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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 QT ECG System is intended to acquire, record and process an electrocardiographic signal so that it can be transmitted digitally via Bluetooth technology to a cell-phone or mobile device, then to a remote location. The QT ECG System is indicated for use on infants, children and adults. It is designed to be operated by adults in the home, or by healthcare workers in non-acute care clinical facilities (such as nursing homes, skilled nursing facilities), and in professional healthcare facilities (such as clinics, hospitals, and ambulances) to record and transmit a 12- lead ECG and rhythm strip in near real-time to enable review at a physician's office, hospital or other medical receiving centers.

The QT ECG system is a non-defibrillator-proof, hand-held, cordless 12-lead electrocardiograph (ECG) system with Bluetooth connectivity. The QT ECG system consists of 5 maior components:

• The QT ECG Recorder-Compact device that records 12-lead, resting electrocardiograms, then transmits the recorded data to a mobile device (smartphone, tablet, etc.) paired via Bluetooth. A Bluetooth-enabled mobile device (not included) is needed to operate the QT ECG Recorder, and to send the recorded rhythm strip to a cardiologist or licensed physician for review.
• The QT ECG Electrode Strip-Disposable, patented electrodes that are prepositioned on a self-adhesive strip.
• The QT ECG App - Software that lets the user uses their mobile device to operate the QT ECG recorder, then send the recorded data via cloud to a certified medical professional for review.
• Analysis The analysis module provides ECG measurement from the collected data. It does not make any interpretation of the intervals provided based on factors such as heart rate, QRS duration, etc.
• Web Service - The web service provides an interface for communication. The recorded ECG data is saved temporarily on the mobile device until it is transferred via the Internet to the cloud server. The QT ECG System does not have monitoring capabilities and does not have diagnostic alarm function. The QT ECG System is indicated for use on infants, children and adults. It is designed to be operated by adults in the home, or by healthcare workers in non-acute care clinical facilities (such as nursing homes, skilled nursing facilities), and in professional healthcare facilities (such as clinics, hospitals, and ambulances) to record and transmit a 12- lead ECG and rhythm strip in near real-time to enable review at a physician's office, hospital or other medical receiving centers.

The provided text describes the QT ECG (QTERD100) device and its submission for FDA clearance. The submission, K233521, is a Special 510(k) comparing the device to a previously cleared version (K220795). The changes primarily relate to an expanded indication for use to include Emergency Medical Services (EMS) environments and updated environmental operating conditions and supported mobile devices.

Here's an analysis of the acceptance criteria and study data based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document presents a comparison between the subject device (K233521) and the original device (K220795), focusing on the differences. The "Acceptance Criteria" column explicitly states the criteria for the tests conducted to validate these differences.

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

The provided document does not specify sample sizes for any of the tests mentioned (e.g., IEC 60601-1-12, software tests).

The data provenance is also not explicitly stated in terms of country of origin or whether it was retrospective or prospective. The document mentions tests being conducted "according to IEC 60601-1-12," which implies standard compliance testing, but doesn't detail the origin of the test data.

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 use of experts to establish a ground truth for the test set, nor does it mention their number or qualifications. The tests conducted appear to be primarily engineering and safety compliance tests rather than clinical studies requiring expert ground truth for interpretation of ECG data.

4. Adjudication Method for the Test Set

Since there's no mention of experts establishing a ground truth or interpreting data, there's no information about an adjudication method.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. The device is described as acquiring, recording, and transmitting ECG signals for review by a physician, but there's no study presented that evaluates the performance of human readers with or without AI assistance, or an effect size. The "Analysis module" for the device provides ECG measurements but "does not make any interpretation."

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

The document describes the device's "Analysis module" which "provides ECG measurement from the collected data. It does not make any interpretation of the intervals provided based on factors such as heart rate, QRS duration, etc." This indicates that the device itself performs some algorithmic processing (measurement) but does not provide diagnostic interpretation. Therefore, a standalone diagnostic performance study (algorithm only) as typically understood for AI-based diagnostic devices, is not described here. The presented studies focus on safety, electrical performance, and software validation.

7. Type of Ground Truth Used

Given the nature of the tests (compliance with standards like IEC 60601-1-12, software validation), the "ground truth" would be defined by the technical specifications of the standards themselves (e.g., passing specific electrical tests, proper software function as per design documents) rather than expert consensus, pathology, or outcomes data related to ECG interpretation. The document does not describe studies requiring such clinical ground truth.

8. Sample Size for the Training Set

The document does not mention a training set sample size. Since the device's "Analysis module" provides measurements but no interpretation, it's unlikely to involve machine learning models that require extensive training data in the traditional sense for diagnostic capabilities. The software validation tests mentioned ("Unit Test, Integration Test, System Test") are for functional correctness rather than training predictive models.

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

As no training set is described, there is no information on how ground truth for a training set was established.

