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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 SimpleSENSE Platform is intended for use at home, or at a healthcare facility, under the direction of a licensed medical professional, to record, display and store the following physiological data: a) 2 leads of Electrocardiogram; b) Respiration rate measured through thoracic impedance; c) Heart Sounds; d) Activity including posture; and e) other validated data sources. The SimpleSENSE Platform is intended for use when the licensed medical professional decides to evaluate the physiologic signals of adult patients as an aid to diagnosis and treatment. The SimpleSENSE Platform is intended to be used by patients at rest and not performing any activities or movements. ECG recordings are indicated for the manual assessment of cardiac rhythm disturbances. The SimpleSENSE Platform does not produce alarms and is not intended for active patient monitoring (real-time). The SimpleSENSE Platform is not intended for use as life supporting equipment on high-risk patients such as critical care patients. The SimpleSENSE Platform is not intended for use in the presence of a pacemaker.

The Nanowear SimpleSENSE Platform is the next generation diagnostic monitoring technology that captures electrocardiographic (ECG) signals, respiration rate though thoracic impedance, heart sounds, activity including posture and movement with sensors embedded on a wearable textile garment. The signals are stored and wirelessly transmitted to a smartphone, which is then forwarded to a medical professional for review. The garment is designed to be unobtrusive to everyday activity and provide an easier and more efficient means of capturing ECG data from patients. The device consists of a combination of: The SimpleSENSE Garment: an integrated network of nanosensor electrodes for measuring ECG and respiratory rate from thoracic impedance. A MEMS microphone for measuring heart sounds. The SimpleSENSE Signal Acquisition Unit (SAU): data acquisition, storage, and transmission to a phone running iOS or Android. An accelerometer to measure activity. The SimpleSENSE Mobile Application: mobile application to start/stop a recording, logging symptoms, and data transmission. SimpleSENSE Web Server: allows initiation of a test, storage, and review of prescribed test data by a medical professional.

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

Here's an analysis based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

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

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

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

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

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

The document does not provide any information about the number or qualifications of experts used to establish ground truth for the test set, as the performance testing primarily focuses on software and firmware verification rather than clinical outcomes or diagnostic accuracy requiring expert interpretation.

4. Adjudication method for the test set

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

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

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

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

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

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

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

8. The sample size for the training set

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

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

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

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The SimpleSENSE System is intended for use at home, or at a healthcare facility, under the direction of a licensed medical professional, to record, display and store the following physiological data: a) 2 leads of Electrocardiogram; b) Respiration rate measured through thoracic impedance; c) Heart Sounds; and d) Activity including posture. The device is intended for use when the clinician decides to evaluate the physiologic signals as an aid to diagnosis and treatment. The SimpleSENSE System is intended to be used by patients at rest and not performing any activities or movements. ECG recordings are indicated for the manual assessment of cardiac rhythm disturbances. The device does not produce alarms and is not intended for active patient monitoring (real-time). The device is not intended for use as life supporting equipment on high-risk patients such as critical care patients. The device is not intended for use in the presence of a pacemaker.

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

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

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

1. Table of Acceptance Criteria and Reported Device Performance

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

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

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

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

3. Number of Experts and Qualifications for Ground Truth

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

4. Adjudication Method

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

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

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

6. Standalone (Algorithm Only) Performance

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

7. Type of Ground Truth Used

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

8. Sample Size for the Training Set

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

9. How Ground Truth for the Training Set Was Established

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

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