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The TeleRehab® Aermos Cardiopulmonary Rehabilitation System is intended to acquire and condition the ECG signal from a patient so that it can be transmitted wirelessly from a radiofrequency transmitter to a workstation in a hospital or a clinical setting where the data is displayed and analyzed. This device also measures heart rate and provides visual and audible alarms if the patient's heart rate goes out of a prescribed range. This device is for use with ambulatory adult patients who need monitoring while undergoing cardiovascular and/or pulmonary rehabilitation. The physiological data from monitoring and other patient information (such as patient demographics, exercise protocol and medical information) is stored in a database for tracking and reporting of the patients' progress through rehabilitation.

The TeleRehab® Aermos Cardiopulmonary Rehabilitation System ("Aermos") provides the ECG monitoring functionality required for performing rehabilitation of cardiovascular and/or pulmonary patients. Patients' ECG may be monitored using the Aermos system during exercise under clinical supervision. During monitoring, Aermos provides both visual and audible alarms if the patient's heart rate goes out of a prescribed range. The heart rate alarm indication is one of multiple inputs a clinician may use to modify and adjust rehabilitation activities such as decreasing the patient's level of physical exertion or halting the exercise entirely.

Aermos also provides the ability to plan a patient's rehabilitation program and document the patient's progress through the creation of various types of reports. The report types supported in Aermos include individual treatment plan reports, daily exercise session reports and various patient information reports. Additionally, the Aermos system provides the ability to transfer various report types to the hospital Electronic Medical Records system.

The main components of Aermos are Argus ECG transmitters, the Aermos Workstation and associated networking equipment.

This FDA 510(k) clearance letter pertains to the TeleRehab Aermos Cardiopulmonary Rehabilitation System, which is a device for monitoring ECG signals and heart rate during patient rehabilitation. The provided documentation (the 510(k) Summary) details non-clinical bench testing for performance and safety but explicitly states that clinical testing was not applicable.

Therefore, based on the provided document, the following information regarding acceptance criteria and a study that proves the device meets those criteria, specifically concerning an AI/algorithm-driven component with clinical performance metrics, cannot be fully extracted or is explicitly stated as not performed:

Here's an analysis of the provided information relative to your request:

Acceptance Criteria and Device Performance (Based on Non-Clinical Bench Testing)

Since no clinical study was performed, the "reported device performance" would pertain to the results of non-clinical bench testing against established performance standards. The document does not provide specific quantitative acceptance criteria or reported numerical performance results for the device. Instead, it states that the device's specifications were "verified through internal verification testing" and its usability "evaluated through internal validation testing," and that it complies with various international standards.

Study Details (Based on the provided 510(k) Summary)

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

   • See the table above. Specific quantitative acceptance criteria beyond "compliance with standard" are not provided in this regulatory summary.

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

   • The document explicitly states "Clinical Testing: Not applicable."
   • For the non-clinical bench testing, specific sample sizes (e.g., number of devices tested, number of test cases) are not detailed in this 510(k) summary.
   • Data provenance for non-clinical testing would typically be internal laboratory data generated during device development and verification. There is no mention of geographical origin or retrospective/prospective nature as this was not 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 clinical study with human interpretation/ground truth was performed. The "ground truth" for bench testing would be defined by validated test equipment and reference standards.

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

   • Not applicable, as there was no study involving human readers or interpretation requiring 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:

   • No MRMC study was done, as clinical testing was "Not applicable." The device is a physiological signal monitor, not an AI-assisted diagnostic tool that interprets images or signals requiring human reader comparison.

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

   • The core functionality of the device (ECG acquisition, heart rate measurement, alarms) is algorithmic. The performance of these algorithms would have been assessed during the non-clinical bench testing, which is essentially "standalone algorithm" testing against known inputs and expected outputs. Specific quantitative results (e.g., algorithm accuracy for heart rate) are not provided in this summary beyond "compliance with IEC 60601-2-27" and "ANSI/AAMI EC57: 2012, Testing and Reporting Performance Results of Cardiac Rhythm and ST-Segment Measure Algorithms."

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

   • For non-clinical bench testing, the "ground truth" is typically established by:
     • Reference standards and calibrated test equipment: For electrical performance, signal acquisition accuracy, frequency response, etc.
     • Simulated physiological signals: For testing heart rate calculation and alarm thresholds.
     • Design specifications and established engineering principles: For software functionality and cybersecurity.

8. The sample size for the training set:

   • Not applicable. The device is a monitoring system and not primarily driven by a deep learning or machine learning algorithm that requires a "training set" in the sense of a large dataset for model development. The algorithms for heart rate calculation, etc., are likely traditional signal processing algorithms.

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

   • Not applicable, as there was no training set for a machine learning model.

Summary of Device Nature and Regulatory Pathway:

The TeleRehab Aermos Cardiopulmonary Rehabilitation System is a Class II device (Product Codes DRG, DRT) which functions as a physiological signal transmitter and receiver. It monitors ECG and heart rate and provides alarms. Its 510(k) clearance relied on demonstrating substantial equivalence to predicate devices primarily through non-clinical bench testing against recognized industry standards (e.g., IEC 60601 series, ANSI/AAMI, ISO standards) and adherence to FDA guidance documents (e.g., for software, cybersecurity, reprocessing). The explicit statement "Clinical Testing: Not applicable" indicates that the nature of the device and its intended use, combined with the comprehensive non-clinical data, satisfied the FDA's requirements for demonstrating safety and effectiveness without the need for a human-subject clinical study. This is common for devices that are evolutionary improvements on existing technologies with well-understood performance parameters.

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iBSM is a wireless monitoring system intended for the display of electrocardiography (ECG) waveform, heart rate measurements, respiratory rate measurement and waveform, functional oxygen saturation of arterial hemoglobin (SpO2), activity, body position, fall detection, skin temperature and Blood Pressure parameter measurements by qualified healthcare professionals in healthcare settings. iBSM continuously monitors the orientation of patients to aid in the prevention of pressure ulcers for at-risk patients. The system provides visual notification when the patient's position has not changed from a preset time threshold.

The iBSM device is intended for use on general care patients who are 18 years of age or older as a general patient monitor to provide continuous physiological information as an aid to diagnosis and treatment.

The iBSM device is not intended for use on critical care patients.

The iBSM BP cuff is not intended for subjects that are considered special populations.

The iBSM device is indicated for monitoring ECG waveforms and heart rate on non-ambulatory patients.

The iBSM device is intended to be used in wards and patient rooms in professional healthcare facility environment hospital settings.

The iBSM device is not intended to be used in Home environment or special environment.

The iBSM device is not intended to be used in an ambulatory environment for noninvasive blood pressure, respiratory rate and SpO2 measurement parameters.

The iBSM device is not intended to monitor or measure respiratory rate, SpO2, or noninvasive blood pressure while the patient undergoes significant motion or is active.

The iBSM device is not intended to be used in the ICU/CCU or Surgery/OT rooms

iBSM is compatible with third-party, FDA cleared devices such as ANNE Chest from Sibel Health Inc, for ECG, HR, RR, body position and skin temperature measurements; and ANNE Limb from Sibel Health Inc. for SpO2 and skin temperature measurements.

iBSM is compatible with third-party, FDA-cleared BP devices such as BP2A from Shenzhen Viatom, for non-invasive blood pressure measurements.

The iBSM device communicates with an external server for patient data communication and storage.

The iBSM device includes the ability to notify healthcare professionals when physiological data fall outside selected parameters with the use of audio and visual alarms.

