which provides an arrhythmia detection algorithm for analysis and reporting." While an algorithm exists, its performance is not detailed or assessed in this specific 510(k) submission as the focus is on the physical hardware's substantial equivalence to a predicate. Evaluations of the ZEUS SaMD's algorithm (which likely includes standalone performance) would have been part of previous submissions for that software.

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

For the nonclinical testing described, the "ground truth" would be the defined standards and specifications (e.g., a device passes the electrical safety test if it meets the voltage and current limits specified in IEC 60601-1). This is not clinical ground truth.

8. The sample size for the training set

Not applicable/not provided. This submission does not discuss the training of any AI algorithm, as it's a 510(k) for an updated physical device and primarily addresses nonclinical performance and substantial equivalence based on engineering and safety standards.

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

Not applicable/not provided for the same reasons as #8.

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The Zio AT device is intended to capture and transmit symptomatic and asymptomatic cardiac events and record continuous electrocardiogram (ECG) data for long-term monitoring. It is indicated for use on patients 18 years or older who may be asymptomatic or who may suffer from transient symptoms such as palpitations, shortness of breath, dizziness, light-headedness, pre-syncope, syncope, fatigue, or anxiety. It is not intended for use on critical care patients.

The Zio AT® Electrocardiogram (ECG) Monitoring System is intended for continuous, long-term monitoring of a patient's ECG data with the ability to provide symptomatic and asymptomatic transmissions of potential arrhythmias during wear time. The Zio AT ECG Monitoring System enables ambulatory Mobile Cardiac Telemetry (MCT) services for non-critical care patients by providing the following devices for use. The Zio AT device consists of the Zio AT patch and Zio AT wireless gateway. The Zio AT patch is a single-use ECG monitor applied to the patient's chest, in-clinic or at home, and worn for up to 14 days without any required patient interaction for maintenance, such as replacing or charging a battery. The patch continuously records ECG data and transmits symptomatic and asymptomatic cardiac events through the Zio AT wireless gateway during the wear period. After the wear period concludes, the patient removes and returns the patch to the monitoring center, an Independent Diagnostic Testing Facility (IDTF), for analysis and end-of-wear reporting. The Zio AT wireless gateway securely receives ECG data from the Zio AT patch using Bluetooth technology. The gateway securely transmits ECG data through cellular technology for subsequent processing.

The provided document, a 510(k) Summary for the Zio AT® device (K240029), states that no clinical testing was performed in support of this premarket notification. The submission relies solely on nonclinical testing to demonstrate substantial equivalence to the predicate device (Zio® AT ECG Monitoring Device [K163512]).

Therefore, based on the provided text, I cannot provide details regarding acceptance criteria, reported device performance, sample sizes for test sets, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, or standalone performance that would typically be associated with clinical studies.

The document indicates that the device's acceptance criteria were based on its conformance to established performance specifications and FDA-recognized consensus standards. The study that proves the device meets these acceptance criteria is the nonclinical testing described.

Here's an overview of the information available:

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

The document does not provide a specific table of quantitative acceptance criteria and reported device performance metrics in the format typically seen with clinical study results (e.g., sensitivity, specificity, accuracy for arrhythmia detection). Instead, it states that "All necessary performance testing was conducted on the Zio AT device to ensure performance as intended per specifications and to support a determination of substantial equivalence to the predicate device."

The acceptance criteria implicitly relate to the successful completion of the following nonclinical tests and their conformance to specified standards:

• System performance testing: This would ensure the device functions as designed in various operational aspects.
• Biocompatibility testing: This confirms the materials used in the device are safe for contact with the human body.
• Firmware verification testing: This validates the software operating the device.
• Electrical safety and EMC testing: This ensures the device is electrically safe and does not interfere with other electronic devices, and vice versa.

The reported device performance, in this context, is that the device "meets the requirements of established conformance standards and performance specifications necessary for its intended use."

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

Not applicable, as no clinical testing was performed. The nonclinical testing would use various test samples and equipment as dictated by the specific standards and internal protocols, but these are not disclosed in terms of number or provenance in the provided summary.

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

Not applicable, as no clinical testing with expert ground truth establishment was performed.

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

Not applicable, as no clinical testing requiring adjudication was performed.