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The V-Patch Cardiac Monitor is intended to record, transfer and store single-channel electrocardiogram (ECG) data via Bluetooth transmission to Bluetooth enabled devices. The monitor is intended for use by healthcare professionals, patients with known or suspected heart conditions and health-conscious individuals. The ECG data is intended to supplement other patient data and is not intended for automated analysis. The device has not been tested and it is not intended for pediatric use.

The V-Patch Cardiac Monitor ("V-Patch CM") is a continuous electrocardiogram (ECG) recording device to record, store, and transfer single channel ECGs and is designed for remote ECG data collection and remote monitoring. The device is in the form of an ECG patch that records ECG signals and transmits directly to a Bluetooth™ enabled device. The V-Patch CM has Bluetooth module for transferring ECG data from V-Patch CM to a Bluetooth enabled computing or mobile devices to be accessible to healthcare professionals. The V-Patch CM includes a battery powered electronic unit that is used with off-the-shelf (OTS) disposable medical grade gel electrodes for long term monitoring. The adhesive electrodes should be replaced by the user every 24 hours or when it no longer adheres to skin. The V-Patch CM is a prescription use device and the recorded ECG data is intended to be used with other patient data. The device does not provide any automated ECG analysis.

The provided document does not contain information about specific acceptance criteria, device performance, sample sizes used, data provenance, expert involvement, adjudication methods, MRMC studies, or standalone performance for the V-Patch™ Cardiac Monitor.

The document is a 510(k) summary for the V-Patch™ Cardiac Monitor (K222842) and focuses on establishing substantial equivalence to a predicate device (eCordum™ Cardiac Monitor, K193296). It outlines the device description, indications for use, and a comparison of technological characteristics, stating that the two devices are "identical in form and function..., using the same components, materials, and software... and the same manufacturing process."

Instead of presenting performance data against specific acceptance criteria, it lists nonclinical testing activities that were successfully passed, indicating compliance with relevant standards. These tests confirm the device's electrical safety, electromagnetic compatibility, biocompatibility, and functionality for ambulatory ECG recording, but they do not provide quantitative performance metrics against pre-defined acceptance criteria.

The document explicitly states: "No clinical testing is required to demonstrate substantial equivalence to the predicate eCordum Cardiac Monitor (K193296)." This implies that no specific clinical study was conducted to prove primary performance criteria for the V-Patch™ Cardiac Monitor itself.

Therefore, I cannot provide the requested information based on the given text.

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The QT ECG System is intended to acquire, record and process an electrocardiographic signal so that it can be transmitted digitally via Bluetooth technology to a cell-phone or mobile device, then to a remote location. The QT ECG System is indicated for use on infants, children and adults. It is designed to be operated by adults in the home, or by healthcare workers in non-acute care clinical facilities (such as nursing facilities), to record and transmit a 12-lead ECG and rhythm strip in near real-time to enable review at a physician's office, hospital or other medical receiving centers.

The OT ECG system is a non-defibrillator-proof, hand-held, cordless 12-lead electrocardiograph (ECG) system with Bluetooth connectivity. The OT ECG system consists of 5 major components:

• ·The QT ECG Recorder—Compact device that records 12-lead, resting electrocardiograms, then transmits the recorded data to a mobile device (smartphone, tablet, etc.) paired via Bluetooth. A Bluetooth-enabled mobile device (not included) is needed to operate the QT ECG Recorder, and to send the recoded rhythm strip to a cardiologist or licensed physician for review.
• . The QT ECG Electrode Strip-Disposable, patented electrodes that are prepositioned on a self-adhesive strip.
• The QT ECG App - Software that lets the user uses their mobile device to operate the QT ECG recorder, then send the recorded data via cloud to a certified medical professional for review.
• . Analysis - The analysis module provides ECG measurement from the collected data. It does not make any interpretation of the intervals provided based on factors such as heart rate, ORS duration, etc.
• . Web Service — The web service provides an interface for communication.
  The recorded ECG data is saved temporarily on the mobile device until it is transferred via the Internet to the cloud server. The QT ECG System does not have monitoring capabilities and does not have diagnostic alarm function. The QT ECG System is intended for use on infants, children and adults patients to acquire ECG signals to be transmitted wirelessly via Bluetooth to a mobile device, and then over the Internet to a web service. The QT ECG System is designed to be used by a patient to record and transmit ECG data to a physician's office, hospital or other medical receiving center for review.

The provided text is a 510(k) Summary for the QT Medical, Inc. QT ECG device (K220795). This document primarily focuses on establishing substantial equivalence to a predicate device (K180157) and outlines various non-clinical testing performed to show safety and performance. However, it does not contain the detailed clinical study information typically required to describe acceptance criteria and the study that proves the device meets those criteria for an AI/ML enabled medical device.

The document states:

• "All the test results demonstrate OT ECG meets the requirements of its pre-defined acceptance criteria and indication for use, and is substantially equivalent to the predicate device." (Page 5)
• "Although there are some different specifications between two devices, the 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 requests." (Page 14)

These statements indicate that acceptance criteria exist and were met through testing. However, the document lists these tests as "Non-clinical Testing" including biocompatibility, software validation, cybersecurity, electromagnetic compatibility, electrical safety, performance (of electrode and recorder, durability, wireless interference), and human factors (usability). These are engineering and regulatory compliance tests, not a clinical study proving diagnostic or predictive performance against specific clinical acceptance criteria for an AI/ML algorithm's output.