The iBSM chest sensor is not intended to be used to provide diagnostic or or interpretive statements to either the patient or the clinician. The iBSM chest sensor is NOT intended to be used on critical care patients and is not a remote diagnostic device. The iBSM chest sensor is NOT intended for use on patients with implanted pacemakers. The iBSM Chest sensor is NOT intended for use on patients with known allergies, or hypersensitivities to, adhesives or nickel. The iBSM Chest Sensor is NOT intended for patients with significant cardiorespiratory disease including patients that are oxygen dependent. The iBSM Chest Sensor is NOT intended for patients with significant respiratory muscle weakness due to an underlying neuromuscular condition (e.g., myasthenia gravis, amyotrophic lateral sclerosis, or muscular dystrophies)

The data and results provided by the BP cuff device are for precheck screening purposes only and cannot be directly used for diagnosis or treatments.

The iBSM device is a wireless vital sign and physiological data monitoring device that streams real-time biosignals including electrocardiography (ECG), photoplethysmography (PPG), 3-axis accelerometry, and temperature to measure vital signs such as heart rate(HR), respiratory rate(RR), body position, SpO2 and skin temperature. The waveforms of ECG, Respiration and PPG are also displayed.

The ECG signal is not intended for automated arrhythmia detection or classification. Rather it is intended for manual interpretation, and the automated computation of heart rate through QRS identification using the well-known Pan-Tomkins beat detection algorithm. The displayed waveform is only intended for display as a check for normal ECG rhythm. The waveform is not intended for manual discrimination of any arrhythmias or cardiac conditions.

The system features two third party FDA cleared skin-mounted, bio-integrated sensors that pair with the iBSM View application for the continuous display and storage of vital sign measurements and physiological waveforms. The two sensors viz. iBSM chest (Anne Chest from Sibel Health Inc) and iBSM limb (Anne Limb from Sibel Health Inc) sensors are used along with their respective biocompatible iBSM chest sensor adhesive and iBSM limb sensor adhesives and attached to the patient. The adhesives are intended for a single use, whereas the sensors are intended for multiple reuse with the predefined processing.

Both the chest and the limb sensors along with their adhesives are third party FDA cleared devices. The system is also compatible with a third-party FDA cleared non-invasive blood pressure measurement device (Blood Pressure monitor BP2A from Shenzhen Viatom Technologies).

The iBSM device consists of a mains powered Docking station that provides the mechanical base station for the iBSM Tablet and has a provision to charge the tablet when docked.

The USB connector provided on the Docking station is intended only to power up the sensor charger accessory and any data transfer to the USB device is disabled.

The iBSM View Application runs on the iBSM tablet in a secure Kiosk mode and is intended to display the patient's physiological parameters and waveforms. The iBSM tablet with the iBSM View Application together is termed as iBSM hub.

The physiological data obtained by the sensors are wirelessly transmitted to their respective SDK's that are part of the iBSM hub with Bluetooth (BLE) connectivity, for continuous display of waveforms and parameters on the iBSM View Application. When connected to WiFi, vital signs data can be transferred in real-time from the iBSM hub to an external Server for data storage. The iBSM system provides an FHIR-compatible interface for patient data communication and storage to an external Server.

iBSM is intended to be used only in an hospital environment within the wards or patient rooms and not in ICU/CCU nor in Surgery/OT rooms. It is intended to be used for monitoring of non critical patients. iBSM is not intended to be used in a home environment.

iBSM uses the third party FDA cleared sensors such as ANNE Chest and ANNE Limb from Sibel Health Inc. and BP2A BP Cuff from Shenzhen Viatom, that fulfill the requirements of performance parameters in the signal acquisition before transmitting the data to their SDK's integrated with the iBSM Application in the iBSM hub for displaying the waveforms and the parameters.

The provided FDA 510(k) clearance letter details the acceptance criteria for the iBSM device and largely refers to its "substantial equivalence" to predicate and reference devices, rather than a standalone clinical study report with detailed performance data derived from a specific test set. The document outlines performance specifications and cites numerous consensus standards and bench testing used to demonstrate this equivalence.

It's important to note that 510(k) clearances typically rely on demonstrating substantial equivalence, and often do not require new, full-scale clinical trials if performance can be shown through bench testing, existing clinical data for predicate devices, or limited clinical validation. This document is a summary of that submission, not a detailed clinical study report.

Based on the provided text, here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The document specifies performance attributes for the iBSM system. These are presented as acceptance criteria and also implicitly as the reported performance, as the clearance is granted based on meeting these specifications.

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

The document does not explicitly state a specific "test set" sample size in terms of number of subjects for a new clinical study. Instead, it refers to performance verification through bench testing and compliance with various consensus standards.

• Sample Size: Not explicitly stated as a number of subjects for a clinical test set. The evaluation seems to rely on an aggregation of compliance with standards and performance data from predicate devices. For specific parameters like BP, compliance with ISO standards (e.g., IEC 80601-2-30) implies certain subject numbers were used for validation of the reference device (BP2A from Shenzhen Viatom, K193348), and the iBSM device demonstrates equivalence to its performance.
• Data Provenance: The document does not specify a country of origin for a new clinical test set. The company, iOrbit Digital Technologies Private Limited, is based in India. The predicate/reference devices are from Sibel Health Inc. and Shenzhen Viatom Technology Co. Ltd. The studies referenced for predicate devices (e.g., K240251 for ANNE Chest, K240305 for ANNE Limb, K193348 for BP2A) would have their own data provenance. The assessment presented appears to be a summary of bench testing, software verification, and compliance with standards. There is no mention of a primary prospective clinical study for the iBSM itself.

3. Number of Experts and their Qualifications for Ground Truth Establishment

The document does not describe the establishment of ground truth by human experts for a specific test set. The validation methodology relies on:

• Bench testing against defined specifications.
• Compliance with international standards (e.g., IEC, ISO, ANSI/AAMI), which often have their own established methods for ground truth, such as calibrated instruments for physiological measurements.
• Equivalence to legally marketed predicate devices (ANNE One, ANNE View, BP2A, ANNE Chest), whose ground truth would have been established during their own clearances.

Therefore, there is no mention of "experts" in the context of establishing ground truth for a diagnostic AI system, as the iBSM is a monitoring device that focuses on accuracy of physiological measurements, not diagnostic interpretation.

4. Adjudication Method for the Test Set

Not applicable, as a new clinical test set requiring expert adjudication for a diagnostic output is not described. The validation focuses on the accuracy of physiological parameter measurements against established standards.

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

No MRMC study was performed or cited. The iBSM system is a physiological monitoring device that provides objective measurements, waveforms, and alerts based on preset parameters. It is not an AI-assisted diagnostic tool that would typically involve human readers interpreting images or data with and without AI assistance to assess an effect size. The chest sensor explicitly states: "The iBSM chest sensor is not intended to be used to provide diagnostic or interpretive statements to either the patient or the clinician."

6. Standalone Performance (Algorithm Only)

The performance described (accuracy of HR, RR, SpO2, Temperature, NIBP) is the "standalone" performance of the device's algorithms for calculating these physiological parameters based on sensor inputs. The acceptance criteria table directly reflects these algorithmic capabilities.

7. Type of Ground Truth Used

The ground truth used for validating the iBSM's performance parameters is implicitly defined by:

• Reference measurement devices/calibrated instruments: This is standard for validating physiological monitoring device accuracy (e.g., a highly accurate reference ECG machine for heart rate, a pulse oximeter for SpO2, a validated sphygmomanometer for NIBP, and a calibrated thermometer for temperature).
• Compliance with international consensus standards: These standards specify accepted methods for determining accuracy and often involve phantom studies or direct comparison with reference methods.

There is no mention of expert consensus, pathology, or outcomes data being used as ground truth for the device's primary physiological measurement functions.

8. Sample Size for the Training Set

The document does not refer to a "training set" in the context of validating a device using machine learning or AI models with a distinct training phase. The iBSM device's core functionality appears to be based on established signal processing algorithms (e.g., Pan-Tompkins beat detection algorithm for HR) rather than deep learning requiring large, labeled training datasets in the manner of medical image analysis AI. The performance is validated through specified accuracy metrics against known physiological ranges.

