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The EarlySense Chair Sensing Unit is intended to be used for continuous measurement of Respiration Rate, Heart Rate and Movement, in an automatic contact-less manner, at home, hospital or clinic setting. The sensor is indicated for use in children, adolescents and adults. The operation of the EarlySense system has been studied in children (weight ≥ 10 Kg) and adults (weight

EarlySense is submitting a new accessory for contactless measurement of heart, respiratory rate and motion, the Chair Sensing Unit. The Chair Sensing Unit, similar to its predicate, the EarlySense Bed Sensing Unit cleared as part of previous EarlySense system submissions (K070375, K082465, K092062, K120465), is intended for continuous measurement of Heart Rate, Respiration Rate and motion while the patient is resting.

The EarlySense Chair sensing unit is comprised of the following components:

1. Sensor: that includes piezoelectric elements incorporated into a plate

2. A cushion made of foam into which the sensor is inserted into - so not to be touched by the patient.

The Chair sensing unit should be connected to a bedside unit that receives and analyzes the signals from the Chair sensing unit to measure and display heart rate, respiratory rate and motion.

The EarlySense Chair Sensing Unit is an accessory to the EarlySense System for continuous, contactless measurement of Respiration Rate, Heart Rate, and Movement. The 510(k) summary provided does not contain specific, quantitative acceptance criteria or detailed results of a clinical study that proves the device meets such criteria. Instead, it relies on bench testing and comparison to a predicate device to establish substantial equivalence.

Here's an analysis of the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

No specific quantitative acceptance criteria or detailed performance data (e.g., accuracy, precision) for the EarlySense Chair Sensing Unit are explicitly stated in the document. The document primarily focuses on establishing substantial equivalence to the predicate device through bench testing rather than reporting precise performance metrics against pre-defined targets.

The general conclusion from bench testing is that: "the signals as detected by the chair sensing unit are similar to those that are detected by the predicate EarlySense Bed Sensor and thus the performance of the Chair Sensing Unit is equivalent to the performance of the Bed Sensing Unit and the performance of the chair sensor is not affected by the new design that includes insertion of the sensor into a cushion (rather than insertion of the sensor under a bed mattress)."

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

The document mentions "Bench Testing" which involved "Performance tests were performed with signals simulating physiological patient signals". No information is provided regarding the sample size of these simulated signals or their provenance (e.g., country of origin, retrospective/prospective). This was a bench test, not human-subject testing.

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

This information is not applicable as the study described is bench testing using simulated physiological signals, not human data requiring expert ground truth establishment.

4. Adjudication Method for the Test Set

Not applicable, as there was no human-subject test set requiring adjudication.

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

No MRMC comparative effectiveness study was mentioned or performed. The submission focuses on validating the device itself, not on evaluating its impact on human reader performance.

6. Standalone Performance Study (Algorithm Only)

The testing described (bench testing with simulated signals) serves as a standalone performance evaluation of the device's ability to detect and transmit signals, and the system's software to analyze these signals. The document states: "The system's detection algorithms differentiate between large body movements, breathing movements and the cardioballistic effect, and thus compute the continuous heart and respiration rates and the body movement." However, detailed performance metrics (e.g., accuracy against a known true value) are not provided, nor is a specific "standalone study" with quantifiable results reported. The performance is largely inferred as being "equivalent" to the predicate device.

7. Type of Ground Truth Used

For the bench testing, the "ground truth" was likely supplied by the "signals simulating physiological patient signals" themselves, which implies a known input with which the device's output could be compared. The nature or source of these simulated signals is not detailed.

8. Sample Size for the Training Set

No information is provided about a training set since the document describes validation activities for a device accessory, not the development of a new algorithm that would typically require a training set. The underlying algorithms for HR, RR, and movement were likely developed and validated with the predicate device.

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

Not applicable, as no training set is mentioned for the validation of this accessory. The existing algorithms from the predicate device (K120465) are utilized.

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The EverOn (modified EarlySense™ ES-16) system is intended for continuous measurement of respiration rate and heart rate, in an automatic contact-less manner, at home, hospital or clinic setting. The system is indicated for use in children, adolescents and adults. The operation of the EverOn has been studied in children (weight ≥10 Kg) and adults (weight ≤111 Kg) during sleep and resting condition.

The modified EarlySense™ EverOn System is designed for continuous and contact-less monitoring of respiration and heart rates. The system automatically starts measuring whenever the patient is in bed under resting or sleeping conditions. The EverOn enables the user to define upper and lower thresholds so an alert notification (audible and visible) is given to the user, if either heart rate or respiration rate exceed the thresholds set by the user. The EverOn also detects patient movement levels and provides patient out-of-bed (Bed Exit) notification to the user. The EverOn System consists of the following main components: - A Sensing Unit placed under the mattress or mattress pad. - A Control Unit (Bedside Unit). - Proprietary recording and data analysis software The under mattress Sensing Unit includes a piezoelectric sensor, which converts mechanical movements into an electric signal. The Control Unit receives the electric signals, processes them and finally calculates, logs, displays the patient's parameters, and generates alerts as per set thresholds. when needed.

Here's a breakdown of the acceptance criteria and study information for the EverOn System, based on the provided text:

1. Acceptance Criteria and Reported Device Performance

The provided text only explicitly states the intended use and performance characteristics the device aims to achieve, primarily related to continuous, contact-less monitoring of respiration and heart rates, and bed exit notification. However, it does not provide specific numerical acceptance criteria (e.g., accuracy percentages, thresholds for error) or detailed reported device performance metrics in a quantifiable format within this 510(k) summary.