The device description on page 5 explicitly mentions:

• "Analysis - The analysis module provides ECG measurement from the collected data. It does not make any interpretation of the intervals provided based on factors such as heart rate, QRS duration, etc."
• "The QT ECG System does not have monitoring capabilities and does not have diagnostic alarm function." (Page 5)

This indicates that the "Analysis module" performs basic ECG measurements (e.g., intervals, durations) but does not provide diagnostic interpretations or AI-driven insights that would require validation through a clinical study with expert ground truth. The device's function is data acquisition and transmission, not automated diagnosis or interpretation. Therefore, a clinical study of the device's diagnostic performance, as might be done for an AI/ML device that provides interpretations, is not described because it appears not to be within the scope of this device's intended use or capabilities.

Given the information provided in the document, I cannot create the requested table or answer most of the questions because the device does not include an AI/ML component for diagnostic interpretation and the detailed clinical study information is not present. The "performance test" mentioned in the non-clinical testing section likely refers to technical specifications for ECG signal acquisition and transmission, not clinical outcome or interpretative accuracy.

Therefore, the following table and answers are based on the absence of such information in the provided document, reflecting that this device's clearance did not hinge on an AI/ML diagnostic performance study.

Acceptance Criteria and Device Performance (Based on available information)

The provided submission does not detail acceptance criteria related to AI/ML diagnostic performance as the device's "Analysis module" performs raw ECG measurement without interpretation or diagnostic capabilities. The acceptance criteria mentioned are general for device functionality, safety, and substantial equivalence to a predicate device.

Answers to Specific Questions (Based on available information):

1. A table of acceptance criteria and the reported device performance:
   (See table above. Note: This device is not described as having an AI/ML diagnostic component, so the clinical performance criteria typically associated with such devices are not present.)

2. Sample sizes used for the test set and the data provenance:
   The document mentions general "validation activities" and "performance tests" but does not specify sample sizes for test sets related to clinical performance or diagnostic accuracy. The data provenance (e.g., country of origin, retrospective/prospective) for any specific performance testing is also not provided. The testing described appears to be primarily engineering and regulatory compliance testing rather than clinical study data.

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/Not provided. Since the device states it "does not make any interpretation" and "does not have diagnostic alarm function," there's no indication that expert-established ground truth for diagnostic or interpretative performance was required or used in this submission.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
   Not applicable/Not provided. No clinical diagnostic test set or adjudication method is described in this document.

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 does not appear to provide AI assistance for human interpretation, as its analysis module only provides measurements, not interpretations.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   No standalone diagnostic performance study was done or described as the device's analysis module explicitly states it "does not make any interpretation."

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
   Not applicable/Not provided regarding diagnostic ground truth, for reasons stated above. The ground truth for the non-clinical performance tests would be defined by engineering standards and specifications.

8. The sample size for the training set:
   Not applicable/Not provided. As the device's "Analysis module" performs measurements rather than AI-driven interpretations, there's no mention of a training set for a machine learning algorithm.

9. How the ground truth for the training set was established:
   Not applicable/Not provided. (See answer to question 8).

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The Study Watch with Irregular Pulse Monitor is indicated for use by adult patients (22 years and older) who have been diagnosed with, or are susceptible to developing, atrial fibrillation enabling them to monitor and record their heart rhythms. Study Watch is also intended to record, store, transfer, and display single-channel electrocardiogram (ECG) rhythms.

The Study Watch is intended for prescription use only.

The Study Watch with Irregular Pulse Monitor is a miniaturized physiological data monitoring device that is intended to record, store, transfer and display single-channel electrocardiogram (ECG) rhythms. The Study Watch with Irregular Pulse Monitor is intended to notify the user in the event of an irregular pulse, such as atrial fibrillation (AF), and recommend acquisition of an ECG. The device utilizes a band and proprietary watch that incorporates two dedicated sensing electrodes to obtain a single-channel ECG measurement. In practice, a healthcare professional (HCP) may prescribe the Study Watch with Irregular Pulse Monitor to a patient and recommend the capture and transmission of one or more ECG rhythms on a daily basis for analysis by the HCP. The patient uses prompts provided on the graphical user interface (GUI) of the watch to collect a real-time 45-second ECG measurement. The patient is able to capture an ECG rhythm on-demand by navigation to the ECG menu, upon receipt of an irregular pulse notification. While an animated ECG waveform is briefly displayed on the GUI of the watch, the patient will not have direct access to the collected waveform. Using the provided charging dock (Cradle) and Verily's Study Hub or Watch App, the ECG measurements are securely transferred to Verily's cloud server and are viewed by the HCP using a web portal. Additionally, data may be securely transferred to interoperable devices for further analysis. The web portal is solely intended for use by the HCP to view time-stamped ECG waveforms collected by the patient and does not include any analysis features. Collectively, the Study Watch consists of the wearable watch and band, the Study Hub or Watch app (used to transfer data from the watch to the cloud), a Cradle, and the web portal.