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, as no clinical testing or MRMC study was performed. The Zio AT device itself functions as a monitoring and transmission system, not an AI-powered diagnostic aid that assists human readers in real-time interpretation.

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

The device is described as "intended to capture and transmit symptomatic and asymptomatic cardiac events and record continuous electrocardiogram (ECG) data." While it transmits events, the overall system for diagnosis involves a monitoring center for analysis and end-of-wear reporting, which would typically involve human oversight. The provided text does not suggest a standalone algorithm-only diagnostic performance evaluation in a clinical setting. The nonclinical testing focused on the device's functional performance and compliance with relevant standards.

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

Not applicable, as no clinical testing that would require such ground truth for diagnostic accuracy was performed. For nonclinical tests, the "ground truth" would be the specified parameters and expected outputs defined by the relevant engineering and safety standards.

8. The sample size for the training set

Not applicable, as no clinical testing or development of an AI algorithm based clinical data was detailed as part of this submission for demonstrating substantial equivalence. The device is an updated version of a previously cleared device, focusing on hardware and firmware changes.

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

Not applicable for the same reasons as #8.

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CareConsole is intended to be used in conjunction with biometric health care measuring devices, mobile applications, and questionnaires to collect and store data, and for clinician-scheduled monitoring at home and/or in medical facilities. The CareConsole platform securely sends data from a patient monitoring device to a central electronic log of patient information, from which notifications, alerts, and reports can be generated and data can be securely viewed by healthcare professionals, authorized caregivers, and patients. Clinicians would then determine how and when to best treat their patients in response to the notifications, alerts, and biometric data. For use by individuals 12 years and older who do not have an emergency health care condition.

· Data can be sent via intranet networks, the internet, landline telephones, and other mobile devices.

· The software supports communication between patients and clinicians, caregivers, or researchers, such as through bidirectional audio and video e-visits, telephone calls, and mobile text messages.

CareConsole is intended for use in capturing remote patient monitoring data from non-invasive remote monitoring devices and to provide remote hospital-at-home level of care where determined necessary by a health care professional. CareConsole is not intended for use in emergency situations or by a patient in an acute care medical facility.

The CareConsole ("CareConsole") is a software only device. CareConsole enables clinicians and patients to conduct bidirectional audio-video conversations and collects patient-reported outcomes and self-care activities via assessment questionnaires. Biometric measurements, using third party devices, can be taken by the patient while being observed over videoconference by a clinician who is located remotely, or measurements can be made by the patient at any time, without being observed by a clinicians can also use CareConsole to exchange messages with patients by text or telephone.

The system is indicated when health professionals wish to directly interact with patients via video, voice and/or text, and/or view reports of medical parameters collected from patients with non-acute conditions using remote biometric measuring devices and questionnaires. The AMC system is not intended for use in emergency situations.

The provided text describes the regulatory clearance of the AMC Health CareConsole, a software-only device for remote patient monitoring. However, it does not contain specific details about acceptance criteria, the methodology of a study proving the device meets those criteria, or performance metrics from such a study.

The document mainly focuses on:

• Regulatory information: FDA clearance, regulation numbers, product codes, and general controls.
• Device description and intended use: How CareConsole functions (collects, stores, and transmits biometric data, facilitates communication) and its target users (individuals 12+, not for emergency situations).
• Predicate devices comparison: It asserts the substantial equivalence of the CareConsole to its predicate devices in terms of intended use and technological specifications, mainly through a comparison table.
• Compatibility with third-party devices: A list of integrated biometric devices.
• General statement on performance: Mentions that "validation and verification testing were performed under the company's Design Control Process" and "The testing has confirmed the device's conformity with specifications."

Therefore, based only on the provided text, I cannot complete the requested information about acceptance criteria and detailed study results. The document states that performance validation was done to meet regulatory requirements but does not provide the specifics of that validation.

Here's what I can extract or infer, and what is explicitly missing:

1. Table of Acceptance Criteria and Reported Device Performance

Missing: Specific quantitative acceptance criteria or performance metrics (e.g., accuracy percentages, latency times, success rates for data transmission, etc.). The document states that testing confirmed conformity but doesn't provide the results of that conformity testing.

