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The BB-613 Watch Oximeter is a small, wrist-worn device indicated for use in measuring and displaying functional oxygen saturation of arterial hemoglobin (%SpO2) and pulse rate. It is intended for spot-checking of adult patients in hospitals, clinics, long-term care, and home use.

The BB-613 device is a wrist-worn device consisting of a light source (LEDs) and sensor array on the backside of the device, with a user interface on the front side of the device. The LEDs transmit light into the subject's skin at their wrist, and part of this light is reflected from the tissue and detected by a photo-diode. The integrated display is used to display the blood saturation and pulse rate results. It also displays symbols that show if there was no signal or a weak signal. The device is powered by a rechargeable battery.

Here's an analysis of the acceptance criteria and study data for the BB-613 Watch Oximeter, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Oximeter Clinical Validation: 10 patients
• Data Provenance: The document does not explicitly state the country of origin. It indicates the study involved "patients with varying Fitzpatrick skin types (I – V)" and their ages ranged from 18 to 40, with 6 males and 4 females. It is a prospective clinical validation.
• Sample Size for Pulse Rate Validation: Not explicitly stated beyond "a custom built simulator." This implies it was a laboratory-based validation rather than human subjects for this specific test.

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

The document does not specify the number of experts or their qualifications for establishing ground truth in the clinical validation. It only states that the clinical validation showed "equivalence to simultaneous measurements from the predicate oximeter." This implies the predicate oximeter itself served as the reference for ground truth in this comparison, rather than independent expert adjudicated measurements.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method in the traditional sense of multiple human readers or experts reviewing data for ground truth establishment. For the clinical validation, the BB-613's readings were compared to a "predicate oximeter" simultaneously. For pulse rate, a "custom built simulator" was used.

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, an MRMC comparative effectiveness study involving human readers and AI assistance was not performed or described in this document. This device is an oximeter, which provides direct physiological measurements, not interpretations that would typically involve human readers or AI assistance in the way a diagnostic imaging device might.

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

Yes, the studies described are essentially standalone performance evaluations of the device. The clinical validation compares the device's output to a predicate, and the pulse rate validation uses a simulator. These tests assess the algorithm and hardware's ability to accurately measure and display SpO2 and pulse rate without user interpretation or interaction being a variable in the performance metric. However, it's important to note that the device's intended use is "spot-checking," implying a user still reads the display.

7. The Type of Ground Truth Used

• For SpO2 Clinical Validation: The "simultaneous measurements from the predicate oximeter" served as the reference or ground truth.
• For Pulse Rate Validation: A "custom built simulator" provided the reference for pulse rate.
• Other tests (biocompatibility, software, electrical safety, home use) relied on adherence to specified international standards and guidances, where the ground truth is defined by the criteria within those standards.

8. The Sample Size for the Training Set

The document does not explicitly reference or provide details for a "training set" in the context of the device's algorithms. If there was machine learning involved in developing the device's algorithms, the training data used is not disclosed here. The performance data focuses on validation/testing.

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

Since a training set is not described, the method for establishing its ground truth is also not provided.

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Belun Ring BLR-100 is a non-invasive and stand-alone pulse oximeter, intending for spot-checking of oxygen saturation of arterial hemoglobin (SpO2) and the pulse rate of adult patients through index finger in hospital and home environment. It is not intended for single-use and out-of-hospital transport use.

The proposed device Belun Ring BLR-100 is a non-invasive and stand-alone pulse oximeter, which can detect and display the measured oxygen saturation of arterial hemoglobin (SpO2) and the pulse rate in hospital and home environment.

The proposed device consists of two parts: Ring and Cradle.

The Ring is intended to be worn on the bottom of index finger. The Cradle collects data from the ring and translates it into text and graph for the user.

