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The Biobeat BB-613-BPM is a noninvasive blood pressure monitor which provides a notification to the user every 15 minutes over a 24 hour period for user- initiated measurements. It includes a device and a platform (BPM) for use in adults by healthcare professionals, for collection of pulse rate and tracking changes in blood pressure based on Pulse Wave Transit Time (PWTT) in hospitals, clinics, long-term care and at home. The BB-613-BPM tracks changes in blood pressure and requires callbration using an FDA-cleared oscillometric blood pressure monitor. The data from the Biobeat BB-613-BPM can be accessed through the Biobeat platform for review by a healthcare professional or can be downloaded as a report. The device is not intended to be used on critical care patients.

The Biobeat BB-613-BPM includes a sensor device that is attached to the patient's chest to collect physiological data for later review by their healthcare provider. The device is designed to measure systolic and diastolic blood pressure and pulse rate, in adults, using a noninvasive technique using a light source (LEDs), and sensor array on the backside of the device. Identical to the method cleared in K190792 and in K222010, the LEDs transmit light into the subject's skin and part of this light is reflected from the tissue and detected by a photo-diode. This allows measurement of pulse rate, and noninvasive blood pressure. The device is a pre-programmed 24-hour blood pressure monitor (BPM), prompting the use to take measurements at fixed intervals every 15 minutes. In addition, the data is transmitted to a mobile application via Bluetooth and then uploaded to the cloud, accessed through the Biobeat platform for review by a healthcare professional. In addition, the data could be downloaded as a report. The device does not contain any alarms. The device is intended to be used by healthcare professionals and patients in clinical and patient's environments.

The provided text is a 510(k) summary for the Biobeat BB-613-BPM. It outlines the device, its indications for use, technological characteristics, and a comparison to predicate devices, ultimately concluding substantial equivalence. However, it does not contain specific details about acceptance criteria, the study design (e.g., sample size, data provenance, expert qualifications, adjudication methods), or performance data results that would be typically found in a clinical study report.

The document explicitly states: "The Biobeat BB-613-BPM uses the same hardware as the cleared Biobeat Platform-2 and the BB-613WP Patch but features some software changes. The device contains the same sensor unit and uses the same algorithm to compute pulse rate and blood pressure. Therefore, these signals' evaluation testing, which was submitted in K222010 and K190792, remains applicable to the subject device. Additional testing was conducted on the updated product features, including: . Software validation per FDA guidance..."

This indicates that the primary focus of the new submission (K241066) was on software validation for the new feature (24-hour, patient-initiated measurements with notifications), rather than extensive new clinical performance studies for blood pressure or pulse rate accuracy, as those were already established for the predicate devices utilizing the same sensor unit and algorithm.

Therefore, many of the requested details about a study proving the device meets acceptance criteria are not present in the provided text. I will answer based on the information that is available.

Here's an attempt to answer your questions based only on the provided text, flagging where information is missing:

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

The document provides a comparison table of technological characteristics, including measurement ranges and accuracies, which can be interpreted as performance specifications inherited from the predicates and serving as acceptance criteria.

Note: The document states, "The device contains the same sensor unit and uses the same algorithm to compute pulse rate and blood pressure. Therefore, these signals' evaluation testing, which was submitted in K222010 and K190792, remains applicable to the subject device." This implies that the BB-613-BPM is expected to meet the same accuracy standards as its predicates for PR and BP. The primary new "performance data" mentioned is "Software validation per FDA guidance."

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

• Sample Size: Not specified in this document. The document refers to prior testing for pulse rate and blood pressure (from K222010 and K190792) and software validation.
• Data Provenance: Not specified.
• Retrospective/Prospective: Not specified.

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)

• This information is not applicable or not provided. The ground truth for blood pressure and pulse rate measurements in medical devices like this is typically established using established reference methods (e.g., intra-arterial measurements, or a validated oscillometric device for calibration as mentioned in the Indications for Use). Expert readers are typically not used to establish ground truth for physiological measurements like BP or PR.

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

• This information is not applicable or not provided, as this is not a study involving human reader interpretation or 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, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted or reported in this document. This type of study is relevant for AI systems that aid human interpretation (e.g., radiology AI), which is not the primary function described for this blood pressure measurement system's new feature.

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

• The document implies that standalone performance for pulse rate and blood pressure was established and deemed acceptable in prior submissions (K222010 and K190792) because the subject device uses the "same sensor unit and uses the same algorithm to compute pulse rate and blood pressure." The new submission focuses on software changes related to the 24-hour monitoring feature and notifications, rather than core measurement algorithm performance.

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

• For blood pressure and pulse rate measurements: The Indications for Use state, "The BB-613-BPM tracks changes in blood pressure and requires calibration using an FDA-cleared oscillometric blood pressure monitor." This strongly suggests that an FDA-cleared oscillometric blood pressure monitor serves as the ground truth or reference method for calibration and presumably for performance validation in the previous submissions.

8. The sample size for the training set

• Not specified. This document only pertains to a 510(k) submission, not a full scientific publication detailing model development.

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

• Not specified. As noted above, the ground truth for physiological measurements typically involves comparison to a gold standard or reference method. However, details of the training set (if any specific to this submission's new features beyond the core algorithm) are not provided. The phrase "pre-programmed" suggests the algorithms are fixed, not adaptively learning from ongoing data.