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

Not applicable, as there is no specifically mentioned "training set" for an AI/ML model for which ground truth would need to be established. The core algorithms for physiological parameter extraction (e.g., ECG waveform display, HR, RR, SpO2 calculation) rely on known signal processing methods and are validated through standard performance tests, not through an AI training paradigm.

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The UbiqVue 2A Multiparameter System is a wireless remote patient monitoring system intended for use by healthcare professionals for continuous collection of physiological data at home and in healthcare settings. This shall include electrocardiography (2-Channel ECG), heart Rate, SpO2%, respiration rate, pulse Rate, photoplethysmography waveform, skin temperature, body posture, body motion, R-R Interval, heart Rate variability (HRV) and blood Pressure (optional). Data is transmitted wirelessly near real time from UbigVue 2A Wearable Biosensor and 3rd party device (for Blood Pressure only) to remote central server for display, storage, and analysis.

The UbiqVue 2A Multiparameter System is intended for non-critical, adult population.

The UbiqVue 2A Multiparameter System shall include the ability to notify healthcare professionals through alerts when physiological parameters fall outside the set limits, manual trigger by the patient and to display multiple patient's physiological data for remote monitoring at home and with visual alarm for active monitoring at hospitals and out-of-hospital patient care settings (such as clinics, outpatient surgery facilities, long-term care facilities and physician offices) in which care is administered by healthcare professionals.

The UbiqVue™ 2A Multiparameter System is similar to LifeSignals Multiparameter Remote Monitoring Platform that is cleared under K202868 but upgraded with monitoring of additional physiological parameters, minor performance improvements and additional User Interface.

The UbiqVue™ 2A Multiparameter System consists of following components:

• 1. UbiqVue™ 2A Wearable Biosensor
• 2. UbigVue™ Single Patient Relay
• 3. UbiqVue™ Multi-Patient Relay
• 4. UbiqVue™ Central Server
• 5. UbiqVue™ Active Monitoring Portal
• 6. UbiqVue™ Relay Bridge Software (optional)
• 7. UbiqVue™ Bluetooth Gateway Software (optional)
• 8. Third-party Blood Pressure device (optional)

The UbigVue™ 2A Wearable Biosensor when attached to body acquires two channels of ECG signals, TTI respiration signals (one of the inputs for deriving Respiration Rate), resistance variation of a Thermistor attached to body (used for deriving Skin Temperature) & accelerometer data (input for deriving Respiration Rate & Posture), pre-processes them and wirelessly transmits to a paired Relay device, as cleared under K202868.

Following are additional features proposed in this submission:

• Ambient temperature sensor for Body temperature derivation.
• Acquisition of PPG (Photoplethysmography) signals using the integrated Optical sensor array.
• Derivation of SpO2% and Pulse Rate within the Biosensor, based on PPG signals acquired through the Optical sensor array.

Biosensor uses standard WLAN (802.11b) secured (AES) communication protocol for wireless data transmission to the Relay Device, as cleared under K202868. The Biosensor is also additionally integrated with BLE Radio for communication with Single Patient Relay device.

As cleared under K202868, when Relay device is available within the wireless range, the acquired data is continuously transmitted to the Relay device immediately. If Relay device is not available or if there is any interruption in the communication between Relay device and Biosensor, data shall be temporarily buffered locally in Biosensor till the wireless connection is re-established.

The UbigVue™ Single Patient Relay Device, a standard Mobile device or custom device that is installed with a UbigVue Single Patient Relay Application software, that receives the physiological data transmitted from any paired Biosensor. It shall transmit the data received from the Biosensor, immediately without any day to Central Server that is configured to receive, after necessary data encryption. The Single Patient Relay Device shall receive data from Biosensor either through WLAN or BLE and transmit it to Central Server using its mobile data network (3G, 4G, LTE, 5G, etc.)
Single Patient Relay Device function is identical to the one cleared under K202868, except it is upgraded to support additional parameters & also improvements in GUI as below:

• To handle additional data packets of Biosensor such as Ambient Temperature, PPG signals. SpO2% and Pulse Rate.
• Interactive GUI that provides feedback to Users about the signal quality of PPG signals to identify the optimal body location for affixing the Biosensor.
• Shall pair with a 3rd party Blood Pressure device using BLE and transfer the data to the Central Server.
• Allows User to enter Oral Temperature reading (for calibration) and/or manual Blood pressure data (optional if no 3td Party device is connected).

The UbiqVue™ Multi-Patient Relay Device (MPR) is an UbiqVue™ Multi-Patient Relay Application Software installed in a standard Linux platform (Physically or in cloud), that has ability to pair & receives data from multiple Biosensors, through wireless access points (WLAN) connected in its network. It shall transmit the received data from Biosensors to Central Server that is configured to receive through internet or private network (VPN), after necessary encryption & authentication. Multi-Patient Relay Device also receives data from multiple third-party Blood Pressure devices worn by the patients & connected to its network (through BLE gateway).

If the Central Server is not available or there is no connectivity, the data shall be temporarily buffered securely in the MPR device itself. There is no GUI component for this software application.

The UbigVue™ Central Server is UbiqVue™ Central Server Application software installed in a compatible Linux Server hardware Platform. The Central Server Application functions are also identical to Secure Server Application in LifeSignals Multi-parameter Remote Monitoring Platform (K202868), other than being upgraded to handle additional parameters. Also, the "Sensor Processing Library", the algorithm that derives various vital parameters is upgraded for performance improvements. The following are additional features:

• Extending the minimum skin temperature measurement capability from 32.0℃ (89.6 °F) to 15.0°C (59.0°F)
• Body Temperature estimation using Skin Temperature, Ambient temperature, Heart Rate (based on clinical condition) and Activity.
• Uses the Oral Temperature entered manually for initial / periodic calibration of derived Body temperature.
• Additional Posture classification & Body motion detection capabilities.
• Improvements in Respiration Rate & Heart Rate derivation algorithm.
• Integration with 3rd Party beat analysis & classification software for deriving Sinus Heart Rate, R-R Interval & Heart Rate Variability.
• The PPG Signal Quality Index (SQI) algorithm module for displaying the SQI on the Active Monitoring dashboard & to access the quality of SpO2 value derived by the Biosensor.
• Support for Early Warning Score (NEWS2) calculation.

Central Server shall have ability to send alert notifications to any configured one or more Users through E-mail, SMS or WhatsApp, for any Clinical, Technical or Manual Alert conditions, as cleared under K202868. However, this alert engine is upgraded to support additional parameters and improved configuration capabilities such as Acknowledgement, priority & condition delay time.

Active Monitoring Portal in UbiqVue™ 2A Multiparameter System is identical to Web UI in LifeSignals Multi-parameter Remote Monitoring Platform cleared under K202868. It is a browser-based User Interface Application that enables Clinical personnel to login to the Central server remotely and access the patient physiological data (Biosensor & derived data) and view/Acknowledge the Alert(s). The Clinical personnel, depending on the roles (normal or supervisory) can access data of multiple patients assigned to them and search them based on the recent alert status. This includes patients that are active (wearing Biosensor) and monitoring procedures completed.
It is in-built with a Monitoring Dashboard that continuously displays physiological parameters, waveforms & alert status of any assigned patients to any authenticated Clinical personnel for (quasi) real time Active Monitoring. It has the option for the User to select multiple patient tile view or Single Patient Zoom View/Hybrid view of any patient based on multiple available filter settings.

Following are the few changes in this 510(k):

• Additional parameters (SpO2%. PR, EWS, SYS, DIA, MAP, PPG, SQI, EWS).
• Visual alarm display for any Clinical, Technical, or manual alert/alarm.
• Hybrid tile view (Zoom View + Tile view) and Group tile view.
• Multi-level User Management, roles & privileges.

Note: Any Third-Party Application / Server may communicate with UbiqVue™ Central Server using a defined set of Application Programming Interface (API) for entering patient information, configuring & generating customized report or any other requirement that does not alter the intended use of the system (e.g., EMR/EHR, HIMS) or to meet the additional intended use claimed by the third-party application. UbigVue™ Active Monitoring Portal shall continue to be used for the claimed Active Monitoring intended use. However, UbiqVue™ Active Monitoring portal may be optional for integration with any other regulatory approved monitoring dashboard or different intended use claims.