Below is a detailed description of the acceptance criteria and the study proving the device meets these criteria, based on the provided document.

Device Name: Study Watch with Irregular Pulse Monitor

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document states the algorithm "exceeds the pre-specified per-interval performance thresholds for sensitivity and specificity," but the exact numerical thresholds are not provided within the given text.

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

• Sample Size for Test Set: The document mentions "thousands of ECG data collected from iRhythm Technologies' Zio devices" for algorithm training but does not explicitly state the sample size for the validation (test) set. However, it describes the "Study Watch AF Detection At Home (NCT04546763) data" as consisting of "free-living, multi-day PPG recordings obtained from the Study Watch, along with ECG-based rhythm labels obtained from reference iRhythm Technologies Zio XT Patches worn simultaneously."
• Data Provenance: The study was conducted in the USA, with regional demographics provided: Midwest (8%), Mountain (32%), West (32%), Northeast (14%), South (13%). The data was collected prospectively in a "free-living (home use) setting."

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

• Number of Experts: Not specified.
• Qualifications of Experts: The algorithm was trained using ECG data that had undergone "Certified Cardiographic Technician (CCT) review." It can be inferred that similar qualified personnel were involved in establishing the ground truth for the validation set, as the reference standard (Zio XT Patches) typically requires expert interpretation.

4. Adjudication Method for the Test Set

• The document does not explicitly state an adjudication method (e.g., 2+1, 3+1). It only mentions that ECG-based rhythm labels were "obtained from reference iRhythm Technologies Zio XT Patches worn simultaneously" and that the training data underwent "Certified Cardiographic Technician (CCT) review."

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

• No, an MRMC comparative effectiveness study was not done in the context of human readers improving with AI vs. without AI assistance. This study focused on the standalone performance of the irregular pulse monitoring algorithm.

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

• Yes, a standalone performance study was done. The described "Clinical Performance Data" section focuses solely on the algorithm's performance (sensitivity and specificity) in detecting irregular pulses based on PPG data, using a reference ECG as ground truth, without human-in-the-loop evaluation.

7. The Type of Ground Truth Used

• Clinical Ground Truth: The ground truth for validation was established using ECG-based rhythm labels obtained from reference iRhythm Technologies Zio XT Patches worn simultaneously with the Study Watch. This is a robust clinical ground truth for cardiac rhythm analysis.

8. The Sample Size for the Training Set

• The algorithm was trained using "thousands of ECG data collected from iRhythm Technologies' Zio devices." A specific number is not provided beyond "thousands."

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

• The ground truth for the training set was established through "ECG data collected from iRhythm Technologies' Zio devices, which have undergone Certified Cardiographic Technician (CCT) review." This indicates human expert review by qualified professionals.

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KardiaMobile 6L is intended to record, store and two-channel electrocardiogram (ECG) rhythms. In single channel mode, KardiaMobile 6L can record Lead-I. In two channel mode, KardiaMobile 6L can record Lead-I and Lead-II simultaneously and derive Lead-III and unipolar limb leads aVR, aVF and aVL. KardiaMobile 6L also displays ECG rhythms and output of ECG analysis from AliveCor's KardiaAI platform including detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, and others. KardiaMobile 6L is intended for use by healthcare professionals, patients with known or suspected heart conditions and health conscious individuals. The device has not been tested and is not intended for pediatric use.

KardiaMobile 6L is a trans-telephonic (transmission by smartphone) electrocardiogram (ECG) event recorder that records, stores, transfers, and analyzes single-channel or two channel ECG rhythm recordings. KardiaMobile 6L provides output of one or six ECG leads, including Lead I, Lead II, Lead III, aVL, aVR and aVF. The device utilizes the computing power of iOS-based or Android-based devices (referred to as "Mobile Computing Platforms" (MCP) within this 510(k)) to record and analyze ECG signals. KardiaMobile 6L consists of KardiaMobile 6L Hardware (portable small wireless hardware with electrodes) and the Kardia Core app. which is installed on an MCP (i.e., iOS or Android devices). KardiaMobile 6L Hardware uses Bluetooth to transmit the ECG signal from the electrodes to the Kardia Core app on the MCP, which then displays the recorded ECG on the MCP's screen. The device is intended to be used by patients with known or suspected heart conditions and health conscious individuals as well as by healthcare professionals (HCPs) who want to remotely monitor their patient's heart health. The device is available for Over-the-Counter (OTC) as well prescription use. The Kardia Core app provides the complete ECG recording and analysis workflow, from acquisition of the signal from the KardiaMobile 6L hardware, to the display of the ECG and analysis results, to printing of the ECG rhythm strip. The app utilizes KardiaAI (K181823, K201985) to provide ECG analysis, which includes the determinations of Normal Sinus Rhythm, Atrial Fibrillation, Bradycardia, Tachycardia, or Unclassified to OTC users and additionally, Sinus Rhythm determinations (Sinus Rhythm with Wide ORS, Sinus Rhythm with Supraventricular Ectopy, and Sinus Rhythm with Premature Ventricular Contractions) for prescription-use only users.