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

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

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

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

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

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

Here's an organized breakdown of the requested information:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

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

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

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

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

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

4. Adjudication Method for the Test Set

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

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

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

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

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

7. The Type of Ground Truth Used

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

8. The Sample Size for the Training Set

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

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

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

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The Alio Medical Remote Monitoring System is a wireless remote monitoring system intended for use by healthcare professionals to intermittently collect physiological data in home use settings. The data includes skin temperature, auscultation sound data and heart rate. Data is transmitted wirelessly from the SmartPatch wearable sensor to a web-based portal for the healthcare provider's (HCP) review.

The Alio Medical RMS is intended for use on general care patients who are 18 years of age or older. The SmartPatch sensor is indicated to measure skin temperature and pulse rate where clinically indicated. The SmartPatch sensor is indicated to record and transmit auscultation sound data where clinically indicated.

The device is not intended for use in critical care or other high-acuity environments. The Alio Medical RMS is a secondary, adjunct patient monitor and is not intended to replace existing standard-of-care patient monitoring practices.

Alio Medical Remote Monitoring System, or "Alio Medical RMS", utilizes a wearable device (SmartPatch) on the skin to gather physiological data and then transmits it to a device (Bedside Hub) located in the subject's home. The Bedside Hub then relays this raw data to the Alio Medical Cloud where it is processed and analyzed using Alio's proprietary algorithms. Data is accessible to Healthcare Professionals and the Alio clinical team via a web-based Clinician Portal. The SmartPatch and Bedside Hub are intended to be used on general care patients who are 18 years of age or older in a non-clinical environment. The web-based Clinical Portal is to be used by healthcare professionals in an office environment.

The Alio Medical Remote Monitoring System includes the following components:

• SmartPatch
• Bedside Hub
• Alio Medical Cloud (backend only - not user facing)
• Clinician Portal

SmartPatch: A flexible, silicone-encased patch that can be worn where clinically indicated for up to seven days at a time. It houses numerous sensor technologies, which include a microphone, accelerometer, temperature sensors, and a PPG sensors collect physiological data including skin temperature, auscultation sound data, and heart rate. Data is transmitted to the Cloud, via the Hub, where it is analyzed and sent to a Healthcare Professional via the Web Portal.

Bedside Hub: The Bedside Hub has the form and finish of an at-home device. It automatically communicates with the activated SmartPatch and uploads physiological data to the Alio Medical Cloud.

Alio Medical Cloud: The Cloud features a database that supports storage, analytics, system monitoring and visualization capabilities. The Alio Medical Cloud is encrypted and HIPAA compliant. All patient data is fully traceable to device and patient ID via the database.

Clinician Portal: The Clinician Portal is the interface tool between a user (healthcare professional users only) and the system that enables the user to visualize and interact with data being generated by the system.

The provided text is a 510(k) summary for the Alio Medical Remote Monitoring System. It details the device's indications for use, components, and a comparison to predicate and reference devices, as well as listing compliance with various safety and performance standards. However, it does not contain the specific acceptance criteria or the study data that proves the device meets those criteria.

The section titled "9. Performance Data" states that "Nonclinical verification and validation test results 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 issues of safety and effectiveness were raised." It also mentions "extensive safety and performance testing as shown in the test results provided in this submission."

Despite these statements, the actual acceptance criteria, reported device performance (e.g., accuracy metrics for heart rate or temperature), sample sizes, ground truth establishment, or details of a multi-reader multi-case study are not included in this summary. The summary focuses on regulatory compliance and substantial equivalence argument rather than detailed performance study results against specific criteria.

Therefore, I cannot populate the requested table and answer many of the questions based solely on the provided text. To fulfill the request, one would need access to the full submission documents, specifically the detailed performance study reports.

Based on the provided text, the following information is available (and what is not):

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

• Not provided in the text. The text only generally states that "the device meets its design requirements and intended use." Specific numerical acceptance criteria for measured parameters (skin temperature, auscultation sound, heart rate) and corresponding achieved performance values are absent.

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

• Not provided in the text. The text mentions "extensive safety and performance testing" but does not specify the sample sizes of patients or data points for any performance tests. Data provenance is also not mentioned.

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

• Not provided in the text. No information about expert involvement in establishing ground truth is present.

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

• Not provided in the text. No details on adjudication methods for test sets are mentioned.

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/Not mentioned. The device described is a "remote monitoring system" that collects physiological data for review by HCPs. It is not an AI-powered diagnostic imaging device typically subject to MRMC studies comparing human reader performance with and without AI assistance. The text does not describe any AI component that directly assists in human interpretation or diagnosis.

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

• Partially inferred/Limited information: The system uses "Alio's proprietary algorithms" to process and analyze raw data in the Alio Medical Cloud. While a standalone algorithm performance evaluation would logically be done internally to ensure accuracy of processed data (heart rate, temperature, sound data), the detailed results of such a standalone performance or how its accuracy was quantitatively measured against a gold standard are not provided in this summary. The stated function is to transmit data for HCP review, implying the algorithm's role is data processing rather than a standalone diagnostic output.

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

• Not provided in the text. The method for establishing ground truth for any measurements (e.g., a clinically validated temperature probe for skin temperature, or a gold standard ECG for heart rate) is not detailed.

8. The sample size for the training set:

• Not applicable/Not provided. While the system uses "proprietary algorithms," the document does not explicitly state that these algorithms are machine learning models requiring "training sets" in the typical sense. Even if they are, the training set size is not mentioned.

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

• Not applicable/Not provided. As with the training set itself, the method for establishing ground truth for any potential training data is not mentioned.

In summary, the provided 510(k) summary serves as a high-level overview for regulatory purposes, demonstrating substantial equivalence. It does not delve into the detailed technical performance study results, acceptance criteria, or statistical validations typically found in comprehensive study reports.

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