The document states:

• "Performance testing demonstrating the accuracy of the system (bench and clinical data)" was performed.
• The EverOn System is "substantially equivalent in all aspects... performance characteristics (accuracy)" to the predicate device.

To fully answer this, we would typically need a more detailed performance study report, which is usually part of the 510(k) submission but not fully contained in this summary.

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

• Sample Size for Test Set: The document states that the operation of the EverOn has been "studied in children (weight ≥10 Kg) and adults (weight ≤111 Kg)". However, it does not specify the exact number of subjects or the sample size used for the performance testing.
• Data Provenance: The document does not explicitly state the country of origin for the clinical data. It generally refers to "clinical data." It also does not explicitly state whether the study was retrospective or prospective.

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

This information is not provided in the given text.

4. Adjudication Method for the Test Set

This information is not provided in the given text.

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

• Was an MRMC study done? No, the EverOn system is a continuous physiological monitor (measuring respiration and heart rate, and bed exit), not an imaging or diagnostic device typically evaluated with MRMC studies comparing human readers with and without AI assistance. Therefore, a comparative effectiveness study of this nature is not applicable and was not conducted/reported here.
• Effect size of human improvement with AI vs without AI: N/A, as an MRMC study was not performed.

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

Yes, the document implies standalone performance testing was done. The device is designed for "continuous and contact-less monitoring" and "automatically starts measuring," generating alerts based on pre-defined thresholds. The "Performance testing demonstrating the accuracy of the system (bench and clinical data)" would inherently evaluate the algorithm's ability to measure these parameters and detect events without human intervention during the measurement phase. The user sets thresholds, but the system automatically detects and alerts.

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth used. For respiration rate and heart rate monitoring devices, common ground truths include:

• Simultaneous monitoring with a reference clinical device (e.g., ECG for heart rate, capnography or impedance pneumography for respiration rate).
• Manual counting by trained clinicians.
• Bench testing with controlled physiological signals.

The text only generally refers to "Performance testing demonstrating the accuracy of the system (bench and clinical data)."

8. Sample Size for the Training Set

This information is not provided in the given text. The 510(k) summary focuses on validation, not the development or training of the underlying algorithms, which might have occurred earlier.

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

This information is not provided in the given text, as information about the training set itself is absent.

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The PAM™3000 system is intended to measure heart rate and respiration rate in adult patients, in a general care hospital environment including, nursing homes The system monitors presence or absence of a patient in bed (bed exit) The system also times the length of continuous patient motion or absence of patient motion

The PAM™3000 System is intended for contact-less and wreless monitoring of bed occupancy, motion and heart and respiration rates of adult patients 11 healthcare facilities The system utilizes a hıghly sensitive UWB-based motion sensor to detect the motion of heart and thorax The system consists of a Bed Sensor Panel (BSP), placed under the patient's mattress, Repeater Base Stations (RBS) that are typically mounted around the hallways in facility, and the Central Computer Station (CCS) with plugged-in Central Base Station (CBS) The signal containing the patient's heart rate and respiration rate data, bed occupancy data, patient motion, and the alerts generated by system are displayed on a PC monitor using Wireless 2000's proprietary Graphic User Interface (GUI) software The Central Computer Station (CCS) is typically located at the nursing station

Here's the detailed breakdown of the acceptance criteria and study information for the Wireless2000 PAM™ 3000 device based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document explicitly states that "The PAM™3000 System underwent bench validation testing and clinical validation testing. The results of the testing indicate that the PAM™3000 performs according to its specifications and accurately detects respiration rate and heart rate of patients and patient presence in bed."

However, it does not provide specific quantitative acceptance criteria or the reported device performance in a table format. It mentions the measurement ranges for heart rate and respiration rate for the device's capabilities, but not as acceptance thresholds for the validation study.

Measurement Ranges:

2. Sample Sizes and Data Provenance

The provided text does not specify the sample size used for the test set or the training set. It also does not mention the data provenance (e.g., country of origin of the data, retrospective or prospective).

3. Number of Experts and Qualifications

The provided text does not mention the number of experts used to establish ground truth or their qualifications.

4. Adjudication Method

The provided text does not mention any adjudication method used for the test set.

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

The provided text does not mention a multi-reader multi-case (MRMC) comparative effectiveness study or any effect size of human readers improving with AI vs. without AI assistance. This device appears to be a standalone monitoring system, not one designed for human interpretation assistance.

6. Standalone (Algorithm Only) Performance

Yes, a standalone performance assessment was done. The document states: "The results of the testing indicate that the PAM™3000 performs according to its specifications and accurately detects respiration rate and heart rate of patients and patient presence in bed." This refers to the device itself (the algorithm/system) directly detecting these parameters.

7. Type of Ground Truth Used

The provided text does not explicitly state the type of ground truth used. Given the nature of the device (heart rate, respiration rate, and bed occupancy), it is highly probable that the ground truth would have been established using reference medical devices (e.g., ECG for heart rate, capnography or a reference respiration monitor for respiration rate, and direct observation for bed occupancy/motion). However, this is an inference and not directly stated in the document.

8. Sample Size for the Training Set

The provided text does not specify the sample size for the training set.

9. How Ground Truth for the Training Set was Established

The provided text does not state how the ground truth for the training set was established.

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