The document provided is a 510(k) summary for the AliveCor KardiaMobile 6L device. It describes the device, its intended use, and its substantial equivalence to a previously cleared predicate device.

Based on the provided information, the current submission (K220350) is for a minor modification (software reorganization and API addition) to an existing device (K210753, KardiaMobile 6L). Therefore, the study described here is primarily focused on demonstrating that these software changes do not adversely affect the device's safety or effectiveness as previously established.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states that the subject device (K220350) is being compared to its predicate (K210753). The performance criteria are implicitly met by demonstrating that the changes do not raise new questions of safety or effectiveness, as stated in the "Nonclinical Testing Summary" and "Conclusions" sections.

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

The document states: "No clinical testing was required for the minor changes made to the software." This implies that the current submission (K220350) did not involve a new clinical test set with human subjects to prove performance, but rather relied on nonclinical testing, specifically software verification activities.

Therefore, information on the sample size for a test set (e.g., number of ECGs, number of patients) or data provenance (country of origin, retrospective/prospective) directly related to a new clinical performance study for K220350 is not provided as it was explicitly deemed not required. The performance is being established by comparing to the predicate and ensuring the software changes did not introduce new risks. The previous predicate devices (K210753, K183319) would have had their own clinical data.

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

Not applicable, as no new clinical testing was performed for this specific submission (K220350). The performance claims are based on the substantial equivalence to the predicate, K210753, which would have established its own ground truth using experts.

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

Not applicable, as no new clinical testing was performed for this specific submission (K220350).

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

Not applicable. The document states "No clinical testing was required for the minor changes made to the software." This submission is not an MRMC study and does not evaluate AI assistance for human readers. It focuses on software reorganization and API addition.

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

The device description indicates that the Kardia Core app utilizes KardiaAI (K181823, K201985) to provide ECG analysis, detecting conditions like Normal Sinus Rhythm, Atrial Fibrillation, Bradycardia, Tachycardia, or Unclassified. This implies a standalone algorithmic analysis component. However, the current submission (K220350) primarily focuses on the software reorganization and API addition and explicitly states no new clinical testing was required. The performance of these AI determinations would have been established in the previous predicate clearances (K181823 and K201985), not in this particular submission.

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

Not directly addressed for this specific submission (K220350), as no new clinical data was collected. For the underlying KardiaAI platform (K181823, K201985), the ground truth for ECG analysis typically involves expert consensus of cardiologists reviewing the ECGs.

8. The sample size for the training set:

The document does not provide details of the training set size, as this submission is not about training a new AI model but rather a software modification to an already cleared device that utilizes existing AI algorithms (KardiaAI K181823, K201985). The training data for those AI algorithms would have been described in their respective 510(k) submissions.

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

Not directly addressed for this specific submission (K220350), as it pertains to the training of the underlying KardiaAI algorithms (K181823, K201985) rather than the software reorganization. For such algorithms, ground truth for training is typically established by expert adjudication/consensus of ECG interpretations by qualified medical professionals (e.g., cardiologists).

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The KardiaMobile Card System is intended to record, store and transfer single-channel electrocardiogram (ECG) rhythms. The KardiaMobile Card System also displays ECG rhythms and output of ECG analysis from AliveCor's KardiaAl platform including detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, and others. The KardiaMobile Card System is intended for use by healthcare professionals, patients with known or suspected heart conditions and health-conscious individuals. The device has not been tested and is not intended for pediatric use.

The AliveCor KardiaMobile Card System is a single-channel ambulatory electrocardiogram (ECG) device that is intended to record, store, transfer, display, and analyze single-channel ECG rhythms in an ambulatory setting. The device utilizes the computing power of Apple iOS- and Google Android-based smartphones to obtain and analyze single-channel ECGs. These smartphones are termed Mobile Computing Platforms (MCPs). The device consists of the hardware (that has the electrodes), and the Kardia phone app (installed on an MCP). The same software is implemented in the iOS and Android MCP. In either configuration, the same hardware is used to sense the ECG. The KardiaMobile Card Hardware transmits the ECG signal from the electrode to the Kardia phone app on the MCP to be analyzed and presented to the user. All ECGs are synced with the user's account.

The provided text, K211668, is an FDA 510(k) clearance letter for the AliveCor KardiaMobile Card System. It outlines the device description, indications for use, and a comparison to a predicate device. However, it does not include detailed information regarding clinical study data to demonstrate the device meets acceptance criteria for the KardiaAI platform's specific ECG analysis functionalities (detecting normal sinus rhythm, atrial fibrillation, bradycardia, and others).

The "PERFORMANCE DATA" section primarily describes bench testing related to the hardware modifications (change in data transmission method from ultrasonic acoustics to BLE, and change in hardware material). It lists various IEC and ISO standards for ECG acquisition, transmission, biocompatibility, electrical safety, and electromagnetic compatibility.