Relay Bridge Software in UbiqVue™ 2A Multiparameter System when installed in a standard OpenWrt based routers, shall provide communication between Biosensor(s) & Multi-Patient Relay. Relay Bridge is an alternate for a standard access point and is intended when Multi-Patient Relay Software is hosted in the cloud. Similar to standard access point, the Relay Bridge communicates with multiple Biosensor and transfers the data to the Multi-Patient Relay without buffering the data. Since the Relay bridge transfers the data to the designated Multi-Patient Relay bridge in the cloud, it further encrypts the data for securely transmitting through the internet via ethernet, Wi-Fi or cellular network.

Bluetooth Gateway Software in UbigVue™ 2A Multiparameter System when installed in a standard OpenWrt based BLE gateway or BLE supported routers, shall provide communication between 3rd party BLE devices (e.g. BP device) & Multi-Patient Relay. Bluetooth Gateway communicates with multiple 3rd party devices and transfers the data to the Multi-Patient Relay without buffering.

LifeSignals, Inc. has developed the UbiqVue™ 2A Multiparameter System (UX2550), a wireless remote patient monitoring system. The device collects continuous physiological data including 2-Channel ECG, heart rate, SpO2%, respiration rate, pulse rate, photoplethysmography waveform, skin temperature, body temperature, body posture, body motion, R-R Interval, heart rate variability (HRV), and optionally blood pressure. The system transmits data wirelessly to a remote central server for display, storage, and analysis, and can notify healthcare professionals through alerts. It is intended for non-critical, adult populations in home and healthcare settings.

The following information describes the acceptance criteria and the study conducted to prove the device meets these criteria:

1. Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the exact sample sizes for all test sets. However, it does mention specific studies:

• SpO2% Accuracy: Clinical validation was performed to determine the accuracy of SpO2% with respect to SaO2 values from simultaneously drawn arterial blood as per ISO 80601-2-61 (Ed. 2.0). The specific sample size for this clinical validation is not provided in the summary.
• Body Temperature Accuracy: Validated using "non-randomized, self-control comparative on-body comparative performance with oral digital thermometer on multiple subject populations" in accordance with ISO 80601-2-56 (Ed.2.0). The specific number of subjects or populations is not provided.
• Wear-life Performance: Validated using "non-randomized, self-control comparative on-body comparative performance study for the wear period of 120 hours." The sample size for this study is not provided.
• Respiration Algorithm Improvement: Validated by comparing against "clinician manually scored end tidal CO2 (EtCO2) capnography, under spontaneous breathing & metronome breathing during normal activity conditions as part of wearlife study." The sample size is part of the wear-life study, but not explicitly stated.

Data Provenance: The document does not explicitly state the country of origin for the clinical study data or whether studies were retrospective or prospective. Given the FDA 510(k) submission, it is implied that the data is acceptable for the US market.

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

The document indicates that for the respiration algorithm validation, the comparison was made against "clinician manually scored end tidal CO2 (EtCO2) capnography." This implies that clinicians (experts) were involved in establishing the ground truth. However, the exact number of experts and their specific qualifications (e.g., years of experience, specialty) are not provided.

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method (e.g., 2+1, 3+1, none) for the test sets. For the "clinician manually scored" data mentioned for respiration, it's not specified if multiple clinicians scored and how discrepancies were resolved.

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

There is no mention of a Multi-Reader Multi-Case (MRMC) comparative effectiveness study or any study evaluating the effect size of how much human readers (or healthcare professionals using the device) improve with AI vs without AI assistance. The device is a monitoring system that provides data and alerts, rather than an AI-driven diagnostic interpretation system typically evaluated with MRMC studies.

6. Standalone (Algorithm Only) Performance

The document describes specific performance tests for various parameters (e.g., heart rate, respiration rate, SpO2%, skin temperature, body temperature) that would inherently reflect the algorithm's performance in deriving these parameters from sensor data. For example:

• SpO2% accuracy was proven through "clinical validation to determine the accuracy of SpO2% with respect to SaO2 values from simultaneously drawn arterial blood." This implies a comparison of the device's output (algorithm only) to a gold standard.
• Body temperature accuracy was validated against an "oral digital thermometer."
• Respiration algorithm validation was against "clinician manually scored end tidal CO2 (EtCO2) capnography."

These tests demonstrate standalone performance metrics against established reference standards.

7. Type of Ground Truth Used

The types of ground truth used include:

• Physiological measurements from reference devices/standards:
  • SaO2 values from simultaneously drawn arterial blood (for SpO2% accuracy).
  • Oral digital thermometer (for Body Temperature accuracy).
  • Bench testing standards (e.g., ASTM E1112-00 for skin temperature, ISO 80601-2-61 for Pulse Rate).
• Clinician-established ground truth:
  • Clinician manually scored end tidal CO2 (EtCO2) capnography (for Respiration Rate algorithm).

8. Sample Size for the Training Set

The document does not explicitly state the sample size used for training the algorithms within the UbiqVue™ 2A Multiparameter System. It discusses validation of improved algorithms and additional features, but provides no detail on the development or training phase data.

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

As the document does not provide details on the training set, it does not describe how the ground truth was established for the training set. It primarily focuses on the verification and validation (testing) of the final device/algorithms.

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The BioButton System is a remote monitoring wearable device intended for continuous collection of physiological data in home and healthcare settings while the patient is at rest. This could include heart rate, respiratory rate, skin temperature, and other data such as activity level, body position, sleep, and step and gait analysis.

Data are securely transmitted via wireless connection for storage, review, analysis, and display.

The Device can include the ability to display data and notify healthcare professionals when physiological data fall outside clinician-specified parameters.

The data from the Device are intended as an aid to diagnosis, disease management, and treatment. The Device is intended for use on patients who are 18 years of age or older.

The Device is not intended to output physiological measurements while the patient undergoes significant motion or is active.

The Device is not intended for critical care.

The BioButton System (the "Device") is a wireless remote monitoring system intended for use by healthcare professionals for continuous collection of physiological data in home and healthcare settings while the patient is at rest. This can include heart rate, respiratory rate, and skin temperature. Data are transmitted from the Device for storage and analysis.

The Device is an extension of the Predicate Device (K212957) with the same intended use. The Device consists of a multiple-use and rechargeable wearable hardware sensor module to collect data from a patient and other Medical Device Data System (MDDS) components that enables remote transfer of collected data. The main components of the Device include the following:

1. A wearable sensor to collect data from a patient
2. A device-based Medical Device Data System (MDDS) data gateway to transfer data from the wearable sensor to the cloud
3. A cloud-based Medical Device Data System (MDDS) for data storage and transmission
4. A cloud-based system for configuration of the wearable sensor and data analysis
5. A cloud-based system for healthcare professionals to view patient information

The Device is used to collect physiological information from a patient using the sensor for a set duration (as defined by different use cases) in home and healthcare settings. Physiological data is collected continuously while the patient is at rest. The medical physiological data collected includes:

• Heart rate at rest,
• Respiratory rate at rest, and
• Skin temperature

There are other wellness parameters that can be collected by the device that include: activity level, body position, sleep, and step and gait analysis. These wellness data types are not discussed in detail the regulatory submission since they do not meet the definition of medical device.

Upon completion of a physiological data collection period, the data offload is conducted via wireless Bluetooth connection using the Offload Software. The data offloading is performed and qualified personnel. The Device also provides a web display for healthcare professionals to view patient information.

The provided text is a 510(k) summary for the BioButton System, a remote monitoring wearable device. It describes the device, its intended use, and comparisons to a predicate device, along with performance testing conducted to support substantial equivalence.