Using spectrophotometric methodology, the proposed device measures oxygen saturation by illuminating the skin and measuring changes in light absorption of oxygenated (oxyhemoglobin) and deoxygenated blood (reduced hemoglobin) using two-wavelengths light: red and infrared. The ratio of absorbance at these wavelengths is calculated and calibrated against direct measurements of arterial oxygen saturation (SaO2 ) to establish the pulse oximeter's measurement of functional oxygen saturation of arterial hemoglobin (SpO2 ). The sensor of the Ring should be placed on palmar side of the proximal phalanx of the index finger and the sensor is being place along the radial artery. The system uses a customized dual CPU design. It consists of two main platforms: the Ring is responsible for signal pre-conditioning, data post-processing (SPO2/PR algorithm), parameters calculation and sensor interfacing, while the Cradle takes care of the user interface including display output and button user input.

The system includes two embedded software, namely Ring firmware and Cradle firmware. The software systems work in conjunction with Ring and Cradle. The two platforms (Ring and Cradle) are connected via "Connectivity software module". The communication protocol is proprietary which provides a reliable and fast communication.

Here's an analysis of the acceptance criteria and the study proving the device meets those criteria, based on the provided text:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

Note: The provided text primarily compares the proposed device to a predicate device and a reference device, rather than explicitly stating acceptance criteria for the proposed device itself. The "Acceptance Criteria" column above is derived from the performance specifications of the predicate device (SONOSAT-W01T) which the proposed device aims to be substantially equivalent to. The "Reported Device Performance" for SpO2 and PR accuracy directly reflect the findings from the non-clinical bench testing.

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

• Clinical Study: The document states that the clinical test was conducted following ISO80601-2-61:2011, clause 201.12.1. This standard requires at least 10 healthy adult volunteers (male and female). However, the exact number of subjects used in the clinical study for the Belun Ring BLR-100 is not explicitly stated in the provided text.
• Data Provenance: The document does not specify the country of origin of the data. It also does not explicitly state whether the study was retrospective or prospective, though a clinical test following a standard like ISO80601-2-61 implies a prospective study design.

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

• The ground truth for the clinical study was established using CO-Oximetry by analyzing arterial blood samples. This method is considered a direct and objective measure of arterial oxygen saturation (SaO2), serving as the "gold standard." Therefore, the ground truth was not established by a panel of human experts in this context.

4. Adjudication method for the test set

• Not applicable, as the ground truth was based on objective laboratory measurements (CO-Oximetry) rather than subjective expert assessment.

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 done. The Belun Ring BLR-100 is a pulse oximeter that directly measures physiological parameters (SpO2 and pulse rate) and does not involve human readers interpreting images or data via an AI algorithm.

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

• Yes, a standalone performance evaluation was done. Both non-clinical (bench testing) and clinical studies (against CO-Oximetry) evaluated the device's performance in measuring SpO2 and pulse rate without active human intervention in the interpretive process. The device provides direct measurements.

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

• For the clinical study, the ground truth for SpO2 accuracy was established using CO-Oximetry analysis of arterial blood samples.
• For pulse rate accuracy, the non-clinical bench testing used a functional tester as the ground truth.

8. The sample size for the training set

• The document describes a medical device for measuring SpO2 and pulse rate, not an AI or machine learning algorithm in the typical sense that would require an extensive "training set" of data for learning and model development. The algorithm for calculating SpO2 and pulse rate from light absorption is based on established spectrophotometric principles and is likely pre-programmed and calibrated, rather than "trained" on a large dataset. Therefore, a specific training set sample size is not mentioned as it's not applicable in the context of this device's underlying technology as described.

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

• As explained in point 8, the concept of a "training set" in the context of an AI/ML algorithm is not directly applicable here. The device uses spectrophotometric methodology, which is based on known physical principles and calibrated against direct measurements (like SaO2 from CO-Oximetry) during its development and manufacturing, rather than a data-driven training process in the AI sense.

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The RMX is a physiological data recorder intended to collect and record data from multiple physiological channels and additional auxiliary inputs from undesignated channels. It is indicated for use by or on order of a physician. The RMX is intended for use in a supervised (hospital) or unsupervised (home) environment.