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

• Missing: No information on specific sample sizes for any test sets.
• Data Provenance: Not specified (e.g., country of origin). The document implies the data is gathered remotely from patients using the system. It states "The CareConsole platform securely sends data from a patient monitoring device to a central electronic log of patient information." and lists various third-party devices, suggesting data would come from these sources. It's unclear if a specific "test set" with a defined provenance was used for a formal clinical performance study, or if "testing" refers to internal software validation.
• Retrospective/Prospective: Not specified.

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

• Missing: The document does not describe a study involving expert readers/evaluators for establishing ground truth, as it is a data aggregation and communication platform, not an AI diagnostic imaging device. The "ground truth" here would relate to the successful and accurate transfer, storage, and display of biometric data. The closest mention of experts is "Clinicians," "healthcare professionals," and "authorized caregivers" who view the data.

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

• Missing: Not applicable or not described, as the device is not an imaging AI requiring multiple reader adjudication.

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:

• Missing: Not applicable. The CareConsole is a data management and communication system, not an AI-assisted diagnostic tool for human readers. No MRMC study is mentioned or implied.

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

• Partially Addressed/Inferred: The device is "software only." Its primary function is automated data collection, transmission, storage, and presentation. Thus, its core performance is "standalone" in terms of these automated processes. The "human-in-the-loop" aspect comes in with clinicians viewing the data and interacting with patients, but the device's fundamental data handling is algorithmic. However, there are no specific standalone performance metrics provided (e.g., "algorithm achieved X% accuracy in data transmission"). The document states the "testing has confirmed the device's conformity with specifications."

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

• Inferred: For a device like CareConsole, the "ground truth" would likely be the accuracy and integrity of the data captured from the third-party devices, its faithful transmission, secure storage, and correct display. This would typically be verified against the direct output of the connected biometric device or a known, verified standard. There's no mention of expert consensus, pathology, or outcomes data being used to establish ground truth for the device's technical performance.

8. The sample size for the training set:

• Missing: No information provided about a training set, as this is a traditional software system, not described as a machine learning/AI model that typically requires a distinct training set. The "testing" mentioned refers to software verification and validation.

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

• Missing: Not applicable, as no training set for an AI model is described.

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The RhythmStar system is intended for use by patients who either have or are at risk of having cardiac disease and those that demonstrate intermittent symptoms indicative of cardiac disease and require cardiac monitoring on a continuing basis. The device continuously records ECG and upon detection by an ECG analysis algorithm or manually initiated by the patient, automatically delivers all recorded cardiac activity to the cloud server where it is presented and can be retrospectively reviewed by a medical professional at a monitoring center. The RhythmStar system is not intended for real-time monitoring.

The data received from the RhythmStar device can be used for retrospective review, arrhythmia analysis, and further evaluation, reporting and signal measurements using RhythmStar system or a compatible arrhythmia analysis software that has been FDA cleared for Lead II analysis using nontraditional wet electrode placement. The RhythmStar system is not intended to sound any alarms.

The device does not deliver any therapy, administer any drugs, or provide for life support. The RhythmStar system does not provide interpretive or diagnostic statements. Interpretation and diagnosis are the responsibility of a physician. RhythmStar is for prescription use only.

The RhythmStar system consists of the RhythmStar device and the server. The RhythmStar device is a portable, battery-powered, wireless cardiac monitor which may be worn by a patient to record ECG and activity level data for up to 30 consecutive days. The device can capture patient activated and autotriggered events such as Bradycardia, Tachycardia, and Atrial Fibrillation as identified by an embedded arrhythmia detection algorithm. The device is capable of automatically delivering the collected ECG data to the server using a built-in 4G LTE wireless data modem, or the data can be transferred from the device using a USB connection. The data transmitted by the RhythmStar device can be stored, evaluated, and presented for review, analysis and reporting by a medical professional using a server, such as the RhvthmStar Svstem server.

The provided document, an FDA 510(k) summary for the RhythmStar System (K233584), describes the device and its indications for use, but it does not contain a detailed study proving the device meets specific acceptance criteria with reported device performance metrics.

The document primarily focuses on demonstrating substantial equivalence to predicate devices (RhythmStar System K141813 and Zio AT ECG Monitoring System K163512) by comparing intended use, indications for use, and technological characteristics. While it mentions various types of testing performed (Biocompatibility, Electrical Safety, EMC, Software V&V, Performance Testing, Cybersecurity), it does not present the acceptance criteria for these tests or the quantitative results of the device's performance against those criteria.