Based on the provided text, here's a detailed breakdown of the acceptance criteria and the study that proves the device meets them:

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

The document provides the following performance specifications for the BioButton System:

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The ANNE Chest is a wearable, wireless sensor intended for the measurement of electrocardioaraphy (ECG) waveforms, heart rate, respiratory rate, activity, fall detection, body position, and skin temperature. The ANNE Chest sensor is not intended to monitor or measure respiratory rate while the patient undergoes significant motion or is active. The ANNE Chest sensor communicates with compatible software applications for the display, storage, and analysis of data. The device is intended to provide continuous physiological information as an aid to diagnosis and treatment by healthcare professionals in general care patients who are 12 years of age or older in clinical and home environments. The device is not intended for use on critical care patients.

The ANNE Chest Sensor is a skin-mounted, bio-integrated sensor that collects real-time biosignals including electrocardiography (ECG), 3-axis accelerometry, and temperature to measure vital signs such as heart rate, respiratory rate, body position, fall detection, and skin temperature. The sensor communicates via Bluetooth to the Sibel SDK, which may be integrated within software applications for the display and storage of data. The ECG signal obtained by the ANNE Chest sensor is not intended for manual discrimination of any arrhythmias or cardiac conditions.

The provided document, primarily an FDA 510(k) clearance letter and summary, details the "ANNE Chest" device and its substantial equivalence to predicate devices. It includes performance data, but it does not contain the level of detail typically found in a comprehensive clinical study report for evaluating acceptance criteria and proving device performance for areas like AI/ML algorithms.

Specifically, the document lacks the following information crucial for a detailed response on acceptance criteria and study proving device meets them for AI/ML components:

• Explicit Acceptance Criteria Tables: While performance specifications are listed for heart rate, respiratory rate, and skin temperature, these are not presented as explicit "acceptance criteria" against which the device passed.
• Detailed Study Design for each feature: Only a brief summary of a clinical validation study for respiratory rate accuracy is provided. Details on ECG waveform analysis, activity, fall detection, and body position, if they incorporate AI/ML, are not detailed in terms of their dedicated performance studies.
• Sample Size for Test Set and Data Provenance for all features: Only n=40 is mentioned for respiratory rate. Data provenance (country, retrospective/prospective) is not specified.
• Expert Ground Truth Details: The number and qualifications of experts for establishing ground truth are not mentioned for any of the features.
• Adjudication Method: No information on adjudication is provided.
• MRMC Study Details: No information on multi-reader multi-case studies or effect sizes of human reader improvement with AI assistance is provided.
• Standalone AI Performance: The document describes the device as a sensor measuring physiological signals. It mentions software for display, storage, and analysis, but doesn't explicitly refer to AI/ML algorithms that operate in a "standalone" fashion where their performance metrics (e.g., sensitivity, specificity, AUC) against a ground truth would be relevant. The respiratory rate accuracy is presented as a direct comparison to a reference device.
• Ground Truth Type for all features: Only "End Tidal Carbon Dioxide (EtCO2) monitor reference" is mentioned for respiratory rate.
• Training Set Sample Size and Ground Truth Establishment: No information about training sets or how their ground truth was established is provided, suggesting that the device's functions might rely more on signal processing rather than intricate AI/ML models requiring large training datasets with defined ground truth methods.

Based on the limited information provided in the document, here's what can be extracted and inferred:

Acceptance Criteria and Reported Device Performance

The document provides performance specifications for certain physiological measurements. While not explicitly stated as "acceptance criteria," these are the performance targets the device claims to meet.

Table 1: Reported Device Performance

Note: The document explicitly states: "The ECG signal obtained by the ANNE Chest sensor is not intended for manual discrimination of any arrhythmias or cardiac conditions." This suggests the ECG waveform is for general display and rate calculation, not for specific diagnostic interpretation that might involve AI/ML for abnormality detection.

Study Details Proving Device Meets Acceptance Criteria

1. Sample Size for Test Set and Data Provenance:
* Respiratory Rate: n=40 healthy adult and adolescent subjects.
* Data Provenance: Not specified (e.g., country of origin). The study is described as "a clinical validation study," implying it was prospective for this evaluation.
* Other features (ECG, Heart Rate, Skin Temperature, Activity, Fall Detection, Body Position): No specific sample sizes for clinical validation studies are mentioned, only adherence to standards (e.g., IEC 60601-2-27, IEC 60601-2-47 for ECG) and "performance testing." This suggests these features might have been validated through bench testing or engineering verification rather than clinical studies of the type described for respiratory rate.

2. Number of Experts used to establish Ground Truth and Qualifications:
* Not specified. The ground truth for respiratory rate was an "End Tidal Carbon Dioxide (EtCO2) monitor reference," which is an objective measurement, not expert consensus. For other features, no details about expert involvement for ground truth are provided.

3. Adjudication Method for the Test Set:
* None specified. Given the use of an objective reference device (EtCO2 monitor) for respiratory rate, human adjudication would not be applicable for this specific metric.

4. If a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done:
* No. The document does not describe any MRMC studies or human reader improvement with AI assistance. The device focuses on physiological measurements rather than interpretive tasks for human readers.

5. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:
* Implied for Respiratory Rate accuracy. The study directly compared the ANNE Chest sensor's respiratory rate measurement against a capnography reference, which aligns with standalone performance evaluation for that specific function. For other parameters like heart rate and skin temperature, this is also implied through performance specifications. The device itself is a measurement tool, outputs direct physiological values, and does not describe AI intended for interpretation or decision support that would typically have a human-in-the-loop component.

6. The Type of Ground Truth Used:
* Respiratory Rate: Objective reference standard: "End Tidal Carbon Dioxide (EtCO2) monitor reference."
* Other features: Not explicitly stated, but likely objective measurements from reference devices/standards (e.g., test ECG signals for ECG compliance, calibrated thermometers for skin temperature).

7. The Sample Size for the Training Set:
* Not specified. The document does not indicate the use of machine learning models that would require a distinct training set. The descriptions of the device functions point towards signal processing and known algorithms for extracting vital signs from raw sensor data, rather than complex AI requiring large, labeled training datasets.

8. How the Ground Truth for the Training Set was Established:
* Not applicable based on available information. Since no training set or complex AI model development requiring one is mentioned, this information is not provided.

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ANNE One is a wireless monitoring platform indicated for the measurement of electrocardiography (ECG) waveforms. heart rate, respiratory rate, function of arterial hemoglobin (SpO2), pulse rate, activity, body position, fall detection, skin temperature by qualified healthcare professionals in home and healthcare settings. ANNE One is compatible with third-party, FDA-cleared devices for noninvasive blood pressure, SpO2, pulse rate, and body temperature measurements. The device is indicated for monitoring ECG waveforms and heart rate on ambulatory patients. The device is not intended to monitor or measure respiratory rate. SpO2, pulse rate, or noninvasive blood pressure while the patient undergoes significant motion or is active.

ANNE One continuously monitors the orients to aid in the prevention of pressure ulcers for at-risk patients. The system provides visual notification when the pation has not changed from a preset threshold of time.

The device is intended for use on general care patients who are 12 years of age or older as a general patient monitor to provide continuous physiological information as an aid to diagnosis and treatment. The data from ANNE One are transmitted wirelessly for display, storage, and analysis. The device is not intended for use on critical care patients.

ANNE One is a wireless monitoring platform that streams and stores real-time biosignals including electrocardiography (ECG), photoplethysmography (PPG), 3-axis accelerometry, and temperature to measure vital signs such as heart rate, respiratory rate, SpO2, pulse rate, skin temperature, and body temperature. The ECG signal is not intended for automated arrhythmia detection or classification; rather it is intended for manual interpretation, and the automated computation of heart rate through QRS identification using the well-known Pan-Tompkins beat detection algorithm. The displayed waveform is only intended for display as a check for normal ECG rhythm. The waveform is not intended for manual discrimination of any arrhythmias or cardiac conditions. The system features two skin-mounted, bio-integrated sensors that pair with the ANNE View software application for the continuous display, storage, and analysis of vital sign measurements and physiological waveforms. The system is also compatible with optional FDA-cleared third-party devices for SpO2, non-invasive blood pressure, and body temperature measurements.