Therefore, I cannot provide a complete answer to your request based on the provided text, as it lacks the specific clinical study data (acceptance criteria, reported performance, sample sizes, expert ground truth establishment, MRMC studies, standalone performance, training set details) related to the diagnostic performance of the KardiaAI platform itself.

The document states: "No modifications were made to the Kardia app software's clinical functionalities with respect to ECG acquisition, display, and analysis because of this change since its prior clearance under K191406, K182396 and K201985." This implies that the clinical performance evaluation of the KardiaAI platform was conducted during the clearance of the predicate devices (K191406, K182396, K201985), and this 510(k) focuses on the substantial equivalence of the new hardware (KardiaMobile Card) to those previously cleared systems.

To answer your question fully, information from the 510(k) submissions for K191406, K182396, and/or K201985 would be required, as they would contain the detailed clinical performance studies for the KardiaAI platform.

Based only on the provided K211668 document, I can infer the following about what is not present:

• No acceptance criteria for diagnostic performance: The document does not state specific accuracy, sensitivity, or specificity thresholds for detecting cardiac rhythms.
• No reported device performance for diagnostic accuracy: There are no tables or summaries of clinical performance metrics for the KardiaAI algorithms.
• No sample sizes for a clinical test set (for diagnostic performance): The document only mentions bench testing for hardware.
• No details on data provenance (for diagnostic performance): No information on origin, retrospective/prospective nature of a clinical test set.
• No information on experts for ground truth (for diagnostic performance): No details on number, qualifications, or adjudication methods for ECG interpretations.
• No MRMC study details: The document does not describe any human reader studies.
• No standalone (algorithm-only) performance data (for diagnostic performance): The focus is on hardware changes, not re-evaluation of the AI algorithms.
• No information on training set size or ground truth establishment for the AI algorithms.

In summary, the provided document K211668 does not contain the information requested about the acceptance criteria and the study that proves the device meets diagnostic performance acceptance criteria for the KardiaAI platform. It only addresses the substantial equivalence of the hardware changes for the KardiaMobile Card.

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The SimpleSENSE Platform is intended for use at home, or at a healthcare facility, 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; and e) 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 and not performing any activities or movements. 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 (real-time). 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 Nanowear SimpleSENSE Platform is the next generation diagnostic monitoring technology that captures electrocardiographic (ECG) signals, respiration rate though thoracic impedance, heart sounds, activity including posture and movement with sensors embedded on a wearable textile garment. The signals are stored and wirelessly transmitted to a smartphone, which is then forwarded to a medical professional for review. The garment is designed to be unobtrusive to everyday activity and provide an easier and more efficient means of capturing ECG data from patients. The device consists of a combination of: The SimpleSENSE Garment: an integrated network of nanosensor electrodes for measuring ECG and respiratory rate from thoracic impedance. A MEMS microphone for measuring heart sounds. The SimpleSENSE Signal Acquisition Unit (SAU): data acquisition, storage, and transmission to a phone running iOS or Android. An accelerometer to measure activity. The SimpleSENSE Mobile Application: mobile application to start/stop a recording, logging symptoms, and data transmission. SimpleSENSE Web Server: allows initiation of a test, storage, and review of prescribed test data by a medical professional.

The provided text describes Nanowear Inc.'s K212160 submission for the SimpleSENSE Platform, an upgraded version of their previously cleared SimpleSENSE System (K201669). The submission is a Special 510(k), which means it primarily focuses on changes to an already cleared device, and thus omits much of the original performance data. Therefore, the information regarding acceptance criteria and performance testing is limited to what was specifically re-evaluated or added for the new device.

Here's an analysis based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly provide a table of acceptance criteria and reported device performance in the format requested. As this is a Special 510(k), the focus is on demonstrating that changes made to the device do not negatively affect safety or efficacy. The "Performance Testing" section (Section 11) lists the tests conducted for the new SimpleSENSE Platform.

However, based on the type of tests performed, we can infer general acceptance criteria for the new or modified components.

Note: The document explicitly states that performance data and verification/validation activities for aspects not affected by product changes were omitted from this Special 510(k). These include core functionalities like multiparametric data capture, ECG sensor performance, electrical current requirements for thoracic impedance, MEMS microphone testing, etc. For those, it relies on the predicate device's clearance (K201669).

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

The document does not specify a sample size for the test set used for the software and firmware verification activities. It also does not specify the data provenance (e.g., country of origin, retrospective/prospective) for these tests. This information would typically be found in detailed test reports, which are not included in this summary.

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 any information about the number or qualifications of experts used to establish ground truth for the test set, as the performance testing primarily focuses on software and firmware verification rather than clinical outcomes or diagnostic accuracy requiring expert interpretation.

4. Adjudication method for the test set

The document does not describe any adjudication method for the test set. Given the nature of the tests (software and firmware verification), a formal adjudication process involving multiple experts is unlikely to have been part of these specific engineering tests.