The RMX is an ambulatory unattended recording device intended for the recording of sleep physiological data. The RMX functions exclusively as a data-recording device and is not intended to monitor Apnea or other vital signs in an intensive care unit or any other real time application. It is used by or on the order of a physician.

The RMX data recording device offers a platform for collecting multiple channels of physiological signals such as pulse rate, ECG, EEG, airflow, thoracic and abdominal respiratory effort, sounds intensity (i.e. noise due to snoring), body position and movements, leg movement, pulse oximetry or similar physiological signals. The data collection box is normally attached over the clothes of the patient's chest using the chest inductive effort sensor band made of clothing-standard woven elastic laces. The device may use its internal sensors, standard wired physiological sensors or several wireless sensors (not covered in this application) to match the specific needs of the patient.

Data collected is transferred on an SD memory card from the recorder to a PC at the physician's clinic, where it is converted into industry standard EDF format, after which it is analyzed by standard scoring software to generate a detailed final report with recommendations.

The RMX data recording device includes 3 software elements; 1) the SETUP part that runs on a PC and uploads the recorder setup parameters to the SD (secure digital) card as determined by the physician, 2) The Firmware operating the main and auxiliary CPU hardware which control the A/D conversion and storage of the data, and 3) the Post-Study Software which runs on a PC, reads the raw data file from the SD card as a single file and converts it into the industry standard EDF format suitable for input to analytical systems (see section 16 for software description).

This document describes the RMX Physiological Data Recorder, but it does not contain a typical acceptance criteria table with performance metrics and a study comparing those metrics against predetermined thresholds. Instead, it focuses on functional testing to ensure accurate data recording.

Here's an analysis of the provided information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or performance metrics in the way a diagnostic device might (e.g., sensitivity, specificity). The "acceptance criteria" can be inferred from the "FUNCTIONAL TEST" section, which describes the device's ability to accurately record signals.

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

• Sample Size for Test Set: Not specified. The description of the "FUNCTIONAL TEST" implies a single setup (a single device or system under test) where simulated signals were injected. It does not mention a "test set" of patient data or a specific number of tests.
• Data Provenance (country of origin, retrospective/prospective): Not applicable. The test involved "known simulated signals injected to its inputs," not real patient data.

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

• Number of Experts: Not applicable. The "ground truth" for the functional test was the "known simulated signals" that were injected into the device. The output was then compared to these known signals.
• Qualifications of Experts: Not applicable for establishing ground truth. The document mentions that the recorded signals are of "sufficient quality for later analysis by trained experts," but these experts are for downstream analysis, not for establishing the ground truth of the recording capability itself.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The functional test involved comparing the device's output to the "known simulated signals" (the ground truth). There's no mention of human adjudication in this technical verification process.

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

• Performed? No. The RMX is described as a "physiological data recorder," not an AI-powered diagnostic tool. The document focuses on its ability to accurately record data, not on the interpretation of that data by humans or AI. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this device's functional validation as presented.
• Effect Size: Not applicable.

6. Standalone (Algorithm Only) Performance Study

• Performed? Not applicable in the context of an "algorithm only" study for diagnostic performance. The device's primary function is recording, not automated interpretation or diagnosis. The "FUNCTIONAL TEST" describes the standalone performance of the recording system (hardware and firmware) in replicating input signals.
  • If "standalone performance" refers to the device's accuracy in recording data without human intervention, then the "FUNCTIONAL TEST" could be considered a form of standalone performance assessment. It confirms the device's ability to capture and store data correctly on its own.

7. Type of Ground Truth Used

• Type of Ground Truth: Known simulated signals. For the functional test described, the ground truth was the precisely known electrical signals injected into the RMX device's inputs.

8. Sample Size for the Training Set

• Sample Size: Not applicable. The RMX is a physiological data recorder, not a machine learning model that requires a training set. Its functionality is based on hardware design and firmware logic, not learned patterns from data.

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

• How Established: Not applicable, as there is no training set for this type of device.

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