Here's an analysis of the acceptance criteria and the studies that prove the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document primarily focuses on demonstrating substantial equivalence to predicate and reference devices, with specific performance values provided for SpO2 and Respiratory Rate from clinical studies. The other parameters are stated to meet relevant standards or are equivalent to predicate/reference device performance.

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

• SpO2 Accuracy Study:

  • Sample Size: n=12 healthy subjects.
  • Data Provenance: Not explicitly stated (e.g., country of origin), but implies a controlled clinical setting. The study is described as "Sibel validated the accuracy...".
  • Retrospective/Prospective: Implied prospective as it's a validation study conducted by Sibel.

• Respiratory Rate Accuracy Study:

  • Sample Size: n=40 healthy adult subjects.
  • Data Provenance: Not explicitly stated (e.g., country of origin), but implies a controlled clinical setting. The study is described as "Sibel validated the accuracy...".
  • Retrospective/Prospective: Implied prospective as it's a validation study conducted by Sibel.

• Other Parameters: For other parameters like Heart Rate, ECG waveform display, Activity, etc., "performance testing" and adherence to "consensus standards" are mentioned, but specific sample sizes for these test sets are not provided in this summary. The comparison table also mentions "ambulatory databases" for ECG during motion, but no sample size is given.

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

• SpO2 Accuracy Study: Ground truth was established by "blood gas analysis." This typically involves laboratory analysis, not expert consensus on visual assessment.
• Respiratory Rate Accuracy Study: Ground truth was established by "etCO2" (end-tidal CO2). This is a physiological measurement, not an expert consensus.
• Other Parameters: No information is provided regarding experts or their qualifications for establishing ground truth for other parameters. Ground truth for these values would likely derive from established measurement techniques compliant with the referenced standards.

4. Adjudication Method for the Test Set

• Given that the ground truth for SpO2 and Respiratory Rate relied on objective physiological measurements (blood gas analysis and etCO2, respectively), there was likely no "adjudication method" in the sense of reconciling disagreements between multiple graders or clinicians. The measurements themselves serve as the ground truth.

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 involving human readers and AI assistance is mentioned in the provided text. The device is a "wireless monitoring platform" for physiological measurements. Its primary function is to collect and display vital sign data, not to interpret complex medical images or data that typically require a human reader for adjudication or enhancement by AI.

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

• Yes, the performance data provided for SpO2 and Respiratory Rate are standalone algorithm capabilities. The device measures these parameters and the reported accuracy is the algorithm's performance against a reference standard, without human intervention in the measurement or calculation process. The description of "automated computation of heart rate through QRS identification using the well-known Pan-Tompkins beat detection algorithm" also indicates a standalone algorithmic function.

7. The Type of Ground Truth Used

• SpO2: Blood gas analysis (objective physiological measurement).
• Respiratory Rate: EtCO2 (objective physiological measurement).
• Heart Rate: Implied to be derived from ECG signals, with validation against established standards (e.g., IEC 60601-2-27, IEC 60601-2-47), which would use a recognized reference for HR. The Pan-Tompkins algorithm is for beat detection, which is then used to compute HR.
• Other Parameters (Skin Temperature, Body Position, Activity, ECG Waveform Display, Pulse Rate): Ground truth is likely established through a combination of physical reference measurements and adherence to recognized consensus standards (e.g., ISO, IEC). Bench testing is mentioned for several parameters.

8. The Sample Size for the Training Set

• The document does not explicitly state the sample size for any training set for machine learning models. The device description mentions the use of "the well-known Pan-Tompkins beat detection algorithm" for heart rate, which is a classical signal processing algorithm and may not require a 'training set' in the modern machine learning sense. While algorithms are likely involved in respiratory rate and SpO2 calculations, the summary focuses on validation, not the development or training phase.

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

• As training set information is not provided, the method for establishing its ground truth is also not detailed.

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The function of the device is the acquisition and transmission of the ECG signal in order to support diagnosis of the patient's conditions.

HD+ is a wireless or USB (with appropriate option) ECG acquisition device, to be used primarily as common front-end for standard PC/tablet platforms (Windows/MAC OS/others), for resting ECG applications.

The device implements wireless communication vireless technology or wired with USB communication. With both connection modes, HD+ sends the data to the receiver device without performing any analysis or filtering. HD+ is not intended for monitoring of the cardiac function or to diagnose the patient's health condition. Display, print and analysis applications on the receiver device are separate products. HD+ is not able to permanently store the acquired data, therefore it does not work unless a connection has been established with a receiver application. Furthermore, HD+ does not collect any of the patient's name, age, previous health conditions etc.).

HD+ detects the QRS complexes and transmit the receiving device. The QRS detection function is intended for patients aged 12 years or older.

*HD+ is indicated for the acquisition of ECG signals with the patient in resting conditions, for example for diagnostic ECG's and rhythm strips

*HD+ is suitable for working at high altitudes, with restrictions.

*HD+ is intended for use on patients, with no limits of age or gender, except for the HR detector function which is intended for patients 12 years or older

• HD+ is intended for use in medical facilities (hospitals, clinics), at home or emergency settings (ambulances).

*HD+ is intended for use by a physician, nurse or other healthcare professional (e.g., ECG technician) who acts following orders by a physician or authorized nurse, including when operated in home environments

*HD+ is not intended for real-time monitoring of vital physiological parameters.

HD+12 and HD+15 are the new revisions of Cardioline's HD+ wireless acquisition module. The HD+ is a digital portable acquisition device which can acquire the electrocardiographic signal of 12 and 15 standard leads. Connected with a receiver via Bluetooth or USB (with the optional USB connector), the HD+ performs no analysis or filtering but sends acquired data to a host application where the User Interface is implemented. By default, the device includes a demo compatible software "HD+ Display" whose purpose is providing a UI for viewing the traces acquired by HD+. HD+ Display provides a simple UI, sufficient to configure the application to connect to an HD+ device via Bluetooth (the application automatically detects if an HD+ device is connected via USB and does not require additional configuration) and sufficient to display the ECG traces as received by HD+. HD+ Display does not provide any clinical functionality; therefore, it does not provide any capability to store, print or analyze the acquired ECG.

lt is the host (PC or Tablet separated by HD+) which performs the analysis. HD+ is not intended to control or analysis heart function and/or to diagnose the patient's health status. The analysis program on the host is a separate product not marketed with the HD+.

HD+ is a wireless acquisition device, to be primarily used as ECG front-end acquisition device for PC/tablet (Windows/MAC OS/Android/iOS/others) standard platforms for Resting ECG applications. Depending on performance/price ratio, HD+ could be also used with selected embedded electrocardiographs. HD+ allows the patient to be ambulatory.

HD+ uses a standard Bluetooth data transmission technology to transmit 12-lead and 15-lead ECG data over a proximity range, providing electrical insulation and freedom of movement for the patient. The device implements the wireless communication via Bluetooth wireless technology. The Bluetooth radio protocol is implemented by a dedicated module, FCC compliant. In order to support the data transmission speed of the application, the device implements the BLE 5 protocol with DLE (Data Length Extension) and 2M PHY (bandwidth up to 2 Mbit/s). The minimum specifications of the device connected to HD+ is BLE 4.2 to support the band required by acquisitions at 500 s/s. In order to operate at 1000 s/s, the connected device must be BLE 5.0 (or higher) and have a compatible 2M PHY radio (2 Mbit/s). Alternatively, in addition to Bluetooth connectivity described above, the HD+ has an optional USB interface that can be used to transmit data. The USB interface provides an electrical insulation offering two means of patient protection (2MPP), allowing HD+ to be connected to any IT equipment conforming to IEC 62368-1.