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. The SimpleSENSE Platform's indications for use state that "ECG recordings are indicated for the manual assessment of cardiac rhythm disturbances" and that the device "does not produce alarms and is not intended for active patient monitoring (real-time)." There is no indication that AI or automated interpretation is part of the device's functionality that would necessitate such a study. The device provides raw physiological data for a medical professional to review.

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

The document does not describe any standalone (algorithm-only) performance testing. The device is intended to record and transfer physiological data for medical professionals to review; it does not explicitly claim automated diagnostic algorithms that would undergo standalone performance evaluation.

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

For the software and firmware verification tests, the "ground truth" would be the expected functional behavior of the software and firmware as per design specifications and requirements. This is not medical ground truth (like pathology or expert consensus) but rather engineering ground truth.

8. The sample size for the training set

The document does not mention a training set sample size. Since the described performance testing is for software/firmware verification and not for machine learning model development, a training set as typically understood in AI/ML contexts would not be relevant here.

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

Not applicable, as no training set for a machine learning model is mentioned or implied by the described performance testing.

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KardiaMobile 6L is intended to record, store and two-channel electrocardiogram (ECG) rhythms. In single channel mode, KardiaMobile 6L can record Lead-I. In two channel mode, KardiaMobile 6L can record Lead-I and Lead-II simultaneously and derive Lead-III and unipolar limb leads aVE. KardiaMobile 6L also displays ECG rhythms and output of ECG analysis from AliveCor's KardiaAI platform including detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, and others. KardiaMobile 6L is intended for use by healthcare professionals, patients with known or suspected heart conditions and health conscious individuals. The device has not been tested and is not intended for pediatric use.

KardiaMobile 6L is a trans-telephonic (transmission by smartphone) electrocardiogram (ECG) event recorder that records, stores, transfers, and analyzes single-channel or two channel ECG rhythm recordings. KardiaMobile 6L provides output of one or six ECG leads, including Lead I, Lead II, Lead III, aVL, aVR and aVF. The device utilizes the computing power of iOS-based or Android-based devices (referred to as "Mobile Computing Platforms" (MCP) within this submission) to obtain and analyze ECG signals. KardiaMobile 6L consists of KardiaMobile 6L Hardware (portable small wireless hardware with electrodes) and the Kardia App, which is installed on an MCP (i.e., iOS or Android devices). KardiaMobile 6L hardware uses Bluetooth to transmit the ECG signal from the electrodes to the Kardia App on the MCP. KardiaMobile 6L displays thus record their ECG and additionally provides ECG analysis using the KardiaAI (K181823, K201985) ECG analysis suite, which includes the determinations of Atrial Fibrillation, Normal Sinus Rhythm, Bradycardia, Tachycardia, or Unclassified. The device is intended to be used by patients with known or suspected heart conditions and health conscious individuals as well as by healthcare professionals (HCPs) who want to remotely monitor their patient's heart health. Patients can forward the recorded ECG to their HCP, who can review the ECG for rhythm and to measure the QT interval. The device is available for Over-the-Counter (OTC) purchase and for purchase with a prescription. The Kardia App is also comes in an alternate variant, called the KardiaStation App that is exclusively used within hospitals and clinics; this app is identical to the Kardia App with the exception of incorporating patient administration workflows.

Here's a summary of the acceptance criteria and study details based on the provided text, focusing on the expanded use case of QT interval measurement for healthcare professionals:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document specifically addresses the expanded use case for healthcare professionals to measure the QT interval. It compares the KardiaMobile 6L's ability to measure QT intervals against a gold standard 12-lead diagnostic ECG device.

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

• Sample Size: 313 subjects.
• Data Provenance: Not explicitly stated regarding country of origin, but the study design suggests prospective data collection as ECG recordings were "taken comparison" and included "both healthy volunteers and patients suspected of long QT syndrome or other genetic heart disease."

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

• The document states that a "core lab used to provide precise QT measurements for Thorough QT studies was utilized to measure the QT and heart-rate corrected QTc in each ECGs."
• Number of Experts: Not specified.
• Qualifications of Experts: Implied expertise in QT measurement for Thorough QT studies, indicating highly specialized cardiac electrophysiology expertise.

4. Adjudication Method for the Test Set

• The document mentions that the core lab measured QT and QTc "in a randomized and blinded order, using standard measurement techniques." This suggests a robust, independent assessment, but a specific "adjudication method" (e.g., 2+1, 3+1) is not explicitly stated.

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

• No, a MRMC comparative effectiveness study was not explicitly described for the expanded QT interval measurement use. The study focused on the equivalence of QT measurements from the device compared to a gold standard, not on the improvement of human readers with AI assistance. The "human readers" in this context were the core lab experts establishing ground truth, not users of the device whose performance was being evaluated for improvement with AI.