Specifically, the following information, crucial for addressing your request, is not available in the provided text:

• A table of acceptance criteria and reported device performance: This is the most significant missing piece. The document states that performance testing was done in accordance with ANSI/AAMI EC57 and that bench testing confirmed certain functionalities, but it does not quantify the performance (e.g., sensitivity, specificity, accuracy for arrhythmia detection) or list the specific target acceptance values.
• Sample size used for the test set and data provenance: No information on the actual test dataset size, age group, or whether the data was retrospective or prospective.
• Number of experts used to establish ground truth and their qualifications: Not mentioned.
• Adjudication method for the test set: Not mentioned.
• Multi-reader multi-case (MRMC) comparative effectiveness study: Not mentioned. The device's primary function is to record and transmit data for retrospective review by a medical professional; it is not presented as an AI-assisted diagnostic tool for human readers itself.
• Standalone (algorithm only) performance: While an embedded arrhythmia detection algorithm is mentioned, its standalone performance metrics (e.g., accuracy for AFib detection) are not provided. The document states: "The RhythmStar system does not provide interpretive or diagnostic statements. Interpretation and diagnosis are the responsibility of a physician." This suggests the algorithm's output is raw data or simple event flags, not a diagnostic interpretation.
• Type of ground truth used: Not specified, as no detailed performance study results are provided.
• Sample size for the training set: Not mentioned.
• How the ground truth for the training set was established: Not mentioned.

Conclusion based on the provided text:

The document serves as a 510(k) summary, demonstrating the substantial equivalence of the RhythmStar System to existing legally marketed devices, primarily the RhythmStar RS-10002 (K141813). It asserts that the device is safe and effective based on various conformance tests to recognized standards (IEC, ANSI/AAMI, ISO) and bench testing, but it does not disclose the specific quantitative acceptance criteria or the numerical performance results that would fulfill your request for detailed proof of meeting acceptance criteria for its core functions (like arrhythmia detection accuracy).

To obtain the information you requested about device performance against acceptance criteria, one would typically need access to the full 510(k) submission, which contains the detailed testing reports and results.

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FibriCheck is indicated for self-testing by patients who have been diagnosed with, or are susceptible to developing, atrial fibrillation and who would like to monitor and record their heart rhythms on an intermittent basis.

FibriCheck is a medical device software that can be used to determine heart rhythm conditions, with a primary focus on the detection of atrial fibrillation.

The FibriCheck Mobile Application is a smartphone application for patients intended to record, display, store and transmit photoplethysmography (PG) data. Heart rhythm measurements are performed by placing the fingertip on the camera of a smartphone device. This way, volumetric changes can be detected.

The FibriCheck Portal is a web application for healthcare providers intended to display data that was captured by the FibriCheck Mobile Application. Healthcare providers can use the issue FibriCheck prescriptions, to manage their patients and to consult measurement data.

This document is a 510(k) Pre-market Notification summary for the FibriCheck device. It outlines the device details, its intended use, comparison to a predicate device, and the non-clinical and clinical tests conducted to demonstrate safety and effectiveness.

Here’s a breakdown of the information relevant to acceptance criteria and the study proving the device meets them:

1. Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with specific numerical thresholds for performance metrics. Instead, it states that "The performance metrics are in line with those reported for the predicate device, and did not raise concerns regarding the safety or effectiveness of the subject device." This implies the acceptance criterion was "performance in line with the predicate device," which is K173872, also named FibriCheck.

The document reports the following general performance statement for the clinical validation study:

2. Sample Size and Data Provenance

• Sample Size for Test Set: 252 cardiology patients.
• Data Provenance: The patients were "recruited in-clinic or consulting the cardiac outpatient clinic," implying the data was collected prospectively in a clinical setting. The country of origin is not explicitly stated, but given the applicant's address in Belgium, it's highly probable the study was conducted there.

3. Number of Experts and Qualifications

The document states, "The participants were instructed to record PPG measurements using the subject device which were compared against the gold-standard reference diagnosis." It does not explicitly specify the number of experts used to establish ground truth or their qualifications. However, given the "gold-standard reference diagnosis" in cardiology and the mention of "cardiology patients," it can be inferred that diagnoses were made by qualified medical professionals, likely cardiologists.