The HD+ function consists of acquiring and transmitting ECG signals for display processing ECG signals for the purpose of supporting the diagnosis of patient conditions. The device does not store nor does it associate patient identification data to the acquired signal, nor does it perform analysis on such signal. The HD+ is used solely for transmission of ECG signals from patient to a host analysis platform.

The HD+ transmits a continuous stream of ECG samples at a rate of 500 s/s or 1000 s/s, with a resolution of 0.817 uV/LSB or 2.495 uV/LSB, selectable by the calling application of the host analysis platform. The average required transmission throughput for sending 15 leads at 1000 s/s is approximately 155kbit/s, while to send 12 leads at 500 s/s the required throughput is approximately 54 kbit/s. BLE 5 2M PHY provides the bandwidth needed to support the maximum required throughput.

The BLE communication link ensures that data is either received correctly or not received at all. It is up to the host application to detect packet losses, handling the data gaps appropriately (e.g. by filling the stream with invalid dummy samples, signaling transmission errors etc...). This approach has been preferred over enabling the data retransmission (supported by the module) to reduce the data iitter and transmission delay.

HD+ uses standard 12 lead or 15 lead ECG cables to acquire the physiological signal from the patient. HD+ is light and compact, comfortable to wear, minimizing motion artifacts caused by traditional electrodes and patient cables.

HD+ offers full ECG acquisition - meeting the standards used in clinical and diagnostic applications (AAMI, ANSI, AHA, ACC). HD+ uses a LED indicator to comfortably monitor the link status (off when unit is powered down, blinking when unit is attempting to connect with the receiver, steady when unit is connected with the receiver). HD+ uses a programmable key to send macro commands to the receiving system (i.e. acquire and print an ECG). Low-power technology allows continuous usage of the device for more than 10 hours (from full battery charge).

The HD+ continuously transmits the acquired data to a computer platform where compatible software, a Host Application authorized by Cardioline, is installed that acts as its User Interface. As an example of such Host Application, the device includes a compatible demo Windows application "HD+ display" from Cardioline to visualize the ECG traces and check the functionality of the results of the analysis must always be validated by qualified, trained medical personnel and the HD+ is intended for use in a medical environment. HD+ is intended to be used on adult and all pediatric patients. The device must be handled with care by taking all the necessary precautions in order to prevent and avoid shocks, vibrations, heat sources, liquids and anything else that may damage it.

The provided text is a 510(k) summary for a medical device (Cardioline HD+12, HD+15), which is a premarket notification to the FDA to demonstrate that the device is substantially equivalent to a legally marketed predicate device. This type of submission focuses on demonstrating equivalence rather than proving a device meets specific acceptance criteria through a clinical study in the way an AI/ML algorithm might.

Therefore, the document does not contain details about acceptance criteria or a study proving the device meets those criteria, especially in the context of an AI/ML algorithm's performance. The device described in the document is an ECG signal acquisition and transmission device, explicitly stating that it "sends the data to the receiver device without performing any analysis or filtering" and "is not intended for monitoring or analysis of the cardiac function or to diagnose the patient's health condition." It also mentions that "clinical evaluation is not required" because it's an acquisition device without analysis, diagnosis, or monitoring features.

However, I can extract information related to performance testing conducted to support the substantial equivalence claim, which serves a similar purpose to meeting acceptance criteria for a non-AI/ML device.

Here's an analysis based on the provided text, while acknowledging that it doesn't align with the detailed AI/ML study requirements in the prompt:

Acceptance Criteria and Device Performance (for a non-AI/ML acquisition device)

The document primarily focuses on demonstrating that the new devices (HD+12, HD+15) are substantially equivalent to a predicate device (HD+) by showing adherence to relevant standards and similar performance characteristics. The "acceptance criteria" here are essentially compliance with safety and performance standards for a physiological signal acquisition device.

1. Table of Acceptance Criteria (based on standards compliance and comparative features):

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Alio is a wireless remote monitoring system intended for use by healthcare providers (HCP) to collect physiological data in clinical and non-clinical settings. The data includes measured hemoglobin (Hgb) and hematocrit (Hct), skin temperature, auscultation sound data, and heart rate. Data is transmitted wirelessly from the SmartPatch wearable sensor to a web-based portal for the HCP's review.

The data also include a qualitative indicator of abnormal levels of potassium derived from relative variability of photoplethysmography waveforms and medically accepted threshold values.

Alio is intended for use on general care patients who are 18 years of age or older. The SmartPatch sensor is indicated to provide measurement of heart rate, skin temperature, Hgb, Hct and a qualitative risk assessment of the patient having an abnormal potassium level. The SmartPatch sensor is indicated to record and transmit auscultation sound data. For qualitative assessment of abnormal potassium levels, and quantitative measurement of heart rate, skin temperature, Hgb and Hct, the SmartPatch should be placed on an arm based arteriovenous access on patients with end stage kidney disease (ESKD).

Alio is a secondary, adjunct patient monitor and is not intended to replace existing standard-of-care patient monitoring practices. Therapeutic management decisions, including management of dyskalemia, should be made based on a complete assessment of the patient's condition and should not be based solely on Alio.

Alio is a wireless remote monitoring system intended for use by healthcare providers (HCP) to collect physiological data in clinical and non-clinical settings. Alio is intended to be used on general care patients and patients with end stage kidney disease (ESKD), who are 18 years of age or older in clinical and non-clinical settings. Alio includes the following components:

Alio SmartPatch: The Alio SmartPatch is a flexible, silicone-encased patch designed to be worn between the cannulation sites of the arteriovenous (AV) fistula or graft for up to seven days. It houses numerous sensor technologies which collect data for the derivation of physiologic parameters including hemoglobin, hematocrit, an assessment of normal or abnormal (hyper or hypokalemic) levels of serum potassium (K+), skin temperature, auscultation sound data, and heart rate. The data from the sensors is transmitted from the SmartPatch to the Alio Hub via a bluetooth connection. The data is then transmitted to the Alio Cloud, via the Alio Hub, where it is analyzed and made available to a clinical care team via the Alio Portal.

Alio Hub: The Alio Hub is designed for use in clinical and non-clinical use settings. It automatically communicates with the activated Alio SmartPatch via Bluetooth and uploads physiological data to the Alio Cloud via cellular connection.

Alio Cloud: The Alio Cloud allows clinicians to access patient data collected via the Alio SmartPatch and wirelessly transferred from the Alio Hub to the secure server (the Alio Cloud).

Alio Portal: The Alio Portal stores data received from the Alio Cloud database that supports storage, analytics, system monitoring and visualization capabilities. This data is encrypted and HIPAA compliant. The Alio Portal also serves as the interface with the HCP who can then visualize and interact with data being generated by the system.

The provided text describes the Alio device, its intended use, and summaries of non-clinical and clinical testing performed for its 510(k) submission (K223073).

Unfortunately, the provided text does not contain the specific acceptance criteria or detailed study results (like sensitivity, specificity, accuracy metrics with confidence intervals for Hgb, Hct, or potassium levels) in a format suitable for a table of acceptance criteria vs. device performance. It broadly states that the device "meets its design requirements and intended use" and "can accurately assess abnormal potassium levels and measure hemoglobin (Hgb) and hematocrit (Hct)."

Therefore, I cannot directly provide a table of acceptance criteria and reported device performance as requested. I can, however, extract and summarize the other requested information based on the provided text.

Here's a summary of the available information regarding the Alio device's clinical study:

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

• Acceptance Criteria: Not explicitly stated in the provided text. The document indicates that the device "meets its design requirements and intended use" and "can accurately assess abnormal potassium levels and measure hemoglobin (Hgb) and hematocrit (Hct)." However, specific numerical thresholds for accuracy, sensitivity, or specificity as acceptance criteria are not detailed.
• Reported Device Performance:
  • The study "establish[ed] the accuracy of Alio in the assessment of abnormal potassium levels, and measurement of Hgb and Hct, compared to the standard of care blood results and heart rate."
  • "The results of the study demonstrate that Alio can accurately assess abnormal potassium levels and measure hemoglobin (Hgb) and hematocrit (Hct) when placed on an arteriovenous access site in patients with ESKD."
  • "The results further confirm that Alio can still accurately measure heart rate and record auscultation sound data at the new location."
  • No specific performance metrics (e.g., mean absolute error, correlation coefficients, sensitivity, specificity, AUC) or their numerical values are provided in this summary document.