6. Standalone (Algorithm Only) Performance

• No, an explicit standalone (algorithm only without human-in-the-loop performance) study for QT interval measurement was not described. The study validated that "a healthcare professional can review and measure the QT interval reliably using an ECG recorded using KardiaMobile 6L." While the device records the ECG, the measurement itself is performed by a human expert/core lab. The device's role here is data acquisition for human interpretation.
• It's important to note that the KardiaAI platform (K181823, K201985) does run algorithms for detecting Atrial Fibrillation, Normal Sinus Rhythm, Bradycardia, Tachycardia, or Unclassified rhythms, and these would have had standalone performance studies in their original clearances. However, for the expanded QT interval measurement claim, the study focuses on the reliability of the ECG recording for human measurement.

7. Type of Ground Truth Used

• Expert Consensus / Highly Specialized Core Lab Measurement: The QT and heart-rate corrected QTc measurements were performed by a "core lab used to provide precise QT measurements for Thorough QT studies." This represents a high-level, specialized form of expert consensus and measurement standard.

8. Sample Size for the Training Set

• Not provided. The document focuses on the clinical validation study for the QT interval measurement claim, which is a test set evaluation. Information about the training set for any underlying algorithms is not included in this 510(k) summary.

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

• Not provided. As the training set size is not mentioned, neither is the method for establishing its ground truth.

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The SimpleSENSE System is intended for use at home, or at a healthcare facility, 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; and d) Activity including posture. The device is intended for use when the clinician decides to evaluate the physiologic signals as an aid to diagnosis and treatment. The SimpleSENSE System is intended to be used by patients at rest and not performing any activities or movements. ECG recordings are indicated for the manual assessment of cardiac rhythm disturbances. The device does not produce alarms and is not intended for active patient monitoring (real-time). The device is not intended for use as life supporting equipment on high-risk patients such as critical care patients. The device is not intended for use in the presence of a pacemaker.

The Nanowear SimpleSENSE device is the next generation diagnostic monitoring technology that captures electrocardiographic (ECG) signals, respiration rate though thoracic impedance, heart sounds, activity including posture with sensors embedded on a wearable textile garment. The signals are stored and wirelessly transmitted to a smartphone, and forwarded to a medical professional for review. The garment is designed to be unobtrusive to everyday activity and provide an easy and efficient means of capturing ECG, respiration rate, heart sounds and activity data from patients. The garment is designed to be unobtrusive to everyday activity and provide an easy and efficient means of capturing ECG data from patients. The device consists of three (3) components:

• The SimpleSENSE Garment: an integrated network of nanosensor electrodes for measuring ECG and respiratory rate from thoracic impedance, and incorporating a MEMS microphone for measuring heart sounds.
• The SimpleSENSE Signal Acquisition Unit (SAU): data acquisition, storage, and transmission to an iPhone 7 using iOS 13.4. Incorporates an accelerometer to measure activity.
• The SimpleSENSE Mobile Application: mobile application for to start/stop a recording and to forward the test report to the medical professional.

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

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary provided does not explicitly list acceptance criteria in a quantitative table format with corresponding reported performance values for clinical metrics. Instead, it describes various performance evaluations against design specifications and equivalence to predicate devices.

However, based on the Performance testing section, we can infer some key areas of evaluation:

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

The summary states that "Equivalency testing against predicate/reference devices" was performed as part of the performance testing. However, it does not provide any details regarding the sample size used for clinical testing or the data provenance (e.g., country of origin, retrospective or prospective) for this equivalency testing.

3. Number of Experts and Qualifications for Ground Truth

The document does not specify the number of experts or their qualifications used to establish ground truth for any clinical test sets. The indications for use mention evaluation by a "licensed medical professional" and "physician who is skilled in rhythm interpretation" for the ECG data, but this pertains to the intended clinical use of the device, not necessarily how the ground truth for regulatory testing was established.

4. Adjudication Method

The document does not mention any adjudication method (e.g., 2+1, 3+1) for establishing ground truth in clinical test sets.

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

The document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with AI assistance versus without AI assistance. The SimpleSENSE system is a data acquisition and display device intended for manual assessment, not an AI-driven interpretive device.

6. Standalone (Algorithm Only) Performance

The SimpleSENSE system itself is described as a device that records, displays, and stores physiological data for manual assessment by a clinician. It does not appear to have an inherent AI algorithm that provides interpretations or diagnoses. Therefore, a standalone (algorithm only) performance study as typically understood for AI devices would not be applicable or described for this device. The phrase "manual assessment of cardiac rhythm disturbances" reinforces this.

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth used for any clinical testing (e.g., expert consensus, pathology, outcomes data). Given the nature of the device as a data recorder for manual assessment, it is implied that the "ground truth" for equivalency would come from comparisons to the outputs of the predicate devices or conventionally accepted methods for measuring parameters like ECG, respiration rate, and heart sounds.

8. Sample Size for the Training Set

The document does not mention a training set or its sample size. As the device is for data acquisition and display rather than AI interpretation, a separate training set for an algorithm is not discussed.

9. How Ground Truth for the Training Set Was Established

Since no training set for an AI algorithm is mentioned, the method for establishing ground truth for such a set is also not applicable or described in this summary.

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