4. Adjudication Method

The document does not describe an adjudication method for the test set. It mentions comparison against a "gold-standard reference diagnosis," suggesting a single, definitive ground truth rather than a process requiring adjudication among multiple readers.

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

The document does not mention an MRMC study or any comparative effectiveness study involving human readers with and without AI assistance. The study described focuses on the device's standalone performance against a gold standard.

6. Standalone (Algorithm Only) Performance

Yes, a standalone performance study was done. The clinical validation study directly compared the PPG measurements from the FibriCheck device (acting as the algorithm) against a "gold-standard reference diagnosis." The statement "The participants were instructed to record PPG measurements using the subject device which were compared against the gold-standard reference diagnosis" highlights the device's algorithmic performance.

7. Type of Ground Truth Used

The ground truth used was a "gold-standard reference diagnosis." While the specific nature of this diagnosis (e.g., expert consensus based on ECG, long-term monitoring data, etc.) is not detailed, in cardiology, a "gold-standard reference diagnosis" for atrial fibrillation typically involves a 12-lead electrocardiogram (ECG) or continuous ECG monitoring interpreted by a cardiologist.

8. Sample Size for Training Set

The document does not provide information on the sample size used for the training set. It only describes the clinical validation study (test set).

9. How Ground Truth for Training Set Was Established

The document does not provide information on how the ground truth for the training set was established, as it does not discuss the training process or dataset.

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The ASSURE Wearable ECG is indicated for adult patients who have been prescribed this device by a medical professional, who were previously prescribed the ASSURE WCD system, and who may be asymptomatic or who may suffer from transient symptoms such as palpitations, shortness of breath, dizziness, light-headedness, presyncope, syncope, fatigue, or anxiety. The signal acquired by the ASSURE Wearable ECG is not intended and should not be used for automated or semi-automated analysis. The device does not deliver any therapy, administer any drugs, provide interpretive or diagnostic statements or provide for any life support.

The ASSURE Wearable ECG is contraindicated for use in patients with an active implantable pacemaker or defibrillator.

The ASSURE Wearable ECG is a reusable, ambulatory electrocardiography-based, cardiac- and physiologicmonitoring, medical-electrical system whose intended purpose is to inform clinical management of options for diagnosing, monitoring and/or mitigating cardiac conditions after patient's improvement following ASSURE® Wearable Cardioverter Defibrillator (WCD) prescriptive use. The system utilizes the same five-electrode SensorFit™ Garment worn previously with the WCD prescription. The system continuously records ECG data and upon detection, it identifies and records episodes as high and low heart rate, as well as patient-triggered events. The system utilizes the same algorithm detection and episode reporting software marketed in the ASSURE WCD with high (Tachy) and low (Brady) capture for later transmission to the medical professional for interpretation. The system captures and stores ECG episodes, and non-ECG patient activity and wear information to be displayed and reported in counters and trends. Recorded events include ECG waveforms and reports identifying high and low heart rates, as well as patient-triggered events. The system uses a 3axis accelerometer to monitor non-ECG patient activity (steps and wear time).

The ASSURE Wearable ECG event reports do not contain diagnostic interpretation. The reported events are provided for review by the prescriber to assist in diagnosis of the recently transitioned WCD patient and to assess care options based on the healthcare professional's judgment and experience.

The ASSURE Wearable Cardiac ECG is a prescription use device. The ASSURE Wearable ECG is intended for use by a patient during their normal daily activities primarily in the home or community setting, but also hospitals, medical clinics, healthcare facilities and transport. The device is non-invasive, and intended to be used on one patient at a time.

The Wearable Cardiac ECG System is comprised of the following reusable patient-worn components:

• Monitor Cable Assembly
• Hub
• Alert Button
• Battery Pack
• SensorFit™ Garment
• Charger

The Kestra Medical Technologies, Inc. ASSURE Wearable ECG (K233864) does not appear to have an artificial intelligence/machine learning component that offers diagnostic interpretation. The provided text states, "The signal acquired by the ASSURE Wearable ECG is not intended and should not be used for automated or semi-automated analysis. The device does not deliver any therapy, administer any drugs, provide interpretive or diagnostic statements, or provide for any life support." and "The ASSURE Wearable ECG event reports do not contain diagnostic interpretation." Therefore, the typical acceptance criteria and study designs for AI/ML devices might not be applicable in the usual sense.

However, based on the information provided, here's a breakdown regarding the device's technical performance and regulatory compliance, reinterpreting "acceptance criteria" through the lens of general medical device performance and safety standards:

1. Table of Acceptance Criteria and Reported Device Performance

Since the device explicitly states it does not perform automated or semi-automated analysis or provide diagnostic statements, traditional AI/ML performance metrics like sensitivity, specificity, or AUC against a ground truth would not be applicable here. Instead, the acceptance criteria are focused on the device's ability to reliably act as a continuous ECG monitor, data recorder, and transmitter, and its compliance with relevant safety and performance standards.

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

The provided text does not explicitly state the sample size for any clinical or technical test sets involving patient data. The performance section focuses on bench testing against recognized standards. There is no mention of a separate "test set" in the context of diagnostic accuracy from patient data, as the device doesn't provide diagnostic interpretation.

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

This information is not applicable as the device explicitly states it does not perform automated or semi-automated analysis or provide diagnostic statements. The "ground truth" here is primarily established by adherence to engineering and safety standards, and functional verification through bench testing. Clinical interpretation of the recorded ECG data is left to medical professionals.

4. Adjudication Method for the Test Set

This information is not applicable given the device's stated function and the type of performance testing described (bench testing against engineering standards, not diagnostic accuracy studies requiring expert adjudication).

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

No, a MRMC comparative effectiveness study was not conducted or described. The device's function is to record ECG data, not to interpret it or assist human readers in interpretation. There is no AI component in this device that provides diagnostic assistance to a human reader.

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

While the device uses an "embedded arrhythmia detection algorithm" for auto-triggering events (high and low heart rates), the submission explicitly states that the signal "is not intended and should not be used for automated or semi-automated analysis" and "does not deliver...interpretive or diagnostic statements." Therefore, a standalone performance study in the sense of evaluating the diagnostic accuracy of an AI algorithm was not performed because the device does not claim diagnostic capabilities. Its "algorithm detection and episode reporting software" is for capture and storage of events for later clinician review, not for automated diagnosis.

7. Type of Ground Truth Used

For the functional aspects (ECG monitoring, event triggering, data storage/transmission), the "ground truth" would have been established through instrumentation calibration, controlled simulated signals, and direct measurement during bench testing, verifying that the device accurately records ECG, identifies specified rate thresholds, and transfers data as intended. For the safety and performance standards (e.g., IEC 60601 series), the ground truth is adherence to the requirements and test methods outlined in those international standards.

8. Sample Size for the Training Set

This information is not applicable. The device, as described, does not utilize machine learning/AI for diagnostic purposes, and therefore would not have a "training set" in the context of developing a diagnostic algorithm. The "proprietary algorithm detection software" for event triggering, while an algorithm, is not presented as a machine learning model requiring a training set for diagnostic output.

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

This information is not applicable. As no machine learning-based diagnostic algorithm is described, there is no "training set" or corresponding ground truth establishment process mentioned.

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The SimpleSense Platform is intended for use at home, a healthcare facility, or medical research organization under the direction of a licensed medical professional to record, display, and store the following physiological data: a) 2 leads of Electrocardiogram; b) Respiration rate measured through thoracic impedance; c) Heart Sounds; d) Activity including posture; e) Systolic and Diastolic Blood Pressure and f) other validated data sources. The SimpleSense Platform is intended for use when the licensed medical professional decides to evaluate the physiologic signals of adult patients as an aid to diagnosis and treatment. The SimpleSense Platform is intended to be used by patients at rest with a stationary torso. ECG recordings are indicated for the manual assessment of cardiac rhythm disturbances.

The SimpleSense Platform does not produce alarms and is not intended for active patient monitoring. The SimpleSense Platform is not intended for use as life supporting equipment on high-risk patients such as critical care patients. The SimpleSense Platform is not intended for use in the presence of a pacemaker.

The SimpleSense-BP software application is intended to estimate, display and store blood pressure data on adult patients who are twenty two (22) years and older. The SimpleSense-BP can be used after a clinician determines the user's hypertension classification via an auscultatory blood pressure cuff measurement. The Blood Pressure algorithm uses patient specific information (age, gender, height and weight) and the blood pressure measurement as inputs. SimpleSense-BP is used to provide blood pressure estimations derived from physiological sensors to qualified medical personnel as a complimentary physiological feature for the purposes of assessing a patient's cardiac health and variance.

The SimpleSense-BP Software Application accesses the physiological parameters like ECG, heart sounds, and thoracic impedance captured by the SimpleSense Device for processing into the vital sign outputs of the product which includes estimation of Systolic and Diastolic blood pressure. The software uses recorded data from the SimpleSense electronics module as inputs into a validated computational model for estimating blood pressure over the period of wear. The system samples blood pressure while the user is at rest. In addition, SimpleSense-BP Software utilizes inputs such as demographic information (age, weight, height, and gender) and a blood pressure measurement for clinical stratification to the algorithm. The blood pressure outputs are returned to the SimpleSense Mobile Application and/or SimpleSense webserver for display, review and interpretation by a physician.

The Nanowear SimpleSense system is a non-invasive, wearable, and portable medical device for the evaluation and monitoring of patients. It utilizes physiologic and biometric sensors embedded in a garment and an electronics module to gather the heart health data. The specific physiological parameters recorded by the device include: two vectors of Electrocardiogram (ECG), respiratory rate though thoracic impedance, heart sounds, and activity including posture. The signals are recorded by the electronics module on a removable data storage card and are periodically transferred to a smartphone mobile application that connects to the electronics module over a wireless Bluetooth connection. The mobile application provides the functionality of transferring the data collected by the electronics module then relaying the data to the Nanowear web server for display of the data by a physician.

The provided text describes the acceptance criteria and study proving the performance of the SimpleSense-BP software application for blood pressure estimation.

Here's an organized breakdown of the requested information:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the SimpleSense-BP algorithm are based on the ISO 81060-2 standard for non-invasive sphygmomanometers. The reported performance refers to the accuracy of the device's blood pressure estimations compared to reference measurements.

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

• Sample Size for Induced Change Test: 149 subjects in total were identified, with 147 subjects having usable data. The study ensured at least 10 subjects had a change in BP of at least 15 mmHg systolic or 10 mmHg diastolic for each of the 4 models used by the device.
• Sample Size for Accuracy over Calibration Period Test: 91 subjects. The study enrolled subjects until at least 85 subjects were included and at least 21 subjects in each clinical stratification (Normal, Prehypertension, Stage 1 hypertension, and Stage 2 hypertension) were represented.
• Data Provenance: The document does not explicitly state the country of origin. It indicates that blood pressure variations were induced using physical activity and thermal stimuli, and auscultatory reference measurements were used for validation, suggesting a prospective study design.

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

The document states that "auscultatory reference measurements were used to validate the SimpleSense-BP algorithm." This implies a clinical setting where blood pressure is manually measured by trained personnel, typically healthcare professionals, using a cuff. However, the exact number of experts, their specific qualifications (e.g., "radiologist with 10 years of experience"), or the method of their involvement (e.g., individual readings, consensus) are not specified in the provided text.

4. Adjudication Method for the Test Set

The document does not describe a formal adjudication method (e.g., 2+1, 3+1, none) for the test set. The ground truth was established by "auscultatory reference measurements," which usually implies direct clinical measurement rather than adjudicated review of digital data.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. The provided text describes a standalone performance study comparing the device's output to a gold standard (auscultatory measurements), not a comparative effectiveness study involving human readers with and without AI assistance. Therefore, there is no mention of an effect size for human reader improvement with AI assistance.

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

Yes. The entire performance testing section (Section 11) is dedicated to evaluating the "SimpleSense-BP algorithm" against auscultatory reference measurements. This represents a standalone (algorithm only) performance evaluation.

7. The Type of Ground Truth Used

The type of ground truth used is auscultatory blood pressure cuff measurements, which is considered the gold standard for non-invasive blood pressure measurement.

8. The Sample Size for the Training Set

The sample size for the training set is not specified. The document explicitly states, "There was no overlap of subjects between the training and test data sets i.e., none of the measurements from subjects in the training data set were included in the test data set and vice versa," confirming that a training set was used but not detailing its size.

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

The document does not explicitly state how the ground truth for the training set was established. However, given that the validation uses "auscultatory reference measurements" as the gold standard, it is highly probable that the training data's ground truth was established using the same (or a similar and equally robust) method of auscultatory blood pressure measurements.

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