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

• Sample Size for Test Set: 125 subjects.
• Data Provenance:
  • Country of Origin: Not explicitly stated, but the study was described as a "multicenter, prospective study." Given the FDA submission, it's highly likely to be U.S.-based, but this is an inference, not a direct statement.
  • Retrospective or Prospective: Prospective. The text states: "An IRB-approved clinical study has been conducted to validate the ability of Alio to quantify the new measurements and support the proposed expanded indications. Alio was studied in a multicenter, prospective study with 125 subjects."

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 text. The ground truth was established by "standard of care blood results" for Hgb and Hct, and for abnormal potassium levels, but the expertise involved in interpreting these and deriving final ground truth labels is not specified.

4. Adjudication method for the test set

• This information is not provided in the text.

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, a multi-reader, multi-case (MRMC) comparative effectiveness study was not described. The study focused on the accuracy of the device in assessing physiological parameters compared to standard of care, not on human reader performance with or without AI assistance. The device is described as a "secondary, adjunct patient monitor," suggesting it aids, but does not necessarily directly compare, human diagnostic performance.

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

• Yes, the described study appears to be a standalone performance evaluation of the Alio device's algorithm. The "AI/ML algorithm used in the calculation of the new physiologic parameters" is specifically mentioned. The study assessed the device's ability to "accurately assess abnormal potassium levels, and measure hemoglobin (Hgb) and hematocrit (Hct)" against "standard of care blood results." This implies the algorithm's output was directly compared to ground truth, which is characteristic of a standalone study.

7. The type of ground truth used

• For Hemoglobin (Hgb) and Hematocrit (Hct): "standard of care blood results."
• For Abnormal Potassium Levels: "standard of care blood results." The study objective was to establish accuracy compared to "standard of care blood results."
• For Heart Rate: "standard of care blood results" (implied as part of the comparison, though usually heart rate ground truth comes from ECG or other direct measurements). The text states "compared to the standard of care blood results and heart rate," which might imply different methods for heart rate ground truth.
• The study stated it evaluated patients within "defined Hgb and Hct reference ranges (7-15 g/dL Hgb, 21-45% Hct)." This suggests quantitative comparison with clinical lab values.

8. The sample size for the training set

• The sample size for the training set is not provided. The text only mentions the clinical study for validation (test set) with 125 subjects. The AI/ML algorithm's training data is not described.

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

• This information is not provided, as the training set details are absent from this summary.

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The Care Team Portal is intended to support management of health conditions. It allows a clinical user to configure the collection of patient data. The Care Team Portal includes the ability to notify the patient and the clinical user when the parameters fall outside set limits and customize patient specific recommendations.

Vivify Remote Patient Monitoring consists of the Care Team Portal, patient portals, and accessory devices.

The Care Team Portal allows the clinical user to view and manage patient information. The functionality includes the ability to add new users and patients, ability to schedule video visits, secure in-app messaging, configure the collection of patient data leveraging care pathways survey questions, educational content and videos with customized notifications, and prioritize patients. It provides a dashboard view of the patients being monitored.

The patient portals enable the patient to provide subjective symptom or health status information that assists the care team in supporting the management of health conditions:
+Home is an option that provides the patient with software pre-loaded on a tablet that allows them to navigate through care pathways for the collection of patient data and view educational content related to their health condition.
+Go is designed for patients to download the software to their own mobile device to navigate through care pathways for the collection of patient data and delivery of educational content related to their health condition.
+Voice allows patients to answer their pathways questions and enter data using their phone.

Accessory devices can be connected to the system to allow for collection of vital signs or used independently to allow for manual input.

The provided text does not contain information about acceptance criteria and a study that proves a device meets those criteria for an AI/machine learning medical device.

The document discusses the Vivify Health, Inc. Care Team Portal, which is a Remote Patient Monitoring System. This system is software-only and designed to help clinical users manage health conditions by configuring the collection of patient data, notifying them when parameters fall outside set limits, and customizing patient-specific recommendations.

The 510(k) summary compares the Vivify Care Team Portal to a predicate device, the Philips (Visicu) eCare Coordinator (K171029). The document states that clinical studies were not required to demonstrate substantial equivalence, and that the device was verified and validated through internal functional, system-level, and usability testing.

Therefore, none of the specific questions regarding acceptance criteria for an AI device, sample sizes, expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance can be answered from this text. The document explicitly states: "Clinical studies were not required to demonstrate substantial equivalence of the Care Team Portal." and "Results from internal verification and validation testing established that the device meets its design requirements and intended use, that it is as safe, as effective, and performs as well as the predicate devices, and that no new questions of safety and effectiveness were raised."

This suggests that the "Care Team Portal" is primarily a data management and notification system, rather than an AI-driven diagnostic or prognostic tool that would typically require the detailed performance studies you've inquired about.

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The BioButton System is a remote monitoring wearable device intended for continuous collection of physiological data in home and healthcare settings while the patient is at rest. This could include heart rate, respiratory rate, skin temperature, and other data such as activity level, body position, sleep, and step and gait analysis.

Data are securely transmitted via wireless connection from the device for storage, review, and further analysis.

The data from the device are intended as an aid to diagnosis, diseases management, and treatment.

The device is intended for use on users who are 18 years of age or older.

The device is not intended to output physiological measurements while the user undergoes significant motion or is active.

The device is not intended for critical care.

The BioButton System is a wireless remote monitoring system intended for use by healthcare professionals for continuous collection of physiological data in home and healthcare settings while the patient is at rest. This can include heart rate, respiratory rate, and skin temperature. Data are transmitted from the BioButton for storage and analysis.

The BioButton System (the System), is an extension of the BioSticker System with the same/similar intended use. The System is intended to monitor physiological parameters of the patient/users for relatively long duration (up to 60 days with medical data collection). The System should now enable the connectivity with the BioButton sensor device (BBN) with the rest of the system components.

The BioButton System consists of a single-use wearable hardware sensor module to collect data from a patient and other Medical Device Data System (MDDS) components that enables remote transfer of collected data. See main components of the BioButton System. The main components of the BioButton System could include the following:

• BioButton Sensor -
• -BioButton adhesives (accessory)
• Data Exchange Hubs (MDDS) -
• -Cloud-based data platform (MDDS)

The BioButton System is used to collect physiological information from a patient using the BioButton Sensor for a set duration (as defined by different use cases) in home and healthcare settings. Physiological data is collected continuously while the patient is at rest¹. The medical physiological data collected includes:

• . Heart rate at rest,
• . Respiratory rate at rest, and
• Skin temperature

¹ "At Rest" means the device will not output measurement data to the user undergoes significant motion or is active.

There are other wellness parameters that can be collected by the device that include: activity level, body position, sleep, and step and gait analysis. These wellness data types are not discussed in detail the requlatory submission since they do not meet the definition of medical device.

Upon completion of a physiological data collection period, the data offload is conducted via wireless Bluetooth connection using the Offload Software. The data offloading is performed and qualified personnel. Also using the Offload Software, a report will be generated to be viewed by a healthcare professional. The report is not intended to be viewed by the patient.

The provided text describes the BioButton System, a remote monitoring wearable device, and its acceptance criteria as part of a 510(k) submission to the FDA. The information focuses on demonstrating substantial equivalence to a predicate device (BioSticker System K191614).

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

1. Acceptance Criteria and Reported Device Performance

The acceptance criteria for performance are clearly stated in the "Performance / Effectiveness" section (page